kpriyanshu256/MultiTabQA-tapex-Salesforce-codet5-base-html

source stringlengths 329 3.81k	target stringlengths 17 2.84k	source_latex stringlengths 411 3.86k	target_latex stringlengths 81 2.88k	source_html stringlengths 983 9.03k	target_html stringlengths 219 4.92k	source_markdown stringlengths 597 28.8k	target_markdown stringlengths 38 10.9k	input_ids sequence	attention_mask sequence	labels sequence
select opp. where venue = 'anz stadium' col : round \| opponent \| result \| bro. \| opp. \| date \| venue \| crowd \| position row 1 : 1 \| auckland warriors \| win \| 14 \| 2 \| 1 mar \| anz stadium \| 42361 \| 2/10 row 2 : 2 \| adelaide rams \| win \| 28 \| 12 \| 9 mar \| anz stadium \| 16279 \| 1/10 row 3 : 3 \| perth reds \| win \| 26 \| 16 \| 16 mar \| waca ground \| 11109 \| 2/10 row 4 : 4 \| canberra raiders \| win \| 24 \| 8 \| 24 mar \| anz stadium \| 26103 \| 2/10 row 5 : 5 \| cronulla sharks \| win \| 14 \| 12 \| 31 mar \| anz stadium \| 17294 \| 1/10 row 6 : 6 \| north queensland cowboys \| win \| 42 \| 16 \| 5 apr \| stockland stadium \| 30122 \| 1/10 row 7 : 7 \| adelaide rams \| win \| 20 \| 10 \| 13 apr \| adelaide oval \| 17633 \| 1/10 row 8 : 8 \| penrith panthers \| loss \| 26 \| 27 \| 21 apr \| penrith football stadium \| 12648 \| 1/10 row 9 : 9 \| canterbury bulldogs \| win \| 34 \| 16 \| 28 apr \| anz stadium \| 17921 \| 1/10 row 10 : 10 \| auckland warriors \| win \| 34 \| 18 \| 4 may \| mt smart stadium \| 16471 \| 1/10 row 11 : 11 \| north queensland cowboys \| draw \| 20 \| 20 \| 25 may \| anz stadium \| 14167 \| 1/10 row 12 : 12 \| hunter mariners \| loss \| 6 \| 24 \| 30 may \| topper stadium \| 7124 \| 1/10 row 13 : 13 \| cronulla sharks \| loss \| 4 \| 32 \| 30 jun \| endeavour field \| 12240 \| 1/10 row 14 : 14 \| perth reds \| win \| 50 \| 14 \| 6 jul \| anz stadium \| 11806 \| 1/10 row 15 : 15 \| canberra raiders \| win \| 19 \| 4 \| 14 jul \| bruce stadium \| 13067 \| 1/10 row 16 : 16 \| penrith panthers \| win \| 54 \| 12 \| 10 aug \| anz stadium \| 13921 \| 1/10 row 17 : 17 \| hunter mariners \| win \| 34 \| 16 \| 18 aug \| anz stadium \| 13830 \| 1/10 row 18 : 18 \| canterbury bulldogs \| win \| 32 \| 24 \| 25 aug \| belmore oval \| 9781 \| 1/10 row 19 : semi final \| cronulla sharks \| win \| 34 \| 2 \| 6 sep \| stockland stadium \| 26256 \| none row 20 : grand final \| cronulla sharks \| win \| 26 \| 8 \| 20 sep \| anz stadium \| 58912 \| none	col : opp. row 1 : 2 row 2 : 12 row 3 : 8 row 4 : 12 row 5 : 16 row 6 : 20 row 7 : 14 row 8 : 12 row 9 : 16 row 10 : 8	select opp. where venue = 'anz stadium' <table_name> : table \begin{tabular}{llllllllll} \toprule & round & opponent & result & bro. & opp. & date & venue & crowd & position \\ \midrule 0 & 1 & auckland warriors & win & 14 & 2 & 1 mar & anz stadium & 42361 & 2/10 \\ 1 & 2 & adelaide rams & win & 28 & 12 & 9 mar & anz stadium & 16279 & 1/10 \\ 2 & 3 & perth reds & win & 26 & 16 & 16 mar & waca ground & 11109 & 2/10 \\ 3 & 4 & canberra raiders & win & 24 & 8 & 24 mar & anz stadium & 26103 & 2/10 \\ 4 & 5 & cronulla sharks & win & 14 & 12 & 31 mar & anz stadium & 17294 & 1/10 \\ 5 & 6 & north queensland cowboys & win & 42 & 16 & 5 apr & stockland stadium & 30122 & 1/10 \\ 6 & 7 & adelaide rams & win & 20 & 10 & 13 apr & adelaide oval & 17633 & 1/10 \\ 7 & 8 & penrith panthers & loss & 26 & 27 & 21 apr & penrith football stadium & 12648 & 1/10 \\ 8 & 9 & canterbury bulldogs & win & 34 & 16 & 28 apr & anz stadium & 17921 & 1/10 \\ 9 & 10 & auckland warriors & win & 34 & 18 & 4 may & mt smart stadium & 16471 & 1/10 \\ 10 & 11 & north queensland cowboys & draw & 20 & 20 & 25 may & anz stadium & 14167 & 1/10 \\ 11 & 12 & hunter mariners & loss & 6 & 24 & 30 may & topper stadium & 7124 & 1/10 \\ 12 & 13 & cronulla sharks & loss & 4 & 32 & 30 jun & endeavour field & 12240 & 1/10 \\ 13 & 14 & perth reds & win & 50 & 14 & 6 jul & anz stadium & 11806 & 1/10 \\ 14 & 15 & canberra raiders & win & 19 & 4 & 14 jul & bruce stadium & 13067 & 1/10 \\ 15 & 16 & penrith panthers & win & 54 & 12 & 10 aug & anz stadium & 13921 & 1/10 \\ 16 & 17 & hunter mariners & win & 34 & 16 & 18 aug & anz stadium & 13830 & 1/10 \\ 17 & 18 & canterbury bulldogs & win & 32 & 24 & 25 aug & belmore oval & 9781 & 1/10 \\ 18 & semi final & cronulla sharks & win & 34 & 2 & 6 sep & stockland stadium & 26256 & none \\ 19 & grand final & cronulla sharks & win & 26 & 8 & 20 sep & anz stadium & 58912 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & opp. \\ \midrule 0 & 2 \\ 1 & 12 \\ 2 & 8 \\ 3 & 12 \\ 4 & 16 \\ 5 & 20 \\ 6 & 14 \\ 7 & 12 \\ 8 & 16 \\ 9 & 8 \\ \bottomrule \end{tabular}	select opp. where venue = 'anz stadium' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>round</th> <th>opponent</th> <th>result</th> <th>bro.</th> <th>opp.</th> <th>date</th> <th>venue</th> <th>crowd</th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>auckland warriors</td> <td>win</td> <td>14</td> <td>2</td> <td>1 mar</td> <td>anz stadium</td> <td>42361</td> <td>2/10</td> </tr> <tr> <th>1</th> <td>2</td> <td>adelaide rams</td> <td>win</td> <td>28</td> <td>12</td> <td>9 mar</td> <td>anz stadium</td> <td>16279</td> <td>1/10</td> </tr> <tr> <th>2</th> <td>3</td> <td>perth reds</td> <td>win</td> <td>26</td> <td>16</td> <td>16 mar</td> <td>waca ground</td> <td>11109</td> <td>2/10</td> </tr> <tr> <th>3</th> <td>4</td> <td>canberra raiders</td> <td>win</td> <td>24</td> <td>8</td> <td>24 mar</td> <td>anz stadium</td> <td>26103</td> <td>2/10</td> </tr> <tr> <th>4</th> <td>5</td> <td>cronulla sharks</td> <td>win</td> <td>14</td> <td>12</td> <td>31 mar</td> <td>anz stadium</td> <td>17294</td> <td>1/10</td> </tr> <tr> <th>5</th> <td>6</td> <td>north queensland cowboys</td> <td>win</td> <td>42</td> <td>16</td> <td>5 apr</td> <td>stockland stadium</td> <td>30122</td> <td>1/10</td> </tr> <tr> <th>6</th> <td>7</td> <td>adelaide rams</td> <td>win</td> <td>20</td> <td>10</td> <td>13 apr</td> <td>adelaide oval</td> <td>17633</td> <td>1/10</td> </tr> <tr> <th>7</th> <td>8</td> <td>penrith panthers</td> <td>loss</td> <td>26</td> <td>27</td> <td>21 apr</td> <td>penrith football stadium</td> <td>12648</td> <td>1/10</td> </tr> <tr> <th>8</th> <td>9</td> <td>canterbury bulldogs</td> <td>win</td> <td>34</td> <td>16</td> <td>28 apr</td> <td>anz stadium</td> <td>17921</td> <td>1/10</td> </tr> <tr> <th>9</th> <td>10</td> <td>auckland warriors</td> <td>win</td> <td>34</td> <td>18</td> <td>4 may</td> <td>mt smart stadium</td> <td>16471</td> <td>1/10</td> </tr> <tr> <th>10</th> <td>11</td> <td>north queensland cowboys</td> <td>draw</td> <td>20</td> <td>20</td> <td>25 may</td> <td>anz stadium</td> <td>14167</td> <td>1/10</td> </tr> <tr> <th>11</th> <td>12</td> <td>hunter mariners</td> <td>loss</td> <td>6</td> <td>24</td> <td>30 may</td> <td>topper stadium</td> <td>7124</td> <td>1/10</td> </tr> <tr> <th>12</th> <td>13</td> <td>cronulla sharks</td> <td>loss</td> <td>4</td> <td>32</td> <td>30 jun</td> <td>endeavour field</td> <td>12240</td> <td>1/10</td> </tr> <tr> <th>13</th> <td>14</td> <td>perth reds</td> <td>win</td> <td>50</td> <td>14</td> <td>6 jul</td> <td>anz stadium</td> <td>11806</td> <td>1/10</td> </tr> <tr> <th>14</th> <td>15</td> <td>canberra raiders</td> <td>win</td> <td>19</td> <td>4</td> <td>14 jul</td> <td>bruce stadium</td> <td>13067</td> <td>1/10</td> </tr> <tr> <th>15</th> <td>16</td> <td>penrith panthers</td> <td>win</td> <td>54</td> <td>12</td> <td>10 aug</td> <td>anz stadium</td> <td>13921</td> <td>1/10</td> </tr> <tr> <th>16</th> <td>17</td> <td>hunter mariners</td> <td>win</td> <td>34</td> <td>16</td> <td>18 aug</td> <td>anz stadium</td> <td>13830</td> <td>1/10</td> </tr> <tr> <th>17</th> <td>18</td> <td>canterbury bulldogs</td> <td>win</td> <td>32</td> <td>24</td> <td>25 aug</td> <td>belmore oval</td> <td>9781</td> <td>1/10</td> </tr> <tr> <th>18</th> <td>semi final</td> <td>cronulla sharks</td> <td>win</td> <td>34</td> <td>2</td> <td>6 sep</td> <td>stockland stadium</td> <td>26256</td> <td>none</td> </tr> <tr> <th>19</th> <td>grand final</td> <td>cronulla sharks</td> <td>win</td> <td>26</td> <td>8</td> <td>20 sep</td> <td>anz stadium</td> <td>58912</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>opp.</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> <tr> <th>1</th> <td>12</td> </tr> <tr> <th>2</th> <td>8</td> </tr> <tr> <th>3</th> <td>12</td> </tr> <tr> <th>4</th> <td>16</td> </tr> <tr> <th>5</th> <td>20</td> </tr> <tr> <th>6</th> <td>14</td> </tr> <tr> <th>7</th> <td>12</td> </tr> <tr> <th>8</th> <td>16</td> </tr> <tr> <th>9</th> <td>8</td> </tr> </tbody> </table>	select opp. where venue = 'anz stadium' <table_name> : table \| \| round \| opponent \| result \| bro. \| opp. \| date \| venue \| crowd \| position \| \|---:\|:------------\|:-------------------------\|:---------\|-------:\|-------:\|:-------\|:-------------------------\|--------:\|:-----------\| \| 0 \| 1 \| auckland warriors \| win \| 14 \| 2 \| 1 mar \| anz stadium \| 42361 \| 2/10 \| \| 1 \| 2 \| adelaide rams \| win \| 28 \| 12 \| 9 mar \| anz stadium \| 16279 \| 1/10 \| \| 2 \| 3 \| perth reds \| win \| 26 \| 16 \| 16 mar \| waca ground \| 11109 \| 2/10 \| \| 3 \| 4 \| canberra raiders \| win \| 24 \| 8 \| 24 mar \| anz stadium \| 26103 \| 2/10 \| \| 4 \| 5 \| cronulla sharks \| win \| 14 \| 12 \| 31 mar \| anz stadium \| 17294 \| 1/10 \| \| 5 \| 6 \| north queensland cowboys \| win \| 42 \| 16 \| 5 apr \| stockland stadium \| 30122 \| 1/10 \| \| 6 \| 7 \| adelaide rams \| win \| 20 \| 10 \| 13 apr \| adelaide oval \| 17633 \| 1/10 \| \| 7 \| 8 \| penrith panthers \| loss \| 26 \| 27 \| 21 apr \| penrith football stadium \| 12648 \| 1/10 \| \| 8 \| 9 \| canterbury bulldogs \| win \| 34 \| 16 \| 28 apr \| anz stadium \| 17921 \| 1/10 \| \| 9 \| 10 \| auckland warriors \| win \| 34 \| 18 \| 4 may \| mt smart stadium \| 16471 \| 1/10 \| \| 10 \| 11 \| north queensland cowboys \| draw \| 20 \| 20 \| 25 may \| anz stadium \| 14167 \| 1/10 \| \| 11 \| 12 \| hunter mariners \| loss \| 6 \| 24 \| 30 may \| topper stadium \| 7124 \| 1/10 \| \| 12 \| 13 \| cronulla sharks \| loss \| 4 \| 32 \| 30 jun \| endeavour field \| 12240 \| 1/10 \| \| 13 \| 14 \| perth reds \| win \| 50 \| 14 \| 6 jul \| anz stadium \| 11806 \| 1/10 \| \| 14 \| 15 \| canberra raiders \| win \| 19 \| 4 \| 14 jul \| bruce stadium \| 13067 \| 1/10 \| \| 15 \| 16 \| penrith panthers \| win \| 54 \| 12 \| 10 aug \| anz stadium \| 13921 \| 1/10 \| \| 16 \| 17 \| hunter mariners \| win \| 34 \| 16 \| 18 aug \| anz stadium \| 13830 \| 1/10 \| \| 17 \| 18 \| canterbury bulldogs \| win \| 32 \| 24 \| 25 aug \| belmore oval \| 9781 \| 1/10 \| \| 18 \| semi final \| cronulla sharks \| win \| 34 \| 2 \| 6 sep \| stockland stadium \| 26256 \| none \| \| 19 \| grand final \| cronulla sharks \| win \| 26 \| 8 \| 20 sep \| anz stadium \| 58912 \| none \|	\| \| opp. \| \|---:\|-------:\| \| 0 \| 2 \| \| 1 \| 12 \| \| 2 \| 8 \| \| 3 \| 12 \| \| 4 \| 16 \| \| 5 \| 20 \| \| 6 \| 14 \| \| 7 \| 12 \| \| 8 \| 16 \| \| 9 \| 8 \|	[ [ 1, 4025, 1061, 84, 18, 1625, 331, 275, 344, 273, 296, 304, 94, 384, 361, 5077, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 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select count ( result ) where tournament = 'world series' col : year \| tournament \| venue \| played \| won \| lost \| tied \| n/r \| result row 1 : 1989-90 \| world series \| australia \| 8 \| 6 \| 2 \| 0 \| 0 \| won row 2 : 1990 \| rothmans cup \| new zealand \| 5 \| 5 \| 0 \| 0 \| 0 \| won row 3 : 1990 \| austral-asia cup \| sharjah \| 4 \| 3 \| 1 \| 0 \| 0 \| runner-up row 4 : 1990-91 \| world series \| australia \| 10 \| 9 \| 1 \| 0 \| 0 \| won row 5 : 1991 \| v west indies \| west indies \| 5 \| 4 \| 1 \| 0 \| 0 \| won row 6 : 1991-92 \| world series \| australia \| 10 \| 7 \| 2 \| 0 \| 1 \| won row 7 : 1992 \| 5th world cup \| aust/nz \| 8 \| 4 \| 4 \| 0 \| 0 \| eliminated row 8 : 1992 \| v sri lanka \| sri lanka \| 3 \| 1 \| 2 \| 0 \| 0 \| lost row 9 : 1992-93 \| world series \| australia \| 10 \| 5 \| 4 \| 1 \| 0 \| runner-up row 10 : 1993 \| v new zealand \| new zealand \| 5 \| 3 \| 2 \| 0 \| 0 \| won row 11 : 1993 \| texaco trophy \| england \| 3 \| 3 \| 0 \| 0 \| 0 \| won row 12 : 1993-94 \| world series \| australia \| 11 \| 7 \| 4 \| 0 \| 0 \| won row 13 : 1994 \| v south africa \| south africa \| 8 \| 4 \| 4 \| 0 \| 0 \| drawn row 14 : 1994 \| austral-asia cup \| sharjah \| 3 \| 2 \| 1 \| 0 \| 0 \| semi-final row 15 : 1994 \| singer world series \| sri lanka \| 3 \| 1 \| 2 \| 0 \| 0 \| eliminated row 16 : 1994 \| wills triangular series \| pakistan \| 6 \| 5 \| 1 \| 0 \| 0 \| won row 17 : 1994-95 \| world series \| australia \| 4 \| 3 \| 1 \| 0 \| 0 \| won row 18 : 1995 \| nz centenary t'ment \| new zealand \| 4 \| 3 \| 1 \| 0 \| 0 \| won row 19 : 1995 \| v west indies \| west indies \| 5 \| 1 \| 4 \| 0 \| 0 \| lost row 20 : 1995-96 \| world series \| australia \| 10 \| 7 \| 3 \| 0 \| 0 \| won row 21 : 1996 \| 6th world cup \| ind/pak/sl \| 7 \| 5 \| 2 \| 0 \| 0 \| runner-up row 22 : 1996 \| singer world series \| sri lanka \| 4 \| 2 \| 2 \| 0 \| 0 \| runner-up row 23 : 1996 \| titan cup \| india \| 5 \| 0 \| 5 \| 0 \| 0 \| eliminated row 24 : 1996-97 \| cub series \| australia \| 8 \| 3 \| 5 \| 0 \| 0 \| eliminated row 25 : 1997 \| v south africa \| south africa \| 7 \| 4 \| 3 \| 0 \| 0 \| won row 26 : 1997 \| texaco trophy \| england \| 3 \| 0 \| 3 \| 0 \| 0 \| lost row 27 : 1997-98 \| cub series \| australia \| 11 \| 5 \| 6 \| 0 \| 0 \| won row 28 : 1998 \| v new zealand \| australia \| 4 \| 2 \| 2 \| 0 \| 0 \| drawn row 29 : 1998 \| pepsi triangular series \| india \| 5 \| 3 \| 2 \| 0 \| 0 \| won row 30 : 1998 \| coca-cola cup \| sharjah \| 5 \| 4 \| 1 \| 0 \| 0 \| runner-up row 31 : 1998 \| wills cup \| bangladesh \| 1 \| 0 \| 1 \| 0 \| 0 \| eliminated row 32 : 1998 \| v pakistan \| pakistan \| 3 \| 3 \| 0 \| 0 \| 0 \| won row 33 : 1999 \| cub series \| australia \| 12 \| 9 \| 3 \| 0 \| 0 \| won row 34 : 1999 \| v west indies \| west indies \| 7 \| 3 \| 3 \| 1 \| 0 \| drawn row 35 : 1999 \| 7th world cup \| uk/ire/neth \| 10 \| 7 \| 2 \| 1 \| 0 \| won row 36 : 1999 \| aiwa cup \| sri lanka \| 5 \| 4 \| 1 \| 0 \| 0 \| runner-up row 37 : 1999 \| v zimbabwe \| zimbabwe \| 3 \| 3 \| 0 \| 0 \| 0 \| won row 38 : totals \| none \| none \| 225 \| 140 \| 81 \| 3 \| 1 \| none	col : count ( "result" ) row 1 : 7	select count ( result ) where tournament = 'world series' <table_name> : table \begin{tabular}{llllllllll} \toprule & year & tournament & venue & played & won & lost & tied & n/r & result \\ \midrule 0 & 1989-90 & world series & australia & 8 & 6 & 2 & 0 & 0 & won \\ 1 & 1990 & rothmans cup & new zealand & 5 & 5 & 0 & 0 & 0 & won \\ 2 & 1990 & austral-asia cup & sharjah & 4 & 3 & 1 & 0 & 0 & runner-up \\ 3 & 1990-91 & world series & australia & 10 & 9 & 1 & 0 & 0 & won \\ 4 & 1991 & v west indies & west indies & 5 & 4 & 1 & 0 & 0 & won \\ 5 & 1991-92 & world series & australia & 10 & 7 & 2 & 0 & 1 & won \\ 6 & 1992 & 5th world cup & aust/nz & 8 & 4 & 4 & 0 & 0 & eliminated \\ 7 & 1992 & v sri lanka & sri lanka & 3 & 1 & 2 & 0 & 0 & lost \\ 8 & 1992-93 & world series & australia & 10 & 5 & 4 & 1 & 0 & runner-up \\ 9 & 1993 & v new zealand & new zealand & 5 & 3 & 2 & 0 & 0 & won \\ 10 & 1993 & texaco trophy & england & 3 & 3 & 0 & 0 & 0 & won \\ 11 & 1993-94 & world series & australia & 11 & 7 & 4 & 0 & 0 & won \\ 12 & 1994 & v south africa & south africa & 8 & 4 & 4 & 0 & 0 & drawn \\ 13 & 1994 & austral-asia cup & sharjah & 3 & 2 & 1 & 0 & 0 & semi-final \\ 14 & 1994 & singer world series & sri lanka & 3 & 1 & 2 & 0 & 0 & eliminated \\ 15 & 1994 & wills triangular series & pakistan & 6 & 5 & 1 & 0 & 0 & won \\ 16 & 1994-95 & world series & australia & 4 & 3 & 1 & 0 & 0 & won \\ 17 & 1995 & nz centenary t'ment & new zealand & 4 & 3 & 1 & 0 & 0 & won \\ 18 & 1995 & v west indies & west indies & 5 & 1 & 4 & 0 & 0 & lost \\ 19 & 1995-96 & world series & australia & 10 & 7 & 3 & 0 & 0 & won \\ 20 & 1996 & 6th world cup & ind/pak/sl & 7 & 5 & 2 & 0 & 0 & runner-up \\ 21 & 1996 & singer world series & sri lanka & 4 & 2 & 2 & 0 & 0 & runner-up \\ 22 & 1996 & titan cup & india & 5 & 0 & 5 & 0 & 0 & eliminated \\ 23 & 1996-97 & cub series & australia & 8 & 3 & 5 & 0 & 0 & eliminated \\ 24 & 1997 & v south africa & south africa & 7 & 4 & 3 & 0 & 0 & won \\ 25 & 1997 & texaco trophy & england & 3 & 0 & 3 & 0 & 0 & lost \\ 26 & 1997-98 & cub series & australia & 11 & 5 & 6 & 0 & 0 & won \\ 27 & 1998 & v new zealand & australia & 4 & 2 & 2 & 0 & 0 & drawn \\ 28 & 1998 & pepsi triangular series & india & 5 & 3 & 2 & 0 & 0 & won \\ 29 & 1998 & coca-cola cup & sharjah & 5 & 4 & 1 & 0 & 0 & runner-up \\ 30 & 1998 & wills cup & bangladesh & 1 & 0 & 1 & 0 & 0 & eliminated \\ 31 & 1998 & v pakistan & pakistan & 3 & 3 & 0 & 0 & 0 & won \\ 32 & 1999 & cub series & australia & 12 & 9 & 3 & 0 & 0 & won \\ 33 & 1999 & v west indies & west indies & 7 & 3 & 3 & 1 & 0 & drawn \\ 34 & 1999 & 7th world cup & uk/ire/neth & 10 & 7 & 2 & 1 & 0 & won \\ 35 & 1999 & aiwa cup & sri lanka & 5 & 4 & 1 & 0 & 0 & runner-up \\ 36 & 1999 & v zimbabwe & zimbabwe & 3 & 3 & 0 & 0 & 0 & won \\ 37 & totals & none & none & 225 & 140 & 81 & 3 & 1 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "result" ) \\ \midrule 0 & 7 \\ \bottomrule \end{tabular}	select count ( result ) where tournament = 'world series' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>tournament</th> <th>venue</th> <th>played</th> <th>won</th> <th>lost</th> <th>tied</th> <th>n/r</th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1989-90</td> <td>world series</td> <td>australia</td> <td>8</td> <td>6</td> <td>2</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>1</th> <td>1990</td> <td>rothmans cup</td> <td>new zealand</td> <td>5</td> <td>5</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>2</th> <td>1990</td> <td>austral-asia cup</td> <td>sharjah</td> <td>4</td> <td>3</td> <td>1</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>3</th> <td>1990-91</td> <td>world series</td> <td>australia</td> <td>10</td> <td>9</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>4</th> <td>1991</td> <td>v west indies</td> <td>west indies</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>5</th> <td>1991-92</td> <td>world series</td> <td>australia</td> <td>10</td> <td>7</td> <td>2</td> <td>0</td> <td>1</td> <td>won</td> </tr> <tr> <th>6</th> <td>1992</td> <td>5th world cup</td> <td>aust/nz</td> <td>8</td> <td>4</td> <td>4</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>7</th> <td>1992</td> <td>v sri lanka</td> <td>sri lanka</td> <td>3</td> <td>1</td> <td>2</td> <td>0</td> <td>0</td> <td>lost</td> </tr> <tr> <th>8</th> <td>1992-93</td> <td>world series</td> <td>australia</td> <td>10</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>9</th> <td>1993</td> <td>v new zealand</td> <td>new zealand</td> <td>5</td> <td>3</td> <td>2</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>10</th> <td>1993</td> <td>texaco trophy</td> <td>england</td> <td>3</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>11</th> <td>1993-94</td> <td>world series</td> <td>australia</td> <td>11</td> <td>7</td> <td>4</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>12</th> <td>1994</td> <td>v south africa</td> <td>south africa</td> <td>8</td> <td>4</td> <td>4</td> <td>0</td> <td>0</td> <td>drawn</td> </tr> <tr> <th>13</th> <td>1994</td> <td>austral-asia cup</td> <td>sharjah</td> <td>3</td> <td>2</td> <td>1</td> <td>0</td> <td>0</td> <td>semi-final</td> </tr> <tr> <th>14</th> <td>1994</td> <td>singer world series</td> <td>sri lanka</td> <td>3</td> <td>1</td> <td>2</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>15</th> <td>1994</td> <td>wills triangular series</td> <td>pakistan</td> <td>6</td> <td>5</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>16</th> <td>1994-95</td> <td>world series</td> <td>australia</td> <td>4</td> <td>3</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>17</th> <td>1995</td> <td>nz centenary t'ment</td> <td>new zealand</td> <td>4</td> <td>3</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>18</th> <td>1995</td> <td>v west indies</td> <td>west indies</td> <td>5</td> <td>1</td> <td>4</td> <td>0</td> <td>0</td> <td>lost</td> </tr> <tr> <th>19</th> <td>1995-96</td> <td>world series</td> <td>australia</td> <td>10</td> <td>7</td> <td>3</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>20</th> <td>1996</td> <td>6th world cup</td> <td>ind/pak/sl</td> <td>7</td> <td>5</td> <td>2</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>21</th> <td>1996</td> <td>singer world series</td> <td>sri lanka</td> <td>4</td> <td>2</td> <td>2</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>22</th> <td>1996</td> <td>titan cup</td> <td>india</td> <td>5</td> <td>0</td> <td>5</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>23</th> <td>1996-97</td> <td>cub series</td> <td>australia</td> <td>8</td> <td>3</td> <td>5</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>24</th> <td>1997</td> <td>v south africa</td> <td>south africa</td> <td>7</td> <td>4</td> <td>3</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>25</th> <td>1997</td> <td>texaco trophy</td> <td>england</td> <td>3</td> <td>0</td> <td>3</td> <td>0</td> <td>0</td> <td>lost</td> </tr> <tr> <th>26</th> <td>1997-98</td> <td>cub series</td> <td>australia</td> <td>11</td> <td>5</td> <td>6</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>27</th> <td>1998</td> <td>v new zealand</td> <td>australia</td> <td>4</td> <td>2</td> <td>2</td> <td>0</td> <td>0</td> <td>drawn</td> </tr> <tr> <th>28</th> <td>1998</td> <td>pepsi triangular series</td> <td>india</td> <td>5</td> <td>3</td> <td>2</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>29</th> <td>1998</td> <td>coca-cola cup</td> <td>sharjah</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>30</th> <td>1998</td> <td>wills cup</td> <td>bangladesh</td> <td>1</td> <td>0</td> <td>1</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>31</th> <td>1998</td> <td>v pakistan</td> <td>pakistan</td> <td>3</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>32</th> <td>1999</td> <td>cub series</td> <td>australia</td> <td>12</td> <td>9</td> <td>3</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>33</th> <td>1999</td> <td>v west indies</td> <td>west indies</td> <td>7</td> <td>3</td> <td>3</td> <td>1</td> <td>0</td> <td>drawn</td> </tr> <tr> <th>34</th> <td>1999</td> <td>7th world cup</td> <td>uk/ire/neth</td> <td>10</td> <td>7</td> <td>2</td> <td>1</td> <td>0</td> <td>won</td> </tr> <tr> <th>35</th> <td>1999</td> <td>aiwa cup</td> <td>sri lanka</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>36</th> <td>1999</td> <td>v zimbabwe</td> <td>zimbabwe</td> <td>3</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>37</th> <td>totals</td> <td>none</td> <td>none</td> <td>225</td> <td>140</td> <td>81</td> <td>3</td> <td>1</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "result" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7</td> </tr> </tbody> </table>	select count ( result ) where tournament = 'world series' <table_name> : table \| \| year \| tournament \| venue \| played \| won \| lost \| tied \| n/r \| result \| \|---:\|:--------\|:------------------------\|:-------------\|---------:\|------:\|-------:\|-------:\|------:\|:-----------\| \| 0 \| 1989-90 \| world series \| australia \| 8 \| 6 \| 2 \| 0 \| 0 \| won \| \| 1 \| 1990 \| rothmans cup \| new zealand \| 5 \| 5 \| 0 \| 0 \| 0 \| won \| \| 2 \| 1990 \| austral-asia cup \| sharjah \| 4 \| 3 \| 1 \| 0 \| 0 \| runner-up \| \| 3 \| 1990-91 \| world series \| australia \| 10 \| 9 \| 1 \| 0 \| 0 \| won \| \| 4 \| 1991 \| v west indies \| west indies \| 5 \| 4 \| 1 \| 0 \| 0 \| won \| \| 5 \| 1991-92 \| world series \| australia \| 10 \| 7 \| 2 \| 0 \| 1 \| won \| \| 6 \| 1992 \| 5th world cup \| aust/nz \| 8 \| 4 \| 4 \| 0 \| 0 \| eliminated \| \| 7 \| 1992 \| v sri lanka \| sri lanka \| 3 \| 1 \| 2 \| 0 \| 0 \| lost \| \| 8 \| 1992-93 \| world series \| australia \| 10 \| 5 \| 4 \| 1 \| 0 \| runner-up \| \| 9 \| 1993 \| v new zealand \| new zealand \| 5 \| 3 \| 2 \| 0 \| 0 \| won \| \| 10 \| 1993 \| texaco trophy \| england \| 3 \| 3 \| 0 \| 0 \| 0 \| won \| \| 11 \| 1993-94 \| world series \| australia \| 11 \| 7 \| 4 \| 0 \| 0 \| won \| \| 12 \| 1994 \| v south africa \| south africa \| 8 \| 4 \| 4 \| 0 \| 0 \| drawn \| \| 13 \| 1994 \| austral-asia cup \| sharjah \| 3 \| 2 \| 1 \| 0 \| 0 \| semi-final \| \| 14 \| 1994 \| singer world series \| sri lanka \| 3 \| 1 \| 2 \| 0 \| 0 \| eliminated \| \| 15 \| 1994 \| wills triangular series \| pakistan \| 6 \| 5 \| 1 \| 0 \| 0 \| won \| \| 16 \| 1994-95 \| world series \| australia \| 4 \| 3 \| 1 \| 0 \| 0 \| won \| \| 17 \| 1995 \| nz centenary t'ment \| new zealand \| 4 \| 3 \| 1 \| 0 \| 0 \| won \| \| 18 \| 1995 \| v west indies \| west indies \| 5 \| 1 \| 4 \| 0 \| 0 \| lost \| \| 19 \| 1995-96 \| world series \| australia \| 10 \| 7 \| 3 \| 0 \| 0 \| won \| \| 20 \| 1996 \| 6th world cup \| ind/pak/sl \| 7 \| 5 \| 2 \| 0 \| 0 \| runner-up \| \| 21 \| 1996 \| singer world series \| sri lanka \| 4 \| 2 \| 2 \| 0 \| 0 \| runner-up \| \| 22 \| 1996 \| titan cup \| india \| 5 \| 0 \| 5 \| 0 \| 0 \| eliminated \| \| 23 \| 1996-97 \| cub series \| australia \| 8 \| 3 \| 5 \| 0 \| 0 \| eliminated \| \| 24 \| 1997 \| v south africa \| south africa \| 7 \| 4 \| 3 \| 0 \| 0 \| won \| \| 25 \| 1997 \| texaco trophy \| england \| 3 \| 0 \| 3 \| 0 \| 0 \| lost \| \| 26 \| 1997-98 \| cub series \| australia \| 11 \| 5 \| 6 \| 0 \| 0 \| won \| \| 27 \| 1998 \| v new zealand \| australia \| 4 \| 2 \| 2 \| 0 \| 0 \| drawn \| \| 28 \| 1998 \| pepsi triangular series \| india \| 5 \| 3 \| 2 \| 0 \| 0 \| won \| \| 29 \| 1998 \| coca-cola cup \| sharjah \| 5 \| 4 \| 1 \| 0 \| 0 \| runner-up \| \| 30 \| 1998 \| wills cup \| bangladesh \| 1 \| 0 \| 1 \| 0 \| 0 \| eliminated \| \| 31 \| 1998 \| v pakistan \| pakistan \| 3 \| 3 \| 0 \| 0 \| 0 \| won \| \| 32 \| 1999 \| cub series \| australia \| 12 \| 9 \| 3 \| 0 \| 0 \| won \| \| 33 \| 1999 \| v west indies \| west indies \| 7 \| 3 \| 3 \| 1 \| 0 \| drawn \| \| 34 \| 1999 \| 7th world cup \| uk/ire/neth \| 10 \| 7 \| 2 \| 1 \| 0 \| won \| \| 35 \| 1999 \| aiwa cup \| sri lanka \| 5 \| 4 \| 1 \| 0 \| 0 \| runner-up \| \| 36 \| 1999 \| v zimbabwe \| zimbabwe \| 3 \| 3 \| 0 \| 0 \| 0 \| won \| \| 37 \| totals \| none \| none \| 225 \| 140 \| 81 \| 3 \| 1 \| none \|	\| \| count ( "result" ) \| \|---:\|---------------------:\| \| 0 \| 7 \|	[ [ 1, 4025, 1056, 261, 563, 262, 1625, 358, 30751, 273, 296, 18179, 4166, 11, 411, 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select length where singer(s) = 'lata mangeshkar' col : # \| title \| singer(s) \| lyricist \| length row 1 : 1 \| "dil ka haal sune dilwaala" \| manna dey \| shailendra \| 5:36 row 2 : 2 \| "ichak dana beechak dana" \| mukesh, lata mangeshkar \| hasrat jaipuri \| 5:08 row 3 : 3 \| "mera juta hai japani" \| mukesh \| shailendra \| 4:33 row 4 : 4 \| "mudh mudh ke na dekh" \| lata mangeshkar, manna dey \| shailendra \| 6:34 row 5 : 5 \| "o janewale" \| lata mangeshkar \| hasrat jaipuri \| 2:20 row 6 : 6 \| "pyar hua iqrar hua" \| lata mangeshkar, manna dey \| shailendra \| 4:22 row 7 : 7 \| "ramaiya vastavaiya" \| mohammed rafi, lata mangeshkar, mukesh \| shailendra \| 6:10 row 8 : 8 \| "sham gayi raat aayi" \| lata mangeshkar \| hasrat jaipuri \| 4:00	col : length row 1 : 2:20 row 2 : 4:00	select length where singer(s) = 'lata mangeshkar' <table_name> : table \begin{tabular}{llllll} \toprule & # & title & singer(s) & lyricist & length \\ \midrule 0 & 1 & "dil ka haal sune dilwaala" & manna dey & shailendra & 5:36 \\ 1 & 2 & "ichak dana beechak dana" & mukesh, lata mangeshkar & hasrat jaipuri & 5:08 \\ 2 & 3 & "mera juta hai japani" & mukesh & shailendra & 4:33 \\ 3 & 4 & "mudh mudh ke na dekh" & lata mangeshkar, manna dey & shailendra & 6:34 \\ 4 & 5 & "o janewale" & lata mangeshkar & hasrat jaipuri & 2:20 \\ 5 & 6 & "pyar hua iqrar hua" & lata mangeshkar, manna dey & shailendra & 4:22 \\ 6 & 7 & "ramaiya vastavaiya" & mohammed rafi, lata mangeshkar, mukesh & shailendra & 6:10 \\ 7 & 8 & "sham gayi raat aayi" & lata mangeshkar & hasrat jaipuri & 4:00 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & length \\ \midrule 0 & 2:20 \\ 1 & 4:00 \\ \bottomrule \end{tabular}	select length where singer(s) = 'lata mangeshkar' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>title</th> <th>singer(s)</th> <th>lyricist</th> <th>length</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>"dil ka haal sune dilwaala"</td> <td>manna dey</td> <td>shailendra</td> <td>5:36</td> </tr> <tr> <th>1</th> <td>2</td> <td>"ichak dana beechak dana"</td> <td>mukesh, lata mangeshkar</td> <td>hasrat jaipuri</td> <td>5:08</td> </tr> <tr> <th>2</th> <td>3</td> <td>"mera juta hai japani"</td> <td>mukesh</td> <td>shailendra</td> <td>4:33</td> </tr> <tr> <th>3</th> <td>4</td> <td>"mudh mudh ke na dekh"</td> <td>lata mangeshkar, manna dey</td> <td>shailendra</td> <td>6:34</td> </tr> <tr> <th>4</th> <td>5</td> <td>"o janewale"</td> <td>lata mangeshkar</td> <td>hasrat jaipuri</td> <td>2:20</td> </tr> <tr> <th>5</th> <td>6</td> <td>"pyar hua iqrar hua"</td> <td>lata mangeshkar, manna dey</td> <td>shailendra</td> <td>4:22</td> </tr> <tr> <th>6</th> <td>7</td> <td>"ramaiya vastavaiya"</td> <td>mohammed rafi, lata mangeshkar, mukesh</td> <td>shailendra</td> <td>6:10</td> </tr> <tr> <th>7</th> <td>8</td> <td>"sham gayi raat aayi"</td> <td>lata mangeshkar</td> <td>hasrat jaipuri</td> <td>4:00</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>length</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2:20</td> </tr> <tr> <th>1</th> <td>4:00</td> </tr> </tbody> </table>	select length where singer(s) = 'lata mangeshkar' <table_name> : table \| \| # \| title \| singer(s) \| lyricist \| length \| \|---:\|----:\|:----------------------------\|:---------------------------------------\|:---------------\|:---------\| \| 0 \| 1 \| "dil ka haal sune dilwaala" \| manna dey \| shailendra \| 5:36 \| \| 1 \| 2 \| "ichak dana beechak dana" \| mukesh, lata mangeshkar \| hasrat jaipuri \| 5:08 \| \| 2 \| 3 \| "mera juta hai japani" \| mukesh \| shailendra \| 4:33 \| \| 3 \| 4 \| "mudh mudh ke na dekh" \| lata mangeshkar, manna dey \| shailendra \| 6:34 \| \| 4 \| 5 \| "o janewale" \| lata mangeshkar \| hasrat jaipuri \| 2:20 \| \| 5 \| 6 \| "pyar hua iqrar hua" \| lata mangeshkar, manna dey \| shailendra \| 4:22 \| \| 6 \| 7 \| "ramaiya vastavaiya" \| mohammed rafi, lata mangeshkar, mukesh \| shailendra \| 6:10 \| \| 7 \| 8 \| "sham gayi raat aayi" \| lata mangeshkar \| hasrat jaipuri \| 4:00 \|	\| \| length \| \|---:\|:---------\| \| 0 \| 2:20 \| \| 1 \| 4:00 \|	[ [ 1, 4025, 769, 1625, 4864, 264, 12, 87, 13, 273, 296, 80, 396, 312, 2054, 76, 79, 297, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 7, 1757, 451, 34, 203, 1377, 411, 451, 34, 2649, 1757, 451, 34, 203, 1377, 411, 451, 34, 2470, 264, 12, 87, 13, 1757, 451, 34, 203, 1377, 411, 451, 34, 715, 1512, 376, 1757, 451, 34, 203, 1377, 411, 451, 34, 2469, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 21, 1757, 4465, 34, 203, 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select count ( a.g. ) where kw < 1605 col : transmitter \| kw \| bbca \| bbcb \| d3&4 \| sdn \| arqa \| arqb \| pol. \| a.g. row 1 : allenheads \| 0.002 \| 27 \| 21 \| 24 \| none \| none \| none \| v \| a k row 2 : alston \| 0.08 \| 39 \| 45 \| 42 \| none \| none \| none \| v \| b e k row 3 : bellingham \| 0.01 \| 27 \| 21 \| 24 \| none \| none \| none \| v \| a k row 4 : blaydon burn \| 0.002 \| 44 \| 47 \| 41 \| none \| none \| none \| v \| b e k row 5 : byrness \| 0.01 \| 27 \| 21 \| 24 \| none \| none \| none \| v \| a k row 6 : catton beacon \| 0.028 \| 40 \| 46 \| 43 \| none \| none \| none \| v \| b e k row 7 : durham \| 0.003 \| 41 \| 47 \| 44 \| none \| none \| none \| v \| b e k row 8 : esh \| 0.0024 \| 39 \| 45 \| 42 \| none \| none \| none \| v \| b e k row 9 : felling \| 0.002 \| 40 \| 43 \| 46 \| none \| none \| none \| v \| b e k row 10 : fenham \| 0.4 \| 27 \| 21 \| 24 \| 25 \| 22 \| 28 \| v \| a k row 11 : haltwhistle \| 0.4 \| 59 \| 55 \| 62- \| none \| none \| none \| v \| c/d e row 12 : haydon bridge \| 0.02 \| 44 \| 41 \| 47 \| none \| none \| none \| v \| b e k row 13 : hedleyhope \| 0.004 \| 41 \| 47 \| 44 \| none \| none \| none \| v \| b e k row 14 : humshaugh \| 0.0118 \| 39 \| 45 \| 42 \| none \| none \| none \| v \| b e k row 15 : ireshopeburn \| 0.0022 \| 55 \| 59 \| 50 \| none \| none \| none \| v \| c/d e row 16 : kielder \| 0.0054 \| 26 \| 23 \| 29 \| none \| none \| none \| v \| a k row 17 : morpeth \| 0.0088 \| 22 \| 28 \| 25 \| none \| none \| none \| v \| a k row 18 : newton \| 0.4 \| 26 \| 23 \| 29 \| none \| none \| none \| v \| a k row 19 : seaham \| 0.059 \| 44 \| 47 \| 46 \| none \| none \| none \| v \| b e k row 20 : shotleyfield \| 0.04 \| 22 \| 28 \| 25 \| none \| none \| none \| v \| a k row 21 : staithes \| 0.002 \| 52 \| 51 \| 48 \| none \| none \| none \| v \| b c/d e row 22 : sunderland \| 0.006 \| 52 \| 51 \| 48 \| none \| none \| none \| v \| b c/d e row 23 : wall \| 0.0042 \| 52 \| 51 \| 48 \| none \| none \| none \| h \| b c/d e row 24 : weardale \| 0.2 \| 44 \| 41 \| 47 \| none \| none \| none \| v \| b e k row 25 : whitaside \| 0.0025 \| 44 \| 41 \| 47 \| none \| none \| none \| v \| b e k	col : count ( "a.g." ) row 1 : 25	select count ( a.g. ) where kw < 1605 <table_name> : table \begin{tabular}{lllllllllll} \toprule & transmitter & kw & bbca & bbcb & d3&4 & sdn & arqa & arqb & pol. & a.g. \\ \midrule 0 & allenheads & 0.002 & 27 & 21 & 24 & none & none & none & v & a k \\ 1 & alston & 0.08 & 39 & 45 & 42 & none & none & none & v & b e k \\ 2 & bellingham & 0.01 & 27 & 21 & 24 & none & none & none & v & a k \\ 3 & blaydon burn & 0.002 & 44 & 47 & 41 & none & none & none & v & b e k \\ 4 & byrness & 0.01 & 27 & 21 & 24 & none & none & none & v & a k \\ 5 & catton beacon & 0.028 & 40 & 46 & 43 & none & none & none & v & b e k \\ 6 & durham & 0.003 & 41 & 47 & 44 & none & none & none & v & b e k \\ 7 & esh & 0.0024 & 39 & 45 & 42 & none & none & none & v & b e k \\ 8 & felling & 0.002 & 40 & 43 & 46 & none & none & none & v & b e k \\ 9 & fenham & 0.4 & 27 & 21 & 24 & 25 & 22 & 28 & v & a k \\ 10 & haltwhistle & 0.4 & 59 & 55 & 62- & none & none & none & v & c/d e \\ 11 & haydon bridge & 0.02 & 44 & 41 & 47 & none & none & none & v & b e k \\ 12 & hedleyhope & 0.004 & 41 & 47 & 44 & none & none & none & v & b e k \\ 13 & humshaugh & 0.0118 & 39 & 45 & 42 & none & none & none & v & b e k \\ 14 & ireshopeburn & 0.0022 & 55 & 59 & 50 & none & none & none & v & c/d e \\ 15 & kielder & 0.0054 & 26 & 23 & 29 & none & none & none & v & a k \\ 16 & morpeth & 0.0088 & 22 & 28 & 25 & none & none & none & v & a k \\ 17 & newton & 0.4 & 26 & 23 & 29 & none & none & none & v & a k \\ 18 & seaham & 0.059 & 44 & 47 & 46 & none & none & none & v & b e k \\ 19 & shotleyfield & 0.04 & 22 & 28 & 25 & none & none & none & v & a k \\ 20 & staithes & 0.002 & 52 & 51 & 48 & none & none & none & v & b c/d e \\ 21 & sunderland & 0.006 & 52 & 51 & 48 & none & none & none & v & b c/d e \\ 22 & wall & 0.0042 & 52 & 51 & 48 & none & none & none & h & b c/d e \\ 23 & weardale & 0.2 & 44 & 41 & 47 & none & none & none & v & b e k \\ 24 & whitaside & 0.0025 & 44 & 41 & 47 & none & none & none & v & b e k \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "a.g." ) \\ \midrule 0 & 25 \\ \bottomrule \end{tabular}	select count ( a.g. ) where kw < 1605 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>transmitter</th> <th>kw</th> <th>bbca</th> <th>bbcb</th> <th>d3&4</th> <th>sdn</th> <th>arqa</th> <th>arqb</th> <th>pol.</th> <th>a.g.</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>allenheads</td> <td>0.002</td> <td>27</td> <td>21</td> <td>24</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>1</th> <td>alston</td> <td>0.08</td> <td>39</td> <td>45</td> <td>42</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>2</th> <td>bellingham</td> <td>0.01</td> <td>27</td> <td>21</td> <td>24</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>3</th> <td>blaydon burn</td> <td>0.002</td> <td>44</td> <td>47</td> <td>41</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>4</th> <td>byrness</td> <td>0.01</td> <td>27</td> <td>21</td> <td>24</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>5</th> <td>catton beacon</td> <td>0.028</td> <td>40</td> <td>46</td> <td>43</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>6</th> <td>durham</td> <td>0.003</td> <td>41</td> <td>47</td> <td>44</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>7</th> <td>esh</td> <td>0.0024</td> <td>39</td> <td>45</td> <td>42</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>8</th> <td>felling</td> <td>0.002</td> <td>40</td> <td>43</td> <td>46</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>9</th> <td>fenham</td> <td>0.4</td> <td>27</td> <td>21</td> <td>24</td> <td>25</td> <td>22</td> <td>28</td> <td>v</td> <td>a k</td> </tr> <tr> <th>10</th> <td>haltwhistle</td> <td>0.4</td> <td>59</td> <td>55</td> <td>62-</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>c/d e</td> </tr> <tr> <th>11</th> <td>haydon bridge</td> <td>0.02</td> <td>44</td> <td>41</td> <td>47</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>12</th> <td>hedleyhope</td> <td>0.004</td> <td>41</td> <td>47</td> <td>44</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>13</th> <td>humshaugh</td> <td>0.0118</td> <td>39</td> <td>45</td> <td>42</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>14</th> <td>ireshopeburn</td> <td>0.0022</td> <td>55</td> <td>59</td> <td>50</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>c/d e</td> </tr> <tr> <th>15</th> <td>kielder</td> <td>0.0054</td> <td>26</td> <td>23</td> <td>29</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>16</th> <td>morpeth</td> <td>0.0088</td> <td>22</td> <td>28</td> <td>25</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>17</th> <td>newton</td> <td>0.4</td> <td>26</td> <td>23</td> <td>29</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>18</th> <td>seaham</td> <td>0.059</td> <td>44</td> <td>47</td> <td>46</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>19</th> <td>shotleyfield</td> <td>0.04</td> <td>22</td> <td>28</td> <td>25</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>20</th> <td>staithes</td> <td>0.002</td> <td>52</td> <td>51</td> <td>48</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b c/d e</td> </tr> <tr> <th>21</th> <td>sunderland</td> <td>0.006</td> <td>52</td> <td>51</td> <td>48</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b c/d e</td> </tr> <tr> <th>22</th> <td>wall</td> <td>0.0042</td> <td>52</td> <td>51</td> <td>48</td> <td>none</td> <td>none</td> <td>none</td> <td>h</td> <td>b c/d e</td> </tr> <tr> <th>23</th> <td>weardale</td> <td>0.2</td> <td>44</td> <td>41</td> <td>47</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>24</th> <td>whitaside</td> <td>0.0025</td> <td>44</td> <td>41</td> <td>47</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "a.g." )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>25</td> </tr> </tbody> </table>	select count ( a.g. ) where kw < 1605 <table_name> : table \| \| transmitter \| kw \| bbca \| bbcb \| d3&4 \| sdn \| arqa \| arqb \| pol. \| a.g. \| \|---:\|:--------------\|-------:\|-------:\|-------:\|:-------\|:------\|:-------\|:-------\|:-------\|:--------\| \| 0 \| allenheads \| 0.002 \| 27 \| 21 \| 24 \| none \| none \| none \| v \| a k \| \| 1 \| alston \| 0.08 \| 39 \| 45 \| 42 \| none \| none \| none \| v \| b e k \| \| 2 \| bellingham \| 0.01 \| 27 \| 21 \| 24 \| none \| none \| none \| v \| a k \| \| 3 \| blaydon burn \| 0.002 \| 44 \| 47 \| 41 \| none \| none \| none \| v \| b e k \| \| 4 \| byrness \| 0.01 \| 27 \| 21 \| 24 \| none \| none \| none \| v \| a k \| \| 5 \| catton beacon \| 0.028 \| 40 \| 46 \| 43 \| none \| none \| none \| v \| b e k \| \| 6 \| durham \| 0.003 \| 41 \| 47 \| 44 \| none \| none \| none \| v \| b e k \| \| 7 \| esh \| 0.0024 \| 39 \| 45 \| 42 \| none \| none \| none \| v \| b e k \| \| 8 \| felling \| 0.002 \| 40 \| 43 \| 46 \| none \| none \| none \| v \| b e k \| \| 9 \| fenham \| 0.4 \| 27 \| 21 \| 24 \| 25 \| 22 \| 28 \| v \| a k \| \| 10 \| haltwhistle \| 0.4 \| 59 \| 55 \| 62- \| none \| none \| none \| v \| c/d e \| \| 11 \| haydon bridge \| 0.02 \| 44 \| 41 \| 47 \| none \| none \| none \| v \| b e k \| \| 12 \| hedleyhope \| 0.004 \| 41 \| 47 \| 44 \| none \| none \| none \| v \| b e k \| \| 13 \| humshaugh \| 0.0118 \| 39 \| 45 \| 42 \| none \| none \| none \| v \| b e k \| \| 14 \| ireshopeburn \| 0.0022 \| 55 \| 59 \| 50 \| none \| none \| none \| v \| c/d e \| \| 15 \| kielder \| 0.0054 \| 26 \| 23 \| 29 \| none \| none \| none \| v \| a k \| \| 16 \| morpeth \| 0.0088 \| 22 \| 28 \| 25 \| none \| none \| none \| v \| a k \| \| 17 \| newton \| 0.4 \| 26 \| 23 \| 29 \| none \| none \| none \| v \| a k \| \| 18 \| seaham \| 0.059 \| 44 \| 47 \| 46 \| none \| none \| none \| v \| b e k \| \| 19 \| shotleyfield \| 0.04 \| 22 \| 28 \| 25 \| none \| none \| none \| v \| a k \| \| 20 \| staithes \| 0.002 \| 52 \| 51 \| 48 \| none \| none \| none \| v \| b c/d e \| \| 21 \| sunderland \| 0.006 \| 52 \| 51 \| 48 \| none \| none \| none \| v \| b c/d e \| \| 22 \| wall \| 0.0042 \| 52 \| 51 \| 48 \| none \| none \| none \| h \| b c/d e \| \| 23 \| weardale \| 0.2 \| 44 \| 41 \| 47 \| none \| none \| none \| v \| b e k \| \| 24 \| whitaside \| 0.0025 \| 44 \| 41 \| 47 \| none \| none \| none \| v \| b e k \|	\| \| count ( "a.g." ) \| \|---:\|-------------------:\| \| 0 \| 25 \|	[ [ 1, 4025, 1056, 261, 279, 18, 75, 18, 262, 1625, 5323, 411, 2872, 6260, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 2338, 1938, 387, 1757, 451, 34, 203, 1377, 411, 451, 34, 9987, 1757, 451, 34, 203, 1377, 411, 451, 34, 9897, 5353, 1757, 451, 34, 203, 1377, 411, 451, 34, 9897, 7358, 1757, 451, 34, 203, 1377, 411, 451, 34, 72, 23, 10, 931, 31, 24, 1757, 451, 34, 203, 1377, 411, 451, 34, 87, 5176, 1757, 451, 34, 203, 1377, 411, 451, 34, 297, 7588, 1757, 451, 34, 203, 1377, 411, 451, 34, 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select competition where games = 19 col : season \| club \| competition \| games \| goals row 1 : 2002/03 \| raec mons \| jupiler league \| 19 \| 0 row 2 : 2003/04 \| raec mons \| jupiler league \| 23 \| 0 row 3 : 2004/05 \| ksv roeselare \| belgian second division \| 29 \| 1 row 4 : 2005/06 \| ksv roeselare \| jupiler league \| 26 \| 0 row 5 : 2006/07 \| ksv roeselare \| jupiler league \| 29 \| 1 row 6 : 2007/08 \| ksv roeselare \| jupiler league \| 25 \| 0 row 7 : 2008/09 \| excelsior mouscron \| jupiler league \| 31 \| 1 row 8 : 2009/10 \| excelsior mouscron \| jupiler league \| 14 \| 1 row 9 : 2009/10 \| gyori eto fc \| soproni liga \| 1 \| 0 row 10 : 2010/11 \| kortrijk \| jupiler league \| 0 \| 0 row 11 : none \| none \| total \| 278 \| 4	col : competition row 1 : jupiler league	select competition where games = 19 <table_name> : table \begin{tabular}{llllll} \toprule & season & club & competition & games & goals \\ \midrule 0 & 2002/03 & raec mons & jupiler league & 19 & 0 \\ 1 & 2003/04 & raec mons & jupiler league & 23 & 0 \\ 2 & 2004/05 & ksv roeselare & belgian second division & 29 & 1 \\ 3 & 2005/06 & ksv roeselare & jupiler league & 26 & 0 \\ 4 & 2006/07 & ksv roeselare & jupiler league & 29 & 1 \\ 5 & 2007/08 & ksv roeselare & jupiler league & 25 & 0 \\ 6 & 2008/09 & excelsior mouscron & jupiler league & 31 & 1 \\ 7 & 2009/10 & excelsior mouscron & jupiler league & 14 & 1 \\ 8 & 2009/10 & gyori eto fc & soproni liga & 1 & 0 \\ 9 & 2010/11 & kortrijk & jupiler league & 0 & 0 \\ 10 & none & none & total & 278 & 4 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & competition \\ \midrule 0 & jupiler league \\ \bottomrule \end{tabular}	select competition where games = 19 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>club</th> <th>competition</th> <th>games</th> <th>goals</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2002/03</td> <td>raec mons</td> <td>jupiler league</td> <td>19</td> <td>0</td> </tr> <tr> <th>1</th> <td>2003/04</td> <td>raec mons</td> <td>jupiler league</td> <td>23</td> <td>0</td> </tr> <tr> <th>2</th> <td>2004/05</td> <td>ksv roeselare</td> <td>belgian second division</td> <td>29</td> <td>1</td> </tr> <tr> <th>3</th> <td>2005/06</td> <td>ksv roeselare</td> <td>jupiler league</td> <td>26</td> <td>0</td> </tr> <tr> <th>4</th> <td>2006/07</td> <td>ksv roeselare</td> <td>jupiler league</td> <td>29</td> <td>1</td> </tr> <tr> <th>5</th> <td>2007/08</td> <td>ksv roeselare</td> <td>jupiler league</td> <td>25</td> <td>0</td> </tr> <tr> <th>6</th> <td>2008/09</td> <td>excelsior mouscron</td> <td>jupiler league</td> <td>31</td> <td>1</td> </tr> <tr> <th>7</th> <td>2009/10</td> <td>excelsior mouscron</td> <td>jupiler league</td> <td>14</td> <td>1</td> </tr> <tr> <th>8</th> <td>2009/10</td> <td>gyori eto fc</td> <td>soproni liga</td> <td>1</td> <td>0</td> </tr> <tr> <th>9</th> <td>2010/11</td> <td>kortrijk</td> <td>jupiler league</td> <td>0</td> <td>0</td> </tr> <tr> <th>10</th> <td>none</td> <td>none</td> <td>total</td> <td>278</td> <td>4</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>competition</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>jupiler league</td> </tr> </tbody> </table>	select competition where games = 19 <table_name> : table \| \| season \| club \| competition \| games \| goals \| \|---:\|:---------\|:-------------------\|:------------------------\|--------:\|--------:\| \| 0 \| 2002/03 \| raec mons \| jupiler league \| 19 \| 0 \| \| 1 \| 2003/04 \| raec mons \| jupiler league \| 23 \| 0 \| \| 2 \| 2004/05 \| ksv roeselare \| belgian second division \| 29 \| 1 \| \| 3 \| 2005/06 \| ksv roeselare \| jupiler league \| 26 \| 0 \| \| 4 \| 2006/07 \| ksv roeselare \| jupiler league \| 29 \| 1 \| \| 5 \| 2007/08 \| ksv roeselare \| jupiler league \| 25 \| 0 \| \| 6 \| 2008/09 \| excelsior mouscron \| jupiler league \| 31 \| 1 \| \| 7 \| 2009/10 \| excelsior mouscron \| jupiler league \| 14 \| 1 \| \| 8 \| 2009/10 \| gyori eto fc \| soproni liga \| 1 \| 0 \| \| 9 \| 2010/11 \| kortrijk \| jupiler league \| 0 \| 0 \| \| 10 \| none \| none \| total \| 278 \| 4 \|	\| \| competition \| \|---:\|:---------------\| \| 0 \| jupiler league \|	[ [ 1, 4025, 25163, 608, 1625, 28422, 273, 5342, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 30321, 1757, 451, 34, 203, 1377, 411, 451, 34, 830, 373, 1757, 451, 34, 203, 1377, 411, 451, 34, 31942, 608, 1757, 451, 34, 203, 1377, 411, 451, 34, 75, 753, 1757, 451, 34, 203, 1377, 411, 451, 34, 3240, 1031, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 6976, 22, 19, 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select count ( competition ) where year = 2002 col : year \| competition \| venue \| position \| event row 1 : 1997 \| world indoor championships \| paris, france \| 5th \| 60 m hurdles row 2 : 1997 \| usa outdoor championships \| indianapolis, united states \| 1st \| 100 m hurdles row 3 : 1998 \| grand prix final \| moscow, russia \| 2nd \| 100 m hurdles row 4 : 1998 \| usa indoor championships \| none \| 1st \| 60 m hurdles row 5 : 1999 \| world indoor championships \| maebashi, japan \| 6th \| 60 m hurdles row 6 : 2000 \| olympic games \| sydney, australia \| 3rd \| 100 m hurdles row 7 : 2000 \| grand prix final \| doha, qatar \| 4th \| 100 m hurdles row 8 : 2002 \| grand prix final \| paris, france \| 7th \| 100 m hurdles row 9 : 2002 \| usa indoor championships \| none \| 1st \| 60 m hurdles row 10 : 2003 \| world indoor championships \| birmingham, england \| 3rd \| 60 m hurdles row 11 : 2003 \| world athletics final \| monaco \| 6th \| 100 m hurdles row 12 : 2004 \| olympic games \| athens, greece \| 3rd \| 100 m hurdles	col : count ( "competition" ) row 1 : 2	select count ( competition ) where year = 2002 <table_name> : table \begin{tabular}{llllll} \toprule & year & competition & venue & position & event \\ \midrule 0 & 1997 & world indoor championships & paris, france & 5th & 60 m hurdles \\ 1 & 1997 & usa outdoor championships & indianapolis, united states & 1st & 100 m hurdles \\ 2 & 1998 & grand prix final & moscow, russia & 2nd & 100 m hurdles \\ 3 & 1998 & usa indoor championships & none & 1st & 60 m hurdles \\ 4 & 1999 & world indoor championships & maebashi, japan & 6th & 60 m hurdles \\ 5 & 2000 & olympic games & sydney, australia & 3rd & 100 m hurdles \\ 6 & 2000 & grand prix final & doha, qatar & 4th & 100 m hurdles \\ 7 & 2002 & grand prix final & paris, france & 7th & 100 m hurdles \\ 8 & 2002 & usa indoor championships & none & 1st & 60 m hurdles \\ 9 & 2003 & world indoor championships & birmingham, england & 3rd & 60 m hurdles \\ 10 & 2003 & world athletics final & monaco & 6th & 100 m hurdles \\ 11 & 2004 & olympic games & athens, greece & 3rd & 100 m hurdles \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "competition" ) \\ \midrule 0 & 2 \\ \bottomrule \end{tabular}	select count ( competition ) where year = 2002 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1997</td> <td>world indoor championships</td> <td>paris, france</td> <td>5th</td> <td>60 m hurdles</td> </tr> <tr> <th>1</th> <td>1997</td> <td>usa outdoor championships</td> <td>indianapolis, united states</td> <td>1st</td> <td>100 m hurdles</td> </tr> <tr> <th>2</th> <td>1998</td> <td>grand prix final</td> <td>moscow, russia</td> <td>2nd</td> <td>100 m hurdles</td> </tr> <tr> <th>3</th> <td>1998</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>4</th> <td>1999</td> <td>world indoor championships</td> <td>maebashi, japan</td> <td>6th</td> <td>60 m hurdles</td> </tr> <tr> <th>5</th> <td>2000</td> <td>olympic games</td> <td>sydney, australia</td> <td>3rd</td> <td>100 m hurdles</td> </tr> <tr> <th>6</th> <td>2000</td> <td>grand prix final</td> <td>doha, qatar</td> <td>4th</td> <td>100 m hurdles</td> </tr> <tr> <th>7</th> <td>2002</td> <td>grand prix final</td> <td>paris, france</td> <td>7th</td> <td>100 m hurdles</td> </tr> <tr> <th>8</th> <td>2002</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>9</th> <td>2003</td> <td>world indoor championships</td> <td>birmingham, england</td> <td>3rd</td> <td>60 m hurdles</td> </tr> <tr> <th>10</th> <td>2003</td> <td>world athletics final</td> <td>monaco</td> <td>6th</td> <td>100 m hurdles</td> </tr> <tr> <th>11</th> <td>2004</td> <td>olympic games</td> <td>athens, greece</td> <td>3rd</td> <td>100 m hurdles</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "competition" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> </tbody> </table>	select count ( competition ) where year = 2002 <table_name> : table \| \| year \| competition \| venue \| position \| event \| \|---:\|-------:\|:---------------------------\|:----------------------------\|:-----------\|:--------------\| \| 0 \| 1997 \| world indoor championships \| paris, france \| 5th \| 60 m hurdles \| \| 1 \| 1997 \| usa outdoor championships \| indianapolis, united states \| 1st \| 100 m hurdles \| \| 2 \| 1998 \| grand prix final \| moscow, russia \| 2nd \| 100 m hurdles \| \| 3 \| 1998 \| usa indoor championships \| none \| 1st \| 60 m hurdles \| \| 4 \| 1999 \| world indoor championships \| maebashi, japan \| 6th \| 60 m hurdles \| \| 5 \| 2000 \| olympic games \| sydney, australia \| 3rd \| 100 m hurdles \| \| 6 \| 2000 \| grand prix final \| doha, qatar \| 4th \| 100 m hurdles \| \| 7 \| 2002 \| grand prix final \| paris, france \| 7th \| 100 m hurdles \| \| 8 \| 2002 \| usa indoor championships \| none \| 1st \| 60 m hurdles \| \| 9 \| 2003 \| world indoor championships \| birmingham, england \| 3rd \| 60 m hurdles \| \| 10 \| 2003 \| world athletics final \| monaco \| 6th \| 100 m hurdles \| \| 11 \| 2004 \| olympic games \| athens, greece \| 3rd \| 100 m hurdles \|	\| \| count ( "competition" ) \| \|---:\|--------------------------:\| \| 0 \| 2 \|	[ [ 1, 4025, 1056, 261, 25163, 608, 262, 1625, 3286, 273, 4044, 22, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 31942, 608, 1757, 451, 34, 203, 1377, 411, 451, 34, 24612, 1757, 451, 34, 203, 1377, 411, 451, 34, 3276, 1757, 451, 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select no. where outcome = 'runner-up' col : outcome \| no. \| date \| tournament \| surface \| partner \| opponents \| score row 1 : winner \| 1 \| 2004-04-18 00:00:00 \| jackson, united states \| clay \| alisa kleybanova \| cory ann avants kristen schlukebir \| 6-2, 6-3 row 2 : runner-up \| 1 \| 2004-09-26 00:00:00 \| albuquerque, united states \| hard \| maria emilia salerni \| maureen drake carly gullickson \| 3-6, 6-7(6-8) row 3 : winner \| 2 \| 2005-03-27 00:00:00 \| redding, united states \| hard \| yulia beygelzimer \| leanne baker francesca lubiani \| 6-4, 6-7(1-7), 6-3 row 4 : runner-up \| 2 \| 2005-05-08 00:00:00 \| raleigh, united states \| clay \| maria fernanda alves \| ashley harkleroad lindsay lee-waters \| 2-6, 6-0, 3-6 row 5 : runner-up \| 3 \| 2006-03-19 00:00:00 \| orange, united states \| hard \| lilia osterloh \| kateryna bondarenko alona bondarenko \| 2-6, 4-6 row 6 : winner \| 3 \| 2006-11-12 00:00:00 \| pittsburgh, united states \| hard (i) \| alisa kleybanova \| ashley harkleroad galina voskoboeva \| 6-4, 5-7, 6-1 row 7 : runner-up \| 4 \| 2007-02-11 00:00:00 \| midland, united states \| hard (i) \| maureen drake \| laura granville abigail spears \| 4-6, 6-3, 3-6 row 8 : runner-up \| 5 \| 2007-07-07 00:00:00 \| southlake, united states \| hard \| valerie tetreault \| surina de beer kim grant \| 6-4, 4-6, 4-6 row 9 : winner \| 4 \| 2007-07-22 00:00:00 \| hamilton, canada \| clay \| surina de beer \| michaela johansson paula zabala \| walkover row 10 : winner \| 5 \| 2007-08-04 00:00:00 \| vancouver, canada \| hard \| marie-eve pelletier \| soledad esperon agustina lepore \| 6-4, 6-4 row 11 : winner \| 6 \| 2007-10-21 00:00:00 \| lawrenceville, united states \| hard \| alisa kleybanova \| leanne baker julie ditty \| 6-2, 6-0 row 12 : winner \| 7 \| 2007-11-12 00:00:00 \| pittsburgh, united states \| hard (i) \| alisa kleybanova \| raquel kops-jones abigail spears \| 6-4, 4-6, [10-6] row 13 : runner-up \| 6 \| 2008-04-27 00:00:00 \| dothan, united states \| clay \| maria fernanda alves \| tetiana luzhanska michaela pastikova \| 1-6, 3-6 row 14 : winner \| 8 \| 2008-10-18 00:00:00 \| toronto, canada \| hard (i) \| marie-eve pelletier \| nikola frankova carmen klaschka \| 6-4, 6-2 row 15 : runner-up \| 7 \| 2009-09-27 00:00:00 \| saguenay, canada \| hard (i) \| rebecca marino \| sofia arvidsson severine bremond beltrame \| 3-6, 1-6 row 16 : runner-up \| 8 \| 2013-04-13 00:00:00 \| poza rica, mexico \| hard \| olga savchuk \| maria fernanda alvarez teran maria fernanda alves \| 2-6, 3-6 row 17 : runner-up \| 9 \| 2013-05-18 00:00:00 \| saint-gaudens, france \| clay \| kurumi nara \| julia glushko paula ormaechea \| 5-7, 6-7(11-13)	col : no. row 1 : 1 row 2 : 2 row 3 : 3 row 4 : 4 row 5 : 5 row 6 : 6 row 7 : 7 row 8 : 8 row 9 : 9	select no. where outcome = 'runner-up' <table_name> : table \begin{tabular}{lllllllll} \toprule & outcome & no. & date & tournament & surface & partner & opponents & score \\ \midrule 0 & winner & 1 & 2004-04-18 00:00:00 & jackson, united states & clay & alisa kleybanova & cory ann avants kristen schlukebir & 6-2, 6-3 \\ 1 & runner-up & 1 & 2004-09-26 00:00:00 & albuquerque, united states & hard & maria emilia salerni & maureen drake carly gullickson & 3-6, 6-7(6-8) \\ 2 & winner & 2 & 2005-03-27 00:00:00 & redding, united states & hard & yulia beygelzimer & leanne baker francesca lubiani & 6-4, 6-7(1-7), 6-3 \\ 3 & runner-up & 2 & 2005-05-08 00:00:00 & raleigh, united states & clay & maria fernanda alves & ashley harkleroad lindsay lee-waters & 2-6, 6-0, 3-6 \\ 4 & runner-up & 3 & 2006-03-19 00:00:00 & orange, united states & hard & lilia osterloh & kateryna bondarenko alona bondarenko & 2-6, 4-6 \\ 5 & winner & 3 & 2006-11-12 00:00:00 & pittsburgh, united states & hard (i) & alisa kleybanova & ashley harkleroad galina voskoboeva & 6-4, 5-7, 6-1 \\ 6 & runner-up & 4 & 2007-02-11 00:00:00 & midland, united states & hard (i) & maureen drake & laura granville abigail spears & 4-6, 6-3, 3-6 \\ 7 & runner-up & 5 & 2007-07-07 00:00:00 & southlake, united states & hard & valerie tetreault & surina de beer kim grant & 6-4, 4-6, 4-6 \\ 8 & winner & 4 & 2007-07-22 00:00:00 & hamilton, canada & clay & surina de beer & michaela johansson paula zabala & walkover \\ 9 & winner & 5 & 2007-08-04 00:00:00 & vancouver, canada & hard & marie-eve pelletier & soledad esperon agustina lepore & 6-4, 6-4 \\ 10 & winner & 6 & 2007-10-21 00:00:00 & lawrenceville, united states & hard & alisa kleybanova & leanne baker julie ditty & 6-2, 6-0 \\ 11 & winner & 7 & 2007-11-12 00:00:00 & pittsburgh, united states & hard (i) & alisa kleybanova & raquel kops-jones abigail spears & 6-4, 4-6, [10-6] \\ 12 & runner-up & 6 & 2008-04-27 00:00:00 & dothan, united states & clay & maria fernanda alves & tetiana luzhanska michaela pastikova & 1-6, 3-6 \\ 13 & winner & 8 & 2008-10-18 00:00:00 & toronto, canada & hard (i) & marie-eve pelletier & nikola frankova carmen klaschka & 6-4, 6-2 \\ 14 & runner-up & 7 & 2009-09-27 00:00:00 & saguenay, canada & hard (i) & rebecca marino & sofia arvidsson severine bremond beltrame & 3-6, 1-6 \\ 15 & runner-up & 8 & 2013-04-13 00:00:00 & poza rica, mexico & hard & olga savchuk & maria fernanda alvarez teran maria fernanda alves & 2-6, 3-6 \\ 16 & runner-up & 9 & 2013-05-18 00:00:00 & saint-gaudens, france & clay & kurumi nara & julia glushko paula ormaechea & 5-7, 6-7(11-13) \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & no. \\ \midrule 0 & 1 \\ 1 & 2 \\ 2 & 3 \\ 3 & 4 \\ 4 & 5 \\ 5 & 6 \\ 6 & 7 \\ 7 & 8 \\ 8 & 9 \\ \bottomrule \end{tabular}	select no. where outcome = 'runner-up' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>outcome</th> <th>no.</th> <th>date</th> <th>tournament</th> <th>surface</th> <th>partner</th> <th>opponents</th> <th>score</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>winner</td> <td>1</td> <td>2004-04-18 00:00:00</td> <td>jackson, united states</td> <td>clay</td> <td>alisa kleybanova</td> <td>cory ann avants kristen schlukebir</td> <td>6-2, 6-3</td> </tr> <tr> <th>1</th> <td>runner-up</td> <td>1</td> <td>2004-09-26 00:00:00</td> <td>albuquerque, united states</td> <td>hard</td> <td>maria emilia salerni</td> <td>maureen drake carly gullickson</td> <td>3-6, 6-7(6-8)</td> </tr> <tr> <th>2</th> <td>winner</td> <td>2</td> <td>2005-03-27 00:00:00</td> <td>redding, united states</td> <td>hard</td> <td>yulia beygelzimer</td> <td>leanne baker francesca lubiani</td> <td>6-4, 6-7(1-7), 6-3</td> </tr> <tr> <th>3</th> <td>runner-up</td> <td>2</td> <td>2005-05-08 00:00:00</td> <td>raleigh, united states</td> <td>clay</td> <td>maria fernanda alves</td> <td>ashley harkleroad lindsay lee-waters</td> <td>2-6, 6-0, 3-6</td> </tr> <tr> <th>4</th> <td>runner-up</td> <td>3</td> <td>2006-03-19 00:00:00</td> <td>orange, united states</td> <td>hard</td> <td>lilia osterloh</td> <td>kateryna bondarenko alona bondarenko</td> <td>2-6, 4-6</td> </tr> <tr> <th>5</th> <td>winner</td> <td>3</td> <td>2006-11-12 00:00:00</td> <td>pittsburgh, united states</td> <td>hard (i)</td> <td>alisa kleybanova</td> <td>ashley harkleroad galina voskoboeva</td> <td>6-4, 5-7, 6-1</td> </tr> <tr> <th>6</th> <td>runner-up</td> <td>4</td> <td>2007-02-11 00:00:00</td> <td>midland, united states</td> <td>hard (i)</td> <td>maureen drake</td> <td>laura granville abigail spears</td> <td>4-6, 6-3, 3-6</td> </tr> <tr> <th>7</th> <td>runner-up</td> <td>5</td> <td>2007-07-07 00:00:00</td> <td>southlake, united states</td> <td>hard</td> <td>valerie tetreault</td> <td>surina de beer kim grant</td> <td>6-4, 4-6, 4-6</td> </tr> <tr> <th>8</th> <td>winner</td> <td>4</td> <td>2007-07-22 00:00:00</td> <td>hamilton, canada</td> <td>clay</td> <td>surina de beer</td> <td>michaela johansson paula zabala</td> <td>walkover</td> </tr> <tr> <th>9</th> <td>winner</td> <td>5</td> <td>2007-08-04 00:00:00</td> <td>vancouver, canada</td> <td>hard</td> <td>marie-eve pelletier</td> <td>soledad esperon agustina lepore</td> <td>6-4, 6-4</td> </tr> <tr> <th>10</th> <td>winner</td> <td>6</td> <td>2007-10-21 00:00:00</td> <td>lawrenceville, united states</td> <td>hard</td> <td>alisa kleybanova</td> <td>leanne baker julie ditty</td> <td>6-2, 6-0</td> </tr> <tr> <th>11</th> <td>winner</td> <td>7</td> <td>2007-11-12 00:00:00</td> <td>pittsburgh, united states</td> <td>hard (i)</td> <td>alisa kleybanova</td> <td>raquel kops-jones abigail spears</td> <td>6-4, 4-6, [10-6]</td> </tr> <tr> <th>12</th> <td>runner-up</td> <td>6</td> <td>2008-04-27 00:00:00</td> <td>dothan, united states</td> <td>clay</td> <td>maria fernanda alves</td> <td>tetiana luzhanska michaela pastikova</td> <td>1-6, 3-6</td> </tr> <tr> <th>13</th> <td>winner</td> <td>8</td> <td>2008-10-18 00:00:00</td> <td>toronto, canada</td> <td>hard (i)</td> <td>marie-eve pelletier</td> <td>nikola frankova carmen klaschka</td> <td>6-4, 6-2</td> </tr> <tr> <th>14</th> <td>runner-up</td> <td>7</td> <td>2009-09-27 00:00:00</td> <td>saguenay, canada</td> <td>hard (i)</td> <td>rebecca marino</td> <td>sofia arvidsson severine bremond beltrame</td> <td>3-6, 1-6</td> </tr> <tr> <th>15</th> <td>runner-up</td> <td>8</td> <td>2013-04-13 00:00:00</td> <td>poza rica, mexico</td> <td>hard</td> <td>olga savchuk</td> <td>maria fernanda alvarez teran maria fernanda alves</td> <td>2-6, 3-6</td> </tr> <tr> <th>16</th> <td>runner-up</td> <td>9</td> <td>2013-05-18 00:00:00</td> <td>saint-gaudens, france</td> <td>clay</td> <td>kurumi nara</td> <td>julia glushko paula ormaechea</td> <td>5-7, 6-7(11-13)</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>no.</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> <tr> <th>1</th> <td>2</td> </tr> <tr> <th>2</th> <td>3</td> </tr> <tr> <th>3</th> <td>4</td> </tr> <tr> <th>4</th> <td>5</td> </tr> <tr> <th>5</th> <td>6</td> </tr> <tr> <th>6</th> <td>7</td> </tr> <tr> <th>7</th> <td>8</td> </tr> <tr> <th>8</th> <td>9</td> </tr> </tbody> </table>	select no. where outcome = 'runner-up' <table_name> : table \| \| outcome \| no. \| date \| tournament \| surface \| partner \| opponents \| score \| \|---:\|:----------\|------:\|:--------------------\|:-----------------------------\|:----------\|:---------------------\|:--------------------------------------------------\|:-------------------\| \| 0 \| winner \| 1 \| 2004-04-18 00:00:00 \| jackson, united states \| clay \| alisa kleybanova \| cory ann avants kristen schlukebir \| 6-2, 6-3 \| \| 1 \| runner-up \| 1 \| 2004-09-26 00:00:00 \| albuquerque, united states \| hard \| maria emilia salerni \| maureen drake carly gullickson \| 3-6, 6-7(6-8) \| \| 2 \| winner \| 2 \| 2005-03-27 00:00:00 \| redding, united states \| hard \| yulia beygelzimer \| leanne baker francesca lubiani \| 6-4, 6-7(1-7), 6-3 \| \| 3 \| runner-up \| 2 \| 2005-05-08 00:00:00 \| raleigh, united states \| clay \| maria fernanda alves \| ashley harkleroad lindsay lee-waters \| 2-6, 6-0, 3-6 \| \| 4 \| runner-up \| 3 \| 2006-03-19 00:00:00 \| orange, united states \| hard \| lilia osterloh \| kateryna bondarenko alona bondarenko \| 2-6, 4-6 \| \| 5 \| winner \| 3 \| 2006-11-12 00:00:00 \| pittsburgh, united states \| hard (i) \| alisa kleybanova \| ashley harkleroad galina voskoboeva \| 6-4, 5-7, 6-1 \| \| 6 \| runner-up \| 4 \| 2007-02-11 00:00:00 \| midland, united states \| hard (i) \| maureen drake \| laura granville abigail spears \| 4-6, 6-3, 3-6 \| \| 7 \| runner-up \| 5 \| 2007-07-07 00:00:00 \| southlake, united states \| hard \| valerie tetreault \| surina de beer kim grant \| 6-4, 4-6, 4-6 \| \| 8 \| winner \| 4 \| 2007-07-22 00:00:00 \| hamilton, canada \| clay \| surina de beer \| michaela johansson paula zabala \| walkover \| \| 9 \| winner \| 5 \| 2007-08-04 00:00:00 \| vancouver, canada \| hard \| marie-eve pelletier \| soledad esperon agustina lepore \| 6-4, 6-4 \| \| 10 \| winner \| 6 \| 2007-10-21 00:00:00 \| lawrenceville, united states \| hard \| alisa kleybanova \| leanne baker julie ditty \| 6-2, 6-0 \| \| 11 \| winner \| 7 \| 2007-11-12 00:00:00 \| pittsburgh, united states \| hard (i) \| alisa kleybanova \| raquel kops-jones abigail spears \| 6-4, 4-6, [10-6] \| \| 12 \| runner-up \| 6 \| 2008-04-27 00:00:00 \| dothan, united states \| clay \| maria fernanda alves \| tetiana luzhanska michaela pastikova \| 1-6, 3-6 \| \| 13 \| winner \| 8 \| 2008-10-18 00:00:00 \| toronto, canada \| hard (i) \| marie-eve pelletier \| nikola frankova carmen klaschka \| 6-4, 6-2 \| \| 14 \| runner-up \| 7 \| 2009-09-27 00:00:00 \| saguenay, canada \| hard (i) \| rebecca marino \| sofia arvidsson severine bremond beltrame \| 3-6, 1-6 \| \| 15 \| runner-up \| 8 \| 2013-04-13 00:00:00 \| poza rica, mexico \| hard \| olga savchuk \| maria fernanda alvarez teran maria fernanda alves \| 2-6, 3-6 \| \| 16 \| runner-up \| 9 \| 2013-05-18 00:00:00 \| saint-gaudens, france \| clay \| kurumi nara \| julia glushko paula ormaechea \| 5-7, 6-7(11-13) \|	\| \| no. \| \|---:\|------:\| \| 0 \| 1 \| \| 1 \| 2 \| \| 2 \| 3 \| \| 3 \| 4 \| \| 4 \| 5 \| \| 5 \| 6 \| \| 6 \| 7 \| \| 7 \| 8 \| \| 8 \| 9 \|	[ [ 1, 4025, 1158, 18, 1625, 12884, 273, 296, 18156, 17, 416, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 21672, 1757, 451, 34, 203, 1377, 411, 451, 34, 2135, 17347, 451, 34, 203, 1377, 411, 451, 34, 712, 1757, 451, 34, 203, 1377, 411, 451, 34, 869, 30751, 1757, 451, 34, 203, 1377, 411, 451, 34, 18266, 1757, 451, 34, 203, 1377, 411, 451, 34, 31993, 1757, 451, 34, 203, 1377, 411, 451, 34, 556, 1029, 87, 1757, 451, 34, 203, 1377, 411, 451, 34, 6355, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 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select count ( * ) where year = 1985 and code = 'h' col : code \| year row 1 : a \| 1927 row 2 : b \| 1928 row 3 : c \| 1929 row 4 : ch \| 1930 row 5 : d \| 1931 row 6 : e \| 1932 row 7 : f \| 1933 row 8 : g \| 1934 row 9 : h \| 1935 row 10 : i \| 1936 row 11 : j \| 1937 row 12 : k \| 1938 row 13 : l \| 1939 row 14 : ll \| 1940 row 15 : m \| 1941 row 16 : n \| 1942 row 17 : n \| 1943 row 18 : o \| 1944 row 19 : p \| 1945 row 20 : q \| 1946 row 21 : r \| 1947 row 22 : s \| 1948 row 23 : t \| 1949 row 24 : u \| 1950 row 25 : v \| 1951 row 26 : x \| 1952 row 27 : y \| 1953 row 28 : z \| 1954 row 29 : a1 \| 1955 row 30 : b1 \| 1956 row 31 : c1 \| 1957 row 32 : ch1 \| none row 33 : d1 \| 1958 row 34 : e1 \| 1959 row 35 : f1 \| 1960 row 36 : g1 \| 1961 row 37 : h1 \| 1962 row 38 : i1 \| 1963 row 39 : j1 \| 1964 row 40 : k1 \| 1965 row 41 : l1 \| 1966 row 42 : ll1 \| none row 43 : m1 \| 1967 row 44 : n1 \| 1968 row 45 : n1 \| 1969 row 46 : o1 \| 1970 row 47 : p1 \| 1971 row 48 : q1 \| 1972 row 49 : r1 \| 1973 row 50 : s1 \| 1974 row 51 : t1 \| 1975 row 52 : u1 \| 1976 row 53 : v1 \| 1977 row 54 : x1 \| 1978 row 55 : y1 \| 1979 row 56 : z1 \| 1980 row 57 : a2 \| 1981 row 58 : b2 \| 1982 row 59 : c2 \| 1983 row 60 : ch2 \| none row 61 : d2 \| 1984 row 62 : e2 \| 1985 row 63 : f2 \| 1986 row 64 : g2 \| 1987 row 65 : h2 \| 1988 row 66 : i2 \| 1989 row 67 : j2 \| 1990 row 68 : k2 \| 1991 row 69 : l2 \| 1992 row 70 : ll2 \| none row 71 : m2 \| 1993 row 72 : n2 \| 1994 row 73 : n2 \| 1995 row 74 : o2 \| 1996 row 75 : p2 \| 1997 row 76 : q2 \| 1998 row 77 : r2 \| 1999 row 78 : s2 \| 2000 row 79 : t2 \| 2001 row 80 : u2 \| 2002 row 81 : v2 \| 2003 row 82 : x2 \| 2004 row 83 : y2 \| 2005 row 84 : z2 \| 2006	col : count ( "*" ) row 1 : 0	select count ( * ) where year = 1985 and code = 'h' <table_name> : table \begin{tabular}{lll} \toprule & code & year \\ \midrule 0 & a & 1927 \\ 1 & b & 1928 \\ 2 & c & 1929 \\ 3 & ch & 1930 \\ 4 & d & 1931 \\ 5 & e & 1932 \\ 6 & f & 1933 \\ 7 & g & 1934 \\ 8 & h & 1935 \\ 9 & i & 1936 \\ 10 & j & 1937 \\ 11 & k & 1938 \\ 12 & l & 1939 \\ 13 & ll & 1940 \\ 14 & m & 1941 \\ 15 & n & 1942 \\ 16 & n & 1943 \\ 17 & o & 1944 \\ 18 & p & 1945 \\ 19 & q & 1946 \\ 20 & r & 1947 \\ 21 & s & 1948 \\ 22 & t & 1949 \\ 23 & u & 1950 \\ 24 & v & 1951 \\ 25 & x & 1952 \\ 26 & y & 1953 \\ 27 & z & 1954 \\ 28 & a1 & 1955 \\ 29 & b1 & 1956 \\ 30 & c1 & 1957 \\ 31 & ch1 & none \\ 32 & d1 & 1958 \\ 33 & e1 & 1959 \\ 34 & f1 & 1960 \\ 35 & g1 & 1961 \\ 36 & h1 & 1962 \\ 37 & i1 & 1963 \\ 38 & j1 & 1964 \\ 39 & k1 & 1965 \\ 40 & l1 & 1966 \\ 41 & ll1 & none \\ 42 & m1 & 1967 \\ 43 & n1 & 1968 \\ 44 & n1 & 1969 \\ 45 & o1 & 1970 \\ 46 & p1 & 1971 \\ 47 & q1 & 1972 \\ 48 & r1 & 1973 \\ 49 & s1 & 1974 \\ 50 & t1 & 1975 \\ 51 & u1 & 1976 \\ 52 & v1 & 1977 \\ 53 & x1 & 1978 \\ 54 & y1 & 1979 \\ 55 & z1 & 1980 \\ 56 & a2 & 1981 \\ 57 & b2 & 1982 \\ 58 & c2 & 1983 \\ 59 & ch2 & none \\ 60 & d2 & 1984 \\ 61 & e2 & 1985 \\ 62 & f2 & 1986 \\ 63 & g2 & 1987 \\ 64 & h2 & 1988 \\ 65 & i2 & 1989 \\ 66 & j2 & 1990 \\ 67 & k2 & 1991 \\ 68 & l2 & 1992 \\ 69 & ll2 & none \\ 70 & m2 & 1993 \\ 71 & n2 & 1994 \\ 72 & n2 & 1995 \\ 73 & o2 & 1996 \\ 74 & p2 & 1997 \\ 75 & q2 & 1998 \\ 76 & r2 & 1999 \\ 77 & s2 & 2000 \\ 78 & t2 & 2001 \\ 79 & u2 & 2002 \\ 80 & v2 & 2003 \\ 81 & x2 & 2004 \\ 82 & y2 & 2005 \\ 83 & z2 & 2006 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where year = 1985 and code = 'h' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>code</th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>a</td> <td>1927</td> </tr> <tr> <th>1</th> <td>b</td> <td>1928</td> </tr> <tr> <th>2</th> <td>c</td> <td>1929</td> </tr> <tr> <th>3</th> <td>ch</td> <td>1930</td> </tr> <tr> <th>4</th> <td>d</td> <td>1931</td> </tr> <tr> <th>5</th> <td>e</td> <td>1932</td> </tr> <tr> <th>6</th> <td>f</td> <td>1933</td> </tr> <tr> <th>7</th> <td>g</td> <td>1934</td> </tr> <tr> <th>8</th> <td>h</td> <td>1935</td> </tr> <tr> <th>9</th> <td>i</td> <td>1936</td> </tr> <tr> <th>10</th> <td>j</td> <td>1937</td> </tr> <tr> <th>11</th> <td>k</td> <td>1938</td> </tr> <tr> <th>12</th> <td>l</td> <td>1939</td> </tr> <tr> <th>13</th> <td>ll</td> <td>1940</td> </tr> <tr> <th>14</th> <td>m</td> <td>1941</td> </tr> <tr> <th>15</th> <td>n</td> <td>1942</td> </tr> <tr> <th>16</th> <td>n</td> <td>1943</td> </tr> <tr> <th>17</th> <td>o</td> <td>1944</td> </tr> <tr> <th>18</th> <td>p</td> <td>1945</td> </tr> <tr> <th>19</th> <td>q</td> <td>1946</td> </tr> <tr> <th>20</th> <td>r</td> <td>1947</td> </tr> <tr> <th>21</th> <td>s</td> <td>1948</td> </tr> <tr> <th>22</th> <td>t</td> <td>1949</td> </tr> <tr> <th>23</th> <td>u</td> <td>1950</td> </tr> <tr> <th>24</th> <td>v</td> <td>1951</td> </tr> <tr> <th>25</th> <td>x</td> <td>1952</td> </tr> <tr> <th>26</th> <td>y</td> <td>1953</td> </tr> <tr> <th>27</th> <td>z</td> <td>1954</td> </tr> <tr> <th>28</th> <td>a1</td> <td>1955</td> </tr> <tr> <th>29</th> <td>b1</td> <td>1956</td> </tr> <tr> <th>30</th> <td>c1</td> <td>1957</td> </tr> <tr> <th>31</th> <td>ch1</td> <td>none</td> </tr> <tr> <th>32</th> <td>d1</td> <td>1958</td> </tr> <tr> <th>33</th> <td>e1</td> <td>1959</td> </tr> <tr> <th>34</th> <td>f1</td> <td>1960</td> </tr> <tr> <th>35</th> <td>g1</td> <td>1961</td> </tr> <tr> <th>36</th> <td>h1</td> <td>1962</td> </tr> <tr> <th>37</th> <td>i1</td> <td>1963</td> </tr> <tr> <th>38</th> <td>j1</td> <td>1964</td> </tr> <tr> <th>39</th> <td>k1</td> <td>1965</td> </tr> <tr> <th>40</th> <td>l1</td> <td>1966</td> </tr> <tr> <th>41</th> <td>ll1</td> <td>none</td> </tr> <tr> <th>42</th> <td>m1</td> <td>1967</td> </tr> <tr> <th>43</th> <td>n1</td> <td>1968</td> </tr> <tr> <th>44</th> <td>n1</td> <td>1969</td> </tr> <tr> <th>45</th> <td>o1</td> <td>1970</td> </tr> <tr> <th>46</th> <td>p1</td> <td>1971</td> </tr> <tr> <th>47</th> <td>q1</td> <td>1972</td> </tr> <tr> <th>48</th> <td>r1</td> <td>1973</td> </tr> <tr> <th>49</th> <td>s1</td> <td>1974</td> </tr> <tr> <th>50</th> <td>t1</td> <td>1975</td> </tr> <tr> <th>51</th> <td>u1</td> <td>1976</td> </tr> <tr> <th>52</th> <td>v1</td> <td>1977</td> </tr> <tr> <th>53</th> <td>x1</td> <td>1978</td> </tr> <tr> <th>54</th> <td>y1</td> <td>1979</td> </tr> <tr> <th>55</th> <td>z1</td> <td>1980</td> </tr> <tr> <th>56</th> <td>a2</td> <td>1981</td> </tr> <tr> <th>57</th> <td>b2</td> <td>1982</td> </tr> <tr> <th>58</th> <td>c2</td> <td>1983</td> </tr> <tr> <th>59</th> <td>ch2</td> <td>none</td> </tr> <tr> <th>60</th> <td>d2</td> <td>1984</td> </tr> <tr> <th>61</th> <td>e2</td> <td>1985</td> </tr> <tr> <th>62</th> <td>f2</td> <td>1986</td> </tr> <tr> <th>63</th> <td>g2</td> <td>1987</td> </tr> <tr> <th>64</th> <td>h2</td> <td>1988</td> </tr> <tr> <th>65</th> <td>i2</td> <td>1989</td> </tr> <tr> <th>66</th> <td>j2</td> <td>1990</td> </tr> <tr> <th>67</th> <td>k2</td> <td>1991</td> </tr> <tr> <th>68</th> <td>l2</td> <td>1992</td> </tr> <tr> <th>69</th> <td>ll2</td> <td>none</td> </tr> <tr> <th>70</th> <td>m2</td> <td>1993</td> </tr> <tr> <th>71</th> <td>n2</td> <td>1994</td> </tr> <tr> <th>72</th> <td>n2</td> <td>1995</td> </tr> <tr> <th>73</th> <td>o2</td> <td>1996</td> </tr> <tr> <th>74</th> <td>p2</td> <td>1997</td> </tr> <tr> <th>75</th> <td>q2</td> <td>1998</td> </tr> <tr> <th>76</th> <td>r2</td> <td>1999</td> </tr> <tr> <th>77</th> <td>s2</td> <td>2000</td> </tr> <tr> <th>78</th> <td>t2</td> <td>2001</td> </tr> <tr> <th>79</th> <td>u2</td> <td>2002</td> </tr> <tr> <th>80</th> <td>v2</td> <td>2003</td> </tr> <tr> <th>81</th> <td>x2</td> <td>2004</td> </tr> <tr> <th>82</th> <td>y2</td> <td>2005</td> </tr> <tr> <th>83</th> <td>z2</td> <td>2006</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where year = 1985 and code = 'h' <table_name> : table \| \| code \| year \| \|---:\|:-------\|:-------\| \| 0 \| a \| 1927 \| \| 1 \| b \| 1928 \| \| 2 \| c \| 1929 \| \| 3 \| ch \| 1930 \| \| 4 \| d \| 1931 \| \| 5 \| e \| 1932 \| \| 6 \| f \| 1933 \| \| 7 \| g \| 1934 \| \| 8 \| h \| 1935 \| \| 9 \| i \| 1936 \| \| 10 \| j \| 1937 \| \| 11 \| k \| 1938 \| \| 12 \| l \| 1939 \| \| 13 \| ll \| 1940 \| \| 14 \| m \| 1941 \| \| 15 \| n \| 1942 \| \| 16 \| n \| 1943 \| \| 17 \| o \| 1944 \| \| 18 \| p \| 1945 \| \| 19 \| q \| 1946 \| \| 20 \| r \| 1947 \| \| 21 \| s \| 1948 \| \| 22 \| t \| 1949 \| \| 23 \| u \| 1950 \| \| 24 \| v \| 1951 \| \| 25 \| x \| 1952 \| \| 26 \| y \| 1953 \| \| 27 \| z \| 1954 \| \| 28 \| a1 \| 1955 \| \| 29 \| b1 \| 1956 \| \| 30 \| c1 \| 1957 \| \| 31 \| ch1 \| none \| \| 32 \| d1 \| 1958 \| \| 33 \| e1 \| 1959 \| \| 34 \| f1 \| 1960 \| \| 35 \| g1 \| 1961 \| \| 36 \| h1 \| 1962 \| \| 37 \| i1 \| 1963 \| \| 38 \| j1 \| 1964 \| \| 39 \| k1 \| 1965 \| \| 40 \| l1 \| 1966 \| \| 41 \| ll1 \| none \| \| 42 \| m1 \| 1967 \| \| 43 \| n1 \| 1968 \| \| 44 \| n1 \| 1969 \| \| 45 \| o1 \| 1970 \| \| 46 \| p1 \| 1971 \| \| 47 \| q1 \| 1972 \| \| 48 \| r1 \| 1973 \| \| 49 \| s1 \| 1974 \| \| 50 \| t1 \| 1975 \| \| 51 \| u1 \| 1976 \| \| 52 \| v1 \| 1977 \| \| 53 \| x1 \| 1978 \| \| 54 \| y1 \| 1979 \| \| 55 \| z1 \| 1980 \| \| 56 \| a2 \| 1981 \| \| 57 \| b2 \| 1982 \| \| 58 \| c2 \| 1983 \| \| 59 \| ch2 \| none \| \| 60 \| d2 \| 1984 \| \| 61 \| e2 \| 1985 \| \| 62 \| f2 \| 1986 \| \| 63 \| g2 \| 1987 \| \| 64 \| h2 \| 1988 \| \| 65 \| i2 \| 1989 \| \| 66 \| j2 \| 1990 \| \| 67 \| k2 \| 1991 \| \| 68 \| l2 \| 1992 \| \| 69 \| ll2 \| none \| \| 70 \| m2 \| 1993 \| \| 71 \| n2 \| 1994 \| \| 72 \| n2 \| 1995 \| \| 73 \| o2 \| 1996 \| \| 74 \| p2 \| 1997 \| \| 75 \| q2 \| 1998 \| \| 76 \| r2 \| 1999 \| \| 77 \| s2 \| 2000 \| \| 78 \| t2 \| 2001 \| \| 79 \| u2 \| 2002 \| \| 80 \| v2 \| 2003 \| \| 81 \| x2 \| 2004 \| \| 82 \| y2 \| 2005 \| \| 83 \| z2 \| 2006 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 3286, 273, 5342, 7140, 471, 981, 273, 296, 76, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 710, 1757, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 69, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 3657, 5324, 1757, 4465, 34, 203, 565, 7765, 313, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 21, 1757, 451, 34, 203, 1377, 411, 4465, 34, 70, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 3657, 6030, 1757, 4465, 34, 203, 565, 7765, 313, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 22, 1757, 451, 34, 203, 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select notes where position = '7th' col : year \| competition \| venue \| position \| event \| notes row 1 : 2003 \| world youth championships \| sherbrooke, canada \| 7th \| hammer \| 54.43 m row 2 : 2005 \| alba games \| la habana, cuba \| 1st \| hammer \| 63.30 m row 3 : 2005 \| central american and caribbean championships \| nassau, bahamas \| 4th \| hammer \| 60.49 m row 4 : 2005 \| pan american junior championships \| windsor, canada \| 1st \| hammer \| 64.80 m row 5 : 2006 \| nacac u23 championships \| santo domingo, dominican republic \| 2nd \| hammer \| 66.28 m row 6 : 2007 \| pan american games \| rio de janeiro, brazil \| 2nd \| hammer \| 68.70 m row 7 : 2007 \| world championships \| osaka, japan \| 9th \| hammer \| 70.20 m row 8 : 2008 \| olympic games \| beijing, china \| 15th (q) \| hammer \| 68.74 m row 9 : 2009 \| alba games \| la habana, cuba \| 2nd \| hammer \| 68.89 m row 10 : 2009 \| central american and caribbean championships \| havana, cuba \| 1st \| hammer \| 71.32 m row 11 : 2009 \| world championships \| berlin, germany \| 16th (q) \| hammer \| 69.97 m row 12 : 2011 \| pan american games \| guadalajara, mexico \| 4th \| hammer \| 68.88 m row 13 : 2012 \| olympic games \| london, united kingdom \| 23rd (q) \| hammer \| 67.93 m	col : notes row 1 : 54.43 m	select notes where position = '7th' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 2003 & world youth championships & sherbrooke, canada & 7th & hammer & 54.43 m \\ 1 & 2005 & alba games & la habana, cuba & 1st & hammer & 63.30 m \\ 2 & 2005 & central american and caribbean championships & nassau, bahamas & 4th & hammer & 60.49 m \\ 3 & 2005 & pan american junior championships & windsor, canada & 1st & hammer & 64.80 m \\ 4 & 2006 & nacac u23 championships & santo domingo, dominican republic & 2nd & hammer & 66.28 m \\ 5 & 2007 & pan american games & rio de janeiro, brazil & 2nd & hammer & 68.70 m \\ 6 & 2007 & world championships & osaka, japan & 9th & hammer & 70.20 m \\ 7 & 2008 & olympic games & beijing, china & 15th (q) & hammer & 68.74 m \\ 8 & 2009 & alba games & la habana, cuba & 2nd & hammer & 68.89 m \\ 9 & 2009 & central american and caribbean championships & havana, cuba & 1st & hammer & 71.32 m \\ 10 & 2009 & world championships & berlin, germany & 16th (q) & hammer & 69.97 m \\ 11 & 2011 & pan american games & guadalajara, mexico & 4th & hammer & 68.88 m \\ 12 & 2012 & olympic games & london, united kingdom & 23rd (q) & hammer & 67.93 m \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & notes \\ \midrule 0 & 54.43 m \\ \bottomrule \end{tabular}	select notes where position = '7th' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2003</td> <td>world youth championships</td> <td>sherbrooke, canada</td> <td>7th</td> <td>hammer</td> <td>54.43 m</td> </tr> <tr> <th>1</th> <td>2005</td> <td>alba games</td> <td>la habana, cuba</td> <td>1st</td> <td>hammer</td> <td>63.30 m</td> </tr> <tr> <th>2</th> <td>2005</td> <td>central american and caribbean championships</td> <td>nassau, bahamas</td> <td>4th</td> <td>hammer</td> <td>60.49 m</td> </tr> <tr> <th>3</th> <td>2005</td> <td>pan american junior championships</td> <td>windsor, canada</td> <td>1st</td> <td>hammer</td> <td>64.80 m</td> </tr> <tr> <th>4</th> <td>2006</td> <td>nacac u23 championships</td> <td>santo domingo, dominican republic</td> <td>2nd</td> <td>hammer</td> <td>66.28 m</td> </tr> <tr> <th>5</th> <td>2007</td> <td>pan american games</td> <td>rio de janeiro, brazil</td> <td>2nd</td> <td>hammer</td> <td>68.70 m</td> </tr> <tr> <th>6</th> <td>2007</td> <td>world championships</td> <td>osaka, japan</td> <td>9th</td> <td>hammer</td> <td>70.20 m</td> </tr> <tr> <th>7</th> <td>2008</td> <td>olympic games</td> <td>beijing, china</td> <td>15th (q)</td> <td>hammer</td> <td>68.74 m</td> </tr> <tr> <th>8</th> <td>2009</td> <td>alba games</td> <td>la habana, cuba</td> <td>2nd</td> <td>hammer</td> <td>68.89 m</td> </tr> <tr> <th>9</th> <td>2009</td> <td>central american and caribbean championships</td> <td>havana, cuba</td> <td>1st</td> <td>hammer</td> <td>71.32 m</td> </tr> <tr> <th>10</th> <td>2009</td> <td>world championships</td> <td>berlin, germany</td> <td>16th (q)</td> <td>hammer</td> <td>69.97 m</td> </tr> <tr> <th>11</th> <td>2011</td> <td>pan american games</td> <td>guadalajara, mexico</td> <td>4th</td> <td>hammer</td> <td>68.88 m</td> </tr> <tr> <th>12</th> <td>2012</td> <td>olympic games</td> <td>london, united kingdom</td> <td>23rd (q)</td> <td>hammer</td> <td>67.93 m</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>54.43 m</td> </tr> </tbody> </table>	select notes where position = '7th' <table_name> : table \| \| year \| competition \| venue \| position \| event \| notes \| \|---:\|-------:\|:---------------------------------------------\|:----------------------------------\|:-----------\|:--------\|:--------\| \| 0 \| 2003 \| world youth championships \| sherbrooke, canada \| 7th \| hammer \| 54.43 m \| \| 1 \| 2005 \| alba games \| la habana, cuba \| 1st \| hammer \| 63.30 m \| \| 2 \| 2005 \| central american and caribbean championships \| nassau, bahamas \| 4th \| hammer \| 60.49 m \| \| 3 \| 2005 \| pan american junior championships \| windsor, canada \| 1st \| hammer \| 64.80 m \| \| 4 \| 2006 \| nacac u23 championships \| santo domingo, dominican republic \| 2nd \| hammer \| 66.28 m \| \| 5 \| 2007 \| pan american games \| rio de janeiro, brazil \| 2nd \| hammer \| 68.70 m \| \| 6 \| 2007 \| world championships \| osaka, japan \| 9th \| hammer \| 70.20 m \| \| 7 \| 2008 \| olympic games \| beijing, china \| 15th (q) \| hammer \| 68.74 m \| \| 8 \| 2009 \| alba games \| la habana, cuba \| 2nd \| hammer \| 68.89 m \| \| 9 \| 2009 \| central american and caribbean championships \| havana, cuba \| 1st \| hammer \| 71.32 m \| \| 10 \| 2009 \| world championships \| berlin, germany \| 16th (q) \| hammer \| 69.97 m \| \| 11 \| 2011 \| pan american games \| guadalajara, mexico \| 4th \| hammer \| 68.88 m \| \| 12 \| 2012 \| olympic games \| london, united kingdom \| 23rd (q) \| hammer \| 67.93 m \|	\| \| notes \| \|---:\|:--------\| \| 0 \| 54.43 m \|	[ [ 1, 4025, 10913, 1625, 1754, 273, 296, 27, 451, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 31942, 608, 1757, 451, 34, 203, 1377, 411, 451, 34, 24612, 1757, 451, 34, 203, 1377, 411, 451, 34, 3276, 1757, 451, 34, 203, 1377, 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select count ( winner ) where route = 'peyrehorade - bayonne' col : stage \| date \| route \| terrain \| length \| winner row 1 : 1 \| 22 june \| rennes - lisieux \| plain stage \| 215 km (134 mi) \| edward sels (bel) row 2 : 2 \| 23 june \| lisieux - amiens \| plain stage \| 208 km (129 mi) \| andre darrigade (fra) row 3 : 3a \| 24 june \| amiens - forest \| plain stage \| 197 km (122 mi) \| bernard vandekerkhove (bel) row 4 : 3b \| 24 june \| forest - forest \| team time trial \| 21 km (13 mi) \| kas-kaskol row 5 : 4 \| 25 june \| forest - metz \| plain stage \| 292 km (181 mi) \| rudi altig (ger) row 6 : 5 \| 26 june \| metz - freiburg \| plain stage \| 161 km (100 mi) \| willy derboven (bel) row 7 : 6 \| 27 june \| freiburg - besancon \| plain stage \| 200 km (120 mi) \| henk nijdam (ned) row 8 : 7 \| 28 june \| besancon - thonon-les-bains \| plain stage \| 195 km (121 mi) \| jan janssen (ned) row 9 : 8 \| 29 june \| thonon-les-bains - briancon \| stage with mountain(s) \| 249 km (155 mi) \| federico bahamontes (esp) row 10 : 9 \| 30 june \| briancon - monaco \| stage with mountain(s) \| 239 km (149 mi) \| jacques anquetil (fra) row 11 : 10a \| 1 july \| monaco - hyeres \| plain stage \| 187 km (116 mi) \| jan janssen (ned) row 12 : 10b \| 1 july \| hyeres - toulon \| individual time trial \| 21 km (13 mi) \| jacques anquetil (fra) row 13 : 11 \| 2 july \| toulon - montpellier \| plain stage \| 250 km (160 mi) \| edward sels (bel) row 14 : 12 \| 3 july \| montpellier - perpignan \| plain stage \| 174 km (108 mi) \| jo de roo (ned) row 15 : 13 \| 4 july \| perpignan - andorra \| stage with mountain(s) \| 170 km (110 mi) \| julio jimenez (esp) row 16 : 14 \| 6 july \| andorra - toulouse \| stage with mountain(s) \| 186 km (116 mi) \| edward sels (bel) row 17 : 15 \| 7 july \| toulouse - luchon \| stage with mountain(s) \| 203 km (126 mi) \| raymond poulidor (fra) row 18 : 16 \| 8 july \| luchon - pau \| stage with mountain(s) \| 197 km (122 mi) \| federico bahamontes (esp) row 19 : 17 \| 9 july \| peyrehorade - bayonne \| individual time trial \| 43 km (27 mi) \| jacques anquetil (fra) row 20 : 18 \| 10 july \| bayonne - bordeaux \| plain stage \| 187 km (116 mi) \| andre darrigade (fra) row 21 : 19 \| 11 july \| bordeaux - brive \| plain stage \| 215 km (134 mi) \| edward sels (bel) row 22 : 20 \| 12 july \| brive - puy de dome \| stage with mountain(s) \| 217 km (135 mi) \| julio jimenez (esp) row 23 : 21 \| 13 july \| clermont-ferrand - orleans \| plain stage \| 311 km (193 mi) \| jean stablinski (fra) row 24 : 22a \| 14 july \| orleans - versailles \| plain stage \| 119 km (74 mi) \| benoni beheyt (bel) row 25 : 22b \| 14 july \| versailles - paris \| individual time trial \| 27 km (17 mi) \| jacques anquetil (fra)	col : count ( "winner" ) row 1 : 1	select count ( winner ) where route = 'peyrehorade - bayonne' <table_name> : table \begin{tabular}{lllllll} \toprule & stage & date & route & terrain & length & winner \\ \midrule 0 & 1 & 22 june & rennes - lisieux & plain stage & 215 km (134 mi) & edward sels (bel) \\ 1 & 2 & 23 june & lisieux - amiens & plain stage & 208 km (129 mi) & andre darrigade (fra) \\ 2 & 3a & 24 june & amiens - forest & plain stage & 197 km (122 mi) & bernard vandekerkhove (bel) \\ 3 & 3b & 24 june & forest - forest & team time trial & 21 km (13 mi) & kas-kaskol \\ 4 & 4 & 25 june & forest - metz & plain stage & 292 km (181 mi) & rudi altig (ger) \\ 5 & 5 & 26 june & metz - freiburg & plain stage & 161 km (100 mi) & willy derboven (bel) \\ 6 & 6 & 27 june & freiburg - besancon & plain stage & 200 km (120 mi) & henk nijdam (ned) \\ 7 & 7 & 28 june & besancon - thonon-les-bains & plain stage & 195 km (121 mi) & jan janssen (ned) \\ 8 & 8 & 29 june & thonon-les-bains - briancon & stage with mountain(s) & 249 km (155 mi) & federico bahamontes (esp) \\ 9 & 9 & 30 june & briancon - monaco & stage with mountain(s) & 239 km (149 mi) & jacques anquetil (fra) \\ 10 & 10a & 1 july & monaco - hyeres & plain stage & 187 km (116 mi) & jan janssen (ned) \\ 11 & 10b & 1 july & hyeres - toulon & individual time trial & 21 km (13 mi) & jacques anquetil (fra) \\ 12 & 11 & 2 july & toulon - montpellier & plain stage & 250 km (160 mi) & edward sels (bel) \\ 13 & 12 & 3 july & montpellier - perpignan & plain stage & 174 km (108 mi) & jo de roo (ned) \\ 14 & 13 & 4 july & perpignan - andorra & stage with mountain(s) & 170 km (110 mi) & julio jimenez (esp) \\ 15 & 14 & 6 july & andorra - toulouse & stage with mountain(s) & 186 km (116 mi) & edward sels (bel) \\ 16 & 15 & 7 july & toulouse - luchon & stage with mountain(s) & 203 km (126 mi) & raymond poulidor (fra) \\ 17 & 16 & 8 july & luchon - pau & stage with mountain(s) & 197 km (122 mi) & federico bahamontes (esp) \\ 18 & 17 & 9 july & peyrehorade - bayonne & individual time trial & 43 km (27 mi) & jacques anquetil (fra) \\ 19 & 18 & 10 july & bayonne - bordeaux & plain stage & 187 km (116 mi) & andre darrigade (fra) \\ 20 & 19 & 11 july & bordeaux - brive & plain stage & 215 km (134 mi) & edward sels (bel) \\ 21 & 20 & 12 july & brive - puy de dome & stage with mountain(s) & 217 km (135 mi) & julio jimenez (esp) \\ 22 & 21 & 13 july & clermont-ferrand - orleans & plain stage & 311 km (193 mi) & jean stablinski (fra) \\ 23 & 22a & 14 july & orleans - versailles & plain stage & 119 km (74 mi) & benoni beheyt (bel) \\ 24 & 22b & 14 july & versailles - paris & individual time trial & 27 km (17 mi) & jacques anquetil (fra) \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "winner" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( winner ) where route = 'peyrehorade - bayonne' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>stage</th> <th>date</th> <th>route</th> <th>terrain</th> <th>length</th> <th>winner</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>22 june</td> <td>rennes - lisieux</td> <td>plain stage</td> <td>215 km (134 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>1</th> <td>2</td> <td>23 june</td> <td>lisieux - amiens</td> <td>plain stage</td> <td>208 km (129 mi)</td> <td>andre darrigade (fra)</td> </tr> <tr> <th>2</th> <td>3a</td> <td>24 june</td> <td>amiens - forest</td> <td>plain stage</td> <td>197 km (122 mi)</td> <td>bernard vandekerkhove (bel)</td> </tr> <tr> <th>3</th> <td>3b</td> <td>24 june</td> <td>forest - forest</td> <td>team time trial</td> <td>21 km (13 mi)</td> <td>kas-kaskol</td> </tr> <tr> <th>4</th> <td>4</td> <td>25 june</td> <td>forest - metz</td> <td>plain stage</td> <td>292 km (181 mi)</td> <td>rudi altig (ger)</td> </tr> <tr> <th>5</th> <td>5</td> <td>26 june</td> <td>metz - freiburg</td> <td>plain stage</td> <td>161 km (100 mi)</td> <td>willy derboven (bel)</td> </tr> <tr> <th>6</th> <td>6</td> <td>27 june</td> <td>freiburg - besancon</td> <td>plain stage</td> <td>200 km (120 mi)</td> <td>henk nijdam (ned)</td> </tr> <tr> <th>7</th> <td>7</td> <td>28 june</td> <td>besancon - thonon-les-bains</td> <td>plain stage</td> <td>195 km (121 mi)</td> <td>jan janssen (ned)</td> </tr> <tr> <th>8</th> <td>8</td> <td>29 june</td> <td>thonon-les-bains - briancon</td> <td>stage with mountain(s)</td> <td>249 km (155 mi)</td> <td>federico bahamontes (esp)</td> </tr> <tr> <th>9</th> <td>9</td> <td>30 june</td> <td>briancon - monaco</td> <td>stage with mountain(s)</td> <td>239 km (149 mi)</td> <td>jacques anquetil (fra)</td> </tr> <tr> <th>10</th> <td>10a</td> <td>1 july</td> <td>monaco - hyeres</td> <td>plain stage</td> <td>187 km (116 mi)</td> <td>jan janssen (ned)</td> </tr> <tr> <th>11</th> <td>10b</td> <td>1 july</td> <td>hyeres - toulon</td> <td>individual time trial</td> <td>21 km (13 mi)</td> <td>jacques anquetil (fra)</td> </tr> <tr> <th>12</th> <td>11</td> <td>2 july</td> <td>toulon - montpellier</td> <td>plain stage</td> <td>250 km (160 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>13</th> <td>12</td> <td>3 july</td> <td>montpellier - perpignan</td> <td>plain stage</td> <td>174 km (108 mi)</td> <td>jo de roo (ned)</td> </tr> <tr> <th>14</th> <td>13</td> <td>4 july</td> <td>perpignan - andorra</td> <td>stage with mountain(s)</td> <td>170 km (110 mi)</td> <td>julio jimenez (esp)</td> </tr> <tr> <th>15</th> <td>14</td> <td>6 july</td> <td>andorra - toulouse</td> <td>stage with mountain(s)</td> <td>186 km (116 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>16</th> <td>15</td> <td>7 july</td> <td>toulouse - luchon</td> <td>stage with mountain(s)</td> <td>203 km (126 mi)</td> <td>raymond poulidor (fra)</td> </tr> <tr> <th>17</th> <td>16</td> <td>8 july</td> <td>luchon - pau</td> <td>stage with mountain(s)</td> <td>197 km (122 mi)</td> <td>federico bahamontes (esp)</td> </tr> <tr> <th>18</th> <td>17</td> <td>9 july</td> <td>peyrehorade - bayonne</td> <td>individual time trial</td> <td>43 km (27 mi)</td> <td>jacques anquetil (fra)</td> </tr> <tr> <th>19</th> <td>18</td> <td>10 july</td> <td>bayonne - bordeaux</td> <td>plain stage</td> <td>187 km (116 mi)</td> <td>andre darrigade (fra)</td> </tr> <tr> <th>20</th> <td>19</td> <td>11 july</td> <td>bordeaux - brive</td> <td>plain stage</td> <td>215 km (134 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>21</th> <td>20</td> <td>12 july</td> <td>brive - puy de dome</td> <td>stage with mountain(s)</td> <td>217 km (135 mi)</td> <td>julio jimenez (esp)</td> </tr> <tr> <th>22</th> <td>21</td> <td>13 july</td> <td>clermont-ferrand - orleans</td> <td>plain stage</td> <td>311 km (193 mi)</td> <td>jean stablinski (fra)</td> </tr> <tr> <th>23</th> <td>22a</td> <td>14 july</td> <td>orleans - versailles</td> <td>plain stage</td> <td>119 km (74 mi)</td> <td>benoni beheyt (bel)</td> </tr> <tr> <th>24</th> <td>22b</td> <td>14 july</td> <td>versailles - paris</td> <td>individual time trial</td> <td>27 km (17 mi)</td> <td>jacques anquetil (fra)</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "winner" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( winner ) where route = 'peyrehorade - bayonne' <table_name> : table \| \| stage \| date \| route \| terrain \| length \| winner \| \|---:\|:--------\|:--------\|:----------------------------\|:-----------------------\|:----------------\|:----------------------------\| \| 0 \| 1 \| 22 june \| rennes - lisieux \| plain stage \| 215 km (134 mi) \| edward sels (bel) \| \| 1 \| 2 \| 23 june \| lisieux - amiens \| plain stage \| 208 km (129 mi) \| andre darrigade (fra) \| \| 2 \| 3a \| 24 june \| amiens - forest \| plain stage \| 197 km (122 mi) \| bernard vandekerkhove (bel) \| \| 3 \| 3b \| 24 june \| forest - forest \| team time trial \| 21 km (13 mi) \| kas-kaskol \| \| 4 \| 4 \| 25 june \| forest - metz \| plain stage \| 292 km (181 mi) \| rudi altig (ger) \| \| 5 \| 5 \| 26 june \| metz - freiburg \| plain stage \| 161 km (100 mi) \| willy derboven (bel) \| \| 6 \| 6 \| 27 june \| freiburg - besancon \| plain stage \| 200 km (120 mi) \| henk nijdam (ned) \| \| 7 \| 7 \| 28 june \| besancon - thonon-les-bains \| plain stage \| 195 km (121 mi) \| jan janssen (ned) \| \| 8 \| 8 \| 29 june \| thonon-les-bains - briancon \| stage with mountain(s) \| 249 km (155 mi) \| federico bahamontes (esp) \| \| 9 \| 9 \| 30 june \| briancon - monaco \| stage with mountain(s) \| 239 km (149 mi) \| jacques anquetil (fra) \| \| 10 \| 10a \| 1 july \| monaco - hyeres \| plain stage \| 187 km (116 mi) \| jan janssen (ned) \| \| 11 \| 10b \| 1 july \| hyeres - toulon \| individual time trial \| 21 km (13 mi) \| jacques anquetil (fra) \| \| 12 \| 11 \| 2 july \| toulon - montpellier \| plain stage \| 250 km (160 mi) \| edward sels (bel) \| \| 13 \| 12 \| 3 july \| montpellier - perpignan \| plain stage \| 174 km (108 mi) \| jo de roo (ned) \| \| 14 \| 13 \| 4 july \| perpignan - andorra \| stage with mountain(s) \| 170 km (110 mi) \| julio jimenez (esp) \| \| 15 \| 14 \| 6 july \| andorra - toulouse \| stage with mountain(s) \| 186 km (116 mi) \| edward sels (bel) \| \| 16 \| 15 \| 7 july \| toulouse - luchon \| stage with mountain(s) \| 203 km (126 mi) \| raymond poulidor (fra) \| \| 17 \| 16 \| 8 july \| luchon - pau \| stage with mountain(s) \| 197 km (122 mi) \| federico bahamontes (esp) \| \| 18 \| 17 \| 9 july \| peyrehorade - bayonne \| individual time trial \| 43 km (27 mi) \| jacques anquetil (fra) \| \| 19 \| 18 \| 10 july \| bayonne - bordeaux \| plain stage \| 187 km (116 mi) \| andre darrigade (fra) \| \| 20 \| 19 \| 11 july \| bordeaux - brive \| plain stage \| 215 km (134 mi) \| edward sels (bel) \| \| 21 \| 20 \| 12 july \| brive - puy de dome \| stage with mountain(s) \| 217 km (135 mi) \| julio jimenez (esp) \| \| 22 \| 21 \| 13 july \| clermont-ferrand - orleans \| plain stage \| 311 km (193 mi) \| jean stablinski (fra) \| \| 23 \| 22a \| 14 july \| orleans - versailles \| plain stage \| 119 km (74 mi) \| benoni beheyt (bel) \| \| 24 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select count ( team ) where team = 'los angeles raiders' col : year \| team \| games \| attempts \| yards \| ypc \| long \| tds row 1 : 1983 \| los angeles rams \| 16 \| 390 \| 1808 \| 4.6 \| 85 \| 18 row 2 : 1984 \| los angeles rams \| 16 \| 379 \| 2105 \| 5.6 \| 66 \| 14 row 3 : 1985 \| los angeles rams \| 14 \| 292 \| 1234 \| 4.2 \| 43 \| 12 row 4 : 1986 \| los angeles rams \| 16 \| 404 \| 1821 \| 4.5 \| 42 \| 11 row 5 : 1987 \| los angeles rams \| 3 \| 60 \| 277 \| 4.6 \| 57 \| 1 row 6 : 1987 \| indianapolis colts \| 9 \| 223 \| 1011 \| 4.5 \| 53 \| 5 row 7 : 1988 \| indianapolis colts \| 16 \| 388 \| 1659 \| 4.3 \| 41 \| 14 row 8 : 1989 \| indianapolis colts \| 15 \| 314 \| 1311 \| 4.2 \| 21 \| 7 row 9 : 1990 \| indianapolis colts \| 11 \| 166 \| 677 \| 4.1 \| 43 \| 4 row 10 : 1991 \| indianapolis colts \| 10 \| 167 \| 536 \| 3.2 \| 28 \| 2 row 11 : 1992 \| los angeles raiders \| 16 \| 187 \| 729 \| 3.9 \| 40 \| 2 row 12 : 1993 \| atlanta falcons \| 4 \| 26 \| 91 \| 3.5 \| 10 \| 0 row 13 : career \| none \| 146 \| 2996 \| 13259 \| 4.4 \| 85 \| 90	col : count ( "team" ) row 1 : 1	select count ( team ) where team = 'los angeles raiders' <table_name> : table \begin{tabular}{lllllllll} \toprule & year & team & games & attempts & yards & ypc & long & tds \\ \midrule 0 & 1983 & los angeles rams & 16 & 390 & 1808 & 4.6 & 85 & 18 \\ 1 & 1984 & los angeles rams & 16 & 379 & 2105 & 5.6 & 66 & 14 \\ 2 & 1985 & los angeles rams & 14 & 292 & 1234 & 4.2 & 43 & 12 \\ 3 & 1986 & los angeles rams & 16 & 404 & 1821 & 4.5 & 42 & 11 \\ 4 & 1987 & los angeles rams & 3 & 60 & 277 & 4.6 & 57 & 1 \\ 5 & 1987 & indianapolis colts & 9 & 223 & 1011 & 4.5 & 53 & 5 \\ 6 & 1988 & indianapolis colts & 16 & 388 & 1659 & 4.3 & 41 & 14 \\ 7 & 1989 & indianapolis colts & 15 & 314 & 1311 & 4.2 & 21 & 7 \\ 8 & 1990 & indianapolis colts & 11 & 166 & 677 & 4.1 & 43 & 4 \\ 9 & 1991 & indianapolis colts & 10 & 167 & 536 & 3.2 & 28 & 2 \\ 10 & 1992 & los angeles raiders & 16 & 187 & 729 & 3.9 & 40 & 2 \\ 11 & 1993 & atlanta falcons & 4 & 26 & 91 & 3.5 & 10 & 0 \\ 12 & career & none & 146 & 2996 & 13259 & 4.4 & 85 & 90 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "team" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( team ) where team = 'los angeles raiders' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>team</th> <th>games</th> <th>attempts</th> <th>yards</th> <th>ypc</th> <th>long</th> <th>tds</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1983</td> <td>los angeles rams</td> <td>16</td> <td>390</td> <td>1808</td> <td>4.6</td> <td>85</td> <td>18</td> </tr> <tr> <th>1</th> <td>1984</td> <td>los angeles rams</td> <td>16</td> <td>379</td> <td>2105</td> <td>5.6</td> <td>66</td> <td>14</td> </tr> <tr> <th>2</th> <td>1985</td> <td>los angeles rams</td> <td>14</td> <td>292</td> <td>1234</td> <td>4.2</td> <td>43</td> <td>12</td> </tr> <tr> <th>3</th> <td>1986</td> <td>los angeles rams</td> <td>16</td> <td>404</td> <td>1821</td> <td>4.5</td> <td>42</td> <td>11</td> </tr> <tr> <th>4</th> <td>1987</td> <td>los angeles rams</td> <td>3</td> <td>60</td> <td>277</td> <td>4.6</td> <td>57</td> <td>1</td> </tr> <tr> <th>5</th> <td>1987</td> <td>indianapolis colts</td> <td>9</td> <td>223</td> <td>1011</td> <td>4.5</td> <td>53</td> <td>5</td> </tr> <tr> <th>6</th> <td>1988</td> <td>indianapolis colts</td> <td>16</td> <td>388</td> <td>1659</td> <td>4.3</td> <td>41</td> <td>14</td> </tr> <tr> <th>7</th> <td>1989</td> <td>indianapolis colts</td> <td>15</td> <td>314</td> <td>1311</td> <td>4.2</td> <td>21</td> <td>7</td> </tr> <tr> <th>8</th> <td>1990</td> <td>indianapolis colts</td> <td>11</td> <td>166</td> <td>677</td> <td>4.1</td> <td>43</td> <td>4</td> </tr> <tr> <th>9</th> <td>1991</td> <td>indianapolis colts</td> <td>10</td> <td>167</td> <td>536</td> <td>3.2</td> <td>28</td> <td>2</td> </tr> <tr> <th>10</th> <td>1992</td> <td>los angeles raiders</td> <td>16</td> <td>187</td> <td>729</td> <td>3.9</td> <td>40</td> <td>2</td> </tr> <tr> <th>11</th> <td>1993</td> <td>atlanta falcons</td> <td>4</td> <td>26</td> <td>91</td> <td>3.5</td> <td>10</td> <td>0</td> </tr> <tr> <th>12</th> <td>career</td> <td>none</td> <td>146</td> <td>2996</td> <td>13259</td> <td>4.4</td> <td>85</td> <td>90</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "team" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( team ) where team = 'los angeles raiders' <table_name> : table \| \| year \| team \| games \| attempts \| yards \| ypc \| long \| tds \| \|---:\|:-------\|:--------------------\|--------:\|-----------:\|--------:\|------:\|-------:\|------:\| \| 0 \| 1983 \| los angeles rams \| 16 \| 390 \| 1808 \| 4.6 \| 85 \| 18 \| \| 1 \| 1984 \| los angeles rams \| 16 \| 379 \| 2105 \| 5.6 \| 66 \| 14 \| \| 2 \| 1985 \| los angeles rams \| 14 \| 292 \| 1234 \| 4.2 \| 43 \| 12 \| \| 3 \| 1986 \| los angeles rams \| 16 \| 404 \| 1821 \| 4.5 \| 42 \| 11 \| \| 4 \| 1987 \| los angeles rams \| 3 \| 60 \| 277 \| 4.6 \| 57 \| 1 \| \| 5 \| 1987 \| indianapolis colts \| 9 \| 223 \| 1011 \| 4.5 \| 53 \| 5 \| \| 6 \| 1988 \| indianapolis colts \| 16 \| 388 \| 1659 \| 4.3 \| 41 \| 14 \| \| 7 \| 1989 \| indianapolis colts \| 15 \| 314 \| 1311 \| 4.2 \| 21 \| 7 \| \| 8 \| 1990 \| indianapolis colts \| 11 \| 166 \| 677 \| 4.1 \| 43 \| 4 \| \| 9 \| 1991 \| indianapolis colts \| 10 \| 167 \| 536 \| 3.2 \| 28 \| 2 \| \| 10 \| 1992 \| los angeles raiders \| 16 \| 187 \| 729 \| 3.9 \| 40 \| 2 \| \| 11 \| 1993 \| atlanta falcons \| 4 \| 26 \| 91 \| 3.5 \| 10 \| 0 \| \| 12 \| career \| none \| 146 \| 2996 \| 13259 \| 4.4 \| 85 \| 90 \|	\| \| count ( "team" ) \| \|---:\|-------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 5927, 262, 1625, 5927, 273, 296, 383, 87, 7603, 19880, 767, 24290, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 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select result where attendance = 73483 col : date \| opponent# \| rank# \| site \| result \| attendance row 1 : september 11 \| baylor \| #14 \| ohio stadium • columbus, oh \| w 21-14 \| 88622 row 2 : september 18 \| at michigan state \| #12 \| spartan stadium • east lansing, mi \| w 31-10 \| 73483 row 3 : september 25 \| stanford \| #13 \| ohio stadium • columbus, oh \| l 20-23 \| 89436 row 4 : october 2 \| florida state \| none \| ohio stadium • columbus, oh \| l 17-34 \| 89491 row 5 : october 9 \| wisconsin \| none \| ohio stadium • columbus, oh \| l 0-6 \| 88344 row 6 : october 16 \| at #15 illinois \| none \| memorial stadium • champaign, il \| w 26-21 \| 73488 row 7 : october 23 \| at indiana \| none \| memorial stadium • bloomington, in \| w 49-25 \| 52,04 row 8 : october 30 \| purdue \| none \| ohio stadium • columbus, oh \| w 38-6 \| 89341 row 9 : november 6 \| minnesota \| none \| ohio stadium • columbus, oh \| w 35-10 \| 87666 row 10 : november 13 \| at northwestern \| none \| dyche stadium • evanston, il \| w 40-28 \| 30074 row 11 : november 20 \| #13 michigan \| none \| ohio stadium • columbus, oh \| w 24-14 \| 90252 row 12 : december 17 \| vs. byu \| #17 \| jack murphy stadium • san diego, ca (holiday bowl) \| w 47-17 \| 52533	col : result row 1 : w 31-10	select result where attendance = 73483 <table_name> : table \begin{tabular}{lllllll} \toprule & date & opponent# & rank# & site & result & attendance \\ \midrule 0 & september 11 & baylor & #14 & ohio stadium • columbus, oh & w 21-14 & 88622 \\ 1 & september 18 & at michigan state & #12 & spartan stadium • east lansing, mi & w 31-10 & 73483 \\ 2 & september 25 & stanford & #13 & ohio stadium • columbus, oh & l 20-23 & 89436 \\ 3 & october 2 & florida state & none & ohio stadium • columbus, oh & l 17-34 & 89491 \\ 4 & october 9 & wisconsin & none & ohio stadium • columbus, oh & l 0-6 & 88344 \\ 5 & october 16 & at #15 illinois & none & memorial stadium • champaign, il & w 26-21 & 73488 \\ 6 & october 23 & at indiana & none & memorial stadium • bloomington, in & w 49-25 & 52,04 \\ 7 & october 30 & purdue & none & ohio stadium • columbus, oh & w 38-6 & 89341 \\ 8 & november 6 & minnesota & none & ohio stadium • columbus, oh & w 35-10 & 87666 \\ 9 & november 13 & at northwestern & none & dyche stadium • evanston, il & w 40-28 & 30074 \\ 10 & november 20 & #13 michigan & none & ohio stadium • columbus, oh & w 24-14 & 90252 \\ 11 & december 17 & vs. byu & #17 & jack murphy stadium • san diego, ca (holiday bowl) & w 47-17 & 52533 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & result \\ \midrule 0 & w 31-10 \\ \bottomrule \end{tabular}	select result where attendance = 73483 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>date</th> <th>opponent#</th> <th>rank#</th> <th>site</th> <th>result</th> <th>attendance</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>september 11</td> <td>baylor</td> <td>#14</td> <td>ohio stadium • columbus, oh</td> <td>w 21-14</td> <td>88622</td> </tr> <tr> <th>1</th> <td>september 18</td> <td>at michigan state</td> <td>#12</td> <td>spartan stadium • east lansing, mi</td> <td>w 31-10</td> <td>73483</td> </tr> <tr> <th>2</th> <td>september 25</td> <td>stanford</td> <td>#13</td> <td>ohio stadium • columbus, oh</td> <td>l 20-23</td> <td>89436</td> </tr> <tr> <th>3</th> <td>october 2</td> <td>florida state</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>l 17-34</td> <td>89491</td> </tr> <tr> <th>4</th> <td>october 9</td> <td>wisconsin</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>l 0-6</td> <td>88344</td> </tr> <tr> <th>5</th> <td>october 16</td> <td>at #15 illinois</td> <td>none</td> <td>memorial stadium • champaign, il</td> <td>w 26-21</td> <td>73488</td> </tr> <tr> <th>6</th> <td>october 23</td> <td>at indiana</td> <td>none</td> <td>memorial stadium • bloomington, in</td> <td>w 49-25</td> <td>52,04</td> </tr> <tr> <th>7</th> <td>october 30</td> <td>purdue</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>w 38-6</td> <td>89341</td> </tr> <tr> <th>8</th> <td>november 6</td> <td>minnesota</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>w 35-10</td> <td>87666</td> </tr> <tr> <th>9</th> <td>november 13</td> <td>at northwestern</td> <td>none</td> <td>dyche stadium • evanston, il</td> <td>w 40-28</td> <td>30074</td> </tr> <tr> <th>10</th> <td>november 20</td> <td>#13 michigan</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>w 24-14</td> <td>90252</td> </tr> <tr> <th>11</th> <td>december 17</td> <td>vs. byu</td> <td>#17</td> <td>jack murphy stadium • san diego, ca (holiday bowl)</td> <td>w 47-17</td> <td>52533</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>w 31-10</td> </tr> </tbody> </table>	select result where attendance = 73483 <table_name> : table \| \| date \| opponent# \| rank# \| site \| result \| attendance \| \|---:\|:-------------\|:------------------\|:--------\|:---------------------------------------------------\|:---------\|:-------------\| \| 0 \| september 11 \| baylor \| #14 \| ohio stadium • columbus, oh \| w 21-14 \| 88622 \| \| 1 \| september 18 \| at michigan state \| #12 \| spartan stadium • east lansing, mi \| w 31-10 \| 73483 \| \| 2 \| september 25 \| stanford \| #13 \| ohio stadium • columbus, oh \| l 20-23 \| 89436 \| \| 3 \| october 2 \| florida state \| none \| ohio stadium • columbus, oh \| l 17-34 \| 89491 \| \| 4 \| october 9 \| wisconsin \| none \| ohio stadium • columbus, oh \| l 0-6 \| 88344 \| \| 5 \| october 16 \| at #15 illinois \| none \| memorial stadium • champaign, il \| w 26-21 \| 73488 \| \| 6 \| october 23 \| at indiana \| none \| memorial stadium • bloomington, in \| w 49-25 \| 52,04 \| \| 7 \| october 30 \| purdue \| none \| ohio stadium • columbus, oh \| w 38-6 \| 89341 \| \| 8 \| november 6 \| minnesota \| none \| ohio stadium • columbus, oh \| w 35-10 \| 87666 \| \| 9 \| november 13 \| at northwestern \| none \| dyche stadium • evanston, il \| w 40-28 \| 30074 \| \| 10 \| november 20 \| #13 michigan \| none \| ohio stadium • columbus, oh \| w 24-14 \| 90252 \| \| 11 \| december 17 \| vs. byu \| #17 \| jack murphy stadium • san diego, ca (holiday bowl) \| w 47-17 \| 52533 \|	\| \| result \| \|---:\|:---------\| \| 0 \| w 31-10 \|	[ [ 1, 4025, 563, 1625, 2403, 409, 1359, 273, 2371, 5026, 10261, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 712, 1757, 451, 34, 203, 1377, 411, 451, 34, 556, 1029, 7, 1757, 451, 34, 203, 1377, 411, 451, 34, 11500, 7, 1757, 451, 34, 203, 1377, 411, 451, 34, 4256, 1757, 451, 34, 203, 1377, 411, 451, 34, 2088, 1757, 451, 34, 203, 1377, 411, 451, 34, 4558, 409, 1359, 1757, 451, 34, 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select position where position = 1 col : year \| single \| chart \| position row 1 : 1999 \| "heavy" \| billboard hot 100 \| 73 row 2 : 1999 \| "heavy" \| mainstream rock tracks \| 1 row 3 : 1999 \| "heavy" \| modern rock tracks \| 5 row 4 : 1999 \| "run" \| billboard hot 100 \| 76 row 5 : 1999 \| "run" \| modern rock tracks \| 36 row 6 : 1999 \| "run" \| adult top 40 \| 12 row 7 : 1999 \| "no more, no less" \| mainstream rock tracks \| 10 row 8 : 1999 \| "no more, no less" \| modern rock tracks \| 32 row 9 : 1999 \| "tremble for my beloved" \| mainstream rock tracks \| 35	col : position row 1 : 1	select position where position = 1 <table_name> : table \begin{tabular}{lllll} \toprule & year & single & chart & position \\ \midrule 0 & 1999 & "heavy" & billboard hot 100 & 73 \\ 1 & 1999 & "heavy" & mainstream rock tracks & 1 \\ 2 & 1999 & "heavy" & modern rock tracks & 5 \\ 3 & 1999 & "run" & billboard hot 100 & 76 \\ 4 & 1999 & "run" & modern rock tracks & 36 \\ 5 & 1999 & "run" & adult top 40 & 12 \\ 6 & 1999 & "no more, no less" & mainstream rock tracks & 10 \\ 7 & 1999 & "no more, no less" & modern rock tracks & 32 \\ 8 & 1999 & "tremble for my beloved" & mainstream rock tracks & 35 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & position \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select position where position = 1 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>single</th> <th>chart</th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>"heavy"</td> <td>billboard hot 100</td> <td>73</td> </tr> <tr> <th>1</th> <td>1999</td> <td>"heavy"</td> <td>mainstream rock tracks</td> <td>1</td> </tr> <tr> <th>2</th> <td>1999</td> <td>"heavy"</td> <td>modern rock tracks</td> <td>5</td> </tr> <tr> <th>3</th> <td>1999</td> <td>"run"</td> <td>billboard hot 100</td> <td>76</td> </tr> <tr> <th>4</th> <td>1999</td> <td>"run"</td> <td>modern rock tracks</td> <td>36</td> </tr> <tr> <th>5</th> <td>1999</td> <td>"run"</td> <td>adult top 40</td> <td>12</td> </tr> <tr> <th>6</th> <td>1999</td> <td>"no more, no less"</td> <td>mainstream rock tracks</td> <td>10</td> </tr> <tr> <th>7</th> <td>1999</td> <td>"no more, no less"</td> <td>modern rock tracks</td> <td>32</td> </tr> <tr> <th>8</th> <td>1999</td> <td>"tremble for my beloved"</td> <td>mainstream rock tracks</td> <td>35</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select position where position = 1 <table_name> : table \| \| year \| single \| chart \| position \| \|---:\|-------:\|:-------------------------\|:-----------------------\|-----------:\| \| 0 \| 1999 \| "heavy" \| billboard hot 100 \| 73 \| \| 1 \| 1999 \| "heavy" \| mainstream rock tracks \| 1 \| \| 2 \| 1999 \| "heavy" \| modern rock tracks \| 5 \| \| 3 \| 1999 \| 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select place where place = 3 col : place \| team \| titles \| runners-up \| winning years row 1 : 1 \| maccabi tel aviv \| 5 \| 1 \| 2007, 2010, 2011, 2012, 2013 row 2 : 2 \| hapoel jerusalem \| 2 \| 3 \| 2008, 2009 row 3 : 3 \| ironi ashkelon \| 1 \| 0 \| 2006 row 4 : 4 \| maccabi rishon lezion \| 0 \| 1 \| none row 5 : 4 \| ironi nahariya \| 0 \| 1 \| none row 6 : 4 \| hapoel holon \| 0 \| 1 \| none row 7 : 4 \| maccabi ashdod \| 0 \| 1 \| none	col : place row 1 : 3	select place where place = 3 <table_name> : table \begin{tabular}{llllll} \toprule & place & team & titles & runners-up & winning years \\ \midrule 0 & 1 & maccabi tel aviv & 5 & 1 & 2007, 2010, 2011, 2012, 2013 \\ 1 & 2 & hapoel jerusalem & 2 & 3 & 2008, 2009 \\ 2 & 3 & ironi ashkelon & 1 & 0 & 2006 \\ 3 & 4 & maccabi rishon lezion & 0 & 1 & none \\ 4 & 4 & ironi nahariya & 0 & 1 & none \\ 5 & 4 & hapoel holon & 0 & 1 & none \\ 6 & 4 & maccabi ashdod & 0 & 1 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & place \\ \midrule 0 & 3 \\ \bottomrule \end{tabular}	select place where place = 3 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> <th>team</th> <th>titles</th> <th>runners-up</th> <th>winning years</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>maccabi tel aviv</td> <td>5</td> <td>1</td> <td>2007, 2010, 2011, 2012, 2013</td> </tr> <tr> <th>1</th> <td>2</td> <td>hapoel jerusalem</td> <td>2</td> <td>3</td> <td>2008, 2009</td> </tr> <tr> <th>2</th> <td>3</td> <td>ironi ashkelon</td> <td>1</td> <td>0</td> <td>2006</td> </tr> <tr> <th>3</th> <td>4</td> <td>maccabi rishon lezion</td> <td>0</td> <td>1</td> <td>none</td> </tr> <tr> <th>4</th> <td>4</td> <td>ironi nahariya</td> <td>0</td> <td>1</td> <td>none</td> </tr> <tr> <th>5</th> <td>4</td> <td>hapoel holon</td> <td>0</td> <td>1</td> <td>none</td> </tr> <tr> <th>6</th> <td>4</td> <td>maccabi ashdod</td> <td>0</td> <td>1</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>3</td> </tr> </tbody> </table>	select place where place = 3 <table_name> : table \| \| place \| team \| titles \| runners-up \| winning years \| \|---:\|--------:\|:----------------------\|---------:\|-------------:\|:-----------------------------\| \| 0 \| 1 \| maccabi tel aviv \| 5 \| 1 \| 2007, 2010, 2011, 2012, 2013 \| \| 1 \| 2 \| hapoel jerusalem \| 2 \| 3 \| 2008, 2009 \| \| 2 \| 3 \| ironi ashkelon \| 1 \| 0 \| 2006 \| \| 3 \| 4 \| maccabi rishon lezion \| 0 \| 1 \| none \| \| 4 \| 4 \| ironi nahariya \| 0 \| 1 \| none \| \| 5 \| 4 \| hapoel holon \| 0 \| 1 \| none \| \| 6 \| 4 \| maccabi ashdod \| 0 \| 1 \| none \|	\| \| place \| \|---:\|--------:\| \| 0 \| 3 \|	[ [ 1, 4025, 3166, 1625, 3166, 273, 890, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 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select count ( group ) where group = 'non-inscrits' col : group \| members \| caucusing \| total row 1 : socialist group \| 242 \| 8 \| 250 row 2 : rpr group \| 136 \| 6 \| 140 row 3 : udf group \| 107 \| 6 \| 113 row 4 : communist group \| 34 \| 2 \| 36 row 5 : radical, citizen and green \| 33 \| 0 \| 33 row 6 : non-inscrits \| 5 \| 0 \| 5 row 7 : total \| 555 \| 22 \| 577	col : count ( "group" ) row 1 : 1	select count ( group ) where group = 'non-inscrits' <table_name> : table \begin{tabular}{lllll} \toprule & group & members & caucusing & total \\ \midrule 0 & socialist group & 242 & 8 & 250 \\ 1 & rpr group & 136 & 6 & 140 \\ 2 & udf group & 107 & 6 & 113 \\ 3 & communist group & 34 & 2 & 36 \\ 4 & radical, citizen and green & 33 & 0 & 33 \\ 5 & non-inscrits & 5 & 0 & 5 \\ 6 & total & 555 & 22 & 577 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "group" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( group ) where group = 'non-inscrits' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>group</th> <th>members</th> <th>caucusing</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>socialist group</td> <td>242</td> <td>8</td> <td>250</td> </tr> <tr> <th>1</th> <td>rpr group</td> <td>136</td> <td>6</td> <td>140</td> </tr> <tr> <th>2</th> <td>udf group</td> <td>107</td> <td>6</td> <td>113</td> </tr> <tr> <th>3</th> <td>communist group</td> <td>34</td> <td>2</td> <td>36</td> </tr> <tr> <th>4</th> <td>radical, citizen and green</td> <td>33</td> <td>0</td> <td>33</td> </tr> <tr> <th>5</th> <td>non-inscrits</td> <td>5</td> <td>0</td> <td>5</td> </tr> <tr> <th>6</th> <td>total</td> <td>555</td> <td>22</td> <td>577</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "group" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( group ) where group = 'non-inscrits' <table_name> : table \| \| group \| members \| caucusing \| total \| \|---:\|:---------------------------\|----------:\|------------:\|--------:\| \| 0 \| socialist group \| 242 \| 8 \| 250 \| \| 1 \| rpr group \| 136 \| 6 \| 140 \| \| 2 \| udf group \| 107 \| 6 \| 113 \| \| 3 \| communist group \| 34 \| 2 \| 36 \| \| 4 \| radical, citizen and green \| 33 \| 0 \| 33 \| \| 5 \| non-inscrits \| 5 \| 0 \| 5 \| \| 6 \| total \| 555 \| 22 \| 577 \|	\| \| count ( "group" ) \| \|---:\|--------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 1041, 262, 1625, 1041, 273, 296, 5836, 17, 267, 1017, 583, 87, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 1655, 1757, 451, 34, 203, 1377, 411, 451, 34, 7640, 1757, 451, 34, 203, 1377, 411, 451, 34, 5353, 5286, 9940, 1757, 451, 34, 203, 1377, 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select event where competition = 'world championships' col : year \| competition \| venue \| position \| event \| notes row 1 : 1994 \| european championships \| helsinki, finland \| 48th \| marathon \| 2:22:49 row 2 : 1995 \| world championships \| gothenburg, sweden \| 49th \| marathon \| 2:33:42 row 3 : 1996 \| summer olympics \| atlanta, georgia \| 58th \| marathon \| 2:23:14 row 4 : 1997 \| world championships \| athens, greece \| 48th \| marathon \| 2:29:10 row 5 : 1998 \| world cross country championships \| marrakech, morocco \| 85th \| long race \| none row 6 : 1998 \| world half marathon championships \| uster, switzerland \| 66th \| half marathon \| 1:05:00 row 7 : 1998 \| european championships \| budapest, hungary \| 29th \| marathon \| 2:19:38 row 8 : 1999 \| world half marathon championships \| palermo, italy \| 55th \| half marathon \| 1:05:45 row 9 : 1999 \| frankfurt marathon \| frankfurt, germany \| 1st \| marathon \| 2:12:37 row 10 : 1999 \| helsinki marathon \| helsinki, finland \| 1st \| marathon \| 2:19:18 row 11 : 2000 \| summer olympics \| sydney, australia \| 35th \| marathon \| 2:19:41 row 12 : 2001 \| frankfurt marathon \| frankfurt, germany \| 1st \| marathon \| 2:11:09 row 13 : 2002 \| paris marathon \| paris, france \| 2nd \| marathon \| 2:08:53 row 14 : 2002 \| european championships \| munich, germany \| 2nd \| marathon \| 2:13:18 row 15 : 2002 \| fukuoka marathon \| fukuoka, japan \| 4th \| marathon \| 2:10:14 row 16 : 2003 \| joongang seoul marathon \| seoul, south korea \| 1st \| marathon \| 2:09:15 row 17 : 2004 \| summer olympics \| athens, greece \| 26th \| marathon \| 2:18:09 row 18 : 2004 \| joongang seoul marathon \| seoul, south korea \| 1st \| marathon \| 2:09:34 row 19 : 2005 \| joongang seoul marathon \| seoul, south korea \| 4th \| marathon \| 2:12:12 row 20 : 2006 \| paris marathon \| paris, france \| 12th \| marathon \| 2:11:25 row 21 : 2007 \| world championships \| osaka, japan \| none \| marathon \| dnf row 22 : 2007 \| beppu-oita marathon \| beppu-oita, japan \| 8th \| marathon \| 2:14:49 row 23 : 2008 \| summer olympics \| beijing, china \| 75th \| marathon \| 2:39:01	col : event row 1 : marathon row 2 : marathon row 3 : marathon	select event where competition = 'world championships' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 1994 & european championships & helsinki, finland & 48th & marathon & 2:22:49 \\ 1 & 1995 & world championships & gothenburg, sweden & 49th & marathon & 2:33:42 \\ 2 & 1996 & summer olympics & atlanta, georgia & 58th & marathon & 2:23:14 \\ 3 & 1997 & world championships & athens, greece & 48th & marathon & 2:29:10 \\ 4 & 1998 & world cross country championships & marrakech, morocco & 85th & long race & none \\ 5 & 1998 & world half marathon championships & uster, switzerland & 66th & half marathon & 1:05:00 \\ 6 & 1998 & european championships & budapest, hungary & 29th & marathon & 2:19:38 \\ 7 & 1999 & world half marathon championships & palermo, italy & 55th & half marathon & 1:05:45 \\ 8 & 1999 & frankfurt marathon & frankfurt, germany & 1st & marathon & 2:12:37 \\ 9 & 1999 & helsinki marathon & helsinki, finland & 1st & marathon & 2:19:18 \\ 10 & 2000 & summer olympics & sydney, australia & 35th & marathon & 2:19:41 \\ 11 & 2001 & frankfurt marathon & frankfurt, germany & 1st & marathon & 2:11:09 \\ 12 & 2002 & paris marathon & paris, france & 2nd & marathon & 2:08:53 \\ 13 & 2002 & european championships & munich, germany & 2nd & marathon & 2:13:18 \\ 14 & 2002 & fukuoka marathon & fukuoka, japan & 4th & marathon & 2:10:14 \\ 15 & 2003 & joongang seoul marathon & seoul, south korea & 1st & marathon & 2:09:15 \\ 16 & 2004 & summer olympics & athens, greece & 26th & marathon & 2:18:09 \\ 17 & 2004 & joongang seoul marathon & seoul, south korea & 1st & marathon & 2:09:34 \\ 18 & 2005 & joongang seoul marathon & seoul, south korea & 4th & marathon & 2:12:12 \\ 19 & 2006 & paris marathon & paris, france & 12th & marathon & 2:11:25 \\ 20 & 2007 & world championships & osaka, japan & none & marathon & dnf \\ 21 & 2007 & beppu-oita marathon & beppu-oita, japan & 8th & marathon & 2:14:49 \\ 22 & 2008 & summer olympics & beijing, china & 75th & marathon & 2:39:01 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & event \\ \midrule 0 & marathon \\ 1 & marathon \\ 2 & marathon \\ \bottomrule \end{tabular}	select event where competition = 'world championships' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1994</td> <td>european championships</td> <td>helsinki, finland</td> <td>48th</td> <td>marathon</td> <td>2:22:49</td> </tr> <tr> <th>1</th> <td>1995</td> <td>world championships</td> <td>gothenburg, sweden</td> <td>49th</td> <td>marathon</td> <td>2:33:42</td> </tr> <tr> <th>2</th> <td>1996</td> <td>summer olympics</td> <td>atlanta, georgia</td> <td>58th</td> <td>marathon</td> <td>2:23:14</td> </tr> <tr> <th>3</th> <td>1997</td> <td>world championships</td> <td>athens, greece</td> <td>48th</td> <td>marathon</td> <td>2:29:10</td> </tr> <tr> <th>4</th> <td>1998</td> <td>world cross country championships</td> <td>marrakech, morocco</td> <td>85th</td> <td>long race</td> <td>none</td> </tr> <tr> <th>5</th> <td>1998</td> <td>world half marathon championships</td> <td>uster, switzerland</td> <td>66th</td> <td>half marathon</td> <td>1:05:00</td> </tr> <tr> <th>6</th> <td>1998</td> <td>european championships</td> <td>budapest, hungary</td> <td>29th</td> <td>marathon</td> <td>2:19:38</td> </tr> <tr> <th>7</th> <td>1999</td> <td>world half marathon championships</td> <td>palermo, italy</td> <td>55th</td> <td>half marathon</td> <td>1:05:45</td> </tr> <tr> <th>8</th> <td>1999</td> <td>frankfurt marathon</td> <td>frankfurt, germany</td> <td>1st</td> <td>marathon</td> <td>2:12:37</td> </tr> <tr> <th>9</th> <td>1999</td> <td>helsinki marathon</td> <td>helsinki, finland</td> <td>1st</td> <td>marathon</td> <td>2:19:18</td> </tr> <tr> <th>10</th> <td>2000</td> <td>summer olympics</td> <td>sydney, australia</td> <td>35th</td> <td>marathon</td> <td>2:19:41</td> </tr> <tr> <th>11</th> <td>2001</td> <td>frankfurt marathon</td> <td>frankfurt, germany</td> <td>1st</td> <td>marathon</td> <td>2:11:09</td> </tr> <tr> <th>12</th> <td>2002</td> <td>paris marathon</td> <td>paris, france</td> <td>2nd</td> <td>marathon</td> <td>2:08:53</td> </tr> <tr> <th>13</th> <td>2002</td> <td>european championships</td> <td>munich, germany</td> <td>2nd</td> <td>marathon</td> <td>2:13:18</td> </tr> <tr> <th>14</th> <td>2002</td> <td>fukuoka marathon</td> <td>fukuoka, japan</td> <td>4th</td> <td>marathon</td> <td>2:10:14</td> </tr> <tr> <th>15</th> <td>2003</td> <td>joongang seoul marathon</td> <td>seoul, south korea</td> <td>1st</td> <td>marathon</td> <td>2:09:15</td> </tr> <tr> <th>16</th> <td>2004</td> <td>summer olympics</td> <td>athens, greece</td> <td>26th</td> <td>marathon</td> <td>2:18:09</td> </tr> <tr> <th>17</th> <td>2004</td> <td>joongang seoul marathon</td> <td>seoul, south korea</td> <td>1st</td> <td>marathon</td> <td>2:09:34</td> </tr> <tr> <th>18</th> <td>2005</td> <td>joongang seoul marathon</td> <td>seoul, south korea</td> <td>4th</td> <td>marathon</td> <td>2:12:12</td> </tr> <tr> <th>19</th> <td>2006</td> <td>paris marathon</td> <td>paris, france</td> <td>12th</td> <td>marathon</td> <td>2:11:25</td> </tr> <tr> <th>20</th> <td>2007</td> <td>world championships</td> <td>osaka, japan</td> <td>none</td> <td>marathon</td> <td>dnf</td> </tr> <tr> <th>21</th> <td>2007</td> <td>beppu-oita marathon</td> <td>beppu-oita, japan</td> <td>8th</td> <td>marathon</td> <td>2:14:49</td> </tr> <tr> <th>22</th> <td>2008</td> <td>summer olympics</td> <td>beijing, china</td> <td>75th</td> <td>marathon</td> <td>2:39:01</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>event</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>marathon</td> </tr> <tr> <th>1</th> <td>marathon</td> </tr> <tr> <th>2</th> <td>marathon</td> </tr> </tbody> </table>	select event where competition = 'world championships' <table_name> : table \| \| year \| competition \| venue \| position \| event \| notes \| \|---:\|-------:\|:----------------------------------\|:-------------------\|:-----------\|:--------------\|:--------\| \| 0 \| 1994 \| european championships \| helsinki, finland \| 48th \| marathon \| 2:22:49 \| \| 1 \| 1995 \| world championships \| gothenburg, sweden \| 49th \| marathon \| 2:33:42 \| \| 2 \| 1996 \| summer olympics \| atlanta, georgia \| 58th \| marathon \| 2:23:14 \| \| 3 \| 1997 \| world championships \| athens, greece \| 48th \| marathon \| 2:29:10 \| \| 4 \| 1998 \| world cross country championships \| marrakech, morocco \| 85th \| long race \| none \| \| 5 \| 1998 \| world half marathon championships \| uster, switzerland \| 66th \| half marathon \| 1:05:00 \| \| 6 \| 1998 \| european championships \| budapest, hungary \| 29th \| marathon \| 2:19:38 \| \| 7 \| 1999 \| world half marathon championships \| palermo, italy \| 55th \| half marathon \| 1:05:45 \| \| 8 \| 1999 \| frankfurt marathon \| frankfurt, germany \| 1st \| marathon \| 2:12:37 \| \| 9 \| 1999 \| helsinki marathon \| helsinki, finland \| 1st \| marathon \| 2:19:18 \| \| 10 \| 2000 \| summer olympics \| sydney, australia \| 35th \| marathon \| 2:19:41 \| \| 11 \| 2001 \| frankfurt marathon \| frankfurt, germany \| 1st \| marathon \| 2:11:09 \| \| 12 \| 2002 \| paris marathon \| paris, france \| 2nd \| marathon \| 2:08:53 \| \| 13 \| 2002 \| european championships \| munich, germany \| 2nd \| marathon \| 2:13:18 \| \| 14 \| 2002 \| fukuoka marathon \| fukuoka, japan \| 4th \| marathon \| 2:10:14 \| \| 15 \| 2003 \| joongang seoul marathon 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select count ( * ) where circle = 'none' and bench = 'none' col : name \| type \| circle \| bench \| formed \| notes row 1 : uberlingen \| imperial city \| swab \| sw \| 1268 \| 1803: mediatized to baden row 2 : ulm \| 1155: free imperial city \| swab \| sw \| 1115 \| 1803: mediatized to bavaria 1809: to wurttemberg row 3 : umpfenbach \| lordship 1805: hre princely county \| none \| none \| none \| to trauttmansdorff row 4 : unterwalden \| imperial valley \| none \| none \| 1415 \| division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation row 5 : upper salm \| 1163: county \| none \| none \| 1170 \| partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach row 6 : upper bavaria (oberbayern) \| duchy \| none \| none \| 1255 \| none row 7 : upper schonburg \| county \| upp sax \| none \| 1569 \| partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg row 8 : urach \| county \| none \| none \| none \| 1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach row 9 : uri \| imperial valley \| none \| none \| 1231 \| split off from habsburg 1648: left empire as member of swiss confederation row 10 : ursberg \| 1143: hre abbey \| swab \| none \| none \| 1803; secularized row 11 : utrecht \| bishopric \| burg \| ec \| 1024 \| 1512: burgundian circle 1528: secularized to austria 1793: council of princes row 12 : uznach \| county \| none \| none \| none \| none	col : count ( "*" ) row 1 : 0	select count ( * ) where circle = 'none' and bench = 'none' <table_name> : table \begin{tabular}{lllllll} \toprule & name & type & circle & bench & formed & notes \\ \midrule 0 & uberlingen & imperial city & swab & sw & 1268 & 1803: mediatized to baden \\ 1 & ulm & 1155: free imperial city & swab & sw & 1115 & 1803: mediatized to bavaria 1809: to wurttemberg \\ 2 & umpfenbach & lordship 1805: hre princely county & none & none & none & to trauttmansdorff \\ 3 & unterwalden & imperial valley & none & none & 1415 & division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation \\ 4 & upper salm & 1163: county & none & none & 1170 & partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach \\ 5 & upper bavaria (oberbayern) & duchy & none & none & 1255 & none \\ 6 & upper schonburg & county & upp sax & none & 1569 & partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg \\ 7 & urach & county & none & none & none & 1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach \\ 8 & uri & imperial valley & none & none & 1231 & split off from habsburg 1648: left empire as member of swiss confederation \\ 9 & ursberg & 1143: hre abbey & swab & none & none & 1803; secularized \\ 10 & utrecht & bishopric & burg & ec & 1024 & 1512: burgundian circle 1528: secularized to austria 1793: council of princes \\ 11 & uznach & county & none & none & none & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where circle = 'none' and bench = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>type</th> <th>circle</th> <th>bench</th> <th>formed</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>uberlingen</td> <td>imperial city</td> <td>swab</td> <td>sw</td> <td>1268</td> <td>1803: mediatized to baden</td> </tr> <tr> <th>1</th> <td>ulm</td> <td>1155: free imperial city</td> <td>swab</td> <td>sw</td> <td>1115</td> <td>1803: mediatized to bavaria 1809: to wurttemberg</td> </tr> <tr> <th>2</th> <td>umpfenbach</td> <td>lordship 1805: hre princely county</td> <td>none</td> <td>none</td> <td>none</td> <td>to trauttmansdorff</td> </tr> <tr> <th>3</th> <td>unterwalden</td> <td>imperial valley</td> <td>none</td> <td>none</td> <td>1415</td> <td>division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation</td> </tr> <tr> <th>4</th> <td>upper salm</td> <td>1163: county</td> <td>none</td> <td>none</td> <td>1170</td> <td>partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach</td> </tr> <tr> <th>5</th> <td>upper bavaria (oberbayern)</td> <td>duchy</td> <td>none</td> <td>none</td> <td>1255</td> <td>none</td> </tr> <tr> <th>6</th> <td>upper schonburg</td> <td>county</td> <td>upp sax</td> <td>none</td> <td>1569</td> <td>partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg</td> </tr> <tr> <th>7</th> <td>urach</td> <td>county</td> <td>none</td> <td>none</td> <td>none</td> <td>1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach</td> </tr> <tr> <th>8</th> <td>uri</td> <td>imperial valley</td> <td>none</td> <td>none</td> <td>1231</td> <td>split off from habsburg 1648: left empire as member of swiss confederation</td> </tr> <tr> <th>9</th> <td>ursberg</td> <td>1143: hre abbey</td> <td>swab</td> <td>none</td> <td>none</td> <td>1803; secularized</td> </tr> <tr> <th>10</th> <td>utrecht</td> <td>bishopric</td> <td>burg</td> <td>ec</td> <td>1024</td> <td>1512: burgundian circle 1528: secularized to austria 1793: council of princes</td> </tr> <tr> <th>11</th> <td>uznach</td> <td>county</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where circle = 'none' and bench = 'none' <table_name> : table \| \| name \| type \| circle \| bench \| formed \| notes \| \|---:\|:---------------------------\|:-----------------------------------\|:---------\|:--------\|:---------\|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| uberlingen \| imperial city \| swab \| sw \| 1268 \| 1803: mediatized to baden \| \| 1 \| ulm \| 1155: free imperial city \| swab \| sw \| 1115 \| 1803: mediatized to bavaria 1809: to wurttemberg \| \| 2 \| umpfenbach \| lordship 1805: hre princely county \| none \| none \| none \| to trauttmansdorff \| \| 3 \| unterwalden \| imperial valley \| none \| none \| 1415 \| division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation \| \| 4 \| upper salm \| 1163: county \| none \| none \| 1170 \| partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach \| \| 5 \| upper bavaria (oberbayern) \| duchy \| none \| none \| 1255 \| none \| \| 6 \| upper schonburg \| county \| upp sax \| none \| 1569 \| partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg \| \| 7 \| urach \| county \| none \| none \| none \| 1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach \| \| 8 \| uri \| imperial valley \| none \| none \| 1231 \| split off from habsburg 1648: left empire as member of swiss confederation \| \| 9 \| ursberg \| 1143: hre abbey \| swab \| none \| 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select type where works number = 76024 col : number \| builder \| type \| date \| works number \| notes row 1 : 51 \| baldwin locomotive works \| ds4-4-750 \| 1949 \| 74408 \| acquired new 1949, retired 1970/wrecked-scrapped row 2 : 52 \| baldwin locomotive works \| ds4-4-750 \| 1949 \| 74409 \| acquired new 1949, retired in 1970 and scrapped in 1990 row 3 : 53 \| baldwin locomotive works \| ds4-4-1000 \| 1949 \| 74193 \| ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection row 4 : 54 \| baldwin locomotive works \| s-12 \| 1952/1953 \| 75823 \| ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped row 5 : 55 \| baldwin locomotive works \| rs-12 \| 1955 \| 76024 \| decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995 row 6 : 56 \| baldwin locomotive works \| rs-12 \| 1955 \| 76105 \| nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56 row 7 : 57 \| baldwin locomotive works \| s-12 \| 1953 \| 75914 \| nee sp 1539, acquired 1970, retired unknown, stored at willits, california row 8 : 61 \| american locomotive works \| rs-11 \| 1979 \| none \| former sp. status unknown row 9 : 62 \| american locomotive works \| rs-11 \| 1979 \| none \| former sp. status unknown row 10 : 63 \| american locomotive works \| rs-11 \| 1979 \| none \| former sp. sold to nvrr 1987 row 11 : 64 \| electro-motive diesel \| gp9m \| 1987 \| none \| former sp # 3411. operational and in regular service row 12 : 65 \| electro-motive diesel \| gp9m \| 1987 \| none \| former sp # 3412. operational row 13 : 66 \| electro-motive diesel \| gp9m \| 1956 \| none \| former c&o # 6145. acquired 1998. operational and in regular service row 14 : 67 \| electro-motive diesel \| gp9m \| 6/1954 \| 19554 \| built as bangor and aroostook railroad # 77; acquired 1998; never delivered row 15 : m-80 \| mack \| railbus \| 1923 \| none \| purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964 row 16 : m-100 \| edwards rail car company \| motor car \| 1925 \| none \| acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme row 17 : m-200 \| ss&iw \| motor car \| 1927 \| none \| ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway row 18 : m-300 \| american car and foundry company \| motor car \| 1935 \| none \| m-300 at fort bragg ex-slgw; nee ar; operable	col : type row 1 : rs-12	select type where works number = 76024 <table_name> : table \begin{tabular}{lllllll} \toprule & number & builder & type & date & works number & notes \\ \midrule 0 & 51 & baldwin locomotive works & ds4-4-750 & 1949 & 74408 & acquired new 1949, retired 1970/wrecked-scrapped \\ 1 & 52 & baldwin locomotive works & ds4-4-750 & 1949 & 74409 & acquired new 1949, retired in 1970 and scrapped in 1990 \\ 2 & 53 & baldwin locomotive works & ds4-4-1000 & 1949 & 74193 & ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection \\ 3 & 54 & baldwin locomotive works & s-12 & 1952/1953 & 75823 & ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped \\ 4 & 55 & baldwin locomotive works & rs-12 & 1955 & 76024 & decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995 \\ 5 & 56 & baldwin locomotive works & rs-12 & 1955 & 76105 & nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56 \\ 6 & 57 & baldwin locomotive works & s-12 & 1953 & 75914 & nee sp 1539, acquired 1970, retired unknown, stored at willits, california \\ 7 & 61 & american locomotive works & rs-11 & 1979 & none & former sp. status unknown \\ 8 & 62 & american locomotive works & rs-11 & 1979 & none & former sp. status unknown \\ 9 & 63 & american locomotive works & rs-11 & 1979 & none & former sp. sold to nvrr 1987 \\ 10 & 64 & electro-motive diesel & gp9m & 1987 & none & former sp # 3411. operational and in regular service \\ 11 & 65 & electro-motive diesel & gp9m & 1987 & none & former sp # 3412. operational \\ 12 & 66 & electro-motive diesel & gp9m & 1956 & none & former c&o # 6145. acquired 1998. operational and in regular service \\ 13 & 67 & electro-motive diesel & gp9m & 6/1954 & 19554 & built as bangor and aroostook railroad # 77; acquired 1998; never delivered \\ 14 & m-80 & mack & railbus & 1923 & none & purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964 \\ 15 & m-100 & edwards rail car company & motor car & 1925 & none & acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme \\ 16 & m-200 & ss&iw & motor car & 1927 & none & ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway \\ 17 & m-300 & american car and foundry company & motor car & 1935 & none & m-300 at fort bragg ex-slgw; nee ar; operable \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & type \\ \midrule 0 & rs-12 \\ \bottomrule \end{tabular}	select type where works number = 76024 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>number</th> <th>builder</th> <th>type</th> <th>date</th> <th>works number</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>51</td> <td>baldwin locomotive works</td> <td>ds4-4-750</td> <td>1949</td> <td>74408</td> <td>acquired new 1949, retired 1970/wrecked-scrapped</td> </tr> <tr> <th>1</th> <td>52</td> <td>baldwin locomotive works</td> <td>ds4-4-750</td> <td>1949</td> <td>74409</td> <td>acquired new 1949, retired in 1970 and scrapped in 1990</td> </tr> <tr> <th>2</th> <td>53</td> <td>baldwin locomotive works</td> <td>ds4-4-1000</td> <td>1949</td> <td>74193</td> <td>ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection</td> </tr> <tr> <th>3</th> <td>54</td> <td>baldwin locomotive works</td> <td>s-12</td> <td>1952/1953</td> <td>75823</td> <td>ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped</td> </tr> <tr> <th>4</th> <td>55</td> <td>baldwin locomotive works</td> <td>rs-12</td> <td>1955</td> <td>76024</td> <td>decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995</td> </tr> <tr> <th>5</th> <td>56</td> <td>baldwin locomotive works</td> <td>rs-12</td> <td>1955</td> <td>76105</td> <td>nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56</td> </tr> <tr> <th>6</th> <td>57</td> <td>baldwin locomotive works</td> <td>s-12</td> <td>1953</td> <td>75914</td> <td>nee sp 1539, acquired 1970, retired unknown, stored at willits, california</td> </tr> <tr> <th>7</th> <td>61</td> <td>american locomotive works</td> <td>rs-11</td> <td>1979</td> <td>none</td> <td>former sp. status unknown</td> </tr> <tr> <th>8</th> <td>62</td> <td>american locomotive works</td> <td>rs-11</td> <td>1979</td> <td>none</td> <td>former sp. status unknown</td> </tr> <tr> <th>9</th> <td>63</td> <td>american locomotive works</td> <td>rs-11</td> <td>1979</td> <td>none</td> <td>former sp. sold to nvrr 1987</td> </tr> <tr> <th>10</th> <td>64</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>1987</td> <td>none</td> <td>former sp # 3411. operational and in regular service</td> </tr> <tr> <th>11</th> <td>65</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>1987</td> <td>none</td> <td>former sp # 3412. operational</td> </tr> <tr> <th>12</th> <td>66</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>1956</td> <td>none</td> <td>former c&o # 6145. acquired 1998. operational and in regular service</td> </tr> <tr> <th>13</th> <td>67</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>6/1954</td> <td>19554</td> <td>built as bangor and aroostook railroad # 77; acquired 1998; never delivered</td> </tr> <tr> <th>14</th> <td>m-80</td> <td>mack</td> <td>railbus</td> <td>1923</td> <td>none</td> <td>purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964</td> </tr> <tr> <th>15</th> <td>m-100</td> <td>edwards rail car company</td> <td>motor car</td> <td>1925</td> <td>none</td> <td>acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme</td> </tr> <tr> <th>16</th> <td>m-200</td> <td>ss&iw</td> <td>motor car</td> <td>1927</td> <td>none</td> <td>ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway</td> </tr> <tr> <th>17</th> <td>m-300</td> <td>american car and foundry company</td> <td>motor car</td> <td>1935</td> <td>none</td> <td>m-300 at fort bragg ex-slgw; nee ar; operable</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>type</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>rs-12</td> </tr> </tbody> </table>	select type where works number = 76024 <table_name> : table \| \| number \| builder \| type \| date \| works number \| notes \| \|---:\|:---------\|:---------------------------------\|:-----------\|:----------\|:---------------\|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 51 \| baldwin locomotive works \| ds4-4-750 \| 1949 \| 74408 \| acquired new 1949, retired 1970/wrecked-scrapped \| \| 1 \| 52 \| baldwin locomotive works \| ds4-4-750 \| 1949 \| 74409 \| acquired new 1949, retired in 1970 and scrapped in 1990 \| \| 2 \| 53 \| baldwin locomotive works \| ds4-4-1000 \| 1949 \| 74193 \| ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection \| \| 3 \| 54 \| baldwin locomotive works \| s-12 \| 1952/1953 \| 75823 \| ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped \| \| 4 \| 55 \| baldwin locomotive works \| rs-12 \| 1955 \| 76024 \| decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995 \| \| 5 \| 56 \| baldwin locomotive works \| rs-12 \| 1955 \| 76105 \| nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56 \| \| 6 \| 57 \| baldwin locomotive works \| s-12 \| 1953 \| 75914 \| nee sp 1539, acquired 1970, retired unknown, stored at willits, california \| \| 7 \| 61 \| american locomotive works \| rs-11 \| 1979 \| none \| former sp. status unknown \| \| 8 \| 62 \| american locomotive works \| rs-11 \| 1979 \| none \| former sp. status unknown \| \| 9 \| 63 \| american locomotive works \| rs-11 \| 1979 \| none \| former sp. sold to nvrr 1987 \| \| 10 \| 64 \| electro-motive diesel \| gp9m \| 1987 \| none \| former sp # 3411. operational and in regular service \| \| 11 \| 65 \| electro-motive diesel \| gp9m \| 1987 \| none \| former sp # 3412. operational \| \| 12 \| 66 \| electro-motive diesel \| gp9m \| 1956 \| none \| former c&o # 6145. acquired 1998. operational and in regular service \| \| 13 \| 67 \| electro-motive diesel \| gp9m \| 6/1954 \| 19554 \| built as bangor and aroostook railroad # 77; acquired 1998; never delivered \| \| 14 \| m-80 \| mack \| railbus \| 1923 \| none \| purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964 \| \| 15 \| m-100 \| edwards rail car company \| motor car \| 1925 \| none \| acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme \| \| 16 \| m-200 \| ss&iw \| motor car \| 1927 \| none \| ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway \| \| 17 \| m-300 \| american car and foundry company \| motor car \| 1935 \| none \| 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select votes where ±% = '-1.8' col : party \| candidate \| votes \| % \| ±% row 1 : conservative \| patrick mcloughlin \| 24280 \| 48 \| 5.9 row 2 : labour \| stephen clamp \| 16910 \| 33.4 \| -0.1 row 3 : liberal democrat \| jeremy beckett \| 7922 \| 15.7 \| -1.8 row 4 : ukip \| stuart bavester \| 672 \| 1.3 \| 0.5 row 5 : monster raving loony \| "the flying brick" delves \| 472 \| 0.9 \| 0.4 row 6 : independent \| robert goodall \| 333 \| 0.7 \| 0.5 row 7 : majority \| majority \| 7370 \| 14.6 \| none row 8 : turnout \| turnout \| 50589 \| 67.8 \| -10.5 row 9 : conservative hold \| conservative hold \| swing \| none \| none	col : votes row 1 : 7922	select votes where ±% = '-1.8' <table_name> : table \begin{tabular}{llllll} \toprule & party & candidate & votes & % & ±% \\ \midrule 0 & conservative & patrick mcloughlin & 24280 & 48 & 5.9 \\ 1 & labour & stephen clamp & 16910 & 33.4 & -0.1 \\ 2 & liberal democrat & jeremy beckett & 7922 & 15.7 & -1.8 \\ 3 & ukip & stuart bavester & 672 & 1.3 & 0.5 \\ 4 & monster raving loony & "the flying brick" delves & 472 & 0.9 & 0.4 \\ 5 & independent & robert goodall & 333 & 0.7 & 0.5 \\ 6 & majority & majority & 7370 & 14.6 & none \\ 7 & turnout & turnout & 50589 & 67.8 & -10.5 \\ 8 & conservative hold & conservative hold & swing & none & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & votes \\ \midrule 0 & 7922 \\ \bottomrule \end{tabular}	select votes where ±% = '-1.8' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>party</th> <th>candidate</th> <th>votes</th> <th>%</th> <th>±%</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>conservative</td> <td>patrick mcloughlin</td> <td>24280</td> <td>48</td> <td>5.9</td> </tr> <tr> <th>1</th> <td>labour</td> <td>stephen clamp</td> <td>16910</td> <td>33.4</td> <td>-0.1</td> </tr> <tr> <th>2</th> <td>liberal democrat</td> <td>jeremy beckett</td> <td>7922</td> <td>15.7</td> <td>-1.8</td> </tr> <tr> <th>3</th> <td>ukip</td> <td>stuart bavester</td> <td>672</td> <td>1.3</td> <td>0.5</td> </tr> <tr> <th>4</th> <td>monster raving loony</td> <td>"the flying brick" delves</td> <td>472</td> <td>0.9</td> <td>0.4</td> </tr> <tr> <th>5</th> <td>independent</td> <td>robert goodall</td> <td>333</td> <td>0.7</td> <td>0.5</td> </tr> <tr> <th>6</th> <td>majority</td> <td>majority</td> <td>7370</td> <td>14.6</td> <td>none</td> </tr> <tr> <th>7</th> <td>turnout</td> <td>turnout</td> <td>50589</td> <td>67.8</td> <td>-10.5</td> </tr> <tr> <th>8</th> <td>conservative hold</td> <td>conservative hold</td> <td>swing</td> <td>none</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>votes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7922</td> </tr> </tbody> </table>	select votes where ±% = '-1.8' <table_name> : table \| \| party \| candidate \| votes \| % \| ±% \| \|---:\|:---------------------\|:--------------------------\|:--------\|:-----\|:------\| \| 0 \| conservative \| patrick mcloughlin \| 24280 \| 48 \| 5.9 \| \| 1 \| labour \| stephen clamp \| 16910 \| 33.4 \| -0.1 \| \| 2 \| liberal democrat \| jeremy beckett \| 7922 \| 15.7 \| -1.8 \| \| 3 \| ukip \| stuart bavester \| 672 \| 1.3 \| 0.5 \| \| 4 \| monster raving loony \| "the flying brick" delves \| 472 \| 0.9 \| 0.4 \| \| 5 \| independent \| robert goodall \| 333 \| 0.7 \| 0.5 \| \| 6 \| majority \| majority \| 7370 \| 14.6 \| none \| \| 7 \| turnout \| turnout \| 50589 \| 67.8 \| -10.5 \| \| 8 \| conservative hold \| conservative hold \| swing \| none \| none \|	\| \| votes \| \|---:\|--------:\| \| 0 \| 7922 \|	[ [ 1, 4025, 19588, 1625, 225, 131, 114, 9, 273, 2400, 21, 18, 28, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 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select count ( pos ) where points > 291 col : pos \| no \| rider \| bike \| laps \| time \| grid \| points row 1 : 1 \| 93 \| marc marquez \| derbi \| 22 \| 40:46.315 \| 1 \| 25 row 2 : 2 \| 38 \| bradley smith \| aprilia \| 22 \| 4.638 \| 3 \| 20 row 3 : 3 \| 44 \| pol espargaro \| derbi \| 22 \| 4.996 \| 2 \| 16 row 4 : 4 \| 11 \| sandro cortese \| derbi \| 22 \| 45.366 \| 5 \| 13 row 5 : 5 \| 7 \| efren vazquez \| derbi \| 22 \| 45.433 \| 8 \| 11 row 6 : 6 \| 71 \| tomoyoshi koyama \| aprilia \| 22 \| 49.685 \| 6 \| 10 row 7 : 7 \| 35 \| randy krummenacher \| aprilia \| 22 \| 49.735 \| 14 \| 9 row 8 : 8 \| 14 \| johann zarco \| aprilia \| 22 \| 49.743 \| 10 \| 8 row 9 : 9 \| 94 \| jonas folger \| aprilia \| 22 \| 49.775 \| 12 \| 7 row 10 : 10 \| 99 \| danny webb \| aprilia \| 22 \| 53.115 \| 16 \| 6 row 11 : 11 \| 26 \| adrian martin \| aprilia \| 22 \| 58.669 \| 19 \| 5 row 12 : 12 \| 15 \| simone grotzkyj \| aprilia \| 22 \| 58.8 \| 11 \| 4 row 13 : 13 \| 23 \| alberto moncayo \| aprilia \| 22 \| +1:02.050 \| 13 \| 3 row 14 : 14 \| 78 \| marcel schrotter \| honda \| 22 \| +1:15.497 \| 23 \| 2 row 15 : 15 \| 63 \| zulfahmi khairuddin \| aprilia \| 22 \| +1:16.029 \| 18 \| 1 row 16 : 16 \| 84 \| jakub kornfeil \| aprilia \| 22 \| +1:26.441 \| 28 \| none row 17 : 17 \| 69 \| louis rossi \| aprilia \| 22 \| +1:33.613 \| 24 \| none row 18 : 18 \| 87 \| luca marconi \| aprilia \| 22 \| +1:36.186 \| 25 \| none row 19 : 19 \| 58 \| joan perello \| honda \| 22 \| +1:36.223 \| 26 \| none row 20 : 20 \| 60 \| michael van der mark \| lambretta \| 22 \| +1:36.340 \| 27 \| none row 21 : 21 \| 59 \| johnny rosell \| honda \| 22 \| +1:43.804 \| 22 \| none row 22 : 22 \| 72 \| marco ravaioli \| lambretta \| 22 \| +1:55.331 \| 30 \| none row 23 : 23 \| 56 \| peter sebestyen \| aprilia \| 21 \| +1 lap \| 32 \| none row 24 : ret \| 40 \| nicolas terol \| aprilia \| 21 \| accident \| 4 \| none row 25 : ret \| 39 \| luis salom \| aprilia \| 14 \| retirement \| 15 \| none row 26 : ret \| 17 \| eduard lopez \| aprilia \| 11 \| retirement \| 31 \| none row 27 : ret \| 55 \| isaac vinales \| aprilia \| 10 \| accident \| 21 \| none row 28 : ret \| 50 \| sturla fagerhaug \| aprilia \| 7 \| accident \| 17 \| none row 29 : ret \| 5 \| alexis masbou \| aprilia \| 5 \| accident \| 9 \| none row 30 : ret \| 12 \| esteve rabat \| aprilia \| 0 \| accident \| 7 \| none row 31 : ret \| 53 \| jasper iwema \| aprilia \| 0 \| accident \| 20 \| none row 32 : dns \| 32 \| lorenzo savadori \| aprilia \| none \| did not start \| 29 \| none	col : count ( "pos" ) row 1 : 24	select count ( pos ) where points > 291 <table_name> : table \begin{tabular}{lllllllll} \toprule & pos & no & rider & bike & laps & time & grid & points \\ \midrule 0 & 1 & 93 & marc marquez & derbi & 22 & 40:46.315 & 1 & 25 \\ 1 & 2 & 38 & bradley smith & aprilia & 22 & 4.638 & 3 & 20 \\ 2 & 3 & 44 & pol espargaro & derbi & 22 & 4.996 & 2 & 16 \\ 3 & 4 & 11 & sandro cortese & derbi & 22 & 45.366 & 5 & 13 \\ 4 & 5 & 7 & efren vazquez & derbi & 22 & 45.433 & 8 & 11 \\ 5 & 6 & 71 & tomoyoshi koyama & aprilia & 22 & 49.685 & 6 & 10 \\ 6 & 7 & 35 & randy krummenacher & aprilia & 22 & 49.735 & 14 & 9 \\ 7 & 8 & 14 & johann zarco & aprilia & 22 & 49.743 & 10 & 8 \\ 8 & 9 & 94 & jonas folger & aprilia & 22 & 49.775 & 12 & 7 \\ 9 & 10 & 99 & danny webb & aprilia & 22 & 53.115 & 16 & 6 \\ 10 & 11 & 26 & adrian martin & aprilia & 22 & 58.669 & 19 & 5 \\ 11 & 12 & 15 & simone grotzkyj & aprilia & 22 & 58.8 & 11 & 4 \\ 12 & 13 & 23 & alberto moncayo & aprilia & 22 & +1:02.050 & 13 & 3 \\ 13 & 14 & 78 & marcel schrotter & honda & 22 & +1:15.497 & 23 & 2 \\ 14 & 15 & 63 & zulfahmi khairuddin & aprilia & 22 & +1:16.029 & 18 & 1 \\ 15 & 16 & 84 & jakub kornfeil & aprilia & 22 & +1:26.441 & 28 & none \\ 16 & 17 & 69 & louis rossi & aprilia & 22 & +1:33.613 & 24 & none \\ 17 & 18 & 87 & luca marconi & aprilia & 22 & +1:36.186 & 25 & none \\ 18 & 19 & 58 & joan perello & honda & 22 & +1:36.223 & 26 & none \\ 19 & 20 & 60 & michael van der mark & lambretta & 22 & +1:36.340 & 27 & none \\ 20 & 21 & 59 & johnny rosell & honda & 22 & +1:43.804 & 22 & none \\ 21 & 22 & 72 & marco ravaioli & lambretta & 22 & +1:55.331 & 30 & none \\ 22 & 23 & 56 & peter sebestyen & aprilia & 21 & +1 lap & 32 & none \\ 23 & ret & 40 & nicolas terol & aprilia & 21 & accident & 4 & none \\ 24 & ret & 39 & luis salom & aprilia & 14 & retirement & 15 & none \\ 25 & ret & 17 & eduard lopez & aprilia & 11 & retirement & 31 & none \\ 26 & ret & 55 & isaac vinales & aprilia & 10 & accident & 21 & none \\ 27 & ret & 50 & sturla fagerhaug & aprilia & 7 & accident & 17 & none \\ 28 & ret & 5 & alexis masbou & aprilia & 5 & accident & 9 & none \\ 29 & ret & 12 & esteve rabat & aprilia & 0 & accident & 7 & none \\ 30 & ret & 53 & jasper iwema & aprilia & 0 & accident & 20 & none \\ 31 & dns & 32 & lorenzo savadori & aprilia & none & did not start & 29 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "pos" ) \\ \midrule 0 & 24 \\ \bottomrule \end{tabular}	select count ( pos ) where points > 291 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pos</th> <th>no</th> <th>rider</th> <th>bike</th> <th>laps</th> <th>time</th> <th>grid</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>93</td> <td>marc marquez</td> <td>derbi</td> <td>22</td> <td>40:46.315</td> <td>1</td> <td>25</td> </tr> <tr> <th>1</th> <td>2</td> <td>38</td> <td>bradley smith</td> <td>aprilia</td> <td>22</td> <td>4.638</td> <td>3</td> <td>20</td> </tr> <tr> <th>2</th> <td>3</td> <td>44</td> <td>pol espargaro</td> <td>derbi</td> <td>22</td> <td>4.996</td> <td>2</td> <td>16</td> </tr> <tr> <th>3</th> <td>4</td> <td>11</td> <td>sandro cortese</td> <td>derbi</td> <td>22</td> <td>45.366</td> <td>5</td> <td>13</td> </tr> <tr> <th>4</th> <td>5</td> <td>7</td> <td>efren vazquez</td> <td>derbi</td> <td>22</td> <td>45.433</td> <td>8</td> <td>11</td> </tr> <tr> <th>5</th> <td>6</td> <td>71</td> <td>tomoyoshi koyama</td> <td>aprilia</td> <td>22</td> <td>49.685</td> <td>6</td> <td>10</td> </tr> <tr> <th>6</th> <td>7</td> <td>35</td> <td>randy krummenacher</td> <td>aprilia</td> <td>22</td> <td>49.735</td> <td>14</td> <td>9</td> </tr> <tr> <th>7</th> <td>8</td> <td>14</td> <td>johann zarco</td> <td>aprilia</td> <td>22</td> <td>49.743</td> <td>10</td> <td>8</td> </tr> <tr> <th>8</th> <td>9</td> <td>94</td> <td>jonas folger</td> <td>aprilia</td> <td>22</td> <td>49.775</td> <td>12</td> <td>7</td> </tr> <tr> <th>9</th> <td>10</td> <td>99</td> <td>danny webb</td> <td>aprilia</td> <td>22</td> <td>53.115</td> <td>16</td> <td>6</td> </tr> <tr> <th>10</th> <td>11</td> <td>26</td> <td>adrian martin</td> <td>aprilia</td> <td>22</td> <td>58.669</td> <td>19</td> <td>5</td> </tr> <tr> <th>11</th> <td>12</td> <td>15</td> <td>simone grotzkyj</td> <td>aprilia</td> <td>22</td> <td>58.8</td> <td>11</td> <td>4</td> </tr> <tr> <th>12</th> <td>13</td> <td>23</td> <td>alberto moncayo</td> <td>aprilia</td> <td>22</td> <td>+1:02.050</td> <td>13</td> <td>3</td> </tr> <tr> <th>13</th> <td>14</td> <td>78</td> <td>marcel schrotter</td> <td>honda</td> <td>22</td> <td>+1:15.497</td> <td>23</td> <td>2</td> </tr> <tr> <th>14</th> <td>15</td> <td>63</td> <td>zulfahmi khairuddin</td> <td>aprilia</td> <td>22</td> <td>+1:16.029</td> <td>18</td> <td>1</td> </tr> <tr> <th>15</th> <td>16</td> <td>84</td> <td>jakub kornfeil</td> <td>aprilia</td> <td>22</td> <td>+1:26.441</td> <td>28</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>69</td> <td>louis rossi</td> <td>aprilia</td> <td>22</td> <td>+1:33.613</td> <td>24</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>87</td> <td>luca marconi</td> <td>aprilia</td> <td>22</td> <td>+1:36.186</td> <td>25</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>58</td> <td>joan perello</td> <td>honda</td> <td>22</td> <td>+1:36.223</td> <td>26</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>60</td> <td>michael van der mark</td> <td>lambretta</td> <td>22</td> <td>+1:36.340</td> <td>27</td> <td>none</td> </tr> <tr> <th>20</th> <td>21</td> <td>59</td> <td>johnny rosell</td> <td>honda</td> <td>22</td> <td>+1:43.804</td> <td>22</td> <td>none</td> </tr> <tr> <th>21</th> <td>22</td> <td>72</td> <td>marco ravaioli</td> <td>lambretta</td> <td>22</td> <td>+1:55.331</td> <td>30</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>56</td> <td>peter sebestyen</td> <td>aprilia</td> <td>21</td> <td>+1 lap</td> <td>32</td> <td>none</td> </tr> <tr> <th>23</th> <td>ret</td> <td>40</td> <td>nicolas terol</td> <td>aprilia</td> <td>21</td> <td>accident</td> <td>4</td> <td>none</td> </tr> <tr> <th>24</th> <td>ret</td> <td>39</td> <td>luis salom</td> <td>aprilia</td> <td>14</td> <td>retirement</td> <td>15</td> <td>none</td> </tr> <tr> <th>25</th> <td>ret</td> <td>17</td> <td>eduard lopez</td> <td>aprilia</td> <td>11</td> <td>retirement</td> <td>31</td> <td>none</td> </tr> <tr> <th>26</th> <td>ret</td> <td>55</td> <td>isaac vinales</td> <td>aprilia</td> <td>10</td> <td>accident</td> <td>21</td> <td>none</td> </tr> <tr> <th>27</th> <td>ret</td> <td>50</td> <td>sturla fagerhaug</td> <td>aprilia</td> <td>7</td> <td>accident</td> <td>17</td> <td>none</td> </tr> <tr> <th>28</th> <td>ret</td> <td>5</td> <td>alexis masbou</td> <td>aprilia</td> <td>5</td> <td>accident</td> <td>9</td> <td>none</td> </tr> <tr> <th>29</th> <td>ret</td> <td>12</td> <td>esteve rabat</td> <td>aprilia</td> <td>0</td> <td>accident</td> <td>7</td> <td>none</td> </tr> <tr> <th>30</th> <td>ret</td> <td>53</td> <td>jasper iwema</td> <td>aprilia</td> <td>0</td> <td>accident</td> <td>20</td> <td>none</td> </tr> <tr> <th>31</th> <td>dns</td> <td>32</td> <td>lorenzo savadori</td> <td>aprilia</td> <td>none</td> <td>did not start</td> <td>29</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "pos" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>24</td> </tr> </tbody> </table>	select count ( pos ) where points > 291 <table_name> : table \| \| pos \| no \| rider \| bike \| laps \| time \| grid \| points \| \|---:\|:------\|-----:\|:---------------------\|:----------\|:-------\|:--------------\|-------:\|:---------\| \| 0 \| 1 \| 93 \| marc marquez \| derbi \| 22 \| 40:46.315 \| 1 \| 25 \| \| 1 \| 2 \| 38 \| bradley smith \| aprilia \| 22 \| 4.638 \| 3 \| 20 \| \| 2 \| 3 \| 44 \| pol espargaro \| derbi \| 22 \| 4.996 \| 2 \| 16 \| \| 3 \| 4 \| 11 \| sandro cortese \| derbi \| 22 \| 45.366 \| 5 \| 13 \| \| 4 \| 5 \| 7 \| efren vazquez \| derbi \| 22 \| 45.433 \| 8 \| 11 \| \| 5 \| 6 \| 71 \| tomoyoshi koyama \| aprilia \| 22 \| 49.685 \| 6 \| 10 \| \| 6 \| 7 \| 35 \| randy krummenacher \| aprilia \| 22 \| 49.735 \| 14 \| 9 \| \| 7 \| 8 \| 14 \| johann zarco \| aprilia \| 22 \| 49.743 \| 10 \| 8 \| \| 8 \| 9 \| 94 \| jonas folger \| aprilia \| 22 \| 49.775 \| 12 \| 7 \| \| 9 \| 10 \| 99 \| danny webb \| aprilia \| 22 \| 53.115 \| 16 \| 6 \| \| 10 \| 11 \| 26 \| adrian martin \| aprilia \| 22 \| 58.669 \| 19 \| 5 \| \| 11 \| 12 \| 15 \| simone grotzkyj \| aprilia \| 22 \| 58.8 \| 11 \| 4 \| \| 12 \| 13 \| 23 \| alberto moncayo \| aprilia \| 22 \| +1:02.050 \| 13 \| 3 \| \| 13 \| 14 \| 78 \| marcel schrotter \| honda \| 22 \| +1:15.497 \| 23 \| 2 \| \| 14 \| 15 \| 63 \| zulfahmi khairuddin \| aprilia \| 22 \| +1:16.029 \| 18 \| 1 \| \| 15 \| 16 \| 84 \| jakub kornfeil \| aprilia \| 22 \| +1:26.441 \| 28 \| none \| \| 16 \| 17 \| 69 \| louis rossi \| aprilia \| 22 \| +1:33.613 \| 24 \| none \| \| 17 \| 18 \| 87 \| luca marconi \| aprilia \| 22 \| +1:36.186 \| 25 \| none \| \| 18 \| 19 \| 58 \| joan perello \| honda \| 22 \| +1:36.223 \| 26 \| none \| \| 19 \| 20 \| 60 \| michael van der mark \| lambretta \| 22 \| +1:36.340 \| 27 \| none \| \| 20 \| 21 \| 59 \| johnny rosell \| honda \| 22 \| +1:43.804 \| 22 \| none \| \| 21 \| 22 \| 72 \| marco ravaioli \| lambretta \| 22 \| +1:55.331 \| 30 \| none \| \| 22 \| 23 \| 56 \| peter sebestyen \| aprilia \| 21 \| +1 lap \| 32 \| none \| \| 23 \| ret \| 40 \| nicolas terol \| aprilia \| 21 \| accident \| 4 \| none \| \| 24 \| ret \| 39 \| luis salom \| aprilia \| 14 \| retirement \| 15 \| none \| \| 25 \| ret \| 17 \| eduard lopez \| aprilia \| 11 \| retirement \| 31 \| none \| \| 26 \| ret \| 55 \| isaac vinales \| aprilia \| 10 \| accident \| 21 \| none \| \| 27 \| ret \| 50 \| sturla fagerhaug \| aprilia \| 7 \| accident \| 17 \| none \| \| 28 \| ret \| 5 \| alexis masbou \| aprilia \| 5 \| accident \| 9 \| none \| \| 29 \| ret \| 12 \| esteve rabat \| aprilia \| 0 \| accident \| 7 \| none \| \| 30 \| ret \| 53 \| jasper iwema \| aprilia \| 0 \| accident \| 20 \| none \| \| 31 \| dns \| 32 \| lorenzo savadori \| aprilia \| none \| did not start \| 29 \| none \|	\| \| count ( "pos" ) \| \|---:\|------------------:\| \| 0 \| 24 \|	[ [ 1, 4025, 1056, 261, 949, 262, 1625, 3143, 405, 576, 12416, 411, 2121, 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select diver where diver = 'tine tollan (nor)' col : rank \| diver \| preliminary points \| preliminary rank \| final points row 1 : 1 \| sylvie bernier (can) \| 489.51 \| 3 \| 530.7 row 2 : 2 \| kelly mccormick (usa) \| 516.75 \| 2 \| 527.46 row 3 : 3 \| christina seufert (usa) \| 481.41 \| 5 \| 517.62 row 4 : 4 \| li yihua (chn) \| 517.92 \| 1 \| 506.52 row 5 : 5 \| li qiaoxian (chn) \| 466.83 \| 6 \| 487.68 row 6 : 6 \| elsa tenorio (mex) \| 460.56 \| 8 \| 463.56 row 7 : 7 \| lesley smith (zim) \| 438.72 \| 10 \| 451.89 row 8 : 8 \| debbie fuller (can) \| 437.04 \| 11 \| 450.99 row 9 : 9 \| jennifer donnet (aus) \| 432.78 \| 12 \| 443.13 row 10 : 10 \| daphne jongejans (ned) \| 487.95 \| 4 \| 437.4 row 11 : 11 \| anita rossing (swe) \| 464.58 \| 7 \| 424.98 row 12 : 12 \| veronica ribot (arg) \| 443.25 \| 9 \| 422.52 row 13 : 13 \| ann fargher (nzl) \| 421.65 \| 13 \| none row 14 : 14 \| tine tollan (nor) \| 419.55 \| 14 \| none row 15 : 15 \| antonette wilken (zim) \| 414.66 \| 15 \| none row 16 : 16 \| guadalupe canseco (mex) \| 411.96 \| 16 \| none row 17 : 17 \| claire izacard (fra) \| 403.17 \| 17 \| none row 18 : 18 \| valerie mcfarland-beddoe (aus) \| 401.13 \| 18 \| none row 19 : 19 \| alison childs (gbr) \| 400.68 \| 19 \| none row 20 : 20 \| kerstin finke (frg) \| 393.93 \| 20 \| none row 21 : 21 \| nicole kreil (aut) \| 382.68 \| 21 \| none row 22 : 22 \| joana figueiredo (por) \| 374.07 \| 22 \| none row 23 : 23 \| angela ribeiro (bra) \| 370.68 \| 23 \| none row 24 : 24 \| rim hassan (egy) \| 258.63 \| 24 \| none	col : diver row 1 : tine tollan (nor)	select diver where diver = 'tine tollan (nor)' <table_name> : table \begin{tabular}{llllll} \toprule & rank & diver & preliminary points & preliminary rank & final points \\ \midrule 0 & 1 & sylvie bernier (can) & 489.51 & 3 & 530.7 \\ 1 & 2 & kelly mccormick (usa) & 516.75 & 2 & 527.46 \\ 2 & 3 & christina seufert (usa) & 481.41 & 5 & 517.62 \\ 3 & 4 & li yihua (chn) & 517.92 & 1 & 506.52 \\ 4 & 5 & li qiaoxian (chn) & 466.83 & 6 & 487.68 \\ 5 & 6 & elsa tenorio (mex) & 460.56 & 8 & 463.56 \\ 6 & 7 & lesley smith (zim) & 438.72 & 10 & 451.89 \\ 7 & 8 & debbie fuller (can) & 437.04 & 11 & 450.99 \\ 8 & 9 & jennifer donnet (aus) & 432.78 & 12 & 443.13 \\ 9 & 10 & daphne jongejans (ned) & 487.95 & 4 & 437.4 \\ 10 & 11 & anita rossing (swe) & 464.58 & 7 & 424.98 \\ 11 & 12 & veronica ribot (arg) & 443.25 & 9 & 422.52 \\ 12 & 13 & ann fargher (nzl) & 421.65 & 13 & none \\ 13 & 14 & tine tollan (nor) & 419.55 & 14 & none \\ 14 & 15 & antonette wilken (zim) & 414.66 & 15 & none \\ 15 & 16 & guadalupe canseco (mex) & 411.96 & 16 & none \\ 16 & 17 & claire izacard (fra) & 403.17 & 17 & none \\ 17 & 18 & valerie mcfarland-beddoe (aus) & 401.13 & 18 & none \\ 18 & 19 & alison childs (gbr) & 400.68 & 19 & none \\ 19 & 20 & kerstin finke (frg) & 393.93 & 20 & none \\ 20 & 21 & nicole kreil (aut) & 382.68 & 21 & none \\ 21 & 22 & joana figueiredo (por) & 374.07 & 22 & none \\ 22 & 23 & angela ribeiro (bra) & 370.68 & 23 & none \\ 23 & 24 & rim hassan (egy) & 258.63 & 24 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & diver \\ \midrule 0 & tine tollan (nor) \\ \bottomrule \end{tabular}	select diver where diver = 'tine tollan (nor)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>diver</th> <th>preliminary points</th> <th>preliminary rank</th> <th>final points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>sylvie bernier (can)</td> <td>489.51</td> <td>3</td> <td>530.7</td> </tr> <tr> <th>1</th> <td>2</td> <td>kelly mccormick (usa)</td> <td>516.75</td> <td>2</td> <td>527.46</td> </tr> <tr> <th>2</th> <td>3</td> <td>christina seufert (usa)</td> <td>481.41</td> <td>5</td> <td>517.62</td> </tr> <tr> <th>3</th> <td>4</td> <td>li yihua (chn)</td> <td>517.92</td> <td>1</td> <td>506.52</td> </tr> <tr> <th>4</th> <td>5</td> <td>li qiaoxian (chn)</td> <td>466.83</td> <td>6</td> <td>487.68</td> </tr> <tr> <th>5</th> <td>6</td> <td>elsa tenorio (mex)</td> <td>460.56</td> <td>8</td> <td>463.56</td> </tr> <tr> <th>6</th> <td>7</td> <td>lesley smith (zim)</td> <td>438.72</td> <td>10</td> <td>451.89</td> </tr> <tr> <th>7</th> <td>8</td> <td>debbie fuller (can)</td> <td>437.04</td> <td>11</td> <td>450.99</td> </tr> <tr> <th>8</th> <td>9</td> <td>jennifer donnet (aus)</td> <td>432.78</td> <td>12</td> <td>443.13</td> </tr> <tr> <th>9</th> <td>10</td> <td>daphne jongejans (ned)</td> <td>487.95</td> <td>4</td> <td>437.4</td> </tr> <tr> <th>10</th> <td>11</td> <td>anita rossing (swe)</td> <td>464.58</td> <td>7</td> <td>424.98</td> </tr> <tr> <th>11</th> <td>12</td> <td>veronica ribot (arg)</td> <td>443.25</td> <td>9</td> <td>422.52</td> </tr> <tr> <th>12</th> <td>13</td> <td>ann fargher (nzl)</td> <td>421.65</td> <td>13</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>tine tollan (nor)</td> <td>419.55</td> <td>14</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>antonette wilken (zim)</td> <td>414.66</td> <td>15</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>guadalupe canseco (mex)</td> <td>411.96</td> <td>16</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>claire izacard (fra)</td> <td>403.17</td> <td>17</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>valerie mcfarland-beddoe (aus)</td> <td>401.13</td> <td>18</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>alison childs (gbr)</td> <td>400.68</td> <td>19</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>kerstin finke (frg)</td> <td>393.93</td> <td>20</td> <td>none</td> </tr> <tr> <th>20</th> <td>21</td> <td>nicole kreil (aut)</td> <td>382.68</td> <td>21</td> <td>none</td> </tr> <tr> <th>21</th> <td>22</td> <td>joana figueiredo (por)</td> <td>374.07</td> <td>22</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>angela ribeiro (bra)</td> <td>370.68</td> <td>23</td> <td>none</td> </tr> <tr> <th>23</th> <td>24</td> <td>rim hassan (egy)</td> <td>258.63</td> <td>24</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>diver</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>tine tollan (nor)</td> </tr> </tbody> </table>	select diver where diver = 'tine tollan (nor)' <table_name> : table \| \| rank \| diver \| preliminary points \| preliminary rank \| final points \| \|---:\|-------:\|:-------------------------------\|---------------------:\|-------------------:\|:---------------\| \| 0 \| 1 \| sylvie bernier (can) \| 489.51 \| 3 \| 530.7 \| \| 1 \| 2 \| kelly mccormick (usa) \| 516.75 \| 2 \| 527.46 \| \| 2 \| 3 \| christina seufert (usa) \| 481.41 \| 5 \| 517.62 \| \| 3 \| 4 \| li yihua (chn) \| 517.92 \| 1 \| 506.52 \| \| 4 \| 5 \| li qiaoxian (chn) \| 466.83 \| 6 \| 487.68 \| \| 5 \| 6 \| elsa tenorio (mex) \| 460.56 \| 8 \| 463.56 \| \| 6 \| 7 \| lesley smith (zim) \| 438.72 \| 10 \| 451.89 \| \| 7 \| 8 \| debbie fuller (can) \| 437.04 \| 11 \| 450.99 \| \| 8 \| 9 \| jennifer donnet (aus) \| 432.78 \| 12 \| 443.13 \| \| 9 \| 10 \| daphne jongejans (ned) \| 487.95 \| 4 \| 437.4 \| \| 10 \| 11 \| anita rossing (swe) \| 464.58 \| 7 \| 424.98 \| \| 11 \| 12 \| veronica ribot (arg) \| 443.25 \| 9 \| 422.52 \| \| 12 \| 13 \| ann fargher (nzl) \| 421.65 \| 13 \| none \| \| 13 \| 14 \| tine tollan (nor) \| 419.55 \| 14 \| none \| \| 14 \| 15 \| antonette wilken (zim) \| 414.66 \| 15 \| none \| \| 15 \| 16 \| guadalupe canseco (mex) \| 411.96 \| 16 \| none \| \| 16 \| 17 \| claire izacard (fra) \| 403.17 \| 17 \| none \| \| 17 \| 18 \| valerie mcfarland-beddoe (aus) \| 401.13 \| 18 \| none \| \| 18 \| 19 \| alison childs (gbr) \| 400.68 \| 19 \| none \| \| 19 \| 20 \| kerstin finke (frg) \| 393.93 \| 20 \| none \| \| 20 \| 21 \| nicole kreil (aut) \| 382.68 \| 21 \| none \| \| 21 \| 22 \| joana figueiredo (por) \| 374.07 \| 22 \| none \| \| 22 \| 23 \| angela ribeiro (bra) \| 370.68 \| 23 \| none \| \| 23 \| 24 \| 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select position where chart = 'mainstream rock tracks' col : year \| single \| chart \| position row 1 : 1999 \| "heavy" \| billboard hot 100 \| 73 row 2 : 1999 \| "heavy" \| mainstream rock tracks \| 1 row 3 : 1999 \| "heavy" \| modern rock tracks \| 5 row 4 : 1999 \| "run" \| billboard hot 100 \| 76 row 5 : 1999 \| "run" \| modern rock tracks \| 36 row 6 : 1999 \| "run" \| adult top 40 \| 12 row 7 : 1999 \| "no more, no less" \| mainstream rock tracks \| 10 row 8 : 1999 \| "no more, no less" \| modern rock tracks \| 32 row 9 : 1999 \| "tremble for my beloved" \| mainstream rock tracks \| 35	col : position row 1 : 1 row 2 : 10 row 3 : 35	select position where chart = 'mainstream rock tracks' <table_name> : table \begin{tabular}{lllll} \toprule & year & single & chart & position \\ \midrule 0 & 1999 & "heavy" & billboard hot 100 & 73 \\ 1 & 1999 & "heavy" & mainstream rock tracks & 1 \\ 2 & 1999 & "heavy" & modern rock tracks & 5 \\ 3 & 1999 & "run" & billboard hot 100 & 76 \\ 4 & 1999 & "run" & modern rock tracks & 36 \\ 5 & 1999 & "run" & adult top 40 & 12 \\ 6 & 1999 & "no more, no less" & mainstream rock tracks & 10 \\ 7 & 1999 & "no more, no less" & modern rock tracks & 32 \\ 8 & 1999 & "tremble for my beloved" & mainstream rock tracks & 35 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & position \\ \midrule 0 & 1 \\ 1 & 10 \\ 2 & 35 \\ \bottomrule \end{tabular}	select position where chart = 'mainstream rock tracks' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>single</th> <th>chart</th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>"heavy"</td> <td>billboard hot 100</td> <td>73</td> </tr> <tr> <th>1</th> <td>1999</td> <td>"heavy"</td> <td>mainstream rock tracks</td> <td>1</td> </tr> <tr> <th>2</th> <td>1999</td> <td>"heavy"</td> <td>modern rock tracks</td> <td>5</td> </tr> <tr> <th>3</th> <td>1999</td> <td>"run"</td> <td>billboard hot 100</td> <td>76</td> </tr> <tr> <th>4</th> <td>1999</td> <td>"run"</td> <td>modern rock tracks</td> <td>36</td> </tr> <tr> <th>5</th> <td>1999</td> <td>"run"</td> <td>adult top 40</td> <td>12</td> </tr> <tr> <th>6</th> <td>1999</td> <td>"no more, no less"</td> <td>mainstream rock tracks</td> <td>10</td> </tr> <tr> <th>7</th> <td>1999</td> <td>"no more, no less"</td> <td>modern rock tracks</td> <td>32</td> </tr> <tr> <th>8</th> <td>1999</td> <td>"tremble for my beloved"</td> <td>mainstream rock tracks</td> <td>35</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> <tr> <th>1</th> <td>10</td> </tr> <tr> <th>2</th> <td>35</td> </tr> </tbody> </table>	select position where chart = 'mainstream rock tracks' <table_name> : table \| \| year \| single \| chart \| position \| \|---:\|-------:\|:-------------------------\|:-----------------------\|-----------:\| \| 0 \| 1999 \| "heavy" \| billboard hot 100 \| 73 \| \| 1 \| 1999 \| "heavy" \| mainstream rock tracks \| 1 \| \| 2 \| 1999 \| "heavy" \| modern rock tracks \| 5 \| \| 3 \| 1999 \| "run" \| billboard hot 100 \| 76 \| \| 4 \| 1999 \| "run" \| modern rock tracks \| 36 \| \| 5 \| 1999 \| "run" \| adult top 40 \| 12 \| \| 6 \| 1999 \| "no more, no less" \| mainstream rock tracks \| 10 \| \| 7 \| 1999 \| "no more, no less" \| modern rock tracks \| 32 \| \| 8 \| 1999 \| "tremble for my beloved" \| mainstream rock tracks \| 35 \|	\| \| position \| \|---:\|-----------:\| \| 0 \| 1 \| \| 1 \| 10 \| \| 2 \| 35 \|	[ [ 1, 4025, 1754, 1625, 4980, 273, 296, 5254, 3256, 23486, 13933, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 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select count ( nation ) where nation = 'switzerland' and gold > 1783 col : rank \| nation \| gold \| silver \| bronze \| total row 1 : 1 \| canada \| 9 \| 6 \| 5 \| 20 row 2 : 2 \| united states \| 8 \| 7 \| 8 \| 23 row 3 : 3 \| austria \| 7 \| 9 \| 8 \| 24 row 4 : 4 \| japan \| 4 \| 2 \| 1 \| 7 row 5 : 5 \| italy \| 3 \| 7 \| 4 \| 14 row 6 : 6 \| france \| 3 \| 4 \| 4 \| 11 row 7 : 7 \| australia \| 3 \| 4 \| 0 \| 7 row 8 : 8 \| norway \| 2 \| 2 \| 2 \| 6 row 9 : 9 \| slovenia \| 2 \| 1 \| 2 \| 5 row 10 : 10 \| finland \| 2 \| 1 \| 1 \| 4 row 11 : 10 \| germany \| 2 \| 1 \| 1 \| 4 row 12 : 12 \| russia \| 2 \| 0 \| 3 \| 5 row 13 : 13 \| switzerland \| 1 \| 5 \| 5 \| 11 row 14 : 14 \| china \| 1 \| 1 \| 1 \| 3 row 15 : 15 \| poland \| 1 \| 1 \| 0 \| 2 row 16 : 16 \| czech republic \| 1 \| 0 \| 1 \| 2 row 17 : 17 \| belgium \| 1 \| 0 \| 0 \| 1 row 18 : 18 \| netherlands \| 0 \| 1 \| 0 \| 1 row 19 : 19 \| spain \| 0 \| 0 \| 3 \| 3 row 20 : 20 \| bulgaria \| 0 \| 0 \| 1 \| 1 row 21 : 20 \| great britain \| 0 \| 0 \| 1 \| 1 row 22 : 20 \| sweden \| 0 \| 0 \| 1 \| 1 row 23 : total \| total \| 52 \| 52 \| 52 \| 156	col : count ( "nation" ) row 1 : 0	select count ( nation ) where nation = 'switzerland' and gold > 1783 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & canada & 9 & 6 & 5 & 20 \\ 1 & 2 & united states & 8 & 7 & 8 & 23 \\ 2 & 3 & austria & 7 & 9 & 8 & 24 \\ 3 & 4 & japan & 4 & 2 & 1 & 7 \\ 4 & 5 & italy & 3 & 7 & 4 & 14 \\ 5 & 6 & france & 3 & 4 & 4 & 11 \\ 6 & 7 & australia & 3 & 4 & 0 & 7 \\ 7 & 8 & norway & 2 & 2 & 2 & 6 \\ 8 & 9 & slovenia & 2 & 1 & 2 & 5 \\ 9 & 10 & finland & 2 & 1 & 1 & 4 \\ 10 & 10 & germany & 2 & 1 & 1 & 4 \\ 11 & 12 & russia & 2 & 0 & 3 & 5 \\ 12 & 13 & switzerland & 1 & 5 & 5 & 11 \\ 13 & 14 & china & 1 & 1 & 1 & 3 \\ 14 & 15 & poland & 1 & 1 & 0 & 2 \\ 15 & 16 & czech republic & 1 & 0 & 1 & 2 \\ 16 & 17 & belgium & 1 & 0 & 0 & 1 \\ 17 & 18 & netherlands & 0 & 1 & 0 & 1 \\ 18 & 19 & spain & 0 & 0 & 3 & 3 \\ 19 & 20 & bulgaria & 0 & 0 & 1 & 1 \\ 20 & 20 & great britain & 0 & 0 & 1 & 1 \\ 21 & 20 & sweden & 0 & 0 & 1 & 1 \\ 22 & total & total & 52 & 52 & 52 & 156 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "nation" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( nation ) where nation = 'switzerland' and gold > 1783 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>canada</td> <td>9</td> <td>6</td> <td>5</td> <td>20</td> </tr> <tr> <th>1</th> <td>2</td> <td>united states</td> <td>8</td> <td>7</td> <td>8</td> <td>23</td> </tr> <tr> <th>2</th> <td>3</td> <td>austria</td> <td>7</td> <td>9</td> <td>8</td> <td>24</td> </tr> <tr> <th>3</th> <td>4</td> <td>japan</td> <td>4</td> <td>2</td> <td>1</td> <td>7</td> </tr> <tr> <th>4</th> <td>5</td> <td>italy</td> <td>3</td> <td>7</td> <td>4</td> <td>14</td> </tr> <tr> <th>5</th> <td>6</td> <td>france</td> <td>3</td> <td>4</td> <td>4</td> <td>11</td> </tr> <tr> <th>6</th> <td>7</td> <td>australia</td> <td>3</td> <td>4</td> <td>0</td> <td>7</td> </tr> <tr> <th>7</th> <td>8</td> <td>norway</td> <td>2</td> <td>2</td> <td>2</td> <td>6</td> </tr> <tr> <th>8</th> <td>9</td> <td>slovenia</td> <td>2</td> <td>1</td> <td>2</td> <td>5</td> </tr> <tr> <th>9</th> <td>10</td> <td>finland</td> <td>2</td> <td>1</td> <td>1</td> <td>4</td> </tr> <tr> <th>10</th> <td>10</td> <td>germany</td> <td>2</td> <td>1</td> <td>1</td> <td>4</td> </tr> <tr> <th>11</th> <td>12</td> <td>russia</td> <td>2</td> <td>0</td> <td>3</td> <td>5</td> </tr> <tr> <th>12</th> <td>13</td> <td>switzerland</td> <td>1</td> <td>5</td> <td>5</td> <td>11</td> </tr> <tr> <th>13</th> <td>14</td> <td>china</td> <td>1</td> <td>1</td> <td>1</td> <td>3</td> </tr> <tr> <th>14</th> <td>15</td> <td>poland</td> <td>1</td> <td>1</td> <td>0</td> <td>2</td> </tr> <tr> <th>15</th> <td>16</td> <td>czech republic</td> <td>1</td> <td>0</td> <td>1</td> <td>2</td> </tr> <tr> <th>16</th> <td>17</td> <td>belgium</td> <td>1</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>17</th> <td>18</td> <td>netherlands</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>18</th> <td>19</td> <td>spain</td> <td>0</td> <td>0</td> <td>3</td> <td>3</td> </tr> <tr> <th>19</th> <td>20</td> <td>bulgaria</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>20</th> <td>20</td> <td>great britain</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>21</th> <td>20</td> <td>sweden</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>22</th> <td>total</td> <td>total</td> <td>52</td> <td>52</td> <td>52</td> <td>156</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "nation" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( nation ) where nation = 'switzerland' and gold > 1783 <table_name> : table \| \| rank \| nation \| gold \| silver \| bronze \| total \| \|---:\|:-------\|:---------------\|-------:\|---------:\|---------:\|--------:\| \| 0 \| 1 \| canada \| 9 \| 6 \| 5 \| 20 \| \| 1 \| 2 \| united states \| 8 \| 7 \| 8 \| 23 \| \| 2 \| 3 \| austria \| 7 \| 9 \| 8 \| 24 \| \| 3 \| 4 \| japan \| 4 \| 2 \| 1 \| 7 \| \| 4 \| 5 \| italy \| 3 \| 7 \| 4 \| 14 \| \| 5 \| 6 \| france \| 3 \| 4 \| 4 \| 11 \| \| 6 \| 7 \| australia \| 3 \| 4 \| 0 \| 7 \| \| 7 \| 8 \| norway \| 2 \| 2 \| 2 \| 6 \| \| 8 \| 9 \| slovenia \| 2 \| 1 \| 2 \| 5 \| \| 9 \| 10 \| finland \| 2 \| 1 \| 1 \| 4 \| \| 10 \| 10 \| germany \| 2 \| 1 \| 1 \| 4 \| \| 11 \| 12 \| russia \| 2 \| 0 \| 3 \| 5 \| \| 12 \| 13 \| switzerland \| 1 \| 5 \| 5 \| 11 \| \| 13 \| 14 \| china \| 1 \| 1 \| 1 \| 3 \| \| 14 \| 15 \| poland \| 1 \| 1 \| 0 \| 2 \| \| 15 \| 16 \| czech republic \| 1 \| 0 \| 1 \| 2 \| \| 16 \| 17 \| belgium \| 1 \| 0 \| 0 \| 1 \| \| 17 \| 18 \| netherlands \| 0 \| 1 \| 0 \| 1 \| \| 18 \| 19 \| spain \| 0 \| 0 \| 3 \| 3 \| \| 19 \| 20 \| bulgaria \| 0 \| 0 \| 1 \| 1 \| \| 20 \| 20 \| great britain \| 0 \| 0 \| 1 \| 1 \| \| 21 \| 20 \| sweden \| 0 \| 0 \| 1 \| 1 \| \| 22 \| total \| total \| 52 \| 52 \| 52 \| 156 \|	\| \| count ( "nation" ) \| \|---:\|---------------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 290, 367, 262, 1625, 290, 367, 273, 296, 5328, 305, 24355, 15733, 11, 471, 20465, 405, 8043, 10261, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 82, 367, 1757, 451, 34, 203, 1377, 411, 451, 34, 75, 1673, 1757, 451, 34, 203, 1377, 411, 451, 34, 25119, 502, 1757, 451, 34, 203, 1377, 411, 451, 34, 70, 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select count ( * ) where country = 'italy' and points < '38.66' col : rank \| athlete \| country \| time \| behind \| points row 1 : 1 \| sven kramer \| netherlands \| 01:53.98 \| 0.0 \| 37.993 row 2 : 2 \| sverre lunde pedersen \| norway \| 1:54.87 \| 0.89 \| 38.29 row 3 : 3 \| jan blokhuijsen \| netherlands \| 1:54.93 \| 0.95 \| 38.31 row 4 : 4 \| denis yuskov \| russia \| 1:55.13 \| 1.15 \| 38.376 row 5 : 5 \| koen verweij \| netherlands \| 1:55.42 \| 1.44 \| 38.473 row 6 : 6 \| haralds silovs \| latvia \| 1:55.48 \| 1.5 \| 38.493 row 7 : 7 \| zbigniew brodka \| poland \| 1:55.98 \| 2.0 \| 38.66 row 8 : 8 \| bart swings \| belgium \| 1:56.08 \| 2.1 \| 38.693 row 9 : 9 \| havard bøkko \| norway \| 1:56.35 \| 2.37 \| 38.783 row 10 : 10 \| jan szymanski \| poland \| 1:56.55 \| 2.57 \| 38.85 row 11 : 11 \| bram smallenbroek \| austria \| 1:57.44 \| 3.46 \| 39.146 row 12 : 12 \| alexis contin \| france \| 1:57.58 \| 3.6 \| 39.193 row 13 : 13 \| benjamin mace \| france \| 1:57.80 \| 3.82 \| 39.266 row 14 : 14 \| konrad niedzwiedzki \| poland \| 1:57.92 \| 3.94 \| 39.306 row 15 : 15 \| sergey gryaztsov \| russia \| 1:58.73 \| 4.75 \| 39.576 row 16 : 16 \| patrick beckert \| germany \| 1:59.08 \| 5.1 \| 39.693 row 17 : 17 \| kristian reistad fredriksen \| norway \| 1:59.19 \| 5.21 \| 39.73 row 18 : 18 \| luca stefani \| italy \| 1:59.82 \| 5.84 \| 39.94 row 19 : 19 \| marco cignini \| italy \| 1:59.97 \| 5.99 \| 39.99 row 20 : 20 \| ferre spruyt \| belgium \| 2:00.00 \| 6.02 \| 40.0 row 21 : 21 \| vitaly mikhailov \| belarus \| 2:00.75 \| 6.77 \| 40.52 row 22 : 22 \| milan sablik \| czech republic \| 2:00.95 \| 6.97 \| 40.316 row 23 : 23 \| ted jan bloemen \| netherlands \| 2:01.58 \| 7.6 \| 40.526 row 24 : 24 \| moritz geisreiter \| germany \| 2:01.64 \| 7.66 \| 40.566	col : count ( "*" ) row 1 : 0	select count ( * ) where country = 'italy' and points < '38.66' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & athlete & country & time & behind & points \\ \midrule 0 & 1 & sven kramer & netherlands & 01:53.98 & 0.0 & 37.993 \\ 1 & 2 & sverre lunde pedersen & norway & 1:54.87 & 0.89 & 38.29 \\ 2 & 3 & jan blokhuijsen & netherlands & 1:54.93 & 0.95 & 38.31 \\ 3 & 4 & denis yuskov & russia & 1:55.13 & 1.15 & 38.376 \\ 4 & 5 & koen verweij & netherlands & 1:55.42 & 1.44 & 38.473 \\ 5 & 6 & haralds silovs & latvia & 1:55.48 & 1.5 & 38.493 \\ 6 & 7 & zbigniew brodka & poland & 1:55.98 & 2.0 & 38.66 \\ 7 & 8 & bart swings & belgium & 1:56.08 & 2.1 & 38.693 \\ 8 & 9 & havard bøkko & norway & 1:56.35 & 2.37 & 38.783 \\ 9 & 10 & jan szymanski & poland & 1:56.55 & 2.57 & 38.85 \\ 10 & 11 & bram smallenbroek & austria & 1:57.44 & 3.46 & 39.146 \\ 11 & 12 & alexis contin & france & 1:57.58 & 3.6 & 39.193 \\ 12 & 13 & benjamin mace & france & 1:57.80 & 3.82 & 39.266 \\ 13 & 14 & konrad niedzwiedzki & poland & 1:57.92 & 3.94 & 39.306 \\ 14 & 15 & sergey gryaztsov & russia & 1:58.73 & 4.75 & 39.576 \\ 15 & 16 & patrick beckert & germany & 1:59.08 & 5.1 & 39.693 \\ 16 & 17 & kristian reistad fredriksen & norway & 1:59.19 & 5.21 & 39.73 \\ 17 & 18 & luca stefani & italy & 1:59.82 & 5.84 & 39.94 \\ 18 & 19 & marco cignini & italy & 1:59.97 & 5.99 & 39.99 \\ 19 & 20 & ferre spruyt & belgium & 2:00.00 & 6.02 & 40.0 \\ 20 & 21 & vitaly mikhailov & belarus & 2:00.75 & 6.77 & 40.52 \\ 21 & 22 & milan sablik & czech republic & 2:00.95 & 6.97 & 40.316 \\ 22 & 23 & ted jan bloemen & netherlands & 2:01.58 & 7.6 & 40.526 \\ 23 & 24 & moritz geisreiter & germany & 2:01.64 & 7.66 & 40.566 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where country = 'italy' and points < '38.66' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>athlete</th> <th>country</th> <th>time</th> <th>behind</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>sven kramer</td> <td>netherlands</td> <td>01:53.98</td> <td>0.0</td> <td>37.993</td> </tr> <tr> <th>1</th> <td>2</td> <td>sverre lunde pedersen</td> <td>norway</td> <td>1:54.87</td> <td>0.89</td> <td>38.29</td> </tr> <tr> <th>2</th> <td>3</td> <td>jan blokhuijsen</td> <td>netherlands</td> <td>1:54.93</td> <td>0.95</td> <td>38.31</td> </tr> <tr> <th>3</th> <td>4</td> <td>denis yuskov</td> <td>russia</td> <td>1:55.13</td> <td>1.15</td> <td>38.376</td> </tr> <tr> <th>4</th> <td>5</td> <td>koen verweij</td> <td>netherlands</td> <td>1:55.42</td> <td>1.44</td> <td>38.473</td> </tr> <tr> <th>5</th> <td>6</td> <td>haralds silovs</td> <td>latvia</td> <td>1:55.48</td> <td>1.5</td> <td>38.493</td> </tr> <tr> <th>6</th> <td>7</td> <td>zbigniew brodka</td> <td>poland</td> <td>1:55.98</td> <td>2.0</td> <td>38.66</td> </tr> <tr> <th>7</th> <td>8</td> <td>bart swings</td> <td>belgium</td> <td>1:56.08</td> <td>2.1</td> <td>38.693</td> </tr> <tr> <th>8</th> <td>9</td> <td>havard bøkko</td> <td>norway</td> <td>1:56.35</td> <td>2.37</td> <td>38.783</td> </tr> <tr> <th>9</th> <td>10</td> <td>jan szymanski</td> <td>poland</td> <td>1:56.55</td> <td>2.57</td> <td>38.85</td> </tr> <tr> <th>10</th> <td>11</td> <td>bram smallenbroek</td> <td>austria</td> <td>1:57.44</td> <td>3.46</td> <td>39.146</td> </tr> <tr> <th>11</th> <td>12</td> <td>alexis contin</td> <td>france</td> <td>1:57.58</td> <td>3.6</td> <td>39.193</td> </tr> <tr> <th>12</th> <td>13</td> <td>benjamin mace</td> <td>france</td> <td>1:57.80</td> <td>3.82</td> <td>39.266</td> </tr> <tr> <th>13</th> <td>14</td> <td>konrad niedzwiedzki</td> <td>poland</td> <td>1:57.92</td> <td>3.94</td> <td>39.306</td> </tr> <tr> <th>14</th> <td>15</td> <td>sergey gryaztsov</td> <td>russia</td> <td>1:58.73</td> <td>4.75</td> <td>39.576</td> </tr> <tr> <th>15</th> <td>16</td> <td>patrick beckert</td> <td>germany</td> <td>1:59.08</td> <td>5.1</td> <td>39.693</td> </tr> <tr> <th>16</th> <td>17</td> <td>kristian reistad fredriksen</td> <td>norway</td> <td>1:59.19</td> <td>5.21</td> <td>39.73</td> </tr> <tr> <th>17</th> <td>18</td> <td>luca stefani</td> <td>italy</td> <td>1:59.82</td> <td>5.84</td> <td>39.94</td> </tr> <tr> <th>18</th> <td>19</td> <td>marco cignini</td> <td>italy</td> <td>1:59.97</td> <td>5.99</td> <td>39.99</td> </tr> <tr> <th>19</th> <td>20</td> <td>ferre spruyt</td> <td>belgium</td> <td>2:00.00</td> <td>6.02</td> <td>40.0</td> </tr> <tr> <th>20</th> <td>21</td> <td>vitaly mikhailov</td> <td>belarus</td> <td>2:00.75</td> <td>6.77</td> <td>40.52</td> </tr> <tr> <th>21</th> <td>22</td> <td>milan sablik</td> <td>czech republic</td> <td>2:00.95</td> <td>6.97</td> <td>40.316</td> </tr> <tr> <th>22</th> <td>23</td> <td>ted jan bloemen</td> <td>netherlands</td> <td>2:01.58</td> <td>7.6</td> <td>40.526</td> </tr> <tr> <th>23</th> <td>24</td> <td>moritz geisreiter</td> <td>germany</td> <td>2:01.64</td> <td>7.66</td> <td>40.566</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where country = 'italy' and points < '38.66' <table_name> : table \| \| rank \| athlete \| country \| time \| behind \| points \| \|---:\|-------:\|:----------------------------\|:---------------\|:---------\|---------:\|---------:\| \| 0 \| 1 \| sven kramer \| netherlands \| 01:53.98 \| 0 \| 37.993 \| \| 1 \| 2 \| sverre lunde pedersen \| norway \| 1:54.87 \| 0.89 \| 38.29 \| \| 2 \| 3 \| jan blokhuijsen \| netherlands \| 1:54.93 \| 0.95 \| 38.31 \| \| 3 \| 4 \| denis yuskov \| russia \| 1:55.13 \| 1.15 \| 38.376 \| \| 4 \| 5 \| koen verweij \| netherlands \| 1:55.42 \| 1.44 \| 38.473 \| \| 5 \| 6 \| haralds silovs \| latvia \| 1:55.48 \| 1.5 \| 38.493 \| \| 6 \| 7 \| zbigniew brodka \| poland \| 1:55.98 \| 2 \| 38.66 \| \| 7 \| 8 \| bart swings \| belgium \| 1:56.08 \| 2.1 \| 38.693 \| \| 8 \| 9 \| havard bøkko \| norway \| 1:56.35 \| 2.37 \| 38.783 \| \| 9 \| 10 \| jan szymanski \| poland \| 1:56.55 \| 2.57 \| 38.85 \| \| 10 \| 11 \| bram smallenbroek \| austria \| 1:57.44 \| 3.46 \| 39.146 \| \| 11 \| 12 \| alexis contin \| france \| 1:57.58 \| 3.6 \| 39.193 \| \| 12 \| 13 \| benjamin mace \| france \| 1:57.80 \| 3.82 \| 39.266 \| \| 13 \| 14 \| konrad niedzwiedzki \| poland \| 1:57.92 \| 3.94 \| 39.306 \| \| 14 \| 15 \| sergey gryaztsov \| russia \| 1:58.73 \| 4.75 \| 39.576 \| \| 15 \| 16 \| patrick beckert \| germany \| 1:59.08 \| 5.1 \| 39.693 \| \| 16 \| 17 \| kristian reistad fredriksen \| norway \| 1:59.19 \| 5.21 \| 39.73 \| \| 17 \| 18 \| luca stefani \| italy \| 1:59.82 \| 5.84 \| 39.94 \| \| 18 \| 19 \| marco cignini \| italy \| 1:59.97 \| 5.99 \| 39.99 \| \| 19 \| 20 \| ferre spruyt \| belgium \| 2:00.00 \| 6.02 \| 40 \| \| 20 \| 21 \| vitaly mikhailov \| belarus \| 2:00.75 \| 6.77 \| 40.52 \| \| 21 \| 22 \| milan sablik \| czech republic \| 2:00.95 \| 6.97 \| 40.316 \| \| 22 \| 23 \| ted jan bloemen \| netherlands \| 2:01.58 \| 7.6 \| 40.526 \| \| 23 \| 24 \| moritz geisreiter \| germany \| 2:01.64 \| 7.66 \| 40.566 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 5251, 273, 296, 305, 3450, 11, 471, 3143, 411, 296, 7414, 18, 6028, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 421, 1810, 73, 1757, 451, 34, 203, 1377, 411, 451, 34, 9082, 1757, 451, 34, 203, 1377, 411, 451, 34, 957, 1757, 451, 34, 203, 1377, 411, 451, 34, 2196, 31748, 1757, 451, 34, 203, 1377, 411, 451, 34, 4139, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 21, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 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select count ( nurse : population ratio ) where mid wife: population ratio = 8 col : region \| physician (gp & specialist) \| physician : population ratio \| health officer \| ho : population ratio \| all nurses \| nurse : population ratio \| mid-wives \| mid wife: population ratio \| hew \| hew : population ratio row 1 : tigray \| 101 \| 1:44,880 \| 188 \| 1:24,111 \| 2332 \| 1:1,944 \| 185 \| 1:24,502 \| 1433 \| 1:3,163 row 2 : afar \| 15 \| 1:98,258 \| 29 \| 1:50,823 \| 185 \| 1:7,967 \| none \| none \| 572 \| 1:2,577 row 3 : amhara \| 304 \| 1:58,567 \| 434 \| 1:41,024 \| 3790 \| 1:4,698 \| 212 \| 1:83,983 \| 7471 \| 1:2,383 row 4 : oromia \| 378 \| 1:76,075 \| 448 \| 1:64,189 \| 5040 \| 1:5,706 \| 287 \| 1:100,197 \| 13856 \| 1:2,075 row 5 : somalia \| 71 \| 1:65,817 \| 12 \| 1:389,415 \| 314 \| 1:14,882 \| 45 \| 1:103,844 \| 1427 \| 1:3,275 row 6 : ben-gumuz \| 12 \| 1:59,309 \| 42 \| 1:16,945 \| 452 \| 1:1,575 \| 37 \| 1:19,235 \| 499 \| 1:1,426 row 7 : snnpr \| 242 \| 1:65,817 \| 220 \| 1:72,398 \| 3980 \| 1:4,002 \| 316 \| 1:50,404 \| 7915 \| 1:2,012 row 8 : gambella \| 13 \| 1:25,585 \| 13 \| 1:25,585 \| 91 \| 1:3,655 \| 4 \| 1:83,150 \| 457 \| 1:728 row 9 : harari \| 29 \| 1:6,655 \| 31 \| 1:6,226 \| 276 \| 1:699 \| 29 \| 1:6,655 \| 47 \| 1:4,106 row 10 : addis ababa \| 934 \| 1:3,056 \| 170 \| 1:16,791 \| 3377 \| 1:845 \| 244 \| 1:11,699 \| none \| none row 11 : diredawa \| 53 \| 1:6,796 \| 19 \| 1:18,957 \| 272 \| 1:1,324 \| 20 \| 1:18,009 \| 142 \| 1:2,537	col : count ( "nurse : population ratio" ) row 1 : 0	select count ( nurse : population ratio ) where mid wife: population ratio = 8 <table_name> : table \begin{tabular}{llllllllllll} \toprule & region & physician (gp & specialist) & physician : population ratio & health officer & ho : population ratio & all nurses & nurse : population ratio & mid-wives & mid wife: population ratio & hew & hew : population ratio \\ \midrule 0 & tigray & 101 & 1:44,880 & 188 & 1:24,111 & 2332 & 1:1,944 & 185 & 1:24,502 & 1433 & 1:3,163 \\ 1 & afar & 15 & 1:98,258 & 29 & 1:50,823 & 185 & 1:7,967 & none & none & 572 & 1:2,577 \\ 2 & amhara & 304 & 1:58,567 & 434 & 1:41,024 & 3790 & 1:4,698 & 212 & 1:83,983 & 7471 & 1:2,383 \\ 3 & oromia & 378 & 1:76,075 & 448 & 1:64,189 & 5040 & 1:5,706 & 287 & 1:100,197 & 13856 & 1:2,075 \\ 4 & somalia & 71 & 1:65,817 & 12 & 1:389,415 & 314 & 1:14,882 & 45 & 1:103,844 & 1427 & 1:3,275 \\ 5 & ben-gumuz & 12 & 1:59,309 & 42 & 1:16,945 & 452 & 1:1,575 & 37 & 1:19,235 & 499 & 1:1,426 \\ 6 & snnpr & 242 & 1:65,817 & 220 & 1:72,398 & 3980 & 1:4,002 & 316 & 1:50,404 & 7915 & 1:2,012 \\ 7 & gambella & 13 & 1:25,585 & 13 & 1:25,585 & 91 & 1:3,655 & 4 & 1:83,150 & 457 & 1:728 \\ 8 & harari & 29 & 1:6,655 & 31 & 1:6,226 & 276 & 1:699 & 29 & 1:6,655 & 47 & 1:4,106 \\ 9 & addis ababa & 934 & 1:3,056 & 170 & 1:16,791 & 3377 & 1:845 & 244 & 1:11,699 & none & none \\ 10 & diredawa & 53 & 1:6,796 & 19 & 1:18,957 & 272 & 1:1,324 & 20 & 1:18,009 & 142 & 1:2,537 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "nurse \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( nurse : population ratio ) where mid wife: population ratio = 8 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>region</th> <th>physician (gp & specialist)</th> <th>physician : population ratio</th> <th>health officer</th> <th>ho : population ratio</th> <th>all nurses</th> <th>nurse : population ratio</th> <th>mid-wives</th> <th>mid wife: population ratio</th> <th>hew</th> <th>hew : population ratio</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>tigray</td> <td>101</td> <td>1:44,880</td> <td>188</td> <td>1:24,111</td> <td>2332</td> <td>1:1,944</td> <td>185</td> <td>1:24,502</td> <td>1433</td> <td>1:3,163</td> </tr> <tr> <th>1</th> <td>afar</td> <td>15</td> <td>1:98,258</td> <td>29</td> <td>1:50,823</td> <td>185</td> <td>1:7,967</td> <td>none</td> <td>none</td> <td>572</td> <td>1:2,577</td> </tr> <tr> <th>2</th> <td>amhara</td> <td>304</td> <td>1:58,567</td> <td>434</td> <td>1:41,024</td> <td>3790</td> <td>1:4,698</td> <td>212</td> <td>1:83,983</td> <td>7471</td> <td>1:2,383</td> </tr> <tr> <th>3</th> <td>oromia</td> <td>378</td> <td>1:76,075</td> <td>448</td> <td>1:64,189</td> <td>5040</td> <td>1:5,706</td> <td>287</td> <td>1:100,197</td> <td>13856</td> <td>1:2,075</td> </tr> <tr> <th>4</th> <td>somalia</td> <td>71</td> <td>1:65,817</td> <td>12</td> <td>1:389,415</td> <td>314</td> <td>1:14,882</td> <td>45</td> <td>1:103,844</td> <td>1427</td> <td>1:3,275</td> </tr> <tr> <th>5</th> <td>ben-gumuz</td> <td>12</td> <td>1:59,309</td> <td>42</td> <td>1:16,945</td> <td>452</td> <td>1:1,575</td> <td>37</td> <td>1:19,235</td> <td>499</td> <td>1:1,426</td> </tr> <tr> <th>6</th> <td>snnpr</td> <td>242</td> <td>1:65,817</td> <td>220</td> <td>1:72,398</td> <td>3980</td> <td>1:4,002</td> <td>316</td> <td>1:50,404</td> <td>7915</td> <td>1:2,012</td> </tr> <tr> <th>7</th> <td>gambella</td> <td>13</td> <td>1:25,585</td> <td>13</td> <td>1:25,585</td> <td>91</td> <td>1:3,655</td> <td>4</td> <td>1:83,150</td> <td>457</td> <td>1:728</td> </tr> <tr> <th>8</th> <td>harari</td> <td>29</td> <td>1:6,655</td> <td>31</td> <td>1:6,226</td> <td>276</td> <td>1:699</td> <td>29</td> <td>1:6,655</td> <td>47</td> <td>1:4,106</td> </tr> <tr> <th>9</th> <td>addis ababa</td> <td>934</td> <td>1:3,056</td> <td>170</td> <td>1:16,791</td> <td>3377</td> <td>1:845</td> <td>244</td> <td>1:11,699</td> <td>none</td> <td>none</td> </tr> <tr> <th>10</th> <td>diredawa</td> <td>53</td> <td>1:6,796</td> <td>19</td> <td>1:18,957</td> <td>272</td> <td>1:1,324</td> <td>20</td> <td>1:18,009</td> <td>142</td> <td>1:2,537</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "nurse</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( nurse : population ratio ) where mid wife: population ratio = 8 <table_name> : table \| \| region \| physician (gp & specialist) \| physician : population ratio \| health officer \| ho : population ratio \| all nurses \| nurse : population ratio \| mid-wives \| mid wife: population ratio \| hew \| hew : population ratio \| \|---:\|:------------\|------------------------------:\|:-------------------------------\|-----------------:\|:------------------------\|-------------:\|:---------------------------\|:------------\|:-----------------------------\|:------\|:-------------------------\| \| 0 \| tigray \| 101 \| 1:44,880 \| 188 \| 1:24,111 \| 2332 \| 1:1,944 \| 185 \| 1:24,502 \| 1433 \| 1:3,163 \| \| 1 \| afar \| 15 \| 1:98,258 \| 29 \| 1:50,823 \| 185 \| 1:7,967 \| none \| none \| 572 \| 1:2,577 \| \| 2 \| amhara \| 304 \| 1:58,567 \| 434 \| 1:41,024 \| 3790 \| 1:4,698 \| 212 \| 1:83,983 \| 7471 \| 1:2,383 \| \| 3 \| oromia \| 378 \| 1:76,075 \| 448 \| 1:64,189 \| 5040 \| 1:5,706 \| 287 \| 1:100,197 \| 13856 \| 1:2,075 \| \| 4 \| somalia \| 71 \| 1:65,817 \| 12 \| 1:389,415 \| 314 \| 1:14,882 \| 45 \| 1:103,844 \| 1427 \| 1:3,275 \| \| 5 \| ben-gumuz \| 12 \| 1:59,309 \| 42 \| 1:16,945 \| 452 \| 1:1,575 \| 37 \| 1:19,235 \| 499 \| 1:1,426 \| \| 6 \| snnpr \| 242 \| 1:65,817 \| 220 \| 1:72,398 \| 3980 \| 1:4,002 \| 316 \| 1:50,404 \| 7915 \| 1:2,012 \| \| 7 \| gambella \| 13 \| 1:25,585 \| 13 \| 1:25,585 \| 91 \| 1:3,655 \| 4 \| 1:83,150 \| 457 \| 1:728 \| \| 8 \| harari \| 29 \| 1:6,655 \| 31 \| 1:6,226 \| 276 \| 1:699 \| 29 \| 1:6,655 \| 47 \| 1:4,106 \| \| 9 \| addis ababa \| 934 \| 1:3,056 \| 170 \| 1:16,791 \| 3377 \| 1:845 \| 244 \| 1:11,699 \| none \| none \| \| 10 \| diredawa \| 53 \| 1:6,796 \| 19 \| 1:18,957 \| 272 \| 1:1,324 \| 20 \| 1:18,009 \| 142 \| 1:2,537 \|	\| \| count ( "nurse \| \|---:\|-----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 290, 295, 307, 294, 11209, 7169, 262, 1625, 7501, 341, 24723, 30, 11209, 7169, 273, 1725, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 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select count ( * ) where score = 'winner' col : outcome \| no. \| date \| tournament \| surface \| opponent \| score row 1 : runner-up \| 1 \| 2004-08-23 00:00:00 \| la paz, bolivia \| clay \| jenifer widjaja \| 6-3, 4-6, 0-6 row 2 : runner-up \| 2 \| 2005-06-06 00:00:00 \| santa tecla, el salvador \| clay \| andrea benitez \| 3-6, 0-6 row 3 : runner-up \| 2 \| 2005-08-22 00:00:00 \| bogota, colombia \| clay \| carla tiene \| 4-6, 0-6 row 4 : runner-up \| 4 \| 2006-05-15 00:00:00 \| ciudad obregon, mexico \| hard \| ellah nze \| 6-4, 3-6, 3-6 row 5 : winner \| 1 \| 2006-06-05 00:00:00 \| xalapa, mexico \| hard \| maria irigoyen \| 6-1, 3-6, 6-4 row 6 : winner \| 2 \| 2009-09-07 00:00:00 \| mazatlan, mexico \| hard \| fernanda hermenegildo \| 6-1, 6-2 row 7 : winner \| 3 \| 2009-11-02 00:00:00 \| bogota, colombia \| clay \| yuliana lizarazo \| 7-6(7-5), 6-4 row 8 : runner-up \| 5 \| 2009-11-16 00:00:00 \| asuncion, paraguay \| clay \| paula ormaechea \| 6-4, 4-6, 2-6 row 9 : winner \| 4 \| 2010-11-08 00:00:00 \| bogota, colombia \| clay \| patricia ku flores \| 6-1, 7-5 row 10 : winner \| 5 \| 2010-11-29 00:00:00 \| santiago, chile \| clay \| veronica cepede royg \| 6-2, 6-2 row 11 : winner \| 6 \| 2011-07-18 00:00:00 \| ribeirao preto, brazil \| clay \| vivian segnini \| 6-2, 6-2 row 12 : runner-up \| 6 \| 2011-08-08 00:00:00 \| santa cruz de la sierra, bolivia \| clay \| maria irigoyen \| 2-6, 3-6 row 13 : winner \| 7 \| 2011-08-15 00:00:00 \| la paz, bolivia \| clay \| maria irigoyen \| 6-0, 7-6(7-1) row 14 : runner-up \| 7 \| 2011-10-03 00:00:00 \| yerevan, armenia \| clay \| julia cohen \| 6-7(6-8), 2-6 row 15 : runner-up \| 8 \| 2012-03-19 00:00:00 \| bangalore, india \| hard \| donna vekic \| 2-6, 4-6 row 16 : runner-up \| 9 \| 2012-05-08 00:00:00 \| brasilia, brazil \| clay \| gabriela paz \| 3-6, 3-6 row 17 : winner \| 8 \| 2012-11-19 00:00:00 \| barranquilla, colombia \| clay \| karolina nowak \| 7-6(7-4), 6-0 row 18 : winner \| 9 \| 2013-10-21 00:00:00 \| bogota, colombia \| hard \| anna katalina alzate esmurzaeva \| 6-3, 6-3 row 19 : winner \| 10 \| 2013-11-11 00:00:00 \| lima, peru \| clay \| patricia ku flores \| 7-5, 6-7(4-7), 6-2 row 20 : winner \| 11 \| 2013-11-25 00:00:00 \| bogota, colombia \| clay \| naomi totka \| 6-1, 6-1 row 21 : runner-up \| 10 \| 2013-12-02 00:00:00 \| barranquilla, colombia \| clay \| maria fernanda herazo \| 4-6, 2-6	col : count ( "*" ) row 1 : 0	select count ( * ) where score = 'winner' <table_name> : table \begin{tabular}{llllllll} \toprule & outcome & no. & date & tournament & surface & opponent & score \\ \midrule 0 & runner-up & 1 & 2004-08-23 00:00:00 & la paz, bolivia & clay & jenifer widjaja & 6-3, 4-6, 0-6 \\ 1 & runner-up & 2 & 2005-06-06 00:00:00 & santa tecla, el salvador & clay & andrea benitez & 3-6, 0-6 \\ 2 & runner-up & 2 & 2005-08-22 00:00:00 & bogota, colombia & clay & carla tiene & 4-6, 0-6 \\ 3 & runner-up & 4 & 2006-05-15 00:00:00 & ciudad obregon, mexico & hard & ellah nze & 6-4, 3-6, 3-6 \\ 4 & winner & 1 & 2006-06-05 00:00:00 & xalapa, mexico & hard & maria irigoyen & 6-1, 3-6, 6-4 \\ 5 & winner & 2 & 2009-09-07 00:00:00 & mazatlan, mexico & hard & fernanda hermenegildo & 6-1, 6-2 \\ 6 & winner & 3 & 2009-11-02 00:00:00 & bogota, colombia & clay & yuliana lizarazo & 7-6(7-5), 6-4 \\ 7 & runner-up & 5 & 2009-11-16 00:00:00 & asuncion, paraguay & clay & paula ormaechea & 6-4, 4-6, 2-6 \\ 8 & winner & 4 & 2010-11-08 00:00:00 & bogota, colombia & clay & patricia ku flores & 6-1, 7-5 \\ 9 & winner & 5 & 2010-11-29 00:00:00 & santiago, chile & clay & veronica cepede royg & 6-2, 6-2 \\ 10 & winner & 6 & 2011-07-18 00:00:00 & ribeirao preto, brazil & clay & vivian segnini & 6-2, 6-2 \\ 11 & runner-up & 6 & 2011-08-08 00:00:00 & santa cruz de la sierra, bolivia & clay & maria irigoyen & 2-6, 3-6 \\ 12 & winner & 7 & 2011-08-15 00:00:00 & la paz, bolivia & clay & maria irigoyen & 6-0, 7-6(7-1) \\ 13 & runner-up & 7 & 2011-10-03 00:00:00 & yerevan, armenia & clay & julia cohen & 6-7(6-8), 2-6 \\ 14 & runner-up & 8 & 2012-03-19 00:00:00 & bangalore, india & hard & donna vekic & 2-6, 4-6 \\ 15 & runner-up & 9 & 2012-05-08 00:00:00 & brasilia, brazil & clay & gabriela paz & 3-6, 3-6 \\ 16 & winner & 8 & 2012-11-19 00:00:00 & barranquilla, colombia & clay & karolina nowak & 7-6(7-4), 6-0 \\ 17 & winner & 9 & 2013-10-21 00:00:00 & bogota, colombia & hard & anna katalina alzate esmurzaeva & 6-3, 6-3 \\ 18 & winner & 10 & 2013-11-11 00:00:00 & lima, peru & clay & patricia ku flores & 7-5, 6-7(4-7), 6-2 \\ 19 & winner & 11 & 2013-11-25 00:00:00 & bogota, colombia & clay & naomi totka & 6-1, 6-1 \\ 20 & runner-up & 10 & 2013-12-02 00:00:00 & barranquilla, colombia & clay & maria fernanda herazo & 4-6, 2-6 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where score = 'winner' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>outcome</th> <th>no.</th> <th>date</th> <th>tournament</th> <th>surface</th> <th>opponent</th> <th>score</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>runner-up</td> <td>1</td> <td>2004-08-23 00:00:00</td> <td>la paz, bolivia</td> <td>clay</td> <td>jenifer widjaja</td> <td>6-3, 4-6, 0-6</td> </tr> <tr> <th>1</th> <td>runner-up</td> <td>2</td> <td>2005-06-06 00:00:00</td> <td>santa tecla, el salvador</td> <td>clay</td> <td>andrea benitez</td> <td>3-6, 0-6</td> </tr> <tr> <th>2</th> <td>runner-up</td> <td>2</td> <td>2005-08-22 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>carla tiene</td> <td>4-6, 0-6</td> </tr> <tr> <th>3</th> <td>runner-up</td> <td>4</td> <td>2006-05-15 00:00:00</td> <td>ciudad obregon, mexico</td> <td>hard</td> <td>ellah nze</td> <td>6-4, 3-6, 3-6</td> </tr> <tr> <th>4</th> <td>winner</td> <td>1</td> <td>2006-06-05 00:00:00</td> <td>xalapa, mexico</td> <td>hard</td> <td>maria irigoyen</td> <td>6-1, 3-6, 6-4</td> </tr> <tr> <th>5</th> <td>winner</td> <td>2</td> <td>2009-09-07 00:00:00</td> <td>mazatlan, mexico</td> <td>hard</td> <td>fernanda hermenegildo</td> <td>6-1, 6-2</td> </tr> <tr> <th>6</th> <td>winner</td> <td>3</td> <td>2009-11-02 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>yuliana lizarazo</td> <td>7-6(7-5), 6-4</td> </tr> <tr> <th>7</th> <td>runner-up</td> <td>5</td> <td>2009-11-16 00:00:00</td> <td>asuncion, paraguay</td> <td>clay</td> <td>paula ormaechea</td> <td>6-4, 4-6, 2-6</td> </tr> <tr> <th>8</th> <td>winner</td> <td>4</td> <td>2010-11-08 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>patricia ku flores</td> <td>6-1, 7-5</td> </tr> <tr> <th>9</th> <td>winner</td> <td>5</td> <td>2010-11-29 00:00:00</td> <td>santiago, chile</td> <td>clay</td> <td>veronica cepede royg</td> <td>6-2, 6-2</td> </tr> <tr> <th>10</th> <td>winner</td> <td>6</td> <td>2011-07-18 00:00:00</td> <td>ribeirao preto, brazil</td> <td>clay</td> <td>vivian segnini</td> <td>6-2, 6-2</td> </tr> <tr> <th>11</th> <td>runner-up</td> <td>6</td> <td>2011-08-08 00:00:00</td> <td>santa cruz de la sierra, bolivia</td> <td>clay</td> <td>maria irigoyen</td> <td>2-6, 3-6</td> </tr> <tr> <th>12</th> <td>winner</td> <td>7</td> <td>2011-08-15 00:00:00</td> <td>la paz, bolivia</td> <td>clay</td> <td>maria irigoyen</td> <td>6-0, 7-6(7-1)</td> </tr> <tr> <th>13</th> <td>runner-up</td> <td>7</td> <td>2011-10-03 00:00:00</td> <td>yerevan, armenia</td> <td>clay</td> <td>julia cohen</td> <td>6-7(6-8), 2-6</td> </tr> <tr> <th>14</th> <td>runner-up</td> <td>8</td> <td>2012-03-19 00:00:00</td> <td>bangalore, india</td> <td>hard</td> <td>donna vekic</td> <td>2-6, 4-6</td> </tr> <tr> <th>15</th> <td>runner-up</td> <td>9</td> <td>2012-05-08 00:00:00</td> <td>brasilia, brazil</td> <td>clay</td> <td>gabriela paz</td> <td>3-6, 3-6</td> </tr> <tr> <th>16</th> <td>winner</td> <td>8</td> <td>2012-11-19 00:00:00</td> <td>barranquilla, colombia</td> <td>clay</td> <td>karolina nowak</td> <td>7-6(7-4), 6-0</td> </tr> <tr> <th>17</th> <td>winner</td> <td>9</td> <td>2013-10-21 00:00:00</td> <td>bogota, colombia</td> <td>hard</td> <td>anna katalina alzate esmurzaeva</td> <td>6-3, 6-3</td> </tr> <tr> <th>18</th> <td>winner</td> <td>10</td> <td>2013-11-11 00:00:00</td> <td>lima, peru</td> <td>clay</td> <td>patricia ku flores</td> <td>7-5, 6-7(4-7), 6-2</td> </tr> <tr> <th>19</th> <td>winner</td> <td>11</td> <td>2013-11-25 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>naomi totka</td> <td>6-1, 6-1</td> </tr> <tr> <th>20</th> <td>runner-up</td> <td>10</td> <td>2013-12-02 00:00:00</td> <td>barranquilla, colombia</td> <td>clay</td> <td>maria fernanda herazo</td> <td>4-6, 2-6</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where score = 'winner' <table_name> : table \| \| outcome \| no. \| date \| tournament \| surface \| opponent \| score \| \|---:\|:----------\|------:\|:--------------------\|:---------------------------------\|:----------\|:--------------------------------\|:-------------------\| \| 0 \| runner-up \| 1 \| 2004-08-23 00:00:00 \| la paz, bolivia \| clay \| jenifer widjaja \| 6-3, 4-6, 0-6 \| \| 1 \| runner-up \| 2 \| 2005-06-06 00:00:00 \| santa tecla, el salvador \| clay \| andrea benitez \| 3-6, 0-6 \| \| 2 \| runner-up \| 2 \| 2005-08-22 00:00:00 \| bogota, colombia \| clay \| carla tiene \| 4-6, 0-6 \| \| 3 \| runner-up \| 4 \| 2006-05-15 00:00:00 \| ciudad obregon, mexico \| hard \| ellah nze \| 6-4, 3-6, 3-6 \| \| 4 \| winner \| 1 \| 2006-06-05 00:00:00 \| xalapa, mexico \| hard \| maria irigoyen \| 6-1, 3-6, 6-4 \| \| 5 \| winner \| 2 \| 2009-09-07 00:00:00 \| mazatlan, mexico \| hard \| fernanda hermenegildo \| 6-1, 6-2 \| \| 6 \| winner \| 3 \| 2009-11-02 00:00:00 \| bogota, colombia \| clay \| yuliana lizarazo \| 7-6(7-5), 6-4 \| \| 7 \| runner-up \| 5 \| 2009-11-16 00:00:00 \| asuncion, paraguay \| clay \| paula ormaechea \| 6-4, 4-6, 2-6 \| \| 8 \| winner \| 4 \| 2010-11-08 00:00:00 \| bogota, colombia \| clay \| patricia ku flores \| 6-1, 7-5 \| \| 9 \| winner \| 5 \| 2010-11-29 00:00:00 \| santiago, chile \| clay \| veronica cepede royg \| 6-2, 6-2 \| \| 10 \| winner \| 6 \| 2011-07-18 00:00:00 \| ribeirao preto, brazil \| clay \| vivian segnini \| 6-2, 6-2 \| \| 11 \| runner-up \| 6 \| 2011-08-08 00:00:00 \| santa cruz de la sierra, bolivia \| clay \| maria irigoyen \| 2-6, 3-6 \| \| 12 \| winner \| 7 \| 2011-08-15 00:00:00 \| la paz, bolivia \| clay \| maria irigoyen \| 6-0, 7-6(7-1) \| \| 13 \| runner-up \| 7 \| 2011-10-03 00:00:00 \| yerevan, armenia \| clay \| julia cohen \| 6-7(6-8), 2-6 \| \| 14 \| runner-up \| 8 \| 2012-03-19 00:00:00 \| bangalore, india \| hard \| donna vekic \| 2-6, 4-6 \| \| 15 \| runner-up \| 9 \| 2012-05-08 00:00:00 \| brasilia, brazil \| clay \| gabriela paz \| 3-6, 3-6 \| \| 16 \| winner \| 8 \| 2012-11-19 00:00:00 \| barranquilla, colombia \| clay \| karolina nowak \| 7-6(7-4), 6-0 \| \| 17 \| winner \| 9 \| 2013-10-21 00:00:00 \| bogota, colombia \| hard \| anna katalina alzate esmurzaeva \| 6-3, 6-3 \| \| 18 \| winner \| 10 \| 2013-11-11 00:00:00 \| lima, peru \| clay \| patricia ku flores \| 7-5, 6-7(4-7), 6-2 \| \| 19 \| winner \| 11 \| 2013-11-25 00:00:00 \| bogota, colombia \| clay \| naomi totka \| 6-1, 6-1 \| \| 20 \| runner-up \| 10 \| 2013-12-02 00:00:00 \| barranquilla, colombia \| clay \| maria fernanda herazo \| 4-6, 2-6 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 4462, 273, 296, 91, 7872, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 21672, 1757, 451, 34, 203, 1377, 411, 451, 34, 2135, 17347, 451, 34, 203, 1377, 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select home town/city where district = 118 col : representative \| party \| home town/city \| district row 1 : trey martinez fischer \| d \| san antonio \| 116 row 2 : philip cortez \| d \| san antonio \| 117 row 3 : joe farias \| d \| san antonio \| 118 row 4 : roland gutierrez \| d \| san antonio \| 119 row 5 : ruth mcclendon \| d \| san antonio \| 120 row 6 : joe straus \| r \| san antonio \| 121 row 7 : lyle larson \| r \| san antonio \| 122 row 8 : mike villarreal \| d \| san antonio \| 123 row 9 : jose menendez \| d \| san antonio \| 124 row 10 : justin rodriguez \| d \| san antonio \| 125	col : home town/city row 1 : san antonio	select home town/city where district = 118 <table_name> : table \begin{tabular}{lllll} \toprule & representative & party & home town/city & district \\ \midrule 0 & trey martinez fischer & d & san antonio & 116 \\ 1 & philip cortez & d & san antonio & 117 \\ 2 & joe farias & d & san antonio & 118 \\ 3 & roland gutierrez & d & san antonio & 119 \\ 4 & ruth mcclendon & d & san antonio & 120 \\ 5 & joe straus & r & san antonio & 121 \\ 6 & lyle larson & r & san antonio & 122 \\ 7 & mike villarreal & d & san antonio & 123 \\ 8 & jose menendez & d & san antonio & 124 \\ 9 & justin rodriguez & d & san antonio & 125 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & home town/city \\ \midrule 0 & san antonio \\ \bottomrule \end{tabular}	select home town/city where district = 118 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>representative</th> <th>party</th> <th>home town/city</th> <th>district</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>trey martinez fischer</td> <td>d</td> <td>san antonio</td> <td>116</td> </tr> <tr> <th>1</th> <td>philip cortez</td> <td>d</td> <td>san antonio</td> <td>117</td> </tr> <tr> <th>2</th> <td>joe farias</td> <td>d</td> <td>san antonio</td> <td>118</td> </tr> <tr> <th>3</th> <td>roland gutierrez</td> <td>d</td> <td>san antonio</td> <td>119</td> </tr> <tr> <th>4</th> <td>ruth mcclendon</td> <td>d</td> <td>san antonio</td> <td>120</td> </tr> <tr> <th>5</th> <td>joe straus</td> <td>r</td> <td>san antonio</td> <td>121</td> </tr> <tr> <th>6</th> <td>lyle larson</td> <td>r</td> <td>san antonio</td> <td>122</td> </tr> <tr> <th>7</th> <td>mike villarreal</td> <td>d</td> <td>san antonio</td> <td>123</td> </tr> <tr> <th>8</th> <td>jose menendez</td> <td>d</td> <td>san antonio</td> <td>124</td> </tr> <tr> <th>9</th> <td>justin rodriguez</td> <td>d</td> <td>san antonio</td> <td>125</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>home town/city</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>san antonio</td> </tr> </tbody> </table>	select home town/city where district = 118 <table_name> : table \| \| representative \| party \| home town/city \| district \| \|---:\|:----------------------\|:--------\|:-----------------\|-----------:\| \| 0 \| trey martinez fischer \| d \| san antonio \| 116 \| \| 1 \| philip cortez \| d \| san antonio \| 117 \| \| 2 \| joe farias \| d \| san antonio \| 118 \| \| 3 \| roland gutierrez \| d \| san antonio \| 119 \| \| 4 \| ruth mcclendon \| d \| san antonio \| 120 \| \| 5 \| joe straus \| r \| san antonio \| 121 \| \| 6 \| lyle larson \| r \| san antonio \| 122 \| \| 7 \| mike villarreal \| d \| san antonio \| 123 \| \| 8 \| jose menendez \| d \| san antonio \| 124 \| \| 9 \| justin rodriguez \| d \| san antonio \| 125 \|	\| \| home town/city \| \|---:\|:-----------------\| \| 0 \| san antonio \|	[ [ 1, 4025, 6382, 358, 91, 82, 19, 14240, 1625, 1015, 5792, 273, 404, 2643, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 28205, 1535, 1757, 451, 34, 203, 1377, 411, 451, 34, 21214, 1757, 451, 34, 203, 1377, 411, 451, 34, 8712, 358, 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select area (km2) where ecclesiastical province = 'santo domingo' col : ecclesiastical jurisdictions \| latin name \| type \| rite \| ecclesiastical province \| established \| area (km2) row 1 : bani \| baniensis \| diocese \| roman \| santo domingo \| 8 november 1986 \| 2892 row 2 : barahona \| barahonensis \| diocese \| roman \| santo domingo \| 24 april 1976 \| 6973 row 3 : dominican republic \| reipublicae dominicanae \| military ordinariate \| roman \| immediately subject to the holy see \| 23 january 1958 \| none row 4 : la vega \| vegensis \| diocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 4919 row 5 : mao-monte cristi \| maoensis-montis christi \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 4841 row 6 : nuestra senora de la altagracia en higuey \| higueyensis / a domina nostra vulgo de la altagracia in higuey \| diocese \| roman \| santo domingo \| 1 april 1959 \| 5437 row 7 : puerto plata \| portus argentarii \| diocese \| roman \| santiago de los caballeros \| 16 december 1996 \| 2700 row 8 : san francisco de macoris \| sancti francisci de macoris \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 3682 row 9 : san juan de la maguana \| sancti ioannis maguanensis \| diocese \| roman \| santo domingo \| 25 september 1953 \| 7476 row 10 : san pedro de macoris \| sancti petri de macoris \| diocese \| roman \| santo domingo \| 1 february 1997 \| 2588 row 11 : santiago de los caballeros \| sancti iacobi equitum \| metropolitan archdiocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 6391 row 12 : santo domingo \| sancti dominici \| metropolitan archdiocese \| roman \| santo domingo \| 8 august 1511 \| 4033	col : area (km2) row 1 : 2892 row 2 : 6973 row 3 : 5437 row 4 : 7476 row 5 : 2588 row 6 : 4033	select area (km2) where ecclesiastical province = 'santo domingo' <table_name> : table \begin{tabular}{llllllll} \toprule & ecclesiastical jurisdictions & latin name & type & rite & ecclesiastical province & established & area (km2) \\ \midrule 0 & bani & baniensis & diocese & roman & santo domingo & 8 november 1986 & 2892 \\ 1 & barahona & barahonensis & diocese & roman & santo domingo & 24 april 1976 & 6973 \\ 2 & dominican republic & reipublicae dominicanae & military ordinariate & roman & immediately subject to the holy see & 23 january 1958 & none \\ 3 & la vega & vegensis & diocese & roman & santiago de los caballeros & 25 september 1953 & 4919 \\ 4 & mao-monte cristi & maoensis-montis christi & diocese & roman & santiago de los caballeros & 16 january 1978 & 4841 \\ 5 & nuestra senora de la altagracia en higuey & higueyensis / a domina nostra vulgo de la altagracia in higuey & diocese & roman & santo domingo & 1 april 1959 & 5437 \\ 6 & puerto plata & portus argentarii & diocese & roman & santiago de los caballeros & 16 december 1996 & 2700 \\ 7 & san francisco de macoris & sancti francisci de macoris & diocese & roman & santiago de los caballeros & 16 january 1978 & 3682 \\ 8 & san juan de la maguana & sancti ioannis maguanensis & diocese & roman & santo domingo & 25 september 1953 & 7476 \\ 9 & san pedro de macoris & sancti petri de macoris & diocese & roman & santo domingo & 1 february 1997 & 2588 \\ 10 & santiago de los caballeros & sancti iacobi equitum & metropolitan archdiocese & roman & santiago de los caballeros & 25 september 1953 & 6391 \\ 11 & santo domingo & sancti dominici & metropolitan archdiocese & roman & santo domingo & 8 august 1511 & 4033 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & area (km2) \\ \midrule 0 & 2892 \\ 1 & 6973 \\ 2 & 5437 \\ 3 & 7476 \\ 4 & 2588 \\ 5 & 4033 \\ \bottomrule \end{tabular}	select area (km2) where ecclesiastical province = 'santo domingo' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>ecclesiastical jurisdictions</th> <th>latin name</th> <th>type</th> <th>rite</th> <th>ecclesiastical province</th> <th>established</th> <th>area (km2)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>bani</td> <td>baniensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>8 november 1986</td> <td>2892</td> </tr> <tr> <th>1</th> <td>barahona</td> <td>barahonensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>24 april 1976</td> <td>6973</td> </tr> <tr> <th>2</th> <td>dominican republic</td> <td>reipublicae dominicanae</td> <td>military ordinariate</td> <td>roman</td> <td>immediately subject to the holy see</td> <td>23 january 1958</td> <td>none</td> </tr> <tr> <th>3</th> <td>la vega</td> <td>vegensis</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>4919</td> </tr> <tr> <th>4</th> <td>mao-monte cristi</td> <td>maoensis-montis christi</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>4841</td> </tr> <tr> <th>5</th> <td>nuestra senora de la altagracia en higuey</td> <td>higueyensis / a domina nostra vulgo de la altagracia in higuey</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 april 1959</td> <td>5437</td> </tr> <tr> <th>6</th> <td>puerto plata</td> <td>portus argentarii</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 december 1996</td> <td>2700</td> </tr> <tr> <th>7</th> <td>san francisco de macoris</td> <td>sancti francisci de macoris</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>3682</td> </tr> <tr> <th>8</th> <td>san juan de la maguana</td> <td>sancti ioannis maguanensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>25 september 1953</td> <td>7476</td> </tr> <tr> <th>9</th> <td>san pedro de macoris</td> <td>sancti petri de macoris</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 february 1997</td> <td>2588</td> </tr> <tr> <th>10</th> <td>santiago de los caballeros</td> <td>sancti iacobi equitum</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>6391</td> </tr> <tr> <th>11</th> <td>santo domingo</td> <td>sancti dominici</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santo domingo</td> <td>8 august 1511</td> <td>4033</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>area (km2)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2892</td> </tr> <tr> <th>1</th> <td>6973</td> </tr> <tr> <th>2</th> <td>5437</td> </tr> <tr> <th>3</th> <td>7476</td> </tr> <tr> <th>4</th> <td>2588</td> </tr> <tr> <th>5</th> <td>4033</td> </tr> </tbody> </table>	select area (km2) where ecclesiastical province = 'santo domingo' <table_name> : table \| \| ecclesiastical jurisdictions \| latin name \| type \| rite \| ecclesiastical province \| established \| area (km2) \| \|---:\|:------------------------------------------\|:---------------------------------------------------------------\|:-------------------------\|:-------\|:------------------------------------\|:------------------\|:-------------\| \| 0 \| bani \| baniensis \| diocese \| roman \| santo domingo \| 8 november 1986 \| 2892 \| \| 1 \| barahona \| barahonensis \| diocese \| roman \| santo domingo \| 24 april 1976 \| 6973 \| \| 2 \| dominican republic \| reipublicae dominicanae \| military ordinariate \| roman \| immediately subject to the holy see \| 23 january 1958 \| none \| \| 3 \| la vega \| vegensis \| diocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 4919 \| \| 4 \| mao-monte cristi \| maoensis-montis christi \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 4841 \| \| 5 \| nuestra senora de la altagracia en higuey \| higueyensis / a domina nostra vulgo de la altagracia in higuey \| diocese \| roman \| santo domingo \| 1 april 1959 \| 5437 \| \| 6 \| puerto plata \| portus argentarii \| diocese \| roman \| santiago de los caballeros \| 16 december 1996 \| 2700 \| \| 7 \| san francisco de macoris \| sancti francisci de macoris \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 3682 \| \| 8 \| san juan de la maguana \| sancti ioannis maguanensis \| diocese \| roman \| santo domingo \| 25 september 1953 \| 7476 \| \| 9 \| san pedro de macoris \| sancti petri de macoris \| diocese \| roman \| santo domingo \| 1 february 1997 \| 2588 \| \| 10 \| santiago de los caballeros \| sancti iacobi equitum \| metropolitan archdiocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 6391 \| \| 11 \| santo domingo \| sancti dominici \| metropolitan archdiocese \| roman \| santo domingo \| 8 august 1511 \| 4033 \|	\| \| area (km2) \| \|---:\|-------------:\| \| 0 \| 2892 \| \| 1 \| 6973 \| \| 2 \| 5437 \| \| 3 \| 7476 \| \| 4 \| 2588 \| \| 5 \| 4033 \|	[ [ 1, 4025, 5091, 261, 18353, 22, 13, 1625, 6557, 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select picture where # = 4 col : # \| picture \| name \| took office \| left office \| party row 1 : 1 \| none \| johan ferrier \| 25 november 1975 \| 13 august 1980 (resigned after a february coup d'etat) \| independent row 2 : 2 \| none \| hendrick chin a sen \| 15 august 1980 \| 4 february 1982 \| pnr row 3 : 3 \| none \| fred ramdat misier \| 8 february 1982 \| 25 january 1988 \| independent row 4 : 4 \| 60px \| ramsewak shankar \| 25 january 1988 \| 24 december 1990 (deposed) \| vhp row 5 : 5 \| 60px \| johan kraag \| 29 december 1990 \| 16 september 1991 \| nps row 6 : 6 \| none \| ronald venetiaan \| 16 september 1991 \| 15 september 1996 \| nps row 7 : 7 \| none \| jules wijdenbosch \| 15 september 1996 \| 12 august 2000 \| ndp row 8 : (6) \| none \| ronald venetiaan \| 12 august 2000 \| 12 august 2010 \| nps row 9 : 8 \| none \| desi bouterse \| 12 august 2010 \| incumbent \| ndp	col : picture row 1 : 60px	select picture where # = 4 <table_name> : table \begin{tabular}{lllllll} \toprule & # & picture & name & took office & left office & party \\ \midrule 0 & 1 & none & johan ferrier & 25 november 1975 & 13 august 1980 (resigned after a february coup d'etat) & independent \\ 1 & 2 & none & hendrick chin a sen & 15 august 1980 & 4 february 1982 & pnr \\ 2 & 3 & none & fred ramdat misier & 8 february 1982 & 25 january 1988 & independent \\ 3 & 4 & 60px & ramsewak shankar & 25 january 1988 & 24 december 1990 (deposed) & vhp \\ 4 & 5 & 60px & johan kraag & 29 december 1990 & 16 september 1991 & nps \\ 5 & 6 & none & ronald venetiaan & 16 september 1991 & 15 september 1996 & nps \\ 6 & 7 & none & jules wijdenbosch & 15 september 1996 & 12 august 2000 & ndp \\ 7 & (6) & none & ronald venetiaan & 12 august 2000 & 12 august 2010 & nps \\ 8 & 8 & none & desi bouterse & 12 august 2010 & incumbent & ndp \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & picture \\ \midrule 0 & 60px \\ \bottomrule \end{tabular}	select picture where # = 4 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>picture</th> <th>name</th> <th>took office</th> <th>left office</th> <th>party</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>none</td> <td>johan ferrier</td> <td>25 november 1975</td> <td>13 august 1980 (resigned after a february coup d'etat)</td> <td>independent</td> </tr> <tr> <th>1</th> <td>2</td> <td>none</td> <td>hendrick chin a sen</td> <td>15 august 1980</td> <td>4 february 1982</td> <td>pnr</td> </tr> <tr> <th>2</th> <td>3</td> <td>none</td> <td>fred ramdat misier</td> <td>8 february 1982</td> <td>25 january 1988</td> <td>independent</td> </tr> <tr> <th>3</th> <td>4</td> <td>60px</td> <td>ramsewak shankar</td> <td>25 january 1988</td> <td>24 december 1990 (deposed)</td> <td>vhp</td> </tr> <tr> <th>4</th> <td>5</td> <td>60px</td> <td>johan kraag</td> <td>29 december 1990</td> <td>16 september 1991</td> <td>nps</td> </tr> <tr> <th>5</th> <td>6</td> <td>none</td> <td>ronald venetiaan</td> <td>16 september 1991</td> <td>15 september 1996</td> <td>nps</td> </tr> <tr> <th>6</th> <td>7</td> <td>none</td> <td>jules wijdenbosch</td> <td>15 september 1996</td> <td>12 august 2000</td> <td>ndp</td> </tr> <tr> <th>7</th> <td>(6)</td> <td>none</td> <td>ronald venetiaan</td> <td>12 august 2000</td> <td>12 august 2010</td> <td>nps</td> </tr> <tr> <th>8</th> <td>8</td> <td>none</td> <td>desi bouterse</td> <td>12 august 2010</td> <td>incumbent</td> <td>ndp</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>picture</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>60px</td> </tr> </tbody> </table>	select picture where # = 4 <table_name> : table \| \| # \| picture \| name \| took office \| left office \| party \| \|---:\|:----\|:----------\|:--------------------\|:------------------\|:-------------------------------------------------------\|:------------\| \| 0 \| 1 \| none \| johan ferrier \| 25 november 1975 \| 13 august 1980 (resigned after a february coup d'etat) \| independent \| \| 1 \| 2 \| none \| hendrick chin a sen \| 15 august 1980 \| 4 february 1982 \| pnr \| \| 2 \| 3 \| none \| fred ramdat misier \| 8 february 1982 \| 25 january 1988 \| independent \| \| 3 \| 4 \| 60px \| ramsewak shankar \| 25 january 1988 \| 24 december 1990 (deposed) \| vhp \| \| 4 \| 5 \| 60px \| johan kraag \| 29 december 1990 \| 16 september 1991 \| nps \| \| 5 \| 6 \| none \| ronald venetiaan \| 16 september 1991 \| 15 september 1996 \| nps \| \| 6 \| 7 \| none \| jules wijdenbosch \| 15 september 1996 \| 12 august 2000 \| ndp \| \| 7 \| (6) \| none \| ronald venetiaan \| 12 august 2000 \| 12 august 2010 \| nps \| \| 8 \| 8 \| none \| desi bouterse \| 12 august 2010 \| incumbent \| ndp \|	\| \| picture \| \|---:\|:----------\| \| 0 \| 60px \|	[ [ 1, 4025, 15406, 1625, 468, 273, 1059, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 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select joined mac where type = 'private/non-sectarian' col : institution \| location \| nickname \| founded \| type \| enrollment \| joined mac row 1 : delaware valley college \| doylestown, pennsylvania \| aggies \| 1917 \| private/non-sectarian \| 2241 \| 1965 row 2 : desales university \| center valley, pennsylvania \| bulldogs \| 1965 \| private/catholic \| 3199 \| 1997 row 3 : eastern university \| st. davids, pennsylvania \| eagles \| 1952 \| private/baptist \| 4235 \| 2008 row 4 : fairleigh dickinson university-florham \| madison, new jersey \| devils \| 1942 \| private/non-sectarian \| 3288 \| 1977 row 5 : king's college \| wilkes-barre, pennsylvania \| monarchs \| 1946 \| private/catholic \| 2725 \| 1977 row 6 : manhattanville college \| purchase, new york \| valiants \| 1841 \| private/non-sectarian \| 2695 \| 2007 row 7 : misericordia university \| dallas, pennsylvania \| cougars \| 1924 \| private/catholic \| 2830 \| 2008 row 8 : wilkes university \| wilkes-barre, pennsylvania \| colonels \| 1933 \| private/non-sectarian \| 5136 \| 1946	col : joined mac row 1 : 1965 row 2 : 1977 row 3 : 2007 row 4 : 1946	select joined mac where type = 'private/non-sectarian' <table_name> : table \begin{tabular}{llllllll} \toprule & institution & location & nickname & founded & type & enrollment & joined mac \\ \midrule 0 & delaware valley college & doylestown, pennsylvania & aggies & 1917 & private/non-sectarian & 2241 & 1965 \\ 1 & desales university & center valley, pennsylvania & bulldogs & 1965 & private/catholic & 3199 & 1997 \\ 2 & eastern university & st. davids, pennsylvania & eagles & 1952 & private/baptist & 4235 & 2008 \\ 3 & fairleigh dickinson university-florham & madison, new jersey & devils & 1942 & private/non-sectarian & 3288 & 1977 \\ 4 & king's college & wilkes-barre, pennsylvania & monarchs & 1946 & private/catholic & 2725 & 1977 \\ 5 & manhattanville college & purchase, new york & valiants & 1841 & private/non-sectarian & 2695 & 2007 \\ 6 & misericordia university & dallas, pennsylvania & cougars & 1924 & private/catholic & 2830 & 2008 \\ 7 & wilkes university & wilkes-barre, pennsylvania & colonels & 1933 & private/non-sectarian & 5136 & 1946 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & joined mac \\ \midrule 0 & 1965 \\ 1 & 1977 \\ 2 & 2007 \\ 3 & 1946 \\ \bottomrule \end{tabular}	select joined mac where type = 'private/non-sectarian' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>institution</th> <th>location</th> <th>nickname</th> <th>founded</th> <th>type</th> <th>enrollment</th> <th>joined mac</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>delaware valley college</td> <td>doylestown, pennsylvania</td> <td>aggies</td> <td>1917</td> <td>private/non-sectarian</td> <td>2241</td> <td>1965</td> </tr> <tr> <th>1</th> <td>desales university</td> <td>center valley, pennsylvania</td> <td>bulldogs</td> <td>1965</td> <td>private/catholic</td> <td>3199</td> <td>1997</td> </tr> <tr> <th>2</th> <td>eastern university</td> <td>st. davids, pennsylvania</td> <td>eagles</td> <td>1952</td> <td>private/baptist</td> <td>4235</td> <td>2008</td> </tr> <tr> <th>3</th> <td>fairleigh dickinson university-florham</td> <td>madison, new jersey</td> <td>devils</td> <td>1942</td> <td>private/non-sectarian</td> <td>3288</td> <td>1977</td> </tr> <tr> <th>4</th> <td>king's college</td> <td>wilkes-barre, pennsylvania</td> <td>monarchs</td> <td>1946</td> <td>private/catholic</td> <td>2725</td> <td>1977</td> </tr> <tr> <th>5</th> <td>manhattanville college</td> <td>purchase, new york</td> <td>valiants</td> <td>1841</td> <td>private/non-sectarian</td> <td>2695</td> <td>2007</td> </tr> <tr> <th>6</th> <td>misericordia university</td> <td>dallas, pennsylvania</td> <td>cougars</td> <td>1924</td> <td>private/catholic</td> <td>2830</td> <td>2008</td> </tr> <tr> <th>7</th> <td>wilkes university</td> <td>wilkes-barre, pennsylvania</td> <td>colonels</td> <td>1933</td> <td>private/non-sectarian</td> <td>5136</td> <td>1946</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>joined mac</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1965</td> </tr> <tr> <th>1</th> <td>1977</td> </tr> <tr> <th>2</th> <td>2007</td> </tr> <tr> <th>3</th> <td>1946</td> </tr> </tbody> </table>	select joined mac where type = 'private/non-sectarian' <table_name> : table \| \| institution \| location \| nickname \| founded \| type \| enrollment \| joined mac \| \|---:\|:---------------------------------------\|:----------------------------\|:-----------\|----------:\|:----------------------\|-------------:\|-------------:\| \| 0 \| delaware valley college \| doylestown, pennsylvania \| aggies \| 1917 \| private/non-sectarian \| 2241 \| 1965 \| \| 1 \| desales university \| center valley, pennsylvania \| bulldogs \| 1965 \| private/catholic \| 3199 \| 1997 \| \| 2 \| eastern university \| st. davids, pennsylvania \| eagles \| 1952 \| private/baptist \| 4235 \| 2008 \| \| 3 \| fairleigh dickinson university-florham \| madison, new jersey \| devils \| 1942 \| private/non-sectarian \| 3288 \| 1977 \| \| 4 \| king's college \| wilkes-barre, pennsylvania \| monarchs \| 1946 \| private/catholic \| 2725 \| 1977 \| \| 5 \| manhattanville college \| purchase, new york \| valiants \| 1841 \| private/non-sectarian \| 2695 \| 2007 \| \| 6 \| misericordia university \| dallas, pennsylvania \| cougars \| 1924 \| private/catholic \| 2830 \| 2008 \| \| 7 \| wilkes university \| wilkes-barre, pennsylvania \| colonels \| 1933 \| private/non-sectarian \| 5136 \| 1946 \|	\| \| joined mac \| \|---:\|-------------:\| \| 0 \| 1965 \| \| 1 \| 1977 \| \| 2 \| 2007 \| \| 3 \| 1946 \|	[ [ 1, 4025, 12114, 5318, 1625, 618, 273, 296, 1152, 19, 5836, 17, 5709, 297, 2779, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 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select trainer where owner = 'dogwood stable' order by post asc limit 1615 col : finished \| post \| horse \| jockey \| trainer \| owner \| time / behind row 1 : 1st \| 6 \| silver charm \| gary l. stevens \| bob baffert \| bob & beverly lewis \| 2:02.44 row 2 : 2nd \| 5 \| captain bodgit \| alex solis \| gary a. capuano \| team valor \| none row 3 : 3rd \| 12 \| free house \| david flores \| j. paco gonzalez \| john toffan & trudy mccaffery \| none row 4 : 4th \| 3 \| pulpit \| shane sellers \| frank l. brothers \| claiborne farm \| none row 5 : 5th \| 10 \| crypto star \| pat day \| wayne m. catalano \| evelyn & darrell yates \| none row 6 : 6th \| 9 \| phantom on tour \| jerry d. bailey \| lynn s. whiting \| w. cal partee \| none row 7 : 7th \| 5 \| jack flash \| craig perret \| nick zito \| dogwood stable \| none row 8 : 8th \| 6 \| hello \| mike smith \| ronald mcanally \| sandee & al kirkwood \| none row 9 : 9th \| 1 \| concerto \| carlos h. marquez, jr \| john j. tammaro, iii \| kinsman stable \| none row 10 : 10th \| 13 \| celtic warrior \| francisco torres \| danny hutt \| hutt, quackenbush & shaffrick \| none row 11 : 11th \| 4 \| crimson classic \| robby albarado \| forrest kaelin \| john w. clay \| none row 12 : 12th \| 15 \| shammy davis \| willie martinez \| nick zito \| fox hill farm \| none row 13 : 13th \| 11 \| deeds not words \| corey nakatani \| d. wayne lukas \| michael tabor & susan magnier \| none	col : trainer row 1 : nick zito	select trainer where owner = 'dogwood stable' order by post asc limit 1615 <table_name> : table \begin{tabular}{llllllll} \toprule & finished & post & horse & jockey & trainer & owner & time / behind \\ \midrule 0 & 1st & 6 & silver charm & gary l. stevens & bob baffert & bob & beverly lewis & 2:02.44 \\ 1 & 2nd & 5 & captain bodgit & alex solis & gary a. capuano & team valor & none \\ 2 & 3rd & 12 & free house & david flores & j. paco gonzalez & john toffan & trudy mccaffery & none \\ 3 & 4th & 3 & pulpit & shane sellers & frank l. brothers & claiborne farm & none \\ 4 & 5th & 10 & crypto star & pat day & wayne m. catalano & evelyn & darrell yates & none \\ 5 & 6th & 9 & phantom on tour & jerry d. bailey & lynn s. whiting & w. cal partee & none \\ 6 & 7th & 5 & jack flash & craig perret & nick zito & dogwood stable & none \\ 7 & 8th & 6 & hello & mike smith & ronald mcanally & sandee & al kirkwood & none \\ 8 & 9th & 1 & concerto & carlos h. marquez, jr & john j. tammaro, iii & kinsman stable & none \\ 9 & 10th & 13 & celtic warrior & francisco torres & danny hutt & hutt, quackenbush & shaffrick & none \\ 10 & 11th & 4 & crimson classic & robby albarado & forrest kaelin & john w. clay & none \\ 11 & 12th & 15 & shammy davis & willie martinez & nick zito & fox hill farm & none \\ 12 & 13th & 11 & deeds not words & corey nakatani & d. wayne lukas & michael tabor & susan magnier & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & trainer \\ \midrule 0 & nick zito \\ \bottomrule \end{tabular}	select trainer where owner = 'dogwood stable' order by post asc limit 1615 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>finished</th> <th>post</th> <th>horse</th> <th>jockey</th> <th>trainer</th> <th>owner</th> <th>time / behind</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1st</td> <td>6</td> <td>silver charm</td> <td>gary l. stevens</td> <td>bob baffert</td> <td>bob & beverly lewis</td> <td>2:02.44</td> </tr> <tr> <th>1</th> <td>2nd</td> <td>5</td> <td>captain bodgit</td> <td>alex solis</td> <td>gary a. capuano</td> <td>team valor</td> <td>none</td> </tr> <tr> <th>2</th> <td>3rd</td> <td>12</td> <td>free house</td> <td>david flores</td> <td>j. paco gonzalez</td> <td>john toffan & trudy mccaffery</td> <td>none</td> </tr> <tr> <th>3</th> <td>4th</td> <td>3</td> <td>pulpit</td> <td>shane sellers</td> <td>frank l. brothers</td> <td>claiborne farm</td> <td>none</td> </tr> <tr> <th>4</th> <td>5th</td> <td>10</td> <td>crypto star</td> <td>pat day</td> <td>wayne m. catalano</td> <td>evelyn & darrell yates</td> <td>none</td> </tr> <tr> <th>5</th> <td>6th</td> <td>9</td> <td>phantom on tour</td> <td>jerry d. bailey</td> <td>lynn s. whiting</td> <td>w. cal partee</td> <td>none</td> </tr> <tr> <th>6</th> <td>7th</td> <td>5</td> <td>jack flash</td> <td>craig perret</td> <td>nick zito</td> <td>dogwood stable</td> <td>none</td> </tr> <tr> <th>7</th> <td>8th</td> <td>6</td> <td>hello</td> <td>mike smith</td> <td>ronald mcanally</td> <td>sandee & al kirkwood</td> <td>none</td> </tr> <tr> <th>8</th> <td>9th</td> <td>1</td> <td>concerto</td> <td>carlos h. marquez, jr</td> <td>john j. tammaro, iii</td> <td>kinsman stable</td> <td>none</td> </tr> <tr> <th>9</th> <td>10th</td> <td>13</td> <td>celtic warrior</td> <td>francisco torres</td> <td>danny hutt</td> <td>hutt, quackenbush & shaffrick</td> <td>none</td> </tr> <tr> <th>10</th> <td>11th</td> <td>4</td> <td>crimson classic</td> <td>robby albarado</td> <td>forrest kaelin</td> <td>john w. clay</td> <td>none</td> </tr> <tr> <th>11</th> <td>12th</td> <td>15</td> <td>shammy davis</td> <td>willie martinez</td> <td>nick zito</td> <td>fox hill farm</td> <td>none</td> </tr> <tr> <th>12</th> <td>13th</td> <td>11</td> <td>deeds not words</td> <td>corey nakatani</td> <td>d. wayne lukas</td> <td>michael tabor & susan magnier</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>trainer</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>nick zito</td> </tr> </tbody> </table>	select trainer where owner = 'dogwood stable' order by post asc limit 1615 <table_name> : table \| \| finished \| post \| horse \| jockey \| trainer \| owner \| time / behind \| \|---:\|:-----------\|-------:\|:----------------\|:----------------------\|:---------------------\|:------------------------------\|:----------------\| \| 0 \| 1st \| 6 \| silver charm \| gary l. stevens \| bob baffert \| bob & beverly lewis \| 2:02.44 \| \| 1 \| 2nd \| 5 \| captain bodgit \| alex solis \| gary a. capuano \| team valor \| none \| \| 2 \| 3rd \| 12 \| free house \| david flores \| j. paco gonzalez \| john toffan & trudy mccaffery \| none \| \| 3 \| 4th \| 3 \| pulpit \| shane sellers \| frank l. brothers \| claiborne farm \| none \| \| 4 \| 5th \| 10 \| crypto star \| pat day \| wayne m. catalano \| evelyn & darrell yates \| none \| \| 5 \| 6th \| 9 \| phantom on tour \| jerry d. bailey \| lynn s. whiting \| w. cal partee \| none \| \| 6 \| 7th \| 5 \| jack flash \| craig perret \| nick zito \| dogwood stable \| none \| \| 7 \| 8th \| 6 \| hello \| mike smith \| ronald mcanally \| sandee & al kirkwood \| none \| \| 8 \| 9th \| 1 \| concerto \| carlos h. marquez, jr \| john j. tammaro, iii \| kinsman stable \| none \| \| 9 \| 10th \| 13 \| celtic warrior \| francisco torres \| danny hutt \| hutt, quackenbush & shaffrick \| none \| \| 10 \| 11th \| 4 \| crimson classic \| robby albarado \| forrest kaelin \| john w. clay \| none \| \| 11 \| 12th \| 15 \| shammy davis \| willie martinez \| nick zito \| fox hill farm \| none \| \| 12 \| 13th \| 11 \| deeds not words \| corey nakatani \| d. wayne lukas \| michael tabor & susan magnier \| none \|	\| \| trainer \| \|---:\|:----------\| \| 0 \| nick zito \|	[ [ 1, 4025, 28974, 1625, 3410, 273, 296, 20330, 91, 4773, 14114, 11, 1353, 635, 1603, 6972, 1800, 2872, 3600, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 13527, 1757, 451, 34, 203, 1377, 411, 451, 34, 2767, 1757, 451, 34, 203, 1377, 411, 451, 34, 76, 23035, 1757, 451, 34, 203, 1377, 411, 451, 34, 78, 975, 402, 1757, 451, 34, 203, 1377, 411, 451, 34, 313, 1521, 1757, 451, 34, 203, 1377, 411, 451, 34, 8443, 1757, 451, 34, 203, 1377, 411, 451, 34, 957, 342, 21478, 1757, 451, 34, 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select count ( distinct term start ) where term end = '1 november 1971' col : name \| term start \| term end row 1 : pier ruggero piccio \| 1 january 1926 \| 6 february 1927 row 2 : armando armani \| 10 february 1927 \| 13 october 1928 row 3 : giuseppe valle \| 22 february 1930 \| 23 november 1933 row 4 : antonio bosio \| 23 november 1933 \| 22 march 1934 row 5 : giuseppe valle \| 22 march 1934 \| 10 november 1939 row 6 : francesco pricolo \| 10 november 1939 \| 15 november 1941 row 7 : rino corso fougier \| 15 november 1941 \| 27 july 1943 row 8 : renato sandalli \| 27 july 1943 \| 18 june 1944 row 9 : pietro piacentini \| 19 june 1944 \| 13 december 1944 row 10 : mario ajmone cat \| 13 december 1944 \| 5 february 1951 row 11 : aldo urbani \| 5 february 1951 \| 10 november 1955 row 12 : ferdinando raffaelli \| 10 november 1955 \| 1 february 1958 row 13 : silvio napoli \| 1 february 1958 \| 1 september 1961 row 14 : aldo remondino \| 1 september 1961 \| 28 february 1968 row 15 : duilio s. fanali \| 28 february 1968 \| 1 november 1971 row 16 : vincenzo lucertini \| 1 november 1971 \| 27 february 1974 row 17 : dino ciarlo \| 27 february 1974 \| 20 june 1977 row 18 : alessandro mettimano \| 20 june 1977 \| 1 april 1980 row 19 : lamberto bartolucci \| 2 april 1980 \| 12 october 1983 row 20 : basilio cottone \| 19 october 1983 \| 17 september 1986 row 21 : franco pisano \| 18 september 1986 \| 15 april 1990 row 22 : stelio nardini \| 16 april 1990 \| 24 march 1993 row 23 : adelchi pillinini \| 25 march 1993 \| 3 june 1995 row 24 : mario arpino \| 4 june 1995 \| 5 february 1999 row 25 : andrea fornasiero \| 5 february 1999 \| 5 august 2001 row 26 : sandro ferracuti \| 5 august 2001 \| 4 august 2004 row 27 : leonardo tricarico \| 5 august 2004 \| 19 september 2006 row 28 : vincenzo camporini \| 19 september 2006 \| 30 january 2008 row 29 : daniele tei \| 30 january 2008 \| 25 february 2010 row 30 : giuseppe bernardis \| 25 february 2010 \| 25 february 2013 row 31 : pasquale preziosa \| 25 february 2013 \| incumbent	col : count ( "distinct term start" ) row 1 : 1	select count ( distinct term start ) where term end = '1 november 1971' <table_name> : table \begin{tabular}{llll} \toprule & name & term start & term end \\ \midrule 0 & pier ruggero piccio & 1 january 1926 & 6 february 1927 \\ 1 & armando armani & 10 february 1927 & 13 october 1928 \\ 2 & giuseppe valle & 22 february 1930 & 23 november 1933 \\ 3 & antonio bosio & 23 november 1933 & 22 march 1934 \\ 4 & giuseppe valle & 22 march 1934 & 10 november 1939 \\ 5 & francesco pricolo & 10 november 1939 & 15 november 1941 \\ 6 & rino corso fougier & 15 november 1941 & 27 july 1943 \\ 7 & renato sandalli & 27 july 1943 & 18 june 1944 \\ 8 & pietro piacentini & 19 june 1944 & 13 december 1944 \\ 9 & mario ajmone cat & 13 december 1944 & 5 february 1951 \\ 10 & aldo urbani & 5 february 1951 & 10 november 1955 \\ 11 & ferdinando raffaelli & 10 november 1955 & 1 february 1958 \\ 12 & silvio napoli & 1 february 1958 & 1 september 1961 \\ 13 & aldo remondino & 1 september 1961 & 28 february 1968 \\ 14 & duilio s. fanali & 28 february 1968 & 1 november 1971 \\ 15 & vincenzo lucertini & 1 november 1971 & 27 february 1974 \\ 16 & dino ciarlo & 27 february 1974 & 20 june 1977 \\ 17 & alessandro mettimano & 20 june 1977 & 1 april 1980 \\ 18 & lamberto bartolucci & 2 april 1980 & 12 october 1983 \\ 19 & basilio cottone & 19 october 1983 & 17 september 1986 \\ 20 & franco pisano & 18 september 1986 & 15 april 1990 \\ 21 & stelio nardini & 16 april 1990 & 24 march 1993 \\ 22 & adelchi pillinini & 25 march 1993 & 3 june 1995 \\ 23 & mario arpino & 4 june 1995 & 5 february 1999 \\ 24 & andrea fornasiero & 5 february 1999 & 5 august 2001 \\ 25 & sandro ferracuti & 5 august 2001 & 4 august 2004 \\ 26 & leonardo tricarico & 5 august 2004 & 19 september 2006 \\ 27 & vincenzo camporini & 19 september 2006 & 30 january 2008 \\ 28 & daniele tei & 30 january 2008 & 25 february 2010 \\ 29 & giuseppe bernardis & 25 february 2010 & 25 february 2013 \\ 30 & pasquale preziosa & 25 february 2013 & incumbent \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "distinct term start" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( distinct term start ) where term end = '1 november 1971' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>term start</th> <th>term end</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>pier ruggero piccio</td> <td>1 january 1926</td> <td>6 february 1927</td> </tr> <tr> <th>1</th> <td>armando armani</td> <td>10 february 1927</td> <td>13 october 1928</td> </tr> <tr> <th>2</th> <td>giuseppe valle</td> <td>22 february 1930</td> <td>23 november 1933</td> </tr> <tr> <th>3</th> <td>antonio bosio</td> <td>23 november 1933</td> <td>22 march 1934</td> </tr> <tr> <th>4</th> <td>giuseppe valle</td> <td>22 march 1934</td> <td>10 november 1939</td> </tr> <tr> <th>5</th> <td>francesco pricolo</td> <td>10 november 1939</td> <td>15 november 1941</td> </tr> <tr> <th>6</th> <td>rino corso fougier</td> <td>15 november 1941</td> <td>27 july 1943</td> </tr> <tr> <th>7</th> <td>renato sandalli</td> <td>27 july 1943</td> <td>18 june 1944</td> </tr> <tr> <th>8</th> <td>pietro piacentini</td> <td>19 june 1944</td> <td>13 december 1944</td> </tr> <tr> <th>9</th> <td>mario ajmone cat</td> <td>13 december 1944</td> <td>5 february 1951</td> </tr> <tr> <th>10</th> <td>aldo urbani</td> <td>5 february 1951</td> <td>10 november 1955</td> </tr> <tr> <th>11</th> <td>ferdinando raffaelli</td> <td>10 november 1955</td> <td>1 february 1958</td> </tr> <tr> <th>12</th> <td>silvio napoli</td> <td>1 february 1958</td> <td>1 september 1961</td> </tr> <tr> <th>13</th> <td>aldo remondino</td> <td>1 september 1961</td> <td>28 february 1968</td> </tr> <tr> <th>14</th> <td>duilio s. fanali</td> <td>28 february 1968</td> <td>1 november 1971</td> </tr> <tr> <th>15</th> <td>vincenzo lucertini</td> <td>1 november 1971</td> <td>27 february 1974</td> </tr> <tr> <th>16</th> <td>dino ciarlo</td> <td>27 february 1974</td> <td>20 june 1977</td> </tr> <tr> <th>17</th> <td>alessandro mettimano</td> <td>20 june 1977</td> <td>1 april 1980</td> </tr> <tr> <th>18</th> <td>lamberto bartolucci</td> <td>2 april 1980</td> <td>12 october 1983</td> </tr> <tr> <th>19</th> <td>basilio cottone</td> <td>19 october 1983</td> <td>17 september 1986</td> </tr> <tr> <th>20</th> <td>franco pisano</td> <td>18 september 1986</td> <td>15 april 1990</td> </tr> <tr> <th>21</th> <td>stelio nardini</td> <td>16 april 1990</td> <td>24 march 1993</td> </tr> <tr> <th>22</th> <td>adelchi pillinini</td> <td>25 march 1993</td> <td>3 june 1995</td> </tr> <tr> <th>23</th> <td>mario arpino</td> <td>4 june 1995</td> <td>5 february 1999</td> </tr> <tr> <th>24</th> <td>andrea fornasiero</td> <td>5 february 1999</td> <td>5 august 2001</td> </tr> <tr> <th>25</th> <td>sandro ferracuti</td> <td>5 august 2001</td> <td>4 august 2004</td> </tr> <tr> <th>26</th> <td>leonardo tricarico</td> <td>5 august 2004</td> <td>19 september 2006</td> </tr> <tr> <th>27</th> <td>vincenzo camporini</td> <td>19 september 2006</td> <td>30 january 2008</td> </tr> <tr> <th>28</th> <td>daniele tei</td> <td>30 january 2008</td> <td>25 february 2010</td> </tr> <tr> <th>29</th> <td>giuseppe bernardis</td> <td>25 february 2010</td> <td>25 february 2013</td> </tr> <tr> <th>30</th> <td>pasquale preziosa</td> <td>25 february 2013</td> <td>incumbent</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "distinct term start" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( distinct term start ) where term end = '1 november 1971' <table_name> : table \| \| name \| term start \| term end \| \|---:\|:---------------------\|:------------------\|:------------------\| \| 0 \| pier ruggero piccio \| 1 january 1926 \| 6 february 1927 \| \| 1 \| armando armani \| 10 february 1927 \| 13 october 1928 \| \| 2 \| giuseppe valle \| 22 february 1930 \| 23 november 1933 \| \| 3 \| antonio bosio \| 23 november 1933 \| 22 march 1934 \| \| 4 \| giuseppe valle \| 22 march 1934 \| 10 november 1939 \| \| 5 \| francesco pricolo \| 10 november 1939 \| 15 november 1941 \| \| 6 \| rino corso fougier \| 15 november 1941 \| 27 july 1943 \| \| 7 \| renato sandalli \| 27 july 1943 \| 18 june 1944 \| \| 8 \| pietro piacentini \| 19 june 1944 \| 13 december 1944 \| \| 9 \| mario ajmone cat \| 13 december 1944 \| 5 february 1951 \| \| 10 \| aldo urbani \| 5 february 1951 \| 10 november 1955 \| \| 11 \| ferdinando raffaelli \| 10 november 1955 \| 1 february 1958 \| \| 12 \| silvio napoli \| 1 february 1958 \| 1 september 1961 \| \| 13 \| aldo remondino \| 1 september 1961 \| 28 february 1968 \| \| 14 \| duilio s. fanali \| 28 february 1968 \| 1 november 1971 \| \| 15 \| vincenzo lucertini \| 1 november 1971 \| 27 february 1974 \| \| 16 \| dino ciarlo \| 27 february 1974 \| 20 june 1977 \| \| 17 \| alessandro mettimano \| 20 june 1977 \| 1 april 1980 \| \| 18 \| lamberto bartolucci \| 2 april 1980 \| 12 october 1983 \| \| 19 \| basilio cottone \| 19 october 1983 \| 17 september 1986 \| \| 20 \| franco pisano \| 18 september 1986 \| 15 april 1990 \| \| 21 \| stelio nardini \| 16 april 1990 \| 24 march 1993 \| \| 22 \| adelchi pillinini \| 25 march 1993 \| 3 june 1995 \| \| 23 \| mario arpino \| 4 june 1995 \| 5 february 1999 \| \| 24 \| andrea fornasiero \| 5 february 1999 \| 5 august 2001 \| \| 25 \| sandro ferracuti \| 5 august 2001 \| 4 august 2004 \| \| 26 \| leonardo tricarico \| 5 august 2004 \| 19 september 2006 \| \| 27 \| vincenzo camporini \| 19 september 2006 \| 30 january 2008 \| \| 28 \| daniele tei \| 30 january 2008 \| 25 february 2010 \| \| 29 \| giuseppe bernardis \| 25 february 2010 \| 25 february 2013 \| \| 30 \| pasquale preziosa \| 25 february 2013 \| incumbent \|	\| \| count ( 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select nation where silver = 4 col : rank \| nation \| gold \| silver \| bronze \| total row 1 : 1 \| germany \| 17 \| 9 \| 14 \| 40 row 2 : 2 \| russia \| 12 \| 16 \| 8 \| 36 row 3 : 3 \| ukraine \| 6 \| 11 \| 9 \| 26 row 4 : 4 \| norway \| 6 \| 2 \| 7 \| 15 row 5 : 5 \| france \| 5 \| 4 \| 3 \| 12 row 6 : 6 \| switzerland \| 3 \| 5 \| 3 \| 11 row 7 : 7 \| finland \| 3 \| 2 \| 4 \| 9 row 8 : 8 \| japan \| 2 \| 2 \| 1 \| 5 row 9 : 9 \| netherlands \| 2 \| 0 \| 1 \| 3 row 10 : 10 \| sweden \| 1 \| 2 \| 2 \| 5 row 11 : 11 \| denmark \| 1 \| 0 \| 1 \| 2 row 12 : 12 \| unified team \| 1 \| 0 \| 0 \| 1 row 13 : 13 \| austria \| 0 \| 4 \| 0 \| 4 row 14 : 14 \| slovakia \| 0 \| 2 \| 1 \| 3 row 15 : 15 \| italy \| 0 \| 0 \| 1 \| 1 row 16 : 15 \| poland \| 0 \| 0 \| 1 \| 1 row 17 : 15 \| canada \| 0 \| 0 \| 1 \| 1 row 18 : 15 \| belarus \| 0 \| 0 \| 1 \| 1 row 19 : 15 \| united states \| 0 \| 0 \| 1 \| 1 row 20 : total 19 nations \| total 19 nations \| 59 \| 59 \| 59 \| 177	col : nation row 1 : france row 2 : austria	select nation where silver = 4 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & germany & 17 & 9 & 14 & 40 \\ 1 & 2 & russia & 12 & 16 & 8 & 36 \\ 2 & 3 & ukraine & 6 & 11 & 9 & 26 \\ 3 & 4 & norway & 6 & 2 & 7 & 15 \\ 4 & 5 & france & 5 & 4 & 3 & 12 \\ 5 & 6 & switzerland & 3 & 5 & 3 & 11 \\ 6 & 7 & finland & 3 & 2 & 4 & 9 \\ 7 & 8 & japan & 2 & 2 & 1 & 5 \\ 8 & 9 & netherlands & 2 & 0 & 1 & 3 \\ 9 & 10 & sweden & 1 & 2 & 2 & 5 \\ 10 & 11 & denmark & 1 & 0 & 1 & 2 \\ 11 & 12 & unified team & 1 & 0 & 0 & 1 \\ 12 & 13 & austria & 0 & 4 & 0 & 4 \\ 13 & 14 & slovakia & 0 & 2 & 1 & 3 \\ 14 & 15 & italy & 0 & 0 & 1 & 1 \\ 15 & 15 & poland & 0 & 0 & 1 & 1 \\ 16 & 15 & canada & 0 & 0 & 1 & 1 \\ 17 & 15 & belarus & 0 & 0 & 1 & 1 \\ 18 & 15 & united states & 0 & 0 & 1 & 1 \\ 19 & total 19 nations & total 19 nations & 59 & 59 & 59 & 177 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & france \\ 1 & austria \\ \bottomrule \end{tabular}	select nation where silver = 4 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>germany</td> <td>17</td> <td>9</td> <td>14</td> <td>40</td> </tr> <tr> <th>1</th> <td>2</td> <td>russia</td> <td>12</td> <td>16</td> <td>8</td> <td>36</td> </tr> <tr> <th>2</th> <td>3</td> <td>ukraine</td> <td>6</td> <td>11</td> <td>9</td> <td>26</td> </tr> <tr> <th>3</th> <td>4</td> <td>norway</td> <td>6</td> <td>2</td> <td>7</td> <td>15</td> </tr> <tr> <th>4</th> <td>5</td> <td>france</td> <td>5</td> <td>4</td> <td>3</td> <td>12</td> </tr> <tr> <th>5</th> <td>6</td> <td>switzerland</td> <td>3</td> <td>5</td> <td>3</td> <td>11</td> </tr> <tr> <th>6</th> <td>7</td> <td>finland</td> <td>3</td> <td>2</td> <td>4</td> <td>9</td> </tr> <tr> <th>7</th> <td>8</td> <td>japan</td> <td>2</td> <td>2</td> <td>1</td> <td>5</td> </tr> <tr> <th>8</th> <td>9</td> <td>netherlands</td> <td>2</td> <td>0</td> <td>1</td> <td>3</td> </tr> <tr> <th>9</th> <td>10</td> <td>sweden</td> <td>1</td> <td>2</td> <td>2</td> <td>5</td> </tr> <tr> <th>10</th> <td>11</td> <td>denmark</td> <td>1</td> <td>0</td> <td>1</td> <td>2</td> </tr> <tr> <th>11</th> <td>12</td> <td>unified team</td> <td>1</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>12</th> <td>13</td> <td>austria</td> <td>0</td> <td>4</td> <td>0</td> <td>4</td> </tr> <tr> <th>13</th> <td>14</td> <td>slovakia</td> <td>0</td> <td>2</td> <td>1</td> <td>3</td> </tr> <tr> <th>14</th> <td>15</td> <td>italy</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>15</th> <td>15</td> <td>poland</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>16</th> <td>15</td> <td>canada</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>17</th> <td>15</td> <td>belarus</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>18</th> <td>15</td> <td>united states</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>19</th> <td>total 19 nations</td> <td>total 19 nations</td> <td>59</td> <td>59</td> <td>59</td> <td>177</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>france</td> </tr> <tr> <th>1</th> <td>austria</td> </tr> </tbody> </table>	select nation where silver = 4 <table_name> : table \| \| rank \| nation \| gold \| silver \| bronze \| total \| \|---:\|:-----------------\|:-----------------\|-------:\|---------:\|---------:\|--------:\| \| 0 \| 1 \| germany \| 17 \| 9 \| 14 \| 40 \| \| 1 \| 2 \| russia \| 12 \| 16 \| 8 \| 36 \| \| 2 \| 3 \| ukraine \| 6 \| 11 \| 9 \| 26 \| \| 3 \| 4 \| norway \| 6 \| 2 \| 7 \| 15 \| \| 4 \| 5 \| france \| 5 \| 4 \| 3 \| 12 \| \| 5 \| 6 \| switzerland \| 3 \| 5 \| 3 \| 11 \| \| 6 \| 7 \| finland \| 3 \| 2 \| 4 \| 9 \| \| 7 \| 8 \| japan \| 2 \| 2 \| 1 \| 5 \| \| 8 \| 9 \| netherlands \| 2 \| 0 \| 1 \| 3 \| \| 9 \| 10 \| sweden \| 1 \| 2 \| 2 \| 5 \| \| 10 \| 11 \| denmark \| 1 \| 0 \| 1 \| 2 \| \| 11 \| 12 \| unified team \| 1 \| 0 \| 0 \| 1 \| \| 12 \| 13 \| austria \| 0 \| 4 \| 0 \| 4 \| \| 13 \| 14 \| slovakia \| 0 \| 2 \| 1 \| 3 \| \| 14 \| 15 \| italy \| 0 \| 0 \| 1 \| 1 \| \| 15 \| 15 \| poland \| 0 \| 0 \| 1 \| 1 \| \| 16 \| 15 \| canada \| 0 \| 0 \| 1 \| 1 \| \| 17 \| 15 \| belarus \| 0 \| 0 \| 1 \| 1 \| \| 18 \| 15 \| united states \| 0 \| 0 \| 1 \| 1 \| \| 19 \| total 19 nations \| total 19 nations \| 59 \| 59 \| 59 \| 177 \|	\| \| nation \| \|---:\|:---------\| \| 0 \| france \| \| 1 \| austria \|	[ [ 1, 4025, 290, 367, 1625, 17714, 502, 273, 1059, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 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select count ( * ) where left office = '26 january 1931' col : # \| name (birth-death) \| took office \| left office \| monarch \| prime minister row 1 : 1 \| the viscount gladstone (1854-1930) \| 31 may 1910 \| 8 september 1914 \| george v \| botha row 2 : 2 \| the viscount buxton (1853-1934) \| 8 september 1914 \| 17 november 1920 \| george v \| botha row 3 : 3 \| hrh prince arthur of connaught (1883-1938) \| 17 november 1920 \| 21 january 1924 \| george v \| smuts row 4 : 4 \| the earl of athlone (1874-1957) \| 21 january 1924 \| 26 january 1931 \| george v \| smuts row 5 : 5 \| the earl of clarendon (1877-1955) \| 26 january 1931 \| 5 april 1937 \| george v \| hertzog row 6 : 6 \| sir patrick duncan (1870-1943) \| 5 april 1937 \| 17 july 1943 \| george vi \| hertzog row 7 : 6 \| nicolaas jacobus de wet (1873-1960) (officer administering the government) \| 17 july 1943 \| 1 january 1946 \| george vi \| smuts row 8 : 7 \| gideon brand van zyl (1873-1956) \| 1 january 1946 \| 1 january 1951 \| george vi \| smuts row 9 : 8 \| ernest george jansen (1881-1959) \| 1 january 1951 \| 25 november 1959 \| george vi \| malan row 10 : 8 \| lucas cornelius steyn (1903-1976) (officer administering the government) \| 26 november 1959 \| 11 december 1959 \| elizabeth ii \| verwoerd row 11 : 9 \| charles robberts swart (1894-1982) \| 11 december 1959 \| 30 april 1961 \| elizabeth ii \| verwoerd row 12 : 9 \| lucas cornelius steyn (1903-1976) (officer administering the government) \| 30 april 1961 \| 31 may 1961 \| elizabeth ii \| verwoerd	col : count ( "*" ) row 1 : 1	select count ( * ) where left office = '26 january 1931' <table_name> : table \begin{tabular}{lllllll} \toprule & # & name (birth-death) & took office & left office & monarch & prime minister \\ \midrule 0 & 1 & the viscount gladstone (1854-1930) & 31 may 1910 & 8 september 1914 & george v & botha \\ 1 & 2 & the viscount buxton (1853-1934) & 8 september 1914 & 17 november 1920 & george v & botha \\ 2 & 3 & hrh prince arthur of connaught (1883-1938) & 17 november 1920 & 21 january 1924 & george v & smuts \\ 3 & 4 & the earl of athlone (1874-1957) & 21 january 1924 & 26 january 1931 & george v & smuts \\ 4 & 5 & the earl of clarendon (1877-1955) & 26 january 1931 & 5 april 1937 & george v & hertzog \\ 5 & 6 & sir patrick duncan (1870-1943) & 5 april 1937 & 17 july 1943 & george vi & hertzog \\ 6 & 6 & nicolaas jacobus de wet (1873-1960) (officer administering the government) & 17 july 1943 & 1 january 1946 & george vi & smuts \\ 7 & 7 & gideon brand van zyl (1873-1956) & 1 january 1946 & 1 january 1951 & george vi & smuts \\ 8 & 8 & ernest george jansen (1881-1959) & 1 january 1951 & 25 november 1959 & george vi & malan \\ 9 & 8 & lucas cornelius steyn (1903-1976) (officer administering the government) & 26 november 1959 & 11 december 1959 & elizabeth ii & verwoerd \\ 10 & 9 & charles robberts swart (1894-1982) & 11 december 1959 & 30 april 1961 & elizabeth ii & verwoerd \\ 11 & 9 & lucas cornelius steyn (1903-1976) (officer administering the government) & 30 april 1961 & 31 may 1961 & elizabeth ii & verwoerd \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where left office = '26 january 1931' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>name (birth-death)</th> <th>took office</th> <th>left office</th> <th>monarch</th> <th>prime minister</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>the viscount gladstone (1854-1930)</td> <td>31 may 1910</td> <td>8 september 1914</td> <td>george v</td> <td>botha</td> </tr> <tr> <th>1</th> <td>2</td> <td>the viscount buxton (1853-1934)</td> <td>8 september 1914</td> <td>17 november 1920</td> <td>george v</td> <td>botha</td> </tr> <tr> <th>2</th> <td>3</td> <td>hrh prince arthur of connaught (1883-1938)</td> <td>17 november 1920</td> <td>21 january 1924</td> <td>george v</td> <td>smuts</td> </tr> <tr> <th>3</th> <td>4</td> <td>the earl of athlone (1874-1957)</td> <td>21 january 1924</td> <td>26 january 1931</td> <td>george v</td> <td>smuts</td> </tr> <tr> <th>4</th> <td>5</td> <td>the earl of clarendon (1877-1955)</td> <td>26 january 1931</td> <td>5 april 1937</td> <td>george v</td> <td>hertzog</td> </tr> <tr> <th>5</th> <td>6</td> <td>sir patrick duncan (1870-1943)</td> <td>5 april 1937</td> <td>17 july 1943</td> <td>george vi</td> <td>hertzog</td> </tr> <tr> <th>6</th> <td>6</td> <td>nicolaas jacobus de wet (1873-1960) (officer administering the government)</td> <td>17 july 1943</td> <td>1 january 1946</td> <td>george vi</td> <td>smuts</td> </tr> <tr> <th>7</th> <td>7</td> <td>gideon brand van zyl (1873-1956)</td> <td>1 january 1946</td> <td>1 january 1951</td> <td>george vi</td> <td>smuts</td> </tr> <tr> <th>8</th> <td>8</td> <td>ernest george jansen (1881-1959)</td> <td>1 january 1951</td> <td>25 november 1959</td> <td>george vi</td> <td>malan</td> </tr> <tr> <th>9</th> <td>8</td> <td>lucas cornelius steyn (1903-1976) (officer administering the government)</td> <td>26 november 1959</td> <td>11 december 1959</td> <td>elizabeth ii</td> <td>verwoerd</td> </tr> <tr> <th>10</th> <td>9</td> <td>charles robberts swart (1894-1982)</td> <td>11 december 1959</td> <td>30 april 1961</td> <td>elizabeth ii</td> <td>verwoerd</td> </tr> <tr> <th>11</th> <td>9</td> <td>lucas cornelius steyn (1903-1976) (officer administering the government)</td> <td>30 april 1961</td> <td>31 may 1961</td> <td>elizabeth ii</td> <td>verwoerd</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where left office = '26 january 1931' <table_name> : table \| \| # \| name (birth-death) \| took office \| left office \| monarch \| prime minister \| \|---:\|----:\|:---------------------------------------------------------------------------\|:-----------------\|:-----------------\|:-------------\|:-----------------\| \| 0 \| 1 \| the viscount gladstone (1854-1930) \| 31 may 1910 \| 8 september 1914 \| george v \| botha \| \| 1 \| 2 \| the viscount buxton (1853-1934) \| 8 september 1914 \| 17 november 1920 \| george v \| botha \| \| 2 \| 3 \| hrh prince arthur of connaught (1883-1938) \| 17 november 1920 \| 21 january 1924 \| george v \| smuts \| \| 3 \| 4 \| the earl of athlone (1874-1957) \| 21 january 1924 \| 26 january 1931 \| george v \| smuts \| \| 4 \| 5 \| the earl of clarendon (1877-1955) \| 26 january 1931 \| 5 april 1937 \| george v \| hertzog \| \| 5 \| 6 \| sir patrick duncan (1870-1943) \| 5 april 1937 \| 17 july 1943 \| george vi \| hertzog \| \| 6 \| 6 \| nicolaas jacobus de wet (1873-1960) (officer administering the government) \| 17 july 1943 \| 1 january 1946 \| george vi \| smuts \| \| 7 \| 7 \| gideon brand van zyl (1873-1956) \| 1 january 1946 \| 1 january 1951 \| george vi \| smuts \| \| 8 \| 8 \| ernest george jansen (1881-1959) \| 1 january 1951 \| 25 november 1959 \| george vi \| malan \| \| 9 \| 8 \| lucas cornelius steyn (1903-1976) (officer administering the government) \| 26 november 1959 \| 11 december 1959 \| elizabeth ii \| verwoerd \| \| 10 \| 9 \| charles robberts swart (1894-1982) \| 11 december 1959 \| 30 april 1961 \| elizabeth ii \| verwoerd \| \| 11 \| 9 \| lucas cornelius steyn (1903-1976) (officer administering the government) \| 30 april 1961 \| 31 may 1961 \| elizabeth ii \| verwoerd \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 2002, 3397, 1812, 273, 296, 5558, 525, 304, 24335, 5342, 6938, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 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select old municipalities where old municipalities = 'north kynouria' col : new municipality \| old municipalities \| seat row 1 : gortynia \| dimitsana \| dimitsana row 2 : gortynia \| vytina \| dimitsana row 3 : gortynia \| iraia \| dimitsana row 4 : gortynia \| kleitor \| dimitsana row 5 : gortynia \| kontovazaina \| dimitsana row 6 : gortynia \| langadia \| dimitsana row 7 : gortynia \| trikolonoi \| dimitsana row 8 : gortynia \| tropaia \| dimitsana row 9 : megalopoli \| gortyna \| megalopoli row 10 : megalopoli \| falaisia \| megalopoli row 11 : north kynouria (voreia kynouria) \| north kynouria \| astros row 12 : south kynouria (notia kynouria) \| leonidio \| leonidio row 13 : south kynouria (notia kynouria) \| kosmas \| leonidio row 14 : south kynouria (notia kynouria) \| tyros \| leonidio row 15 : tripoli \| valtetsi \| tripoli row 16 : tripoli \| korythio \| tripoli row 17 : tripoli \| levidi \| tripoli row 18 : tripoli \| mantineia \| tripoli row 19 : tripoli \| skyritida \| tripoli row 20 : tripoli \| tegea \| tripoli row 21 : tripoli \| falanthos \| tripoli	col : old municipalities row 1 : north kynouria	select old municipalities where old municipalities = 'north kynouria' <table_name> : table \begin{tabular}{llll} \toprule & new municipality & old municipalities & seat \\ \midrule 0 & gortynia & dimitsana & dimitsana \\ 1 & gortynia & vytina & dimitsana \\ 2 & gortynia & iraia & dimitsana \\ 3 & gortynia & kleitor & dimitsana \\ 4 & gortynia & kontovazaina & dimitsana \\ 5 & gortynia & langadia & dimitsana \\ 6 & gortynia & trikolonoi & dimitsana \\ 7 & gortynia & tropaia & dimitsana \\ 8 & megalopoli & gortyna & megalopoli \\ 9 & megalopoli & falaisia & megalopoli \\ 10 & north kynouria (voreia kynouria) & north kynouria & astros \\ 11 & south kynouria (notia kynouria) & leonidio & leonidio \\ 12 & south kynouria (notia kynouria) & kosmas & leonidio \\ 13 & south kynouria (notia kynouria) & tyros & leonidio \\ 14 & tripoli & valtetsi & tripoli \\ 15 & tripoli & korythio & tripoli \\ 16 & tripoli & levidi & tripoli \\ 17 & tripoli & mantineia & tripoli \\ 18 & tripoli & skyritida & tripoli \\ 19 & tripoli & tegea & tripoli \\ 20 & tripoli & falanthos & tripoli \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & old municipalities \\ \midrule 0 & north kynouria \\ \bottomrule \end{tabular}	select old municipalities where old municipalities = 'north kynouria' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>new municipality</th> <th>old municipalities</th> <th>seat</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>gortynia</td> <td>dimitsana</td> <td>dimitsana</td> </tr> <tr> <th>1</th> <td>gortynia</td> <td>vytina</td> <td>dimitsana</td> </tr> <tr> <th>2</th> <td>gortynia</td> <td>iraia</td> <td>dimitsana</td> </tr> <tr> <th>3</th> <td>gortynia</td> <td>kleitor</td> <td>dimitsana</td> </tr> <tr> <th>4</th> <td>gortynia</td> <td>kontovazaina</td> <td>dimitsana</td> </tr> <tr> <th>5</th> <td>gortynia</td> <td>langadia</td> <td>dimitsana</td> </tr> <tr> <th>6</th> <td>gortynia</td> <td>trikolonoi</td> <td>dimitsana</td> </tr> <tr> <th>7</th> <td>gortynia</td> <td>tropaia</td> <td>dimitsana</td> </tr> <tr> <th>8</th> <td>megalopoli</td> <td>gortyna</td> <td>megalopoli</td> </tr> <tr> <th>9</th> <td>megalopoli</td> <td>falaisia</td> <td>megalopoli</td> </tr> <tr> <th>10</th> <td>north kynouria\t\t (voreia kynouria)</td> <td>north kynouria</td> <td>astros</td> </tr> <tr> <th>11</th> <td>south kynouria\t\t (notia kynouria)</td> <td>leonidio</td> <td>leonidio</td> </tr> <tr> <th>12</th> <td>south kynouria\t\t (notia kynouria)</td> <td>kosmas</td> <td>leonidio</td> </tr> <tr> <th>13</th> <td>south kynouria\t\t (notia kynouria)</td> <td>tyros</td> <td>leonidio</td> </tr> <tr> <th>14</th> <td>tripoli</td> <td>valtetsi</td> <td>tripoli</td> </tr> <tr> <th>15</th> <td>tripoli</td> <td>korythio</td> <td>tripoli</td> </tr> <tr> <th>16</th> <td>tripoli</td> <td>levidi</td> <td>tripoli</td> </tr> <tr> <th>17</th> <td>tripoli</td> <td>mantineia</td> <td>tripoli</td> </tr> <tr> <th>18</th> <td>tripoli</td> <td>skyritida</td> <td>tripoli</td> </tr> <tr> <th>19</th> <td>tripoli</td> <td>tegea</td> <td>tripoli</td> </tr> <tr> <th>20</th> <td>tripoli</td> <td>falanthos</td> <td>tripoli</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>old municipalities</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>north kynouria</td> </tr> </tbody> </table>	select old municipalities where old municipalities = 'north kynouria' <table_name> : table \| \| new municipality \| old municipalities \| seat \| \|---:\|:-------------------\|:---------------------\|:-----------\| \| 0 \| gortynia \| dimitsana \| dimitsana \| \| 1 \| gortynia \| vytina \| dimitsana \| \| 2 \| gortynia \| iraia \| dimitsana \| \| 3 \| gortynia \| kleitor \| dimitsana \| \| 4 \| gortynia \| kontovazaina \| dimitsana \| \| 5 \| gortynia \| langadia \| dimitsana \| \| 6 \| gortynia \| trikolonoi \| dimitsana \| \| 7 \| gortynia \| tropaia \| dimitsana \| \| 8 \| megalopoli \| gortyna \| megalopoli \| \| 9 \| megalopoli \| falaisia \| megalopoli \| \| 10 \| north kynouria (voreia kynouria) \| north kynouria \| astros \| \| 11 \| south kynouria (notia kynouria) \| leonidio \| leonidio \| \| 12 \| south kynouria (notia kynouria) \| kosmas \| leonidio \| \| 13 \| south kynouria (notia kynouria) \| tyros \| leonidio \| \| 14 \| tripoli \| valtetsi \| tripoli \| \| 15 \| tripoli \| korythio \| tripoli \| \| 16 \| tripoli \| levidi \| tripoli \| \| 17 \| tripoli \| mantineia \| tripoli \| \| 18 \| tripoli \| skyritida \| tripoli \| \| 19 \| tripoli \| tegea \| tripoli \| \| 20 \| tripoli \| falanthos \| tripoli \|	\| \| old municipalities \| \|---:\|:---------------------\| \| 0 \| north kynouria \|	[ [ 1, 4025, 1592, 312, 318, 24629, 287, 1961, 1625, 1592, 312, 318, 24629, 287, 1961, 273, 296, 82, 7825, 417, 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select count ( act ) where act = 'janelle monae' col : act \| year signed \| # albums released under bad boy row 1 : diddy \| 1993 \| 6 row 2 : the notorious b.i.g \| 1993 \| 5 row 3 : harve pierre \| 1993 \| none row 4 : the hitmen \| 1993 \| none row 5 : mario winans \| 1995 \| 1 row 6 : kalenna harper \| 2004 \| none row 7 : cassie \| 2006 \| 1 row 8 : janelle monae \| 2007 \| 2 row 9 : red cafe \| 2009 \| none row 10 : machine gun kelly \| 2011 \| 1 row 11 : french montana \| 2012 \| 1 row 12 : megan nicole \| 2012 \| none	col : count ( "act" ) row 1 : 1	select count ( act ) where act = 'janelle monae' <table_name> : table \begin{tabular}{llll} \toprule & act & year signed & # albums released under bad boy \\ \midrule 0 & diddy & 1993 & 6 \\ 1 & the notorious b.i.g & 1993 & 5 \\ 2 & harve pierre & 1993 & none \\ 3 & the hitmen & 1993 & none \\ 4 & mario winans & 1995 & 1 \\ 5 & kalenna harper & 2004 & none \\ 6 & cassie & 2006 & 1 \\ 7 & janelle monae & 2007 & 2 \\ 8 & red cafe & 2009 & none \\ 9 & machine gun kelly & 2011 & 1 \\ 10 & french montana & 2012 & 1 \\ 11 & megan nicole & 2012 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "act" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( act ) where act = 'janelle monae' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>act</th> <th>year signed</th> <th># albums released under bad boy</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>diddy</td> <td>1993</td> <td>6</td> </tr> <tr> <th>1</th> <td>the notorious b.i.g</td> <td>1993</td> <td>5</td> </tr> <tr> <th>2</th> <td>harve pierre</td> <td>1993</td> <td>none</td> </tr> <tr> <th>3</th> <td>the hitmen</td> <td>1993</td> <td>none</td> </tr> <tr> <th>4</th> <td>mario winans</td> <td>1995</td> <td>1</td> </tr> <tr> <th>5</th> <td>kalenna harper</td> <td>2004</td> <td>none</td> </tr> <tr> <th>6</th> <td>cassie</td> <td>2006</td> <td>1</td> </tr> <tr> <th>7</th> <td>janelle monae</td> <td>2007</td> <td>2</td> </tr> <tr> <th>8</th> <td>red cafe</td> <td>2009</td> <td>none</td> </tr> <tr> <th>9</th> <td>machine gun kelly</td> <td>2011</td> <td>1</td> </tr> <tr> <th>10</th> <td>french montana</td> <td>2012</td> <td>1</td> </tr> <tr> <th>11</th> <td>megan nicole</td> <td>2012</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "act" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( act ) where act = 'janelle monae' <table_name> : table \| \| act \| year signed \| # albums released under bad boy \| \|---:\|:--------------------\|--------------:\|:----------------------------------\| \| 0 \| diddy \| 1993 \| 6 \| \| 1 \| the notorious b.i.g \| 1993 \| 5 \| \| 2 \| harve pierre \| 1993 \| none \| \| 3 \| the hitmen \| 1993 \| none \| \| 4 \| mario winans \| 1995 \| 1 \| \| 5 \| kalenna harper \| 2004 \| none \| \| 6 \| cassie \| 2006 \| 1 \| \| 7 \| janelle monae \| 2007 \| 2 \| \| 8 \| red cafe \| 2009 \| none \| \| 9 \| machine gun kelly \| 2011 \| 1 \| \| 10 \| french montana \| 2012 \| 1 \| \| 11 \| megan nicole \| 2012 \| none \|	\| \| count ( "act" ) \| \|---:\|------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 1328, 262, 1625, 1328, 273, 296, 78, 30427, 298, 6921, 8906, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 621, 1757, 451, 34, 203, 1377, 411, 451, 34, 6874, 6726, 1757, 451, 34, 203, 1377, 411, 451, 34, 7, 14844, 87, 15976, 3613, 5570, 800, 93, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 72, 1873, 93, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 19818, 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select driver where no > 5 order by no asc limit 1 col : pos \| no \| driver \| constructor \| laps \| time/retired \| grid \| points row 1 : 1 \| 15 \| sebastian vettel \| red bull-renault \| 56 \| 1:57:43.485 \| 1 \| 10 row 2 : 2 \| 14 \| mark webber \| red bull-renault \| 56 \| 10.97 \| 3 \| 8 row 3 : 3 \| 22 \| jenson button \| brawn-mercedes \| 56 \| 44.975 \| 5 \| 6 row 4 : 4 \| 23 \| rubens barrichello \| brawn-mercedes \| 56 \| +1:03.704 \| 4 \| 5 row 5 : 5 \| 2 \| heikki kovalainen \| mclaren-mercedes \| 56 \| +1:05.102 \| 12 \| 4 row 6 : 6 \| 1 \| lewis hamilton \| mclaren-mercedes \| 56 \| +1:11.866 \| 9 \| 3 row 7 : 7 \| 10 \| timo glock \| toyota \| 56 \| +1:14.476 \| 19 \| 2 row 8 : 8 \| 12 \| sebastien buemi \| toro rosso-ferrari \| 56 \| +1:16.439 \| 10 \| 1 row 9 : 9 \| 7 \| fernando alonso \| renault \| 56 \| +1:24.309 \| 2 \| none row 10 : 10 \| 4 \| kimi raikkonen \| ferrari \| 56 \| +1:31.750 \| 8 \| none row 11 : 11 \| 11 \| sebastien bourdais \| toro rosso-ferrari \| 56 \| +1:34.156 \| 15 \| none row 12 : 12 \| 6 \| nick heidfeld \| bmw sauber \| 56 \| +1:35.834 \| 11 \| none row 13 : 13 \| 5 \| robert kubica \| bmw sauber \| 56 \| +1:46.853 \| 17 \| none row 14 : 14 \| 21 \| giancarlo fisichella \| force india-mercedes \| 55 \| +1 lap \| 20 \| none row 15 : 15 \| 16 \| nico rosberg \| williams-toyota \| 55 \| +1 lap \| 7 \| none row 16 : 16 \| 8 \| nelson piquet, jr \| renault \| 54 \| +2 laps \| 16 \| none row 17 : 17 \| 20 \| adrian sutil \| force india-mercedes \| 50 \| accident \| 18 \| none row 18 : ret \| 17 \| kazuki nakajima \| williams-toyota \| 43 \| transmission \| 14 \| none row 19 : ret \| 3 \| felipe massa \| ferrari \| 20 \| electrical \| 13 \| none row 20 : ret \| 9 \| jarno trulli \| toyota \| 18 \| collision damage \| 6 \| none	col : driver row 1 : fernando alonso row 2 : nick heidfeld row 3 : nelson piquet, jr row 4 : jarno trulli	select driver where no > 5 order by no asc limit 1 <table_name> : table \begin{tabular}{lllllllll} \toprule & pos & no & driver & constructor & laps & time/retired & grid & points \\ \midrule 0 & 1 & 15 & sebastian vettel & red bull-renault & 56 & 1:57:43.485 & 1 & 10 \\ 1 & 2 & 14 & mark webber & red bull-renault & 56 & 10.97 & 3 & 8 \\ 2 & 3 & 22 & jenson button & brawn-mercedes & 56 & 44.975 & 5 & 6 \\ 3 & 4 & 23 & rubens barrichello & brawn-mercedes & 56 & +1:03.704 & 4 & 5 \\ 4 & 5 & 2 & heikki kovalainen & mclaren-mercedes & 56 & +1:05.102 & 12 & 4 \\ 5 & 6 & 1 & lewis hamilton & mclaren-mercedes & 56 & +1:11.866 & 9 & 3 \\ 6 & 7 & 10 & timo glock & toyota & 56 & +1:14.476 & 19 & 2 \\ 7 & 8 & 12 & sebastien buemi & toro rosso-ferrari & 56 & +1:16.439 & 10 & 1 \\ 8 & 9 & 7 & fernando alonso & renault & 56 & +1:24.309 & 2 & none \\ 9 & 10 & 4 & kimi raikkonen & ferrari & 56 & +1:31.750 & 8 & none \\ 10 & 11 & 11 & sebastien bourdais & toro rosso-ferrari & 56 & +1:34.156 & 15 & none \\ 11 & 12 & 6 & nick heidfeld & bmw sauber & 56 & +1:35.834 & 11 & none \\ 12 & 13 & 5 & robert kubica & bmw sauber & 56 & +1:46.853 & 17 & none \\ 13 & 14 & 21 & giancarlo fisichella & force india-mercedes & 55 & +1 lap & 20 & none \\ 14 & 15 & 16 & nico rosberg & williams-toyota & 55 & +1 lap & 7 & none \\ 15 & 16 & 8 & nelson piquet, jr & renault & 54 & +2 laps & 16 & none \\ 16 & 17 & 20 & adrian sutil & force india-mercedes & 50 & accident & 18 & none \\ 17 & ret & 17 & kazuki nakajima & williams-toyota & 43 & transmission & 14 & none \\ 18 & ret & 3 & felipe massa & ferrari & 20 & electrical & 13 & none \\ 19 & ret & 9 & jarno trulli & toyota & 18 & collision damage & 6 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & driver \\ \midrule 0 & fernando alonso \\ 1 & nick heidfeld \\ 2 & nelson piquet, jr \\ 3 & jarno trulli \\ \bottomrule \end{tabular}	select driver where no > 5 order by no asc limit 1 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pos</th> <th>no</th> <th>driver</th> <th>constructor</th> <th>laps</th> <th>time/retired</th> <th>grid</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>15</td> <td>sebastian vettel</td> <td>red bull-renault</td> <td>56</td> <td>1:57:43.485</td> <td>1</td> <td>10</td> </tr> <tr> <th>1</th> <td>2</td> <td>14</td> <td>mark webber</td> <td>red bull-renault</td> <td>56</td> <td>10.97</td> <td>3</td> <td>8</td> </tr> <tr> <th>2</th> <td>3</td> <td>22</td> <td>jenson button</td> <td>brawn-mercedes</td> <td>56</td> <td>44.975</td> <td>5</td> <td>6</td> </tr> <tr> <th>3</th> <td>4</td> <td>23</td> <td>rubens barrichello</td> <td>brawn-mercedes</td> <td>56</td> <td>+1:03.704</td> <td>4</td> <td>5</td> </tr> <tr> <th>4</th> <td>5</td> <td>2</td> <td>heikki kovalainen</td> <td>mclaren-mercedes</td> <td>56</td> <td>+1:05.102</td> <td>12</td> <td>4</td> </tr> <tr> <th>5</th> <td>6</td> <td>1</td> <td>lewis hamilton</td> <td>mclaren-mercedes</td> <td>56</td> <td>+1:11.866</td> <td>9</td> <td>3</td> </tr> <tr> <th>6</th> <td>7</td> <td>10</td> <td>timo glock</td> <td>toyota</td> <td>56</td> <td>+1:14.476</td> <td>19</td> <td>2</td> </tr> <tr> <th>7</th> <td>8</td> <td>12</td> <td>sebastien buemi</td> <td>toro rosso-ferrari</td> <td>56</td> <td>+1:16.439</td> <td>10</td> <td>1</td> </tr> <tr> <th>8</th> <td>9</td> <td>7</td> <td>fernando alonso</td> <td>renault</td> <td>56</td> <td>+1:24.309</td> <td>2</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>4</td> <td>kimi raikkonen</td> <td>ferrari</td> <td>56</td> <td>+1:31.750</td> <td>8</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>11</td> <td>sebastien bourdais</td> <td>toro rosso-ferrari</td> <td>56</td> <td>+1:34.156</td> <td>15</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>6</td> <td>nick heidfeld</td> <td>bmw sauber</td> <td>56</td> <td>+1:35.834</td> <td>11</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>5</td> <td>robert kubica</td> <td>bmw sauber</td> <td>56</td> <td>+1:46.853</td> <td>17</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>21</td> <td>giancarlo fisichella</td> <td>force india-mercedes</td> <td>55</td> <td>+1 lap</td> <td>20</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>16</td> <td>nico rosberg</td> <td>williams-toyota</td> <td>55</td> <td>+1 lap</td> <td>7</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>8</td> <td>nelson piquet, jr</td> <td>renault</td> <td>54</td> <td>+2 laps</td> <td>16</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>20</td> <td>adrian sutil</td> <td>force india-mercedes</td> <td>50</td> <td>accident</td> <td>18</td> <td>none</td> </tr> <tr> <th>17</th> <td>ret</td> <td>17</td> <td>kazuki nakajima</td> <td>williams-toyota</td> <td>43</td> <td>transmission</td> <td>14</td> <td>none</td> </tr> <tr> <th>18</th> <td>ret</td> <td>3</td> <td>felipe massa</td> <td>ferrari</td> <td>20</td> <td>electrical</td> <td>13</td> <td>none</td> </tr> <tr> <th>19</th> <td>ret</td> <td>9</td> <td>jarno trulli</td> <td>toyota</td> <td>18</td> <td>collision damage</td> <td>6</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>driver</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>fernando alonso</td> </tr> <tr> <th>1</th> <td>nick heidfeld</td> </tr> <tr> <th>2</th> <td>nelson piquet, jr</td> </tr> <tr> <th>3</th> <td>jarno trulli</td> </tr> </tbody> </table>	select driver where no > 5 order by no asc limit 1 <table_name> : table \| \| pos \| no \| driver \| constructor \| laps \| time/retired \| grid \| points \| \|---:\|:------\|-----:\|:---------------------\|:---------------------\|-------:\|:-----------------\|-------:\|:---------\| \| 0 \| 1 \| 15 \| sebastian vettel \| red bull-renault \| 56 \| 1:57:43.485 \| 1 \| 10 \| \| 1 \| 2 \| 14 \| mark webber \| red bull-renault \| 56 \| 10.97 \| 3 \| 8 \| \| 2 \| 3 \| 22 \| jenson button \| brawn-mercedes \| 56 \| 44.975 \| 5 \| 6 \| \| 3 \| 4 \| 23 \| rubens barrichello \| brawn-mercedes \| 56 \| +1:03.704 \| 4 \| 5 \| \| 4 \| 5 \| 2 \| heikki kovalainen \| mclaren-mercedes \| 56 \| +1:05.102 \| 12 \| 4 \| \| 5 \| 6 \| 1 \| lewis hamilton \| mclaren-mercedes \| 56 \| +1:11.866 \| 9 \| 3 \| \| 6 \| 7 \| 10 \| timo glock \| toyota \| 56 \| +1:14.476 \| 19 \| 2 \| \| 7 \| 8 \| 12 \| sebastien buemi \| toro rosso-ferrari \| 56 \| +1:16.439 \| 10 \| 1 \| \| 8 \| 9 \| 7 \| fernando alonso \| renault \| 56 \| +1:24.309 \| 2 \| none \| \| 9 \| 10 \| 4 \| kimi raikkonen \| ferrari \| 56 \| +1:31.750 \| 8 \| none \| \| 10 \| 11 \| 11 \| sebastien bourdais \| toro rosso-ferrari \| 56 \| +1:34.156 \| 15 \| none \| \| 11 \| 12 \| 6 \| nick heidfeld \| bmw sauber \| 56 \| +1:35.834 \| 11 \| none \| \| 12 \| 13 \| 5 \| robert kubica \| bmw sauber \| 56 \| +1:46.853 \| 17 \| none \| \| 13 \| 14 \| 21 \| giancarlo fisichella \| force india-mercedes \| 55 \| +1 lap \| 20 \| none \| \| 14 \| 15 \| 16 \| nico rosberg \| williams-toyota \| 55 \| +1 lap \| 7 \| none \| \| 15 \| 16 \| 8 \| nelson piquet, jr \| renault \| 54 \| +2 laps \| 16 \| none \| \| 16 \| 17 \| 20 \| adrian sutil \| force india-mercedes \| 50 \| accident \| 18 \| none \| \| 17 \| ret \| 17 \| kazuki nakajima \| williams-toyota \| 43 \| transmission \| 14 \| none \| \| 18 \| ret \| 3 \| felipe massa \| ferrari \| 20 \| electrical \| 13 \| none \| \| 19 \| ret \| 9 \| jarno trulli \| toyota \| 18 \| collision damage \| 6 \| none \|	\| \| driver \| \|---:\|:------------------\| \| 0 \| fernando alonso \| \| 1 \| nick heidfeld \| \| 2 \| nelson piquet, jr \| \| 3 \| jarno trulli \|	[ [ 1, 4025, 3419, 1625, 1158, 405, 1381, 1353, 635, 1158, 6972, 1800, 404, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 917, 1757, 451, 34, 203, 1377, 411, 451, 34, 2135, 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select team where postseason lost = 0 col : team \| year \| regular season won \| regular season lost \| regular season win % \| regular season finish \| postseason won \| postseason lost \| postseason win % \| postseason result row 1 : cle \| 1991 \| 32 \| 53 \| 0.376 \| 7th in al east \| none \| none \| none \| none row 2 : cle \| 1992 \| 76 \| 86 \| 0.469 \| 5th in al east \| none \| none \| none \| none row 3 : cle \| 1993 \| 76 \| 86 \| 0.469 \| 6th in al east \| none \| none \| none \| none row 4 : cle \| 1994 \| 66 \| 47 \| 0.584 \| 2nd in al central \| none \| none \| none \| no mlb postseason row 5 : cle \| 1995 \| 100 \| 44 \| 0.694 \| 1st in al central \| 9 \| 6 \| 0.6 \| lost ws to atl row 6 : cle \| 1996 \| 99 \| 62 \| 0.615 \| 1st in al central \| 1 \| 3 \| 0.25 \| lost lds to bal row 7 : cle \| 1997 \| 86 \| 75 \| 0.534 \| 1st in al central \| 10 \| 8 \| 0.556 \| lost ws to fla row 8 : cle \| 1998 \| 89 \| 73 \| 0.549 \| 1st in al central \| 5 \| 5 \| 0.5 \| lost lcs to nyy row 9 : cle \| 1999 \| 97 \| 65 \| 0.599 \| 1st in al central \| 2 \| 3 \| 0.4 \| lost lds to bos row 10 : bal \| 2000 \| 74 \| 88 \| 0.457 \| 4th in al east \| none \| none \| none \| none row 11 : bal \| 2001 \| 63 \| 98 \| 0.391 \| 4th in al east \| none \| none \| none \| none row 12 : bal \| 2002 \| 67 \| 95 \| 0.414 \| 4th in al east \| none \| none \| none \| none row 13 : bal \| 2003 \| 71 \| 91 \| 0.438 \| 4th in al east \| none \| none \| none \| none row 14 : sea \| 2005 \| 69 \| 93 \| 0.426 \| 4th in al west \| none \| none \| none \| none row 15 : sea \| 2006 \| 78 \| 84 \| 0.481 \| 4th in al west \| none \| none \| none \| none row 16 : sea \| 2007 \| 45 \| 33 \| 0.571 \| 2nd in al west \| none \| none \| none \| none row 17 : cle total \| cle total \| 721 \| 591 \| 0.55 \| none \| 27 \| 25 \| 0.519 \| none row 18 : bal total \| bal total \| 275 \| 372 \| 0.425 \| none \| 0 \| 0 \| 0 \| none row 19 : sea total \| sea total \| 192 \| 210 \| 0.478 \| none \| 0 \| 0 \| 0 \| none row 20 : total \| total \| 1188 \| 1173 \| 0.503 \| none \| 27 \| 25 \| 0.519 \| none	col : team row 1 : bal total row 2 : sea total	select team where postseason lost = 0 <table_name> : table \begin{tabular}{lllllllllll} \toprule & team & year & regular season won & regular season lost & regular season win % & regular season finish & postseason won & postseason lost & postseason win % & postseason result \\ \midrule 0 & cle & 1991 & 32 & 53 & 0.376 & 7th in al east & none & none & none & none \\ 1 & cle & 1992 & 76 & 86 & 0.469 & 5th in al east & none & none & none & none \\ 2 & cle & 1993 & 76 & 86 & 0.469 & 6th in al east & none & none & none & none \\ 3 & cle & 1994 & 66 & 47 & 0.584 & 2nd in al central & none & none & none & no mlb postseason \\ 4 & cle & 1995 & 100 & 44 & 0.694 & 1st in al central & 9 & 6 & 0.6 & lost ws to atl \\ 5 & cle & 1996 & 99 & 62 & 0.615 & 1st in al central & 1 & 3 & 0.25 & lost lds to bal \\ 6 & cle & 1997 & 86 & 75 & 0.534 & 1st in al central & 10 & 8 & 0.556 & lost ws to fla \\ 7 & cle & 1998 & 89 & 73 & 0.549 & 1st in al central & 5 & 5 & 0.5 & lost lcs to nyy \\ 8 & cle & 1999 & 97 & 65 & 0.599 & 1st in al central & 2 & 3 & 0.4 & lost lds to bos \\ 9 & bal & 2000 & 74 & 88 & 0.457 & 4th in al east & none & none & none & none \\ 10 & bal & 2001 & 63 & 98 & 0.391 & 4th in al east & none & none & none & none \\ 11 & bal & 2002 & 67 & 95 & 0.414 & 4th in al east & none & none & none & none \\ 12 & bal & 2003 & 71 & 91 & 0.438 & 4th in al east & none & none & none & none \\ 13 & sea & 2005 & 69 & 93 & 0.426 & 4th in al west & none & none & none & none \\ 14 & sea & 2006 & 78 & 84 & 0.481 & 4th in al west & none & none & none & none \\ 15 & sea & 2007 & 45 & 33 & 0.571 & 2nd in al west & none & none & none & none \\ 16 & cle total & cle total & 721 & 591 & 0.55 & none & 27 & 25 & 0.519 & none \\ 17 & bal total & bal total & 275 & 372 & 0.425 & none & 0 & 0 & 0 & none \\ 18 & sea total & sea total & 192 & 210 & 0.478 & none & 0 & 0 & 0 & none \\ 19 & total & total & 1188 & 1173 & 0.503 & none & 27 & 25 & 0.519 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & team \\ \midrule 0 & bal total \\ 1 & sea total \\ \bottomrule \end{tabular}	select team where postseason lost = 0 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>year</th> <th>regular season won</th> <th>regular season lost</th> <th>regular season win %</th> <th>regular season finish</th> <th>postseason won</th> <th>postseason lost</th> <th>postseason win %</th> <th>postseason result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>cle</td> <td>1991</td> <td>32</td> <td>53</td> <td>0.376</td> <td>7th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>1</th> <td>cle</td> <td>1992</td> <td>76</td> <td>86</td> <td>0.469</td> <td>5th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>2</th> <td>cle</td> <td>1993</td> <td>76</td> <td>86</td> <td>0.469</td> <td>6th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>3</th> <td>cle</td> <td>1994</td> <td>66</td> <td>47</td> <td>0.584</td> <td>2nd in al central</td> <td>none</td> <td>none</td> <td>none</td> <td>no mlb postseason</td> </tr> <tr> <th>4</th> <td>cle</td> <td>1995</td> <td>100</td> <td>44</td> <td>0.694</td> <td>1st in al central</td> <td>9</td> <td>6</td> <td>0.6</td> <td>lost ws to atl</td> </tr> <tr> <th>5</th> <td>cle</td> <td>1996</td> <td>99</td> <td>62</td> <td>0.615</td> <td>1st in al central</td> <td>1</td> <td>3</td> <td>0.25</td> <td>lost lds to bal</td> </tr> <tr> <th>6</th> <td>cle</td> <td>1997</td> <td>86</td> <td>75</td> <td>0.534</td> <td>1st in al central</td> <td>10</td> <td>8</td> <td>0.556</td> <td>lost ws to fla</td> </tr> <tr> <th>7</th> <td>cle</td> <td>1998</td> <td>89</td> <td>73</td> <td>0.549</td> <td>1st in al central</td> <td>5</td> <td>5</td> <td>0.5</td> <td>lost lcs to nyy</td> </tr> <tr> <th>8</th> <td>cle</td> <td>1999</td> <td>97</td> <td>65</td> <td>0.599</td> <td>1st in al central</td> <td>2</td> <td>3</td> <td>0.4</td> <td>lost lds to bos</td> </tr> <tr> <th>9</th> <td>bal</td> <td>2000</td> <td>74</td> <td>88</td> <td>0.457</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>10</th> <td>bal</td> <td>2001</td> <td>63</td> <td>98</td> <td>0.391</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>11</th> <td>bal</td> <td>2002</td> <td>67</td> <td>95</td> <td>0.414</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>12</th> <td>bal</td> <td>2003</td> <td>71</td> <td>91</td> <td>0.438</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>13</th> <td>sea</td> <td>2005</td> <td>69</td> <td>93</td> <td>0.426</td> <td>4th in al west</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>14</th> <td>sea</td> <td>2006</td> <td>78</td> <td>84</td> <td>0.481</td> <td>4th in al west</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>15</th> <td>sea</td> <td>2007</td> <td>45</td> <td>33</td> <td>0.571</td> <td>2nd in al west</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>16</th> <td>cle total</td> <td>cle total</td> <td>721</td> <td>591</td> <td>0.55</td> <td>none</td> <td>27</td> <td>25</td> <td>0.519</td> <td>none</td> </tr> <tr> <th>17</th> <td>bal total</td> <td>bal total</td> <td>275</td> <td>372</td> <td>0.425</td> <td>none</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>18</th> <td>sea total</td> <td>sea total</td> <td>192</td> <td>210</td> <td>0.478</td> <td>none</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>19</th> <td>total</td> <td>total</td> <td>1188</td> <td>1173</td> <td>0.503</td> <td>none</td> <td>27</td> <td>25</td> <td>0.519</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>bal total</td> </tr> <tr> <th>1</th> <td>sea total</td> </tr> </tbody> </table>	select team where postseason lost = 0 <table_name> : table \| \| team \| year \| regular season won \| regular season lost \| regular season win % \| regular season finish \| postseason won \| postseason lost \| postseason win % \| postseason result \| \|---:\|:----------\|:----------\|---------------------:\|----------------------:\|-----------------------:\|:------------------------\|:-----------------\|:------------------\|:-------------------\|:--------------------\| \| 0 \| cle \| 1991 \| 32 \| 53 \| 0.376 \| 7th in al east \| none \| none \| none \| none \| \| 1 \| cle \| 1992 \| 76 \| 86 \| 0.469 \| 5th in al east \| none \| none \| none \| none \| \| 2 \| cle \| 1993 \| 76 \| 86 \| 0.469 \| 6th in al east \| none \| none \| none \| none \| \| 3 \| cle \| 1994 \| 66 \| 47 \| 0.584 \| 2nd in al central \| none \| none \| none \| no mlb postseason \| \| 4 \| cle \| 1995 \| 100 \| 44 \| 0.694 \| 1st in al central \| 9 \| 6 \| 0.6 \| lost ws to atl \| \| 5 \| cle \| 1996 \| 99 \| 62 \| 0.615 \| 1st in al central \| 1 \| 3 \| 0.25 \| lost lds to bal \| \| 6 \| cle \| 1997 \| 86 \| 75 \| 0.534 \| 1st in al central \| 10 \| 8 \| 0.556 \| lost ws to fla \| \| 7 \| cle \| 1998 \| 89 \| 73 \| 0.549 \| 1st in al central \| 5 \| 5 \| 0.5 \| lost lcs to nyy \| \| 8 \| cle \| 1999 \| 97 \| 65 \| 0.599 \| 1st in al central \| 2 \| 3 \| 0.4 \| lost lds to bos \| \| 9 \| bal \| 2000 \| 74 \| 88 \| 0.457 \| 4th in al east \| none \| none \| none \| none \| \| 10 \| bal \| 2001 \| 63 \| 98 \| 0.391 \| 4th in al east \| none \| none \| none \| none \| \| 11 \| bal \| 2002 \| 67 \| 95 \| 0.414 \| 4th in al east \| none \| none \| none \| none \| \| 12 \| bal \| 2003 \| 71 \| 91 \| 0.438 \| 4th in al east \| none \| none \| none \| none \| \| 13 \| sea \| 2005 \| 69 \| 93 \| 0.426 \| 4th in al west \| none \| none \| none \| none \| \| 14 \| sea \| 2006 \| 78 \| 84 \| 0.481 \| 4th in al west \| none \| none \| none \| none \| \| 15 \| sea \| 2007 \| 45 \| 33 \| 0.571 \| 2nd in al west \| none \| none \| none \| none \| \| 16 \| cle total \| cle total \| 721 \| 591 \| 0.55 \| none \| 27 \| 25 \| 0.519 \| none \| \| 17 \| bal total \| bal total \| 275 \| 372 \| 0.425 \| none \| 0 \| 0 \| 0 \| none \| \| 18 \| sea total \| sea total \| 192 \| 210 \| 0.478 \| none \| 0 \| 0 \| 0 \| none \| \| 19 \| total \| total \| 1188 \| 1173 \| 0.503 \| none \| 27 \| 25 \| 0.519 \| none \|	\| \| team \| \|---:\|:----------\| \| 0 \| bal total \| \| 1 \| sea total \|	[ [ 1, 4025, 5927, 1625, 1603, 30321, 13557, 273, 374, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 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select count ( nation ) where name = 1924 col : rank \| name \| nation \| time \| speed \| note row 1 : 1 \| vilija sereikaite \| lithuania \| 3:33.766 \| 50.522 \| q row 2 : 2 \| ellen van dijk \| netherlands \| 3:35.951 \| 50.011 \| q row 3 : 3 \| joanna rowsell \| united kingdom \| 3:37.641 \| 49.623 \| q row 4 : 4 \| svitlana halyuk \| ukraine \| 3:42.498 \| 48.539 \| q row 5 : 5 \| aksana papko \| belarus \| 3:43.935 \| 48.288 \| none row 6 : 6 \| oxana kozonchuk \| russia \| 3:45.132 \| 47.971 \| none row 7 : 7 \| jarmila machacova \| czech republic \| 3:47.209 \| 47.533 \| none row 8 : 8 \| stephanie pohl \| germany \| 3:47.483 \| 47.476 \| none row 9 : 9 \| lisa brennauer \| germany \| 3:48.017 \| 47.364 \| none row 10 : 10 \| edyta jasinska \| poland \| 3:48.628 \| 47.238 \| none row 11 : 11 \| audrey cordon \| france \| 3:49.376 \| 47.084 \| none row 12 : 12 \| alena amialyusik \| belarus \| 3:49.711 \| 47.015 \| none row 13 : 13 \| hannah mayho \| united kingdom \| 3:50.176 \| 46.92 \| none row 14 : 14 \| viktoriya kondel \| russia \| 3:51.349 \| 46.682 \| none row 15 : 15 \| oksana lyesnik \| ukraine \| 3:51.543 \| 46.643 \| none row 16 : 16 \| elise van hage \| netherlands \| 3:55.349 \| 45.889 \| none row 17 : 17 \| dominika maczka \| poland \| 4:01.597 \| 44.702 \| none	col : count ( "nation" ) row 1 : 0	select count ( nation ) where name = 1924 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & name & nation & time & speed & note \\ \midrule 0 & 1 & vilija sereikaite & lithuania & 3:33.766 & 50.522 & q \\ 1 & 2 & ellen van dijk & netherlands & 3:35.951 & 50.011 & q \\ 2 & 3 & joanna rowsell & united kingdom & 3:37.641 & 49.623 & q \\ 3 & 4 & svitlana halyuk & ukraine & 3:42.498 & 48.539 & q \\ 4 & 5 & aksana papko & belarus & 3:43.935 & 48.288 & none \\ 5 & 6 & oxana kozonchuk & russia & 3:45.132 & 47.971 & none \\ 6 & 7 & jarmila machacova & czech republic & 3:47.209 & 47.533 & none \\ 7 & 8 & stephanie pohl & germany & 3:47.483 & 47.476 & none \\ 8 & 9 & lisa brennauer & germany & 3:48.017 & 47.364 & none \\ 9 & 10 & edyta jasinska & poland & 3:48.628 & 47.238 & none \\ 10 & 11 & audrey cordon & france & 3:49.376 & 47.084 & none \\ 11 & 12 & alena amialyusik & belarus & 3:49.711 & 47.015 & none \\ 12 & 13 & hannah mayho & united kingdom & 3:50.176 & 46.92 & none \\ 13 & 14 & viktoriya kondel & russia & 3:51.349 & 46.682 & none \\ 14 & 15 & oksana lyesnik & ukraine & 3:51.543 & 46.643 & none \\ 15 & 16 & elise van hage & netherlands & 3:55.349 & 45.889 & none \\ 16 & 17 & dominika maczka & poland & 4:01.597 & 44.702 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "nation" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( nation ) where name = 1924 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>name</th> <th>nation</th> <th>time</th> <th>speed</th> <th>note</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>vilija sereikaite</td> <td>lithuania</td> <td>3:33.766</td> <td>50.522</td> <td>q</td> </tr> <tr> <th>1</th> <td>2</td> <td>ellen van dijk</td> <td>netherlands</td> <td>3:35.951</td> <td>50.011</td> <td>q</td> </tr> <tr> <th>2</th> <td>3</td> <td>joanna rowsell</td> <td>united kingdom</td> <td>3:37.641</td> <td>49.623</td> <td>q</td> </tr> <tr> <th>3</th> <td>4</td> <td>svitlana halyuk</td> <td>ukraine</td> <td>3:42.498</td> <td>48.539</td> <td>q</td> </tr> <tr> <th>4</th> <td>5</td> <td>aksana papko</td> <td>belarus</td> <td>3:43.935</td> <td>48.288</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>oxana kozonchuk</td> <td>russia</td> <td>3:45.132</td> <td>47.971</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>jarmila machacova</td> <td>czech republic</td> <td>3:47.209</td> <td>47.533</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>stephanie pohl</td> <td>germany</td> <td>3:47.483</td> <td>47.476</td> <td>none</td> </tr> <tr> <th>8</th> <td>9</td> <td>lisa brennauer</td> <td>germany</td> <td>3:48.017</td> <td>47.364</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>edyta jasinska</td> <td>poland</td> <td>3:48.628</td> <td>47.238</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>audrey cordon</td> <td>france</td> <td>3:49.376</td> <td>47.084</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>alena amialyusik</td> <td>belarus</td> <td>3:49.711</td> <td>47.015</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>hannah mayho</td> <td>united kingdom</td> <td>3:50.176</td> <td>46.92</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>viktoriya kondel</td> <td>russia</td> <td>3:51.349</td> <td>46.682</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>oksana lyesnik</td> <td>ukraine</td> <td>3:51.543</td> <td>46.643</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>elise van hage</td> <td>netherlands</td> <td>3:55.349</td> <td>45.889</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>dominika maczka</td> <td>poland</td> <td>4:01.597</td> <td>44.702</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "nation" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( nation ) where name = 1924 <table_name> : table \| \| rank \| name \| nation \| time \| speed \| note \| \|---:\|-------:\|:------------------\|:---------------\|:---------\|--------:\|:-------\| \| 0 \| 1 \| vilija sereikaite \| lithuania \| 3:33.766 \| 50.522 \| q \| \| 1 \| 2 \| ellen van dijk \| netherlands \| 3:35.951 \| 50.011 \| q \| \| 2 \| 3 \| joanna rowsell \| united kingdom \| 3:37.641 \| 49.623 \| q \| \| 3 \| 4 \| svitlana halyuk \| ukraine \| 3:42.498 \| 48.539 \| q \| \| 4 \| 5 \| aksana papko \| belarus \| 3:43.935 \| 48.288 \| none \| \| 5 \| 6 \| oxana kozonchuk \| russia \| 3:45.132 \| 47.971 \| none \| \| 6 \| 7 \| jarmila machacova \| czech republic \| 3:47.209 \| 47.533 \| none \| \| 7 \| 8 \| stephanie pohl \| germany \| 3:47.483 \| 47.476 \| none \| \| 8 \| 9 \| lisa brennauer \| germany \| 3:48.017 \| 47.364 \| none \| \| 9 \| 10 \| edyta jasinska \| poland \| 3:48.628 \| 47.238 \| none \| \| 10 \| 11 \| audrey cordon \| france \| 3:49.376 \| 47.084 \| none \| \| 11 \| 12 \| alena amialyusik \| belarus \| 3:49.711 \| 47.015 \| none \| \| 12 \| 13 \| hannah mayho \| united kingdom \| 3:50.176 \| 46.92 \| none \| \| 13 \| 14 \| viktoriya kondel \| russia \| 3:51.349 \| 46.682 \| none \| \| 14 \| 15 \| oksana lyesnik \| ukraine \| 3:51.543 \| 46.643 \| none \| \| 15 \| 16 \| elise van hage \| netherlands \| 3:55.349 \| 45.889 \| none \| \| 16 \| 17 \| dominika maczka \| poland \| 4:01.597 \| 44.702 \| none \|	\| \| count ( "nation" ) \| \|---:\|---------------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 290, 367, 262, 1625, 508, 273, 5342, 3247, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 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select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' col : rank \| airport \| passengers handled \| % change 2011 / 12 row 1 : 1 \| netherlands - amsterdam \| 105349 \| none row 2 : 2 \| united kingdom - belfast-international \| 92502 \| none row 3 : 3 \| portugal - faro \| 71676 \| none row 4 : 4 \| spain - barcelona \| 66565 \| none row 5 : 5 \| spain - alicante \| 64090 \| none row 6 : 6 \| spain - malaga \| 59175 \| none row 7 : 7 \| ireland - dublin \| 35524 \| none row 8 : 8 \| jersey - jersey \| 35169 \| 1128 row 9 : 9 \| ireland - waterford \| 31907 \| 25 row 10 : 10 \| spain - palma de mallorca \| 27718 \| none	col : "% change 2011 / 12 + passengers handled" row 1 : % change 2011 / 12 + passengers handled	select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' <table_name> : table \begin{tabular}{lllll} \toprule & rank & airport & passengers handled & % change 2011 / 12 \\ \midrule 0 & 1 & netherlands - amsterdam & 105349 & none \\ 1 & 2 & united kingdom - belfast-international & 92502 & none \\ 2 & 3 & portugal - faro & 71676 & none \\ 3 & 4 & spain - barcelona & 66565 & none \\ 4 & 5 & spain - alicante & 64090 & none \\ 5 & 6 & spain - malaga & 59175 & none \\ 6 & 7 & ireland - dublin & 35524 & none \\ 7 & 8 & jersey - jersey & 35169 & 1128 \\ 8 & 9 & ireland - waterford & 31907 & 25 \\ 9 & 10 & spain - palma de mallorca & 27718 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & "% change 2011 / 12 + passengers handled" \\ \midrule 0 & % change 2011 / 12 + passengers handled \\ \bottomrule \end{tabular}	select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>airport</th> <th>passengers handled</th> <th>% change 2011 / 12</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>netherlands - amsterdam</td> <td>105349</td> <td>none</td> </tr> <tr> <th>1</th> <td>2</td> <td>united kingdom - belfast-international</td> <td>92502</td> <td>none</td> </tr> <tr> <th>2</th> <td>3</td> <td>portugal - faro</td> <td>71676</td> <td>none</td> </tr> <tr> <th>3</th> <td>4</td> <td>spain - barcelona</td> <td>66565</td> <td>none</td> </tr> <tr> <th>4</th> <td>5</td> <td>spain - alicante</td> <td>64090</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>spain - malaga</td> <td>59175</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>ireland - dublin</td> <td>35524</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>jersey - jersey</td> <td>35169</td> <td>1128</td> </tr> <tr> <th>8</th> <td>9</td> <td>ireland - waterford</td> <td>31907</td> <td>25</td> </tr> <tr> <th>9</th> <td>10</td> <td>spain - palma de mallorca</td> <td>27718</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"% change 2011 / 12 + passengers handled"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>% change 2011 / 12 + passengers handled</td> </tr> </tbody> </table>	select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' <table_name> : table \| \| rank \| airport \| passengers handled \| % change 2011 / 12 \| \|---:\|-------:\|:---------------------------------------\|---------------------:\|:---------------------\| \| 0 \| 1 \| netherlands - amsterdam \| 105349 \| none \| \| 1 \| 2 \| united kingdom - belfast-international \| 92502 \| none \| \| 2 \| 3 \| portugal - faro \| 71676 \| none \| \| 3 \| 4 \| spain - barcelona \| 66565 \| none \| \| 4 \| 5 \| spain - alicante \| 64090 \| none \| \| 5 \| 6 \| spain - malaga \| 59175 \| none \| \| 6 \| 7 \| ireland - dublin \| 35524 \| none \| \| 7 \| 8 \| jersey - jersey \| 35169 \| 1128 \| \| 8 \| 9 \| ireland - waterford \| 31907 \| 25 \| \| 9 \| 10 \| spain - palma de mallorca \| 27718 \| none \|	\| \| "% change 2011 / 12 + passengers handled" \| 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select count ( * ) where games = '3' col : games \| athletes \| gold \| silver \| bronze \| total \| rank row 1 : 1988 seoul \| 14 \| 0 \| 0 \| 1 \| 1 \| 48 row 2 : 1992 barcelona \| 5 \| 0 \| 0 \| 0 \| 0 \| none row 3 : 1996 atlanta \| 4 \| 0 \| 0 \| 0 \| 0 \| none row 4 : 2000 sydney \| 7 \| 0 \| 0 \| 0 \| 0 \| none row 5 : 2004 athens \| 10 \| 2 \| 4 \| 0 \| 6 \| 42 row 6 : 2008 beijing \| 18 \| 4 \| 1 \| 2 \| 7 \| 32 row 7 : 2012 london \| 31 \| 3 \| 0 \| 3 \| 6 \| 37 row 8 : total \| total \| 9 \| 5 \| 6 \| 20 \| 54 row 9 : none \| none \| none \| none \| none \| none \| none	col : count ( "*" ) row 1 : 0	select count ( * ) where games = '3' <table_name> : table \begin{tabular}{llllllll} \toprule & games & athletes & gold & silver & bronze & total & rank \\ \midrule 0 & 1988 seoul & 14 & 0 & 0 & 1 & 1 & 48 \\ 1 & 1992 barcelona & 5 & 0 & 0 & 0 & 0 & none \\ 2 & 1996 atlanta & 4 & 0 & 0 & 0 & 0 & none \\ 3 & 2000 sydney & 7 & 0 & 0 & 0 & 0 & none \\ 4 & 2004 athens & 10 & 2 & 4 & 0 & 6 & 42 \\ 5 & 2008 beijing & 18 & 4 & 1 & 2 & 7 & 32 \\ 6 & 2012 london & 31 & 3 & 0 & 3 & 6 & 37 \\ 7 & total & total & 9 & 5 & 6 & 20 & 54 \\ 8 & none & none & none & none & none & none & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where games = '3' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>games</th> <th>athletes</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> <th>rank</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1988 seoul</td> <td>14</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> <td>48</td> </tr> <tr> <th>1</th> <td>1992 barcelona</td> <td>5</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>2</th> <td>1996 atlanta</td> <td>4</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>3</th> <td>2000 sydney</td> <td>7</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>4</th> <td>2004 athens</td> <td>10</td> <td>2</td> <td>4</td> <td>0</td> <td>6</td> <td>42</td> </tr> <tr> <th>5</th> <td>2008 beijing</td> <td>18</td> <td>4</td> <td>1</td> <td>2</td> <td>7</td> <td>32</td> </tr> <tr> <th>6</th> <td>2012 london</td> <td>31</td> <td>3</td> <td>0</td> <td>3</td> <td>6</td> <td>37</td> </tr> <tr> <th>7</th> <td>total</td> <td>total</td> <td>9</td> <td>5</td> <td>6</td> <td>20</td> <td>54</td> </tr> <tr> <th>8</th> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where games = '3' <table_name> : table \| \| games \| athletes \| gold \| silver \| bronze \| total \| rank \| \|---:\|:---------------\|:-----------\|:-------\|:---------\|:---------\|:--------\|:-------\| \| 0 \| 1988 seoul \| 14 \| 0 \| 0 \| 1 \| 1 \| 48 \| \| 1 \| 1992 barcelona \| 5 \| 0 \| 0 \| 0 \| 0 \| none \| \| 2 \| 1996 atlanta \| 4 \| 0 \| 0 \| 0 \| 0 \| none \| \| 3 \| 2000 sydney \| 7 \| 0 \| 0 \| 0 \| 0 \| none \| \| 4 \| 2004 athens \| 10 \| 2 \| 4 \| 0 \| 6 \| 42 \| \| 5 \| 2008 beijing \| 18 \| 4 \| 1 \| 2 \| 7 \| 32 \| \| 6 \| 2012 london \| 31 \| 3 \| 0 \| 3 \| 6 \| 37 \| \| 7 \| total \| total \| 9 \| 5 \| 6 \| 20 \| 54 \| \| 8 \| none \| none \| none \| none \| none \| none \| none \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 28422, 273, 296, 23, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 75, 753, 1757, 451, 34, 203, 1377, 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select count ( player ) where player = 'bruce murray' col : # \| player \| goals \| caps \| career row 1 : 1 \| landon donovan \| 57 \| 155 \| 2000-present row 2 : 2 \| clint dempsey \| 36 \| 103 \| 2004-present row 3 : 3 \| eric wynalda \| 34 \| 106 \| 1990-2000 row 4 : 4 \| brian mcbride \| 30 \| 95 \| 1993-2006 row 5 : 5 \| joe-max moore \| 24 \| 100 \| 1992-2002 row 6 : 6 \| jozy altidore \| 21 \| 67 \| 2007-present row 7 : 6 \| bruce murray \| 21 \| 86 \| 1985-1993 row 8 : 8 \| eddie johnson \| 19 \| 62 \| 2004-present row 9 : 9 \| earnie stewart \| 17 \| 101 \| 1990-2004 row 10 : 9 \| damarcus beasley \| 17 \| 114 \| 2001-present	col : count ( "player" ) row 1 : 1	select count ( player ) where player = 'bruce murray' <table_name> : table \begin{tabular}{llllll} \toprule & # & player & goals & caps & career \\ \midrule 0 & 1 & landon donovan & 57 & 155 & 2000-present \\ 1 & 2 & clint dempsey & 36 & 103 & 2004-present \\ 2 & 3 & eric wynalda & 34 & 106 & 1990-2000 \\ 3 & 4 & brian mcbride & 30 & 95 & 1993-2006 \\ 4 & 5 & joe-max moore & 24 & 100 & 1992-2002 \\ 5 & 6 & jozy altidore & 21 & 67 & 2007-present \\ 6 & 6 & bruce murray & 21 & 86 & 1985-1993 \\ 7 & 8 & eddie johnson & 19 & 62 & 2004-present \\ 8 & 9 & earnie stewart & 17 & 101 & 1990-2004 \\ 9 & 9 & damarcus beasley & 17 & 114 & 2001-present \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "player" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( player ) where player = 'bruce murray' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>player</th> <th>goals</th> <th>caps</th> <th>career</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>landon donovan</td> <td>57</td> <td>155</td> <td>2000-present</td> </tr> <tr> <th>1</th> <td>2</td> <td>clint dempsey</td> <td>36</td> <td>103</td> <td>2004-present</td> </tr> <tr> <th>2</th> <td>3</td> <td>eric wynalda</td> <td>34</td> <td>106</td> <td>1990-2000</td> </tr> <tr> <th>3</th> <td>4</td> <td>brian mcbride</td> <td>30</td> <td>95</td> <td>1993-2006</td> </tr> <tr> <th>4</th> <td>5</td> <td>joe-max moore</td> <td>24</td> <td>100</td> <td>1992-2002</td> </tr> <tr> <th>5</th> <td>6</td> <td>jozy altidore</td> <td>21</td> <td>67</td> <td>2007-present</td> </tr> <tr> <th>6</th> <td>6</td> <td>bruce murray</td> <td>21</td> <td>86</td> <td>1985-1993</td> </tr> <tr> <th>7</th> <td>8</td> <td>eddie johnson</td> <td>19</td> <td>62</td> <td>2004-present</td> </tr> <tr> <th>8</th> <td>9</td> <td>earnie stewart</td> <td>17</td> <td>101</td> <td>1990-2004</td> </tr> <tr> <th>9</th> <td>9</td> <td>damarcus beasley</td> <td>17</td> <td>114</td> <td>2001-present</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "player" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( player ) where player = 'bruce murray' <table_name> : table \| \| # \| player \| goals \| caps \| career \| \|---:\|----:\|:-----------------\|--------:\|-------:\|:-------------\| \| 0 \| 1 \| landon donovan \| 57 \| 155 \| 2000-present \| \| 1 \| 2 \| clint dempsey \| 36 \| 103 \| 2004-present \| \| 2 \| 3 \| eric wynalda \| 34 \| 106 \| 1990-2000 \| \| 3 \| 4 \| brian mcbride \| 30 \| 95 \| 1993-2006 \| \| 4 \| 5 \| joe-max moore \| 24 \| 100 \| 1992-2002 \| \| 5 \| 6 \| jozy altidore \| 21 \| 67 \| 2007-present \| \| 6 \| 6 \| bruce murray \| 21 \| 86 \| 1985-1993 \| \| 7 \| 8 \| eddie johnson \| 19 \| 62 \| 2004-present \| \| 8 \| 9 \| earnie stewart \| 17 \| 101 \| 1990-2004 \| \| 9 \| 9 \| damarcus beasley \| 17 \| 114 \| 2001-present \|	\| \| count ( "player" ) \| \|---:\|---------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 7291, 262, 1625, 7291, 273, 296, 2848, 3965, 312, 295, 435, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 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select count ( * ) where total time < 1817 col : athlete \| event \| race 1 time \| race 2 time \| total time \| total rank row 1 : johann haraldsson \| giant slalom \| 1:19.10 \| dnf \| dnf \| none row 2 : kristinn magnusson \| giant slalom \| 1:17.50 \| 1:16.29 \| 2:33.79 \| 42 row 3 : bjorgvin bjorgvinsson \| giant slalom \| 1:15.86 \| dnf \| dnf \| none row 4 : kristinn magnusson \| slalom \| dnf \| none \| dnf \| none row 5 : bjorgvin bjorgvinsson \| slalom \| dnf \| none \| dnf \| none row 6 : johann haraldsson \| slalom \| 56.98 \| 1:00.19 \| 1:57.17 \| 28 row 7 : kristinn bjornsson \| slalom \| 53.05 \| 56.76 \| 1:49.81 \| 21	col : count ( "*" ) row 1 : 0	select count ( * ) where total time < 1817 <table_name> : table \begin{tabular}{lllllll} \toprule & athlete & event & race 1 time & race 2 time & total time & total rank \\ \midrule 0 & johann haraldsson & giant slalom & 1:19.10 & dnf & dnf & none \\ 1 & kristinn magnusson & giant slalom & 1:17.50 & 1:16.29 & 2:33.79 & 42 \\ 2 & bjorgvin bjorgvinsson & giant slalom & 1:15.86 & dnf & dnf & none \\ 3 & kristinn magnusson & slalom & dnf & none & dnf & none \\ 4 & bjorgvin bjorgvinsson & slalom & dnf & none & dnf & none \\ 5 & johann haraldsson & slalom & 56.98 & 1:00.19 & 1:57.17 & 28 \\ 6 & kristinn bjornsson & slalom & 53.05 & 56.76 & 1:49.81 & 21 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where total time < 1817 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>athlete</th> <th>event</th> <th>race 1 time</th> <th>race 2 time</th> <th>total time</th> <th>total rank</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>johann haraldsson</td> <td>giant slalom</td> <td>1:19.10</td> <td>dnf</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>1</th> <td>kristinn magnusson</td> <td>giant slalom</td> <td>1:17.50</td> <td>1:16.29</td> <td>2:33.79</td> <td>42</td> </tr> <tr> <th>2</th> <td>bjorgvin bjorgvinsson</td> <td>giant slalom</td> <td>1:15.86</td> <td>dnf</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>3</th> <td>kristinn magnusson</td> <td>slalom</td> <td>dnf</td> <td>none</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>4</th> <td>bjorgvin bjorgvinsson</td> <td>slalom</td> <td>dnf</td> <td>none</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>5</th> <td>johann haraldsson</td> <td>slalom</td> <td>56.98</td> <td>1:00.19</td> <td>1:57.17</td> <td>28</td> </tr> <tr> <th>6</th> <td>kristinn bjornsson</td> <td>slalom</td> <td>53.05</td> <td>56.76</td> <td>1:49.81</td> <td>21</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where total time < 1817 <table_name> : table \| \| athlete \| event \| race 1 time \| race 2 time \| total time \| total rank \| \|---:\|:----------------------\|:-------------\|:--------------\|:--------------\|:-------------\|:-------------\| \| 0 \| johann haraldsson \| giant slalom \| 1:19.10 \| dnf \| dnf \| none \| \| 1 \| kristinn magnusson \| giant slalom \| 1:17.50 \| 1:16.29 \| 2:33.79 \| 42 \| \| 2 \| bjorgvin bjorgvinsson \| giant slalom \| 1:15.86 \| dnf \| dnf \| none \| \| 3 \| kristinn magnusson \| slalom \| dnf \| none \| dnf \| none \| \| 4 \| bjorgvin bjorgvinsson \| slalom \| dnf \| none \| dnf \| none \| \| 5 \| johann haraldsson \| slalom \| 56.98 \| 1:00.19 \| 1:57.17 \| 28 \| \| 6 \| kristinn bjornsson \| slalom \| 53.05 \| 56.76 \| 1:49.81 \| 21 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 2078, 813, 411, 6549, 4033, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 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select owner where network name = 'canal 5' col : network name \| flagship \| programming type \| owner \| affiliates row 1 : canal de las estrellas \| xew 2 \| soap operas, retro movies and sports \| televisa \| 1 row 2 : canal 5 \| xhgc 5 \| cartoons, movies, and series \| televisa \| 1 row 3 : azteca 7 \| xhimt 7 \| sports, series, and movies \| tv azteca \| 1 row 4 : galavision \| xeq 9 \| retro programming and sports \| televisa \| 1 row 5 : once tv \| xeipn 11 \| educational and cultural \| national polytechnic institute \| 1 row 6 : azteca 13 \| xhdf 13 \| news, soap operas, and sports \| tv azteca \| 1 row 7 : independent \| none \| varies \| independent \| 2	col : owner row 1 : televisa	select owner where network name = 'canal 5' <table_name> : table \begin{tabular}{llllll} \toprule & network name & flagship & programming type & owner & affiliates \\ \midrule 0 & canal de las estrellas & xew 2 & soap operas, retro movies and sports & televisa & 1 \\ 1 & canal 5 & xhgc 5 & cartoons, movies, and series & televisa & 1 \\ 2 & azteca 7 & xhimt 7 & sports, series, and movies & tv azteca & 1 \\ 3 & galavision & xeq 9 & retro programming and sports & televisa & 1 \\ 4 & once tv & xeipn 11 & educational and cultural & national polytechnic institute & 1 \\ 5 & azteca 13 & xhdf 13 & news, soap operas, and sports & tv azteca & 1 \\ 6 & independent & none & varies & independent & 2 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & owner \\ \midrule 0 & televisa \\ \bottomrule \end{tabular}	select owner where network name = 'canal 5' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>network name</th> <th>flagship</th> <th>programming type</th> <th>owner</th> <th>affiliates</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>canal de las estrellas</td> <td>xew 2</td> <td>soap operas, retro movies and sports</td> <td>televisa</td> <td>1</td> </tr> <tr> <th>1</th> <td>canal 5</td> <td>xhgc 5</td> <td>cartoons, movies, and series</td> <td>televisa</td> <td>1</td> </tr> <tr> <th>2</th> <td>azteca 7</td> <td>xhimt 7</td> <td>sports, series, and movies</td> <td>tv azteca</td> <td>1</td> </tr> <tr> <th>3</th> <td>galavision</td> <td>xeq 9</td> <td>retro programming and sports</td> <td>televisa</td> <td>1</td> </tr> <tr> <th>4</th> <td>once tv</td> <td>xeipn 11</td> <td>educational and cultural</td> <td>national polytechnic institute</td> <td>1</td> </tr> <tr> <th>5</th> <td>azteca 13</td> <td>xhdf 13</td> <td>news, soap operas, and sports</td> <td>tv azteca</td> <td>1</td> </tr> <tr> <th>6</th> <td>independent</td> <td>none</td> <td>varies</td> <td>independent</td> <td>2</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>owner</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>televisa</td> </tr> </tbody> </table>	select owner where network name = 'canal 5' <table_name> : table \| \| network name \| flagship \| programming type \| owner \| affiliates \| \|---:\|:-----------------------\|:-----------\|:-------------------------------------\|:-------------------------------\|-------------:\| \| 0 \| canal de las estrellas \| xew 2 \| soap operas, retro movies and sports \| televisa \| 1 \| \| 1 \| canal 5 \| xhgc 5 \| cartoons, movies, and series \| televisa \| 1 \| \| 2 \| azteca 7 \| xhimt 7 \| sports, series, and movies \| tv azteca \| 1 \| \| 3 \| galavision \| xeq 9 \| retro programming and sports \| televisa \| 1 \| \| 4 \| once tv \| xeipn 11 \| educational and cultural \| national polytechnic institute \| 1 \| \| 5 \| azteca 13 \| xhdf 13 \| news, soap operas, and sports \| tv azteca \| 1 \| \| 6 \| independent \| none \| varies \| independent \| 2 \|	\| \| owner \| \|---:\|:---------\| \| 0 \| televisa \|	[ [ 1, 4025, 3410, 1625, 2483, 508, 273, 296, 4169, 287, 1381, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 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select season where position = '7th' col : season \| level \| division \| section \| position \| movements row 1 : 1999 \| tier 5 \| division 4 \| gotland \| 6th \| varserier (spring series) row 2 : none \| tier 5 \| division 4 \| gotland \| 5th \| hostserier (autumn series) row 3 : 2000 \| tier 5 \| division 4 \| gotland \| 2nd \| varserier (spring series) row 4 : none \| tier 5 \| division 4 \| uppland/gotland host \| 10th \| hostserier (autumn series) row 5 : 2001 \| tier 5 \| division 4 \| gotland \| 4th \| varserier (spring series) row 6 : none \| tier 5 \| division 4 \| gotland \| 4th \| slutspel a (playoff a) row 7 : 2002 \| tier 5 \| division 4 \| gotland \| 3rd \| promotion playoffs row 8 : 2003 \| tier 5 \| division 4 \| gotland \| 6th \| none row 9 : 2004 \| tier 5 \| division 4 \| gotland \| 4th \| none row 10 : 2005 \| tier 5 \| division 4 \| gotland \| 1st \| none row 11 : 2006 \| tier 5 \| division 3 \| ostra svealand \| 12th \| relegated row 12 : 2007 \| tier 6 \| division 4 \| gotland \| 2nd \| none row 13 : 2008 \| tier 6 \| division 4 \| gotland \| 3rd \| none row 14 : 2009 \| tier 6 \| division 4 \| gotland \| 7th \| none row 15 : 2010 \| tier 6 \| division 4 \| gotland \| 2nd \| none row 16 : 2011 \| tier 6 \| division 4 \| gotland \| 4th \| none	col : season row 1 : 2009	select season where position = '7th' <table_name> : table \begin{tabular}{lllllll} \toprule & season & level & division & section & position & movements \\ \midrule 0 & 1999 & tier 5 & division 4 & gotland & 6th & varserier (spring series) \\ 1 & none & tier 5 & division 4 & gotland & 5th & hostserier (autumn series) \\ 2 & 2000 & tier 5 & division 4 & gotland & 2nd & varserier (spring series) \\ 3 & none & tier 5 & division 4 & uppland/gotland host & 10th & hostserier (autumn series) \\ 4 & 2001 & tier 5 & division 4 & gotland & 4th & varserier (spring series) \\ 5 & none & tier 5 & division 4 & gotland & 4th & slutspel a (playoff a) \\ 6 & 2002 & tier 5 & division 4 & gotland & 3rd & promotion playoffs \\ 7 & 2003 & tier 5 & division 4 & gotland & 6th & none \\ 8 & 2004 & tier 5 & division 4 & gotland & 4th & none \\ 9 & 2005 & tier 5 & division 4 & gotland & 1st & none \\ 10 & 2006 & tier 5 & division 3 & ostra svealand & 12th & relegated \\ 11 & 2007 & tier 6 & division 4 & gotland & 2nd & none \\ 12 & 2008 & tier 6 & division 4 & gotland & 3rd & none \\ 13 & 2009 & tier 6 & division 4 & gotland & 7th & none \\ 14 & 2010 & tier 6 & division 4 & gotland & 2nd & none \\ 15 & 2011 & tier 6 & division 4 & gotland & 4th & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & season \\ \midrule 0 & 2009 \\ \bottomrule \end{tabular}	select season where position = '7th' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>level</th> <th>division</th> <th>section</th> <th>position</th> <th>movements</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>6th</td> <td>varserier (spring series)</td> </tr> <tr> <th>1</th> <td>none</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>5th</td> <td>hostserier (autumn series)</td> </tr> <tr> <th>2</th> <td>2000</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>2nd</td> <td>varserier (spring series)</td> </tr> <tr> <th>3</th> <td>none</td> <td>tier 5</td> <td>division 4</td> <td>uppland/gotland host</td> <td>10th</td> <td>hostserier (autumn series)</td> </tr> <tr> <th>4</th> <td>2001</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>varserier (spring series)</td> </tr> <tr> <th>5</th> <td>none</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>slutspel a (playoff a)</td> </tr> <tr> <th>6</th> <td>2002</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>3rd</td> <td>promotion playoffs</td> </tr> <tr> <th>7</th> <td>2003</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>6th</td> <td>none</td> </tr> <tr> <th>8</th> <td>2004</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>none</td> </tr> <tr> <th>9</th> <td>2005</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>1st</td> <td>none</td> </tr> <tr> <th>10</th> <td>2006</td> <td>tier 5</td> <td>division 3</td> <td>ostra svealand</td> <td>12th</td> <td>relegated</td> </tr> <tr> <th>11</th> <td>2007</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>2nd</td> <td>none</td> </tr> <tr> <th>12</th> <td>2008</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>3rd</td> <td>none</td> </tr> <tr> <th>13</th> <td>2009</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>7th</td> <td>none</td> </tr> <tr> <th>14</th> <td>2010</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>2nd</td> <td>none</td> </tr> <tr> <th>15</th> <td>2011</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2009</td> </tr> </tbody> </table>	select season where position = '7th' <table_name> : table \| \| season \| level \| division \| section \| position \| movements \| \|---:\|:---------\|:--------\|:-----------\|:---------------------\|:-----------\|:---------------------------\| \| 0 \| 1999 \| tier 5 \| division 4 \| gotland \| 6th \| varserier (spring series) \| \| 1 \| none \| tier 5 \| division 4 \| gotland \| 5th \| hostserier (autumn series) \| \| 2 \| 2000 \| tier 5 \| division 4 \| gotland \| 2nd \| varserier (spring series) \| \| 3 \| none \| tier 5 \| division 4 \| uppland/gotland host \| 10th \| hostserier (autumn series) \| \| 4 \| 2001 \| tier 5 \| division 4 \| gotland \| 4th \| varserier (spring series) \| \| 5 \| none \| tier 5 \| division 4 \| gotland \| 4th \| slutspel a (playoff a) \| \| 6 \| 2002 \| tier 5 \| division 4 \| gotland \| 3rd \| promotion playoffs \| \| 7 \| 2003 \| tier 5 \| division 4 \| gotland \| 6th \| none \| \| 8 \| 2004 \| tier 5 \| division 4 \| gotland \| 4th \| none \| \| 9 \| 2005 \| tier 5 \| division 4 \| gotland \| 1st \| none \| \| 10 \| 2006 \| tier 5 \| division 3 \| ostra svealand \| 12th \| relegated \| \| 11 \| 2007 \| tier 6 \| division 4 \| gotland \| 2nd \| none \| \| 12 \| 2008 \| tier 6 \| division 4 \| gotland \| 3rd \| none \| \| 13 \| 2009 \| tier 6 \| division 4 \| gotland \| 7th \| none \| \| 14 \| 2010 \| tier 6 \| division 4 \| gotland \| 2nd \| none \| \| 15 \| 2011 \| tier 6 \| division 4 \| gotland \| 4th \| none \|	\| \| season \| \|---:\|---------:\| \| 0 \| 2009 \|	[ [ 1, 4025, 15874, 1625, 1754, 273, 296, 27, 451, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 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select count ( rider ) where tyres = 'm' col : team \| constructor \| motorcycle \| tyres \| no \| rider \| rounds row 1 : camel yamaha team \| yamaha \| yamaha yzr-m1 \| m \| 5 \| colin edwards \| all row 2 : camel yamaha team \| yamaha \| yamaha yzr-m1 \| m \| 46 \| valentino rossi \| all row 3 : konica minolta honda \| honda \| honda rc211v \| m \| 6 \| makoto tamada \| all row 4 : tech 3 yamaha \| yamaha \| yamaha yzr-m1 \| d \| 7 \| carlos checa \| all row 5 : tech 3 yamaha \| yamaha \| yamaha yzr-m1 \| d \| 77 \| james ellison \| all row 6 : team roberts \| team roberts \| kr211v \| m \| 10 \| kenny roberts, jr \| all row 7 : ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 15 \| sete gibernau \| 1-7, 10-11, 13-16 row 8 : ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 65 \| loris capirossi \| all row 9 : ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 66 \| alex hofmann \| 8-9, 12 row 10 : ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 12 \| troy bayliss \| 17 row 11 : kawasaki racing team \| kawasaki \| kawasaki ninja zx-rr \| b \| 17 \| randy de puniet \| all row 12 : kawasaki racing team \| kawasaki \| kawasaki ninja zx-rr \| b \| 56 \| shinya nakano \| all row 13 : kawasaki racing team \| kawasaki \| kawasaki ninja zx-rr \| b \| 8 \| naoki matsudo \| 15 row 14 : rizla suzuki motogp \| suzuki \| suzuki gsv-r \| b \| 21 \| john hopkins \| all row 15 : rizla suzuki motogp \| suzuki \| suzuki gsv-r \| b \| 71 \| chris vermeulen \| all row 16 : rizla suzuki motogp \| suzuki \| suzuki gsv-r \| b \| 64 \| kousuke akiyoshi \| 15 row 17 : repsol honda team \| honda \| honda rc211v \| m \| 26 \| dani pedrosa \| all row 18 : repsol honda team \| honda \| honda rc211v \| m \| 69 \| nicky hayden \| all row 19 : honda lcr \| honda \| honda rc211v \| m \| 27 \| casey stoner \| all row 20 : pramac d'antin motogp \| ducati \| ducati desmosedici gp5 \| d \| 30 \| jose luis cardoso \| all row 21 : pramac d'antin motogp \| ducati \| ducati desmosedici gp5 \| d \| 66 \| alex hofmann \| 1-7, 10-11, 13-17 row 22 : pramac d'antin motogp \| ducati \| ducati desmosedici gp5 \| d \| 22 \| ivan silva \| 8-9, 12 row 23 : fortuna honda \| honda \| honda rc211v \| m \| 24 \| toni elias \| 1-8, 10-17 row 24 : fortuna honda \| honda \| honda rc211v \| m \| 33 \| marco melandri \| all row 25 : fortuna honda \| honda \| honda rc211v \| m \| 84 \| michel fabrizio \| 9 row 26 : ilmor srt \| ilmor \| ilmor x3 \| m \| 8 \| garry mccoy \| 16-17	col : count ( "rider" ) row 1 : 11	select count ( rider ) where tyres = 'm' <table_name> : table \begin{tabular}{llllllll} \toprule & team & constructor & motorcycle & tyres & no & rider & rounds \\ \midrule 0 & camel yamaha team & yamaha & yamaha yzr-m1 & m & 5 & colin edwards & all \\ 1 & camel yamaha team & yamaha & yamaha yzr-m1 & m & 46 & valentino rossi & all \\ 2 & konica minolta honda & honda & honda rc211v & m & 6 & makoto tamada & all \\ 3 & tech 3 yamaha & yamaha & yamaha yzr-m1 & d & 7 & carlos checa & all \\ 4 & tech 3 yamaha & yamaha & yamaha yzr-m1 & d & 77 & james ellison & all \\ 5 & team roberts & team roberts & kr211v & m & 10 & kenny roberts, jr & all \\ 6 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 15 & sete gibernau & 1-7, 10-11, 13-16 \\ 7 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 65 & loris capirossi & all \\ 8 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 66 & alex hofmann & 8-9, 12 \\ 9 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 12 & troy bayliss & 17 \\ 10 & kawasaki racing team & kawasaki & kawasaki ninja zx-rr & b & 17 & randy de puniet & all \\ 11 & kawasaki racing team & kawasaki & kawasaki ninja zx-rr & b & 56 & shinya nakano & all \\ 12 & kawasaki racing team & kawasaki & kawasaki ninja zx-rr & b & 8 & naoki matsudo & 15 \\ 13 & rizla suzuki motogp & suzuki & suzuki gsv-r & b & 21 & john hopkins & all \\ 14 & rizla suzuki motogp & suzuki & suzuki gsv-r & b & 71 & chris vermeulen & all \\ 15 & rizla suzuki motogp & suzuki & suzuki gsv-r & b & 64 & kousuke akiyoshi & 15 \\ 16 & repsol honda team & honda & honda rc211v & m & 26 & dani pedrosa & all \\ 17 & repsol honda team & honda & honda rc211v & m & 69 & nicky hayden & all \\ 18 & honda lcr & honda & honda rc211v & m & 27 & casey stoner & all \\ 19 & pramac d'antin motogp & ducati & ducati desmosedici gp5 & d & 30 & jose luis cardoso & all \\ 20 & pramac d'antin motogp & ducati & ducati desmosedici gp5 & d & 66 & alex hofmann & 1-7, 10-11, 13-17 \\ 21 & pramac d'antin motogp & ducati & ducati desmosedici gp5 & d & 22 & ivan silva & 8-9, 12 \\ 22 & fortuna honda & honda & honda rc211v & m & 24 & toni elias & 1-8, 10-17 \\ 23 & fortuna honda & honda & honda rc211v & m & 33 & marco melandri & all \\ 24 & fortuna honda & honda & honda rc211v & m & 84 & michel fabrizio & 9 \\ 25 & ilmor srt & ilmor & ilmor x3 & m & 8 & garry mccoy & 16-17 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "rider" ) \\ \midrule 0 & 11 \\ \bottomrule \end{tabular}	select count ( rider ) where tyres = 'm' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>constructor</th> <th>motorcycle</th> <th>tyres</th> <th>no</th> <th>rider</th> <th>rounds</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>camel yamaha team</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>m</td> <td>5</td> <td>colin edwards</td> <td>all</td> </tr> <tr> <th>1</th> <td>camel yamaha team</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>m</td> <td>46</td> <td>valentino rossi</td> <td>all</td> </tr> <tr> <th>2</th> <td>konica minolta honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>6</td> <td>makoto tamada</td> <td>all</td> </tr> <tr> <th>3</th> <td>tech 3 yamaha</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>d</td> <td>7</td> <td>carlos checa</td> <td>all</td> </tr> <tr> <th>4</th> <td>tech 3 yamaha</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>d</td> <td>77</td> <td>james ellison</td> <td>all</td> </tr> <tr> <th>5</th> <td>team roberts</td> <td>team roberts</td> <td>kr211v</td> <td>m</td> <td>10</td> <td>kenny roberts, jr</td> <td>all</td> </tr> <tr> <th>6</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>15</td> <td>sete gibernau</td> <td>1-7, 10-11, 13-16</td> </tr> <tr> <th>7</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>65</td> <td>loris capirossi</td> <td>all</td> </tr> <tr> <th>8</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>66</td> <td>alex hofmann</td> <td>8-9, 12</td> </tr> <tr> <th>9</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>12</td> <td>troy bayliss</td> <td>17</td> </tr> <tr> <th>10</th> <td>kawasaki racing team</td> <td>kawasaki</td> <td>kawasaki ninja zx-rr</td> <td>b</td> <td>17</td> <td>randy de puniet</td> <td>all</td> </tr> <tr> <th>11</th> <td>kawasaki racing team</td> <td>kawasaki</td> <td>kawasaki ninja zx-rr</td> <td>b</td> <td>56</td> <td>shinya nakano</td> <td>all</td> </tr> <tr> <th>12</th> <td>kawasaki racing team</td> <td>kawasaki</td> <td>kawasaki ninja zx-rr</td> <td>b</td> <td>8</td> <td>naoki matsudo</td> <td>15</td> </tr> <tr> <th>13</th> <td>rizla suzuki motogp</td> <td>suzuki</td> <td>suzuki gsv-r</td> <td>b</td> <td>21</td> <td>john hopkins</td> <td>all</td> </tr> <tr> <th>14</th> <td>rizla suzuki motogp</td> <td>suzuki</td> <td>suzuki gsv-r</td> <td>b</td> <td>71</td> <td>chris vermeulen</td> <td>all</td> </tr> <tr> <th>15</th> <td>rizla suzuki motogp</td> <td>suzuki</td> <td>suzuki gsv-r</td> <td>b</td> <td>64</td> <td>kousuke akiyoshi</td> <td>15</td> </tr> <tr> <th>16</th> <td>repsol honda team</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>26</td> <td>dani pedrosa</td> <td>all</td> </tr> <tr> <th>17</th> <td>repsol honda team</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>69</td> <td>nicky hayden</td> <td>all</td> </tr> <tr> <th>18</th> <td>honda lcr</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>27</td> <td>casey stoner</td> <td>all</td> </tr> <tr> <th>19</th> <td>pramac d'antin motogp</td> <td>ducati</td> <td>ducati desmosedici gp5</td> <td>d</td> <td>30</td> <td>jose luis cardoso</td> <td>all</td> </tr> <tr> <th>20</th> <td>pramac d'antin motogp</td> <td>ducati</td> <td>ducati desmosedici gp5</td> <td>d</td> <td>66</td> <td>alex hofmann</td> <td>1-7, 10-11, 13-17</td> </tr> <tr> <th>21</th> <td>pramac d'antin motogp</td> <td>ducati</td> <td>ducati desmosedici gp5</td> <td>d</td> <td>22</td> <td>ivan silva</td> <td>8-9, 12</td> </tr> <tr> <th>22</th> <td>fortuna honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>24</td> <td>toni elias</td> <td>1-8, 10-17</td> </tr> <tr> <th>23</th> <td>fortuna honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>33</td> <td>marco melandri</td> <td>all</td> </tr> <tr> <th>24</th> <td>fortuna honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>84</td> <td>michel fabrizio</td> <td>9</td> </tr> <tr> <th>25</th> <td>ilmor srt</td> <td>ilmor</td> <td>ilmor x3</td> <td>m</td> <td>8</td> <td>garry mccoy</td> <td>16-17</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "rider" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>11</td> </tr> </tbody> </table>	select count ( rider ) where tyres = 'm' <table_name> : table \| \| team \| constructor \| motorcycle \| tyres \| no \| rider \| rounds \| \|---:\|:----------------------\|:--------------\|:-----------------------\|:--------\|-----:\|:------------------\|:------------------\| \| 0 \| camel yamaha team \| yamaha \| yamaha yzr-m1 \| m \| 5 \| colin edwards \| all \| \| 1 \| camel yamaha team \| yamaha \| yamaha yzr-m1 \| m \| 46 \| valentino rossi \| all \| \| 2 \| konica minolta honda \| honda \| honda rc211v \| m \| 6 \| makoto tamada \| all \| \| 3 \| tech 3 yamaha \| yamaha \| yamaha yzr-m1 \| d \| 7 \| carlos checa \| all \| \| 4 \| tech 3 yamaha \| yamaha \| yamaha yzr-m1 \| d \| 77 \| james ellison \| all \| \| 5 \| team roberts \| team roberts \| kr211v \| m \| 10 \| kenny roberts, jr \| all \| \| 6 \| ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 15 \| sete gibernau \| 1-7, 10-11, 13-16 \| \| 7 \| ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 65 \| loris capirossi \| all \| \| 8 \| ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 66 \| alex hofmann \| 8-9, 12 \| \| 9 \| ducati marlboro team \| ducati \| ducati desmosedici gp6 \| b \| 12 \| troy bayliss \| 17 \| \| 10 \| kawasaki racing team \| kawasaki \| kawasaki ninja zx-rr \| b \| 17 \| randy de puniet \| all \| \| 11 \| kawasaki racing team \| kawasaki \| kawasaki ninja zx-rr \| b \| 56 \| shinya nakano \| all \| \| 12 \| kawasaki racing team \| kawasaki \| kawasaki ninja zx-rr \| b \| 8 \| naoki matsudo \| 15 \| \| 13 \| rizla suzuki motogp \| suzuki \| suzuki gsv-r \| b \| 21 \| john hopkins \| all \| \| 14 \| rizla suzuki motogp \| suzuki \| suzuki gsv-r \| b \| 71 \| chris vermeulen \| all \| \| 15 \| rizla suzuki motogp \| suzuki \| suzuki gsv-r \| b \| 64 \| kousuke akiyoshi \| 15 \| \| 16 \| repsol honda team \| honda \| honda rc211v \| m \| 26 \| dani pedrosa \| all \| \| 17 \| repsol honda team \| honda \| honda rc211v \| m \| 69 \| nicky hayden \| all \| \| 18 \| honda lcr \| honda \| honda rc211v \| m \| 27 \| casey stoner \| all \| \| 19 \| pramac d'antin motogp \| ducati \| ducati desmosedici gp5 \| d \| 30 \| jose luis cardoso \| all \| \| 20 \| pramac d'antin motogp \| ducati \| ducati desmosedici gp5 \| d \| 66 \| alex hofmann \| 1-7, 10-11, 13-17 \| \| 21 \| pramac d'antin motogp \| ducati \| ducati desmosedici gp5 \| d \| 22 \| ivan silva \| 8-9, 12 \| \| 22 \| fortuna honda \| honda \| honda rc211v \| m \| 24 \| toni elias \| 1-8, 10-17 \| \| 23 \| fortuna honda \| honda \| honda rc211v \| m \| 33 \| marco melandri \| all \| \| 24 \| fortuna honda \| honda \| honda rc211v \| m \| 84 \| michel fabrizio \| 9 \| \| 25 \| ilmor srt \| ilmor \| ilmor x3 \| m \| 8 \| garry mccoy \| 16-17 \|	\| \| count ( "rider" ) \| \|---:\|--------------------:\| \| 0 \| 11 \|	[ [ 1, 4025, 1056, 261, 436, 3585, 262, 1625, 13806, 455, 273, 296, 81, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 10035, 1757, 451, 34, 203, 1377, 411, 451, 34, 12316, 1757, 451, 34, 203, 1377, 411, 451, 34, 18313, 280, 13946, 1757, 451, 34, 203, 1377, 411, 451, 34, 4098, 455, 1757, 451, 34, 203, 1377, 411, 451, 34, 2135, 1757, 451, 34, 203, 1377, 411, 451, 34, 1691, 264, 1757, 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select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' col : date \| time \| opponent \| site \| tv \| result \| attendance row 1 : september 5 \| 2:30 p.m \| jackson state \| davis wade stadium • starkville, ms \| espnu \| w 45-7 \| 54232 row 2 : september 12 \| 6:00 p.m \| at auburn \| jordan-hare stadium • auburn, al \| secrn \| l 24-49 \| 85269 row 3 : september 19 \| 6:00 p.m \| at vanderbilt \| vanderbilt stadium • nashville, tn \| secrn \| w 15-3 \| 31840 row 4 : september 26 \| 11:21 a.m \| #7 lsu \| davis wade stadium • starkville, ms \| secn \| l 26-30 \| 53612 row 5 : october 3 \| 6:30 p.m \| #25 georgia tech \| davis wade stadium • starkville, ms \| css \| l 31-42 \| 50035 row 6 : october 10 \| 11:30 a.m \| houston \| davis wade stadium • starkville, ms \| espnu \| l 24-31 \| 48019 row 7 : october 17 \| 11:30 a.m \| at middle tennessee \| johnny "red" floyd stadium • murfreesboro, tn \| espnu \| w 27-6 \| 23882 row 8 : october 24 \| 6:30 p.m \| #1 florida \| davis wade stadium • starkville, ms \| espn \| l 19-29 \| 57178 row 9 : october 31 \| 6:00 p.m \| at kentucky \| commonwealth stadium • lexington, ky \| secrn \| w 31-24 \| 67953 row 10 : november 14 \| 6:00 p.m \| #2 alabama \| davis wade stadium • starkville, ms (rivalry) \| espn \| l 3-31 \| 58103 row 11 : november 21 \| 11:21 a.m \| at arkansas \| war memorial stadium • little rock, ar \| secn \| l 21-42 \| 55634 row 12 : november 28 \| 11:21 a.m \| #25 ole miss \| davis wade stadium • starkville, ms (egg bowl) \| secn \| w 41-27 \| 55365	col : count ( "*" ) row 1 : 1	select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' <table_name> : table \begin{tabular}{llllllll} \toprule & date & time & opponent & site & tv & result & attendance \\ \midrule 0 & september 5 & 2:30 p.m & jackson state & davis wade stadium • starkville, ms & espnu & w 45-7 & 54232 \\ 1 & september 12 & 6:00 p.m & at auburn & jordan-hare stadium • auburn, al & secrn & l 24-49 & 85269 \\ 2 & september 19 & 6:00 p.m & at vanderbilt & vanderbilt stadium • nashville, tn & secrn & w 15-3 & 31840 \\ 3 & september 26 & 11:21 a.m & #7 lsu & davis wade stadium • starkville, ms & secn & l 26-30 & 53612 \\ 4 & october 3 & 6:30 p.m & #25 georgia tech & davis wade stadium • starkville, ms & css & l 31-42 & 50035 \\ 5 & october 10 & 11:30 a.m & houston & davis wade stadium • starkville, ms & espnu & l 24-31 & 48019 \\ 6 & october 17 & 11:30 a.m & at middle tennessee & johnny "red" floyd stadium • murfreesboro, tn & espnu & w 27-6 & 23882 \\ 7 & october 24 & 6:30 p.m & #1 florida & davis wade stadium • starkville, ms & espn & l 19-29 & 57178 \\ 8 & october 31 & 6:00 p.m & at kentucky & commonwealth stadium • lexington, ky & secrn & w 31-24 & 67953 \\ 9 & november 14 & 6:00 p.m & #2 alabama & davis wade stadium • starkville, ms (rivalry) & espn & l 3-31 & 58103 \\ 10 & november 21 & 11:21 a.m & at arkansas & war memorial stadium • little rock, ar & secn & l 21-42 & 55634 \\ 11 & november 28 & 11:21 a.m & #25 ole miss & davis wade stadium • starkville, ms (egg bowl) & secn & w 41-27 & 55365 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>date</th> <th>time</th> <th>opponent</th> <th>site</th> <th>tv</th> <th>result</th> <th>attendance</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>september 5</td> <td>2:30 p.m</td> <td>jackson state</td> <td>davis wade stadium • starkville, ms</td> <td>espnu</td> <td>w 45-7</td> <td>54232</td> </tr> <tr> <th>1</th> <td>september 12</td> <td>6:00 p.m</td> <td>at auburn</td> <td>jordan-hare stadium • auburn, al</td> <td>secrn</td> <td>l 24-49</td> <td>85269</td> </tr> <tr> <th>2</th> <td>september 19</td> <td>6:00 p.m</td> <td>at vanderbilt</td> <td>vanderbilt stadium • nashville, tn</td> <td>secrn</td> <td>w 15-3</td> <td>31840</td> </tr> <tr> <th>3</th> <td>september 26</td> <td>11:21 a.m</td> <td>#7 lsu</td> <td>davis wade stadium • starkville, ms</td> <td>secn</td> <td>l 26-30</td> <td>53612</td> </tr> <tr> <th>4</th> <td>october 3</td> <td>6:30 p.m</td> <td>#25 georgia tech</td> <td>davis wade stadium • starkville, ms</td> <td>css</td> <td>l 31-42</td> <td>50035</td> </tr> <tr> <th>5</th> <td>october 10</td> <td>11:30 a.m</td> <td>houston</td> <td>davis wade stadium • starkville, ms</td> <td>espnu</td> <td>l 24-31</td> <td>48019</td> </tr> <tr> <th>6</th> <td>october 17</td> <td>11:30 a.m</td> <td>at middle tennessee</td> <td>johnny "red" floyd stadium • murfreesboro, tn</td> <td>espnu</td> <td>w 27-6</td> <td>23882</td> </tr> <tr> <th>7</th> <td>october 24</td> <td>6:30 p.m</td> <td>#1 florida</td> <td>davis wade stadium • starkville, ms</td> <td>espn</td> <td>l 19-29</td> <td>57178</td> </tr> <tr> <th>8</th> <td>october 31</td> <td>6:00 p.m</td> <td>at kentucky</td> <td>commonwealth stadium • lexington, ky</td> <td>secrn</td> <td>w 31-24</td> <td>67953</td> </tr> <tr> <th>9</th> <td>november 14</td> <td>6:00 p.m</td> <td>#2 alabama</td> <td>davis wade stadium • starkville, ms (rivalry)</td> <td>espn</td> <td>l 3-31</td> <td>58103</td> </tr> <tr> <th>10</th> <td>november 21</td> <td>11:21 a.m</td> <td>at arkansas</td> <td>war memorial stadium • little rock, ar</td> <td>secn</td> <td>l 21-42</td> <td>55634</td> </tr> <tr> <th>11</th> <td>november 28</td> <td>11:21 a.m</td> <td>#25 ole miss</td> <td>davis wade stadium • starkville, ms (egg bowl)</td> <td>secn</td> <td>w 41-27</td> <td>55365</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' <table_name> : table \| \| date \| time \| opponent \| site \| tv \| result \| attendance \| \|---:\|:-------------\|:----------\|:--------------------\|:-----------------------------------------------\|:------\|:---------\|-------------:\| \| 0 \| september 5 \| 2:30 p.m \| jackson state \| davis wade stadium • starkville, ms \| espnu \| w 45-7 \| 54232 \| \| 1 \| september 12 \| 6:00 p.m \| at auburn \| jordan-hare stadium • auburn, al \| secrn \| l 24-49 \| 85269 \| \| 2 \| september 19 \| 6:00 p.m \| at vanderbilt \| vanderbilt stadium • nashville, tn \| secrn \| w 15-3 \| 31840 \| \| 3 \| september 26 \| 11:21 a.m \| #7 lsu \| davis wade stadium • starkville, ms \| secn \| l 26-30 \| 53612 \| \| 4 \| october 3 \| 6:30 p.m \| #25 georgia tech \| davis wade stadium • starkville, ms \| css \| l 31-42 \| 50035 \| \| 5 \| october 10 \| 11:30 a.m \| houston \| davis wade stadium • starkville, ms \| espnu \| l 24-31 \| 48019 \| \| 6 \| october 17 \| 11:30 a.m \| at middle tennessee \| johnny "red" floyd stadium • murfreesboro, tn \| espnu \| w 27-6 \| 23882 \| \| 7 \| october 24 \| 6:30 p.m \| #1 florida \| davis wade stadium • starkville, ms \| espn \| l 19-29 \| 57178 \| \| 8 \| october 31 \| 6:00 p.m \| at kentucky \| commonwealth stadium • lexington, ky \| secrn \| w 31-24 \| 67953 \| \| 9 \| november 14 \| 6:00 p.m \| #2 alabama \| davis wade stadium • starkville, ms (rivalry) \| espn \| l 3-31 \| 58103 \| \| 10 \| november 21 \| 11:21 a.m \| at arkansas \| war memorial stadium • little rock, ar \| secn \| l 21-42 \| 55634 \| \| 11 \| november 28 \| 11:21 a.m \| #25 ole miss \| davis wade stadium • starkville, ms (egg bowl) \| secn \| w 41-27 \| 55365 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 2834, 273, 296, 20752, 291, 341, 2486, 384, 361, 5077, 225, 163, 227, 100, 384, 1313, 90, 14120, 16, 4086, 261, 86, 5162, 1176, 2506, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 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select count ( parking ) where parking = 'none' col : stations \| connections \| city/ neighborhood \| parking \| date opened row 1 : north hollywood \| metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757 \| north hollywood \| 951 spaces \| october 29, 2005 row 2 : laurel canyon \| metro local: 156, 230, 656 \| valley village \| none \| october 29, 2005 row 3 : valley college \| metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city \| valley glen \| none \| october 29, 2005 row 4 : woodman \| metro local:154, 158 \| valley glen \| none \| october 29, 2005 row 5 : van nuys \| metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798 \| van nuys \| 776 spaces \| october 29, 2005 row 6 : sepulveda \| metro local: 234 metro rapid: 734 \| van nuys \| 1,205 spaces \| october 29, 2005 row 7 : woodley \| metro local:164, 237 \| van nuys \| none \| october 29, 2005 row 8 : balboa \| metro local: 164, 236, 237 ladot commuter express: 573, 574 \| lake balboa \| 270 spaces \| october 29, 2005 row 9 : reseda \| metro rapid: 741 metro local: 240 \| tarzana \| 522 spaces \| october 29, 2005 row 10 : tampa \| metro local: 242 \| tarzana \| none \| october 29, 2005 row 11 : pierce college \| metro local: 164, 243 \| winnetka \| 373 spaces \| october 29, 2005 row 12 : de soto \| metro local: 164, 244 city of santa clarita transit: 796 \| winnetka \| none \| october 29, 2005 row 13 : canoga \| metro local:164, 165 city of santa clarita transit: 796 \| canoga park \| 612 spaces \| december 27, 2006 row 14 : warner center \| metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection \| woodland hills \| none \| october 29, 2005 row 15 : sherman way \| metro local: 162, 163 \| canoga park \| park & ride lot \| june 30, 2012 row 16 : roscoe \| metro local: 152, 353 \| canoga park \| none \| june 30, 2012 row 17 : nordhoff \| metro local: 166, 364 ladot dash northridge \| chatsworth \| none \| june 30, 2012 row 18 : chatsworth \| metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner \| chatsworth \| parking expanded \| june 30, 2012	col : count ( "parking" ) row 1 : 9	select count ( parking ) where parking = 'none' <table_name> : table \begin{tabular}{llllll} \toprule & stations & connections & city/ neighborhood & parking & date opened \\ \midrule 0 & north hollywood & metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757 & north hollywood & 951 spaces & october 29, 2005 \\ 1 & laurel canyon & metro local: 156, 230, 656 & valley village & none & october 29, 2005 \\ 2 & valley college & metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city & valley glen & none & october 29, 2005 \\ 3 & woodman & metro local:154, 158 & valley glen & none & october 29, 2005 \\ 4 & van nuys & metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798 & van nuys & 776 spaces & october 29, 2005 \\ 5 & sepulveda & metro local: 234 metro rapid: 734 & van nuys & 1,205 spaces & october 29, 2005 \\ 6 & woodley & metro local:164, 237 & van nuys & none & october 29, 2005 \\ 7 & balboa & metro local: 164, 236, 237 ladot commuter express: 573, 574 & lake balboa & 270 spaces & october 29, 2005 \\ 8 & reseda & metro rapid: 741 metro local: 240 & tarzana & 522 spaces & october 29, 2005 \\ 9 & tampa & metro local: 242 & tarzana & none & october 29, 2005 \\ 10 & pierce college & metro local: 164, 243 & winnetka & 373 spaces & october 29, 2005 \\ 11 & de soto & metro local: 164, 244 city of santa clarita transit: 796 & winnetka & none & october 29, 2005 \\ 12 & canoga & metro local:164, 165 city of santa clarita transit: 796 & canoga park & 612 spaces & december 27, 2006 \\ 13 & warner center & metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection & woodland hills & none & october 29, 2005 \\ 14 & sherman way & metro local: 162, 163 & canoga park & park & ride lot & june 30, 2012 \\ 15 & roscoe & metro local: 152, 353 & canoga park & none & june 30, 2012 \\ 16 & nordhoff & metro local: 166, 364 ladot dash northridge & chatsworth & none & june 30, 2012 \\ 17 & chatsworth & metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner & chatsworth & parking expanded & june 30, 2012 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "parking" ) \\ \midrule 0 & 9 \\ \bottomrule \end{tabular}	select count ( parking ) where parking = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>stations</th> <th>connections</th> <th>city/ neighborhood</th> <th>parking</th> <th>date opened</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>north hollywood</td> <td>metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757</td> <td>north hollywood</td> <td>951 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>1</th> <td>laurel canyon</td> <td>metro local: 156, 230, 656</td> <td>valley village</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>2</th> <td>valley college</td> <td>metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city</td> <td>valley glen</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>3</th> <td>woodman</td> <td>metro local:154, 158</td> <td>valley glen</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>4</th> <td>van nuys</td> <td>metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798</td> <td>van nuys</td> <td>776 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>5</th> <td>sepulveda</td> <td>metro local: 234 metro rapid: 734</td> <td>van nuys</td> <td>1,205 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>6</th> <td>woodley</td> <td>metro local:164, 237</td> <td>van nuys</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>7</th> <td>balboa</td> <td>metro local: 164, 236, 237 ladot commuter express: 573, 574</td> <td>lake balboa</td> <td>270 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>8</th> <td>reseda</td> <td>metro rapid: 741 metro local: 240</td> <td>tarzana</td> <td>522 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>9</th> <td>tampa</td> <td>metro local: 242</td> <td>tarzana</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>10</th> <td>pierce college</td> <td>metro local: 164, 243</td> <td>winnetka</td> <td>373 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>11</th> <td>de soto</td> <td>metro local: 164, 244 city of santa clarita transit: 796</td> <td>winnetka</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>12</th> <td>canoga</td> <td>metro local:164, 165 city of santa clarita transit: 796</td> <td>canoga park</td> <td>612 spaces</td> <td>december 27, 2006</td> </tr> <tr> <th>13</th> <td>warner center</td> <td>metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection</td> <td>woodland hills</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>14</th> <td>sherman way</td> <td>metro local: 162, 163</td> <td>canoga park</td> <td>park & ride lot</td> <td>june 30, 2012</td> </tr> <tr> <th>15</th> <td>roscoe</td> <td>metro local: 152, 353</td> <td>canoga park</td> <td>none</td> <td>june 30, 2012</td> </tr> <tr> <th>16</th> <td>nordhoff</td> <td>metro local: 166, 364 ladot dash northridge</td> <td>chatsworth</td> <td>none</td> <td>june 30, 2012</td> </tr> <tr> <th>17</th> <td>chatsworth</td> <td>metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner</td> <td>chatsworth</td> <td>parking expanded</td> <td>june 30, 2012</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "parking" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>9</td> </tr> </tbody> </table>	select count ( parking ) where parking = 'none' <table_name> : table \| \| stations \| connections \| city/ neighborhood \| parking \| date opened \| \|---:\|:----------------\|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\|:---------------------\|:-----------------\|:------------------\| \| 0 \| north hollywood \| metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757 \| north hollywood \| 951 spaces \| october 29, 2005 \| \| 1 \| laurel canyon \| metro local: 156, 230, 656 \| valley village \| none \| october 29, 2005 \| \| 2 \| valley college \| metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city \| valley glen \| none \| october 29, 2005 \| \| 3 \| woodman \| metro local:154, 158 \| valley glen \| none \| october 29, 2005 \| \| 4 \| van nuys \| metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798 \| van nuys \| 776 spaces \| october 29, 2005 \| \| 5 \| sepulveda \| metro local: 234 metro rapid: 734 \| van nuys \| 1,205 spaces \| october 29, 2005 \| \| 6 \| woodley \| metro local:164, 237 \| van nuys \| none \| october 29, 2005 \| \| 7 \| balboa \| metro local: 164, 236, 237 ladot commuter express: 573, 574 \| lake balboa \| 270 spaces \| october 29, 2005 \| \| 8 \| reseda \| metro rapid: 741 metro local: 240 \| tarzana \| 522 spaces \| october 29, 2005 \| \| 9 \| tampa \| metro local: 242 \| tarzana \| none \| october 29, 2005 \| \| 10 \| pierce college \| metro local: 164, 243 \| winnetka \| 373 spaces \| october 29, 2005 \| \| 11 \| de soto \| metro local: 164, 244 city of santa clarita transit: 796 \| winnetka \| none \| october 29, 2005 \| \| 12 \| canoga \| metro local:164, 165 city of santa clarita transit: 796 \| canoga park \| 612 spaces \| december 27, 2006 \| \| 13 \| warner center \| metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection \| woodland hills \| none \| october 29, 2005 \| \| 14 \| sherman way \| metro local: 162, 163 \| canoga park \| park & ride lot \| june 30, 2012 \| \| 15 \| roscoe \| metro local: 152, 353 \| canoga park \| none \| june 30, 2012 \| \| 16 \| nordhoff \| metro local: 166, 364 ladot dash northridge \| chatsworth \| none \| june 30, 2012 \| \| 17 \| chatsworth \| metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner \| chatsworth \| parking expanded \| june 30, 2012 \|	\| \| count ( "parking" ) \| \|---:\|----------------------:\| \| 0 \| 9 \|	[ [ 1, 4025, 1056, 261, 779, 79, 310, 262, 1625, 779, 79, 310, 273, 296, 6102, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 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select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' col : award \| category \| recipients and nominees \| result row 1 : 71st academy awards \| best original screenplay \| warren beatty and jeremy pikser \| nominated row 2 : 56th golden globe awards \| best screenplay \| warren beatty and jeremy pikser \| nominated row 3 : 56th golden globe awards \| best picture \| bulworth \| nominated row 4 : 56th golden globe awards \| best actor \| warren beatty \| nominated row 5 : 1998 satellite awards \| best actor \| warren beatty \| nominated row 6 : 1998 writers guild of america awards \| best screenplay \| warren beatty and jeremy pikser \| nominated row 7 : chicago film critics association awards 1998 \| best screenplay \| warren beatty and jeremy pikser \| nominated row 8 : los angeles film critics association \| best screenplay (1998) \| warren beatty and jeremy pikser \| won row 9 : 1998 golden lion awards \| best film \| bulworth \| nominated row 10 : 1999 naacp image awards \| outstanding actress \| halle berry \| nominated row 11 : 1999 naacp image awards \| outstanding supporting actor \| don cheadle \| nominated row 12 : american film institute \| 100 years...100 laughs \| bulworth \| nominated	col : count ( "*" ) row 1 : 5	select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' <table_name> : table \begin{tabular}{lllll} \toprule & award & category & recipients and nominees & result \\ \midrule 0 & 71st academy awards & best original screenplay & warren beatty and jeremy pikser & nominated \\ 1 & 56th golden globe awards & best screenplay & warren beatty and jeremy pikser & nominated \\ 2 & 56th golden globe awards & best picture & bulworth & nominated \\ 3 & 56th golden globe awards & best actor & warren beatty & nominated \\ 4 & 1998 satellite awards & best actor & warren beatty & nominated \\ 5 & 1998 writers guild of america awards & best screenplay & warren beatty and jeremy pikser & nominated \\ 6 & chicago film critics association awards 1998 & best screenplay & warren beatty and jeremy pikser & nominated \\ 7 & los angeles film critics association & best screenplay (1998) & warren beatty and jeremy pikser & won \\ 8 & 1998 golden lion awards & best film & bulworth & nominated \\ 9 & 1999 naacp image awards & outstanding actress & halle berry & nominated \\ 10 & 1999 naacp image awards & outstanding supporting actor & don cheadle & nominated \\ 11 & american film institute & 100 years...100 laughs & bulworth & nominated \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 5 \\ \bottomrule \end{tabular}	select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>award</th> <th>category</th> <th>recipients and nominees</th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>71st academy awards</td> <td>best original screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>1</th> <td>56th golden globe awards</td> <td>best screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>2</th> <td>56th golden globe awards</td> <td>best picture</td> <td>bulworth</td> <td>nominated</td> </tr> <tr> <th>3</th> <td>56th golden globe awards</td> <td>best actor</td> <td>warren beatty</td> <td>nominated</td> </tr> <tr> <th>4</th> <td>1998 satellite awards</td> <td>best actor</td> <td>warren beatty</td> <td>nominated</td> </tr> <tr> <th>5</th> <td>1998 writers guild of america awards</td> <td>best screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>6</th> <td>chicago film critics association awards 1998</td> <td>best screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>7</th> <td>los angeles film critics association</td> <td>best screenplay (1998)</td> <td>warren beatty and jeremy pikser</td> <td>won</td> </tr> <tr> <th>8</th> <td>1998 golden lion awards</td> <td>best film</td> <td>bulworth</td> <td>nominated</td> </tr> <tr> <th>9</th> <td>1999 naacp image awards</td> <td>outstanding actress</td> <td>halle berry</td> <td>nominated</td> </tr> <tr> <th>10</th> <td>1999 naacp image awards</td> <td>outstanding supporting actor</td> <td>don cheadle</td> <td>nominated</td> </tr> <tr> <th>11</th> <td>american film institute</td> <td>100 years...100 laughs</td> <td>bulworth</td> <td>nominated</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>5</td> </tr> </tbody> </table>	select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' <table_name> : table \| \| award \| category \| recipients and nominees \| result \| \|---:\|:---------------------------------------------\|:-----------------------------\|:--------------------------------\|:----------\| \| 0 \| 71st academy awards \| best original screenplay \| warren beatty and jeremy pikser \| nominated \| \| 1 \| 56th golden globe awards \| best screenplay \| warren beatty and jeremy pikser \| nominated \| \| 2 \| 56th golden globe awards \| best picture \| bulworth \| nominated \| \| 3 \| 56th golden globe awards \| best actor \| warren beatty \| nominated \| \| 4 \| 1998 satellite awards \| best actor \| warren beatty \| nominated \| \| 5 \| 1998 writers guild of america awards \| best screenplay \| warren beatty and jeremy pikser \| nominated \| \| 6 \| chicago film critics association awards 1998 \| best screenplay \| warren beatty and jeremy pikser \| nominated \| \| 7 \| los angeles film critics association \| best screenplay (1998) \| warren beatty and jeremy pikser \| won \| \| 8 \| 1998 golden lion awards \| best film \| bulworth \| nominated \| \| 9 \| 1999 naacp image awards \| outstanding actress \| halle berry \| nominated \| \| 10 \| 1999 naacp image awards \| outstanding supporting actor \| don cheadle \| nominated \| \| 11 \| american film institute \| 100 years...100 laughs \| bulworth \| nominated \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 5 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 12045, 471, 12457, 558, 281, 273, 296, 905, 1187, 23795, 4098, 471, 525, 264, 351, 93, 293, 1766, 550, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 69, 2913, 1757, 451, 34, 203, 1377, 411, 451, 34, 4743, 1757, 451, 34, 203, 1377, 411, 451, 34, 27925, 471, 12457, 558, 281, 1757, 451, 34, 203, 1377, 411, 451, 34, 2088, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 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select count ( * ) where office ended = 1939 col : # \| name \| birth and death \| office started \| office ended row 1 : 1 \| geir vidalin \| 27 october 1761 - 20 september 1823 \| 1801 \| 1823 row 2 : 2 \| steingrimur jonsson \| none \| 1824 \| 1845 row 3 : 3 \| helgi thordersen \| 8 april 1794 - 4 december 1867 \| 1846 \| 1866 row 4 : 4 \| 'petur petursson \| 3 october 1808 - 15 may 1891 \| 1866 \| 1889 row 5 : 5 \| hallgrimur sveinsson \| 5 april 1841 - 16 december 1909 \| 1889 \| 1908 row 6 : 6 \| þorhallur bjarnarson \| 2 december 1855 - 15 december 1916 \| 1908 \| 1916 row 7 : 7 \| jon helgason \| 1866 - 1942 \| 1917 \| 1939 row 8 : 8 \| sigurgeir sigurðsson \| 3 august 1890 - 13 october 1953 \| 1939 \| 1953 row 9 : 9 \| asmundur guðmundsson \| 6 october 1888 reykholt - 29 may 1969 reykjavik \| 1954 \| 1989 row 10 : 10 \| sigurbjorn einarsson \| 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik \| 1959 \| 1981 row 11 : 11 \| petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) \| 2 june 1919 - 3 june 2010 \| 1981 \| 1989 row 12 : 12 \| olafur skulason \| 29 december 1929 - 9 june 2008 \| 1989 \| 1997 row 13 : 13 \| karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) \| 5 february 1947 reykjavik \| 1998 \| 2012 row 14 : 14 \| agnes sigurðardottir \| 19 october 1954 isafjorður \| 24 june 2012 \| incumbent	col : count ( "*" ) row 1 : 1	select count ( * ) where office ended = 1939 <table_name> : table \begin{tabular}{llllll} \toprule & # & name & birth and death & office started & office ended \\ \midrule 0 & 1 & geir vidalin & 27 october 1761 - 20 september 1823 & 1801 & 1823 \\ 1 & 2 & steingrimur jonsson & none & 1824 & 1845 \\ 2 & 3 & helgi thordersen & 8 april 1794 - 4 december 1867 & 1846 & 1866 \\ 3 & 4 & 'petur petursson & 3 october 1808 - 15 may 1891 & 1866 & 1889 \\ 4 & 5 & hallgrimur sveinsson & 5 april 1841 - 16 december 1909 & 1889 & 1908 \\ 5 & 6 & þorhallur bjarnarson & 2 december 1855 - 15 december 1916 & 1908 & 1916 \\ 6 & 7 & jon helgason & 1866 - 1942 & 1917 & 1939 \\ 7 & 8 & sigurgeir sigurðsson & 3 august 1890 - 13 october 1953 & 1939 & 1953 \\ 8 & 9 & asmundur guðmundsson & 6 october 1888 reykholt - 29 may 1969 reykjavik & 1954 & 1989 \\ 9 & 10 & sigurbjorn einarsson & 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik & 1959 & 1981 \\ 10 & 11 & petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) & 2 june 1919 - 3 june 2010 & 1981 & 1989 \\ 11 & 12 & olafur skulason & 29 december 1929 - 9 june 2008 & 1989 & 1997 \\ 12 & 13 & karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) & 5 february 1947 reykjavik & 1998 & 2012 \\ 13 & 14 & agnes sigurðardottir & 19 october 1954 isafjorður & 24 june 2012 & incumbent \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where office ended = 1939 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>name</th> <th>birth and death</th> <th>office started</th> <th>office ended</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>geir vidalin</td> <td>27 october 1761 - 20 september 1823</td> <td>1801</td> <td>1823</td> </tr> <tr> <th>1</th> <td>2</td> <td>steingrimur jonsson</td> <td>none</td> <td>1824</td> <td>1845</td> </tr> <tr> <th>2</th> <td>3</td> <td>helgi thordersen</td> <td>8 april 1794 - 4 december 1867</td> <td>1846</td> <td>1866</td> </tr> <tr> <th>3</th> <td>4</td> <td>'petur petursson</td> <td>3 october 1808 - 15 may 1891</td> <td>1866</td> <td>1889</td> </tr> <tr> <th>4</th> <td>5</td> <td>hallgrimur sveinsson</td> <td>5 april 1841 - 16 december 1909</td> <td>1889</td> <td>1908</td> </tr> <tr> <th>5</th> <td>6</td> <td>þorhallur bjarnarson</td> <td>2 december 1855 - 15 december 1916</td> <td>1908</td> <td>1916</td> </tr> <tr> <th>6</th> <td>7</td> <td>jon helgason</td> <td>1866 - 1942</td> <td>1917</td> <td>1939</td> </tr> <tr> <th>7</th> <td>8</td> <td>sigurgeir sigurðsson</td> <td>3 august 1890 - 13 october 1953</td> <td>1939</td> <td>1953</td> </tr> <tr> <th>8</th> <td>9</td> <td>asmundur guðmundsson</td> <td>6 october 1888 reykholt - 29 may 1969 reykjavik</td> <td>1954</td> <td>1989</td> </tr> <tr> <th>9</th> <td>10</td> <td>sigurbjorn einarsson</td> <td>30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik</td> <td>1959</td> <td>1981</td> </tr> <tr> <th>10</th> <td>11</td> <td>petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland)</td> <td>2 june 1919 - 3 june 2010</td> <td>1981</td> <td>1989</td> </tr> <tr> <th>11</th> <td>12</td> <td>olafur skulason</td> <td>29 december 1929 - 9 june 2008</td> <td>1989</td> <td>1997</td> </tr> <tr> <th>12</th> <td>13</td> <td>karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland)</td> <td>5 february 1947 reykjavik</td> <td>1998</td> <td>2012</td> </tr> <tr> <th>13</th> <td>14</td> <td>agnes sigurðardottir</td> <td>19 october 1954 isafjorður</td> <td>24 june 2012</td> <td>incumbent</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where office ended = 1939 <table_name> : table \| \| # \| name \| birth and death \| office started \| office ended \| \|---:\|----:\|:--------------------------------------------------------------------------\|:----------------------------------------------------------------\|:-----------------\|:---------------\| \| 0 \| 1 \| geir vidalin \| 27 october 1761 - 20 september 1823 \| 1801 \| 1823 \| \| 1 \| 2 \| steingrimur jonsson \| none \| 1824 \| 1845 \| \| 2 \| 3 \| helgi thordersen \| 8 april 1794 - 4 december 1867 \| 1846 \| 1866 \| \| 3 \| 4 \| 'petur petursson \| 3 october 1808 - 15 may 1891 \| 1866 \| 1889 \| \| 4 \| 5 \| hallgrimur sveinsson \| 5 april 1841 - 16 december 1909 \| 1889 \| 1908 \| \| 5 \| 6 \| þorhallur bjarnarson \| 2 december 1855 - 15 december 1916 \| 1908 \| 1916 \| \| 6 \| 7 \| jon helgason \| 1866 - 1942 \| 1917 \| 1939 \| \| 7 \| 8 \| sigurgeir sigurðsson \| 3 august 1890 - 13 october 1953 \| 1939 \| 1953 \| \| 8 \| 9 \| asmundur guðmundsson \| 6 october 1888 reykholt - 29 may 1969 reykjavik \| 1954 \| 1989 \| \| 9 \| 10 \| sigurbjorn einarsson \| 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik \| 1959 \| 1981 \| \| 10 \| 11 \| petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) \| 2 june 1919 - 3 june 2010 \| 1981 \| 1989 \| \| 11 \| 12 \| olafur skulason \| 29 december 1929 - 9 june 2008 \| 1989 \| 1997 \| \| 12 \| 13 \| karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) \| 5 february 1947 reykjavik \| 1998 \| 2012 \| \| 13 \| 14 \| agnes sigurðardottir \| 19 october 1954 isafjorður \| 24 june 2012 \| incumbent \|	\| \| count ( "*" 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select count ( event ) where year > 15 col : year \| competition \| venue \| position \| event row 1 : 1997 \| world indoor championships \| paris, france \| 5th \| 60 m hurdles row 2 : 1997 \| usa outdoor championships \| indianapolis, united states \| 1st \| 100 m hurdles row 3 : 1998 \| grand prix final \| moscow, russia \| 2nd \| 100 m hurdles row 4 : 1998 \| usa indoor championships \| none \| 1st \| 60 m hurdles row 5 : 1999 \| world indoor championships \| maebashi, japan \| 6th \| 60 m hurdles row 6 : 2000 \| olympic games \| sydney, australia \| 3rd \| 100 m hurdles row 7 : 2000 \| grand prix final \| doha, qatar \| 4th \| 100 m hurdles row 8 : 2002 \| grand prix final \| paris, france \| 7th \| 100 m hurdles row 9 : 2002 \| usa indoor championships \| none \| 1st \| 60 m hurdles row 10 : 2003 \| world indoor championships \| birmingham, england \| 3rd \| 60 m hurdles row 11 : 2003 \| world athletics final \| monaco \| 6th \| 100 m hurdles row 12 : 2004 \| olympic games \| athens, greece \| 3rd \| 100 m hurdles	col : count ( "event" ) row 1 : 12	select count ( event ) where year > 15 <table_name> : table \begin{tabular}{llllll} \toprule & year & competition & venue & position & event \\ \midrule 0 & 1997 & world indoor championships & paris, france & 5th & 60 m hurdles \\ 1 & 1997 & usa outdoor championships & indianapolis, united states & 1st & 100 m hurdles \\ 2 & 1998 & grand prix final & moscow, russia & 2nd & 100 m hurdles \\ 3 & 1998 & usa indoor championships & none & 1st & 60 m hurdles \\ 4 & 1999 & world indoor championships & maebashi, japan & 6th & 60 m hurdles \\ 5 & 2000 & olympic games & sydney, australia & 3rd & 100 m hurdles \\ 6 & 2000 & grand prix final & doha, qatar & 4th & 100 m hurdles \\ 7 & 2002 & grand prix final & paris, france & 7th & 100 m hurdles \\ 8 & 2002 & usa indoor championships & none & 1st & 60 m hurdles \\ 9 & 2003 & world indoor championships & birmingham, england & 3rd & 60 m hurdles \\ 10 & 2003 & world athletics final & monaco & 6th & 100 m hurdles \\ 11 & 2004 & olympic games & athens, greece & 3rd & 100 m hurdles \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "event" ) \\ \midrule 0 & 12 \\ \bottomrule \end{tabular}	select count ( event ) where year > 15 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1997</td> <td>world indoor championships</td> <td>paris, france</td> <td>5th</td> <td>60 m hurdles</td> </tr> <tr> <th>1</th> <td>1997</td> <td>usa outdoor championships</td> <td>indianapolis, united states</td> <td>1st</td> <td>100 m hurdles</td> </tr> <tr> <th>2</th> <td>1998</td> <td>grand prix final</td> <td>moscow, russia</td> <td>2nd</td> <td>100 m hurdles</td> </tr> <tr> <th>3</th> <td>1998</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>4</th> <td>1999</td> <td>world indoor championships</td> <td>maebashi, japan</td> <td>6th</td> <td>60 m hurdles</td> </tr> <tr> <th>5</th> <td>2000</td> <td>olympic games</td> <td>sydney, australia</td> <td>3rd</td> <td>100 m hurdles</td> </tr> <tr> <th>6</th> <td>2000</td> <td>grand prix final</td> <td>doha, qatar</td> <td>4th</td> <td>100 m hurdles</td> </tr> <tr> <th>7</th> <td>2002</td> <td>grand prix final</td> <td>paris, france</td> <td>7th</td> <td>100 m hurdles</td> </tr> <tr> <th>8</th> <td>2002</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>9</th> <td>2003</td> <td>world indoor championships</td> <td>birmingham, england</td> <td>3rd</td> <td>60 m hurdles</td> </tr> <tr> <th>10</th> <td>2003</td> <td>world athletics final</td> <td>monaco</td> <td>6th</td> <td>100 m hurdles</td> </tr> <tr> <th>11</th> <td>2004</td> <td>olympic games</td> <td>athens, greece</td> <td>3rd</td> <td>100 m hurdles</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "event" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>12</td> </tr> </tbody> </table>	select count ( event ) where year > 15 <table_name> : table \| \| year \| competition \| venue \| position \| event \| \|---:\|-------:\|:---------------------------\|:----------------------------\|:-----------\|:--------------\| \| 0 \| 1997 \| world indoor championships \| paris, france \| 5th \| 60 m hurdles \| \| 1 \| 1997 \| usa outdoor championships \| indianapolis, united states \| 1st \| 100 m hurdles \| \| 2 \| 1998 \| grand prix final \| moscow, russia \| 2nd \| 100 m hurdles \| \| 3 \| 1998 \| usa indoor championships \| none \| 1st \| 60 m hurdles \| \| 4 \| 1999 \| world indoor championships \| maebashi, japan \| 6th \| 60 m hurdles \| \| 5 \| 2000 \| olympic games \| sydney, australia \| 3rd \| 100 m hurdles \| \| 6 \| 2000 \| grand prix final \| doha, qatar \| 4th \| 100 m 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select count ( * ) where established = '16 january 1978' col : ecclesiastical jurisdictions \| latin name \| type \| rite \| ecclesiastical province \| established \| area (km2) row 1 : bani \| baniensis \| diocese \| roman \| santo domingo \| 8 november 1986 \| 2892 row 2 : barahona \| barahonensis \| diocese \| roman \| santo domingo \| 24 april 1976 \| 6973 row 3 : dominican republic \| reipublicae dominicanae \| military ordinariate \| roman \| immediately subject to the holy see \| 23 january 1958 \| none row 4 : la vega \| vegensis \| diocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 4919 row 5 : mao-monte cristi \| maoensis-montis christi \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 4841 row 6 : nuestra senora de la altagracia en higuey \| higueyensis / a domina nostra vulgo de la altagracia in higuey \| diocese \| roman \| santo domingo \| 1 april 1959 \| 5437 row 7 : puerto plata \| portus argentarii \| diocese \| roman \| santiago de los caballeros \| 16 december 1996 \| 2700 row 8 : san francisco de macoris \| sancti francisci de macoris \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 3682 row 9 : san juan de la maguana \| sancti ioannis maguanensis \| diocese \| roman \| santo domingo \| 25 september 1953 \| 7476 row 10 : san pedro de macoris \| sancti petri de macoris \| diocese \| roman \| santo domingo \| 1 february 1997 \| 2588 row 11 : santiago de los caballeros \| sancti iacobi equitum \| metropolitan archdiocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 6391 row 12 : santo domingo \| sancti dominici \| metropolitan archdiocese \| roman \| santo domingo \| 8 august 1511 \| 4033	col : count ( "*" ) row 1 : 2	select count ( * ) where established = '16 january 1978' <table_name> : table \begin{tabular}{llllllll} \toprule & ecclesiastical jurisdictions & latin name & type & rite & ecclesiastical province & established & area (km2) \\ \midrule 0 & bani & baniensis & diocese & roman & santo domingo & 8 november 1986 & 2892 \\ 1 & barahona & barahonensis & diocese & roman & santo domingo & 24 april 1976 & 6973 \\ 2 & dominican republic & reipublicae dominicanae & military ordinariate & roman & immediately subject to the holy see & 23 january 1958 & none \\ 3 & la vega & vegensis & diocese & roman & santiago de los caballeros & 25 september 1953 & 4919 \\ 4 & mao-monte cristi & maoensis-montis christi & diocese & roman & santiago de los caballeros & 16 january 1978 & 4841 \\ 5 & nuestra senora de la altagracia en higuey & higueyensis / a domina nostra vulgo de la altagracia in higuey & diocese & roman & santo domingo & 1 april 1959 & 5437 \\ 6 & puerto plata & portus argentarii & diocese & roman & santiago de los caballeros & 16 december 1996 & 2700 \\ 7 & san francisco de macoris & sancti francisci de macoris & diocese & roman & santiago de los caballeros & 16 january 1978 & 3682 \\ 8 & san juan de la maguana & sancti ioannis maguanensis & diocese & roman & santo domingo & 25 september 1953 & 7476 \\ 9 & san pedro de macoris & sancti petri de macoris & diocese & roman & santo domingo & 1 february 1997 & 2588 \\ 10 & santiago de los caballeros & sancti iacobi equitum & metropolitan archdiocese & roman & santiago de los caballeros & 25 september 1953 & 6391 \\ 11 & santo domingo & sancti dominici & metropolitan archdiocese & roman & santo domingo & 8 august 1511 & 4033 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 2 \\ \bottomrule \end{tabular}	select count ( * ) where established = '16 january 1978' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>ecclesiastical jurisdictions</th> <th>latin name</th> <th>type</th> <th>rite</th> <th>ecclesiastical province</th> <th>established</th> <th>area (km2)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>bani</td> <td>baniensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>8 november 1986</td> <td>2892</td> </tr> <tr> <th>1</th> <td>barahona</td> <td>barahonensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>24 april 1976</td> <td>6973</td> </tr> <tr> <th>2</th> <td>dominican republic</td> <td>reipublicae dominicanae</td> <td>military ordinariate</td> <td>roman</td> <td>immediately subject to the holy see</td> <td>23 january 1958</td> <td>none</td> </tr> <tr> <th>3</th> <td>la vega</td> <td>vegensis</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>4919</td> </tr> <tr> <th>4</th> <td>mao-monte cristi</td> <td>maoensis-montis christi</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>4841</td> </tr> <tr> <th>5</th> <td>nuestra senora de la altagracia en higuey</td> <td>higueyensis / a domina nostra vulgo de la altagracia in higuey</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 april 1959</td> <td>5437</td> </tr> <tr> <th>6</th> <td>puerto plata</td> <td>portus argentarii</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 december 1996</td> <td>2700</td> </tr> <tr> <th>7</th> <td>san francisco de macoris</td> <td>sancti francisci de macoris</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>3682</td> </tr> <tr> <th>8</th> <td>san juan de la maguana</td> <td>sancti ioannis maguanensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>25 september 1953</td> <td>7476</td> </tr> <tr> <th>9</th> <td>san pedro de macoris</td> <td>sancti petri de macoris</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 february 1997</td> <td>2588</td> </tr> <tr> <th>10</th> <td>santiago de los caballeros</td> <td>sancti iacobi equitum</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>6391</td> </tr> <tr> <th>11</th> <td>santo domingo</td> <td>sancti dominici</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santo domingo</td> <td>8 august 1511</td> <td>4033</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> </tbody> </table>	select count ( * ) where established = '16 january 1978' <table_name> : table \| \| ecclesiastical jurisdictions \| latin name \| type \| rite \| ecclesiastical province \| established \| area (km2) \| \|---:\|:------------------------------------------\|:---------------------------------------------------------------\|:-------------------------\|:-------\|:------------------------------------\|:------------------\|:-------------\| \| 0 \| bani \| baniensis \| diocese \| roman \| santo domingo \| 8 november 1986 \| 2892 \| \| 1 \| barahona \| barahonensis \| diocese \| roman \| santo domingo \| 24 april 1976 \| 6973 \| \| 2 \| dominican republic \| reipublicae dominicanae \| military ordinariate \| roman \| immediately subject to the holy see \| 23 january 1958 \| none \| \| 3 \| la vega \| vegensis \| diocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 4919 \| \| 4 \| mao-monte cristi \| maoensis-montis christi \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 4841 \| \| 5 \| nuestra senora de la altagracia en higuey \| higueyensis / a domina nostra vulgo de la altagracia in higuey \| diocese \| roman \| santo domingo \| 1 april 1959 \| 5437 \| \| 6 \| puerto plata \| portus argentarii \| diocese \| roman \| santiago de los caballeros \| 16 december 1996 \| 2700 \| \| 7 \| san francisco de macoris \| sancti francisci de macoris \| diocese \| roman \| santiago de los caballeros \| 16 january 1978 \| 3682 \| \| 8 \| san juan de la maguana \| sancti ioannis maguanensis \| diocese \| roman \| santo domingo \| 25 september 1953 \| 7476 \| \| 9 \| san pedro de macoris \| sancti petri de macoris \| diocese \| roman \| santo domingo \| 1 february 1997 \| 2588 \| \| 10 \| santiago de los caballeros \| sancti iacobi equitum \| metropolitan archdiocese \| roman \| santiago de los caballeros \| 25 september 1953 \| 6391 \| \| 11 \| santo domingo \| sancti dominici \| metropolitan archdiocese \| roman \| santo domingo \| 8 august 1511 \| 4033 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 2 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 19703, 273, 296, 2313, 525, 304, 24335, 5342, 8285, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 557, 9558, 77, 689, 1706, 525, 23510, 72, 2228, 87, 1757, 451, 34, 203, 1377, 411, 451, 34, 26578, 508, 1757, 451, 34, 203, 1377, 411, 451, 34, 723, 1757, 451, 34, 203, 1377, 411, 451, 34, 796, 1757, 451, 34, 203, 1377, 411, 451, 34, 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select count ( * ) where position = '3rd' col : year \| competition \| venue \| position \| event \| notes row 1 : 1979 \| grandma's marathon \| duluth, united states \| 1st \| marathon \| 2:37:37 row 2 : 1980 \| grandma's marathon \| duluth, united states \| 1st \| marathon \| 2:38:35 row 3 : 1981 \| grandma's marathon \| duluth, united states \| 1st \| marathon \| 2:29:35 row 4 : 1984 \| boston marathon \| boston, united states \| 1st \| marathon \| 2:29:28 row 5 : 1984 \| olympic games \| los angeles, united states \| 5th \| marathon \| 2:28:54 row 6 : 1986 \| osaka ladies marathon \| osaka, japan \| 1st \| marathon \| 2:30:24 row 7 : 1986 \| commonwealth games \| edinburgh, scotland \| 2nd \| marathon \| 2:28:17 row 8 : 1987 \| osaka ladies marathon \| osaka, japan \| 1st \| marathon \| 2:30:40 row 9 : 1987 \| world championships \| rome, italy \| 21st \| 10,000 m \| 34:07.26 row 10 : 1988 \| olympic games \| seoul, south korea \| 33rd \| marathon \| 2:37:52 row 11 : 1989 \| osaka ladies marathon \| osaka, japan \| 1st \| marathon \| 2:30:21 row 12 : 1989 \| hokkaido marathon \| sapporo, japan \| 1st \| marathon \| 2:36:39 row 13 : 1991 \| hokkaido marathon \| sapporo, japan \| 1st \| marathon \| 2:33:20 row 14 : 1992 \| olympic games \| barcelona, spain \| 3rd \| marathon \| 2:33:59 row 15 : 1996 \| olympic games \| atlanta, united states \| 46th \| marathon \| 2:42:21	col : count ( "*" ) row 1 : 1	select count ( * ) where position = '3rd' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 1979 & grandma's marathon & duluth, united states & 1st & marathon & 2:37:37 \\ 1 & 1980 & grandma's marathon & duluth, united states & 1st & marathon & 2:38:35 \\ 2 & 1981 & grandma's marathon & duluth, united states & 1st & marathon & 2:29:35 \\ 3 & 1984 & boston marathon & boston, united states & 1st & marathon & 2:29:28 \\ 4 & 1984 & olympic games & los angeles, united states & 5th & marathon & 2:28:54 \\ 5 & 1986 & osaka ladies marathon & osaka, japan & 1st & marathon & 2:30:24 \\ 6 & 1986 & commonwealth games & edinburgh, scotland & 2nd & marathon & 2:28:17 \\ 7 & 1987 & osaka ladies marathon & osaka, japan & 1st & marathon & 2:30:40 \\ 8 & 1987 & world championships & rome, italy & 21st & 10,000 m & 34:07.26 \\ 9 & 1988 & olympic games & seoul, south korea & 33rd & marathon & 2:37:52 \\ 10 & 1989 & osaka ladies marathon & osaka, japan & 1st & marathon & 2:30:21 \\ 11 & 1989 & hokkaido marathon & sapporo, japan & 1st & marathon & 2:36:39 \\ 12 & 1991 & hokkaido marathon & sapporo, japan & 1st & marathon & 2:33:20 \\ 13 & 1992 & olympic games & barcelona, spain & 3rd & marathon & 2:33:59 \\ 14 & 1996 & olympic games & atlanta, united states & 46th & marathon & 2:42:21 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where position = '3rd' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1979</td> <td>grandma's marathon</td> <td>duluth, united states</td> <td>1st</td> <td>marathon</td> <td>2:37:37</td> </tr> <tr> <th>1</th> <td>1980</td> <td>grandma's marathon</td> <td>duluth, united states</td> <td>1st</td> <td>marathon</td> <td>2:38:35</td> </tr> <tr> <th>2</th> <td>1981</td> <td>grandma's marathon</td> <td>duluth, united states</td> <td>1st</td> <td>marathon</td> <td>2:29:35</td> </tr> <tr> <th>3</th> <td>1984</td> <td>boston marathon</td> <td>boston, united states</td> <td>1st</td> <td>marathon</td> <td>2:29:28</td> </tr> <tr> <th>4</th> <td>1984</td> <td>olympic games</td> <td>los angeles, united states</td> <td>5th</td> <td>marathon</td> <td>2:28:54</td> </tr> <tr> <th>5</th> <td>1986</td> <td>osaka ladies marathon</td> <td>osaka, japan</td> <td>1st</td> <td>marathon</td> <td>2:30:24</td> </tr> <tr> <th>6</th> <td>1986</td> <td>commonwealth games</td> <td>edinburgh, scotland</td> <td>2nd</td> <td>marathon</td> <td>2:28:17</td> </tr> <tr> <th>7</th> <td>1987</td> <td>osaka ladies marathon</td> <td>osaka, japan</td> <td>1st</td> <td>marathon</td> <td>2:30:40</td> </tr> <tr> <th>8</th> <td>1987</td> <td>world championships</td> <td>rome, italy</td> <td>21st</td> <td>10,000 m</td> <td>34:07.26</td> </tr> <tr> <th>9</th> <td>1988</td> <td>olympic games</td> <td>seoul, south korea</td> <td>33rd</td> <td>marathon</td> <td>2:37:52</td> </tr> <tr> <th>10</th> <td>1989</td> <td>osaka ladies marathon</td> <td>osaka, japan</td> <td>1st</td> <td>marathon</td> <td>2:30:21</td> </tr> <tr> <th>11</th> <td>1989</td> <td>hokkaido marathon</td> <td>sapporo, japan</td> <td>1st</td> <td>marathon</td> <td>2:36:39</td> </tr> <tr> <th>12</th> <td>1991</td> <td>hokkaido marathon</td> <td>sapporo, japan</td> <td>1st</td> <td>marathon</td> <td>2:33:20</td> </tr> <tr> <th>13</th> <td>1992</td> <td>olympic games</td> <td>barcelona, spain</td> <td>3rd</td> <td>marathon</td> <td>2:33:59</td> </tr> <tr> <th>14</th> <td>1996</td> <td>olympic games</td> <td>atlanta, united states</td> <td>46th</td> <td>marathon</td> <td>2:42:21</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where position = '3rd' <table_name> : table \| \| year \| competition \| venue \| position \| event \| notes \| \|---:\|-------:\|:----------------------\|:---------------------------\|:-----------\|:---------\|:---------\| \| 0 \| 1979 \| grandma's marathon \| duluth, united states \| 1st \| marathon \| 2:37:37 \| \| 1 \| 1980 \| grandma's marathon \| duluth, united states \| 1st \| marathon \| 2:38:35 \| \| 2 \| 1981 \| grandma's marathon \| duluth, united states \| 1st \| marathon \| 2:29:35 \| \| 3 \| 1984 \| boston marathon \| boston, united states \| 1st \| marathon \| 2:29:28 \| \| 4 \| 1984 \| olympic games \| los angeles, united states \| 5th \| marathon \| 2:28:54 \| \| 5 \| 1986 \| osaka ladies marathon \| osaka, japan \| 1st \| marathon \| 2:30:24 \| \| 6 \| 1986 \| commonwealth games \| edinburgh, scotland \| 2nd \| marathon \| 2:28:17 \| \| 7 \| 1987 \| osaka ladies marathon \| osaka, japan \| 1st \| marathon \| 2:30:40 \| \| 8 \| 1987 \| world championships \| rome, italy \| 21st \| 10,000 m \| 34:07.26 \| \| 9 \| 1988 \| olympic games \| seoul, south korea \| 33rd \| marathon \| 2:37:52 \| \| 10 \| 1989 \| osaka ladies marathon \| osaka, japan \| 1st \| marathon \| 2:30:21 \| \| 11 \| 1989 \| hokkaido marathon \| sapporo, japan \| 1st \| marathon \| 2:36:39 \| \| 12 \| 1991 \| hokkaido marathon \| sapporo, japan \| 1st \| marathon \| 2:33:20 \| \| 13 \| 1992 \| olympic games \| barcelona, spain \| 3rd \| marathon \| 2:33:59 \| \| 14 \| 1996 \| olympic games \| 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select nation where nation = 'north korea (prk)' col : rank \| nation \| gold \| silver \| bronze \| total row 1 : 1 \| china (chn) \| 127 \| 63 \| 33 \| 223 row 2 : 2 \| japan (jpn) \| 46 \| 56 \| 77 \| 179 row 3 : 3 \| south korea (kor) \| 32 \| 48 \| 65 \| 145 row 4 : 4 \| chinese taipei (tpe) \| 12 \| 34 \| 26 \| 72 row 5 : 5 \| macau (mac) \| 11 \| 16 \| 17 \| 44 row 6 : 6 \| north korea (prk) \| 6 \| 10 \| 20 \| 36 row 7 : 7 \| hong kong (hkg) \| 2 \| 2 \| 9 \| 13 row 8 : 8 \| mongolia (mgl) \| 1 \| 1 \| 6 \| 8 row 9 : 9 \| guam (gum) \| 0 \| 0 \| 1 \| 1 row 10 : total \| total \| 237 \| 230 \| 254 \| 721	col : nation row 1 : north korea (prk)	select nation where nation = 'north korea (prk)' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & china (chn) & 127 & 63 & 33 & 223 \\ 1 & 2 & japan (jpn) & 46 & 56 & 77 & 179 \\ 2 & 3 & south korea (kor) & 32 & 48 & 65 & 145 \\ 3 & 4 & chinese taipei (tpe) & 12 & 34 & 26 & 72 \\ 4 & 5 & macau (mac) & 11 & 16 & 17 & 44 \\ 5 & 6 & north korea (prk) & 6 & 10 & 20 & 36 \\ 6 & 7 & hong kong (hkg) & 2 & 2 & 9 & 13 \\ 7 & 8 & mongolia (mgl) & 1 & 1 & 6 & 8 \\ 8 & 9 & guam (gum) & 0 & 0 & 1 & 1 \\ 9 & total & total & 237 & 230 & 254 & 721 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & north korea (prk) \\ \bottomrule \end{tabular}	select nation where nation = 'north korea (prk)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>china (chn)</td> <td>127</td> <td>63</td> <td>33</td> <td>223</td> </tr> <tr> <th>1</th> <td>2</td> <td>japan (jpn)</td> <td>46</td> <td>56</td> <td>77</td> <td>179</td> </tr> <tr> <th>2</th> <td>3</td> <td>south korea (kor)</td> <td>32</td> <td>48</td> <td>65</td> <td>145</td> </tr> <tr> <th>3</th> <td>4</td> <td>chinese taipei (tpe)</td> <td>12</td> <td>34</td> <td>26</td> <td>72</td> </tr> <tr> <th>4</th> <td>5</td> <td>macau (mac)</td> <td>11</td> <td>16</td> <td>17</td> <td>44</td> </tr> <tr> <th>5</th> <td>6</td> <td>north korea (prk)</td> <td>6</td> <td>10</td> <td>20</td> <td>36</td> </tr> <tr> <th>6</th> <td>7</td> <td>hong kong (hkg)</td> <td>2</td> <td>2</td> <td>9</td> <td>13</td> </tr> <tr> <th>7</th> <td>8</td> <td>mongolia (mgl)</td> <td>1</td> <td>1</td> <td>6</td> <td>8</td> </tr> <tr> <th>8</th> <td>9</td> <td>guam (gum)</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>9</th> <td>total</td> <td>total</td> <td>237</td> <td>230</td> <td>254</td> <td>721</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>north korea (prk)</td> </tr> </tbody> </table>	select nation where nation = 'north korea (prk)' <table_name> : table \| \| rank \| nation \| gold \| silver \| bronze \| total \| \|---:\|:-------\|:---------------------\|-------:\|---------:\|---------:\|--------:\| \| 0 \| 1 \| china (chn) \| 127 \| 63 \| 33 \| 223 \| \| 1 \| 2 \| japan (jpn) \| 46 \| 56 \| 77 \| 179 \| \| 2 \| 3 \| south korea (kor) \| 32 \| 48 \| 65 \| 145 \| \| 3 \| 4 \| chinese taipei (tpe) \| 12 \| 34 \| 26 \| 72 \| \| 4 \| 5 \| macau (mac) \| 11 \| 16 \| 17 \| 44 \| \| 5 \| 6 \| north korea (prk) \| 6 \| 10 \| 20 \| 36 \| \| 6 \| 7 \| hong kong (hkg) \| 2 \| 2 \| 9 \| 13 \| \| 7 \| 8 \| mongolia (mgl) \| 1 \| 1 \| 6 \| 8 \| \| 8 \| 9 \| guam (gum) \| 0 \| 0 \| 1 \| 1 \| \| 9 \| total \| total \| 237 \| 230 \| 254 \| 721 \|	\| \| nation \| \|---:\|:------------------\| \| 0 \| north korea (prk) \|	[ [ 1, 4025, 290, 367, 1625, 290, 367, 273, 296, 82, 7825, 417, 479, 69, 261, 683, 79, 2506, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 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select year where engine = 'honda' col : year \| chassis \| engine \| start \| finish \| team row 1 : 2001 \| dallara \| oldsmobile \| 11 \| 1 \| team penske row 2 : 2002 \| dallara \| chevrolet \| 13 \| 1 \| team penske row 3 : 2003 \| dallara \| toyota \| 1 \| 2 \| team penske row 4 : 2004 \| dallara \| toyota \| 8 \| 9 \| team penske row 5 : 2005 \| dallara \| toyota \| 5 \| 9 \| team penske row 6 : 2006 \| dallara \| honda \| 2 \| 25 \| team penske row 7 : 2007 \| dallara \| honda \| 1 \| 3 \| team penske row 8 : 2008 \| dallara \| honda \| 4 \| 4 \| team penske row 9 : 2009 \| dallara \| honda \| 1 \| 1 \| team penske row 10 : 2010 \| dallara \| honda \| 1 \| 9 \| team penske row 11 : 2011 \| dallara \| honda \| 16 \| 17 \| team penske row 12 : 2012 \| dallara \| chevrolet \| 6 \| 10 \| team penske row 13 : 2013 \| dallara \| chevrolet \| 8 \| 6 \| team penske	col : year row 1 : 2006 row 2 : 2007 row 3 : 2008 row 4 : 2009 row 5 : 2010 row 6 : 2011	select year where engine = 'honda' <table_name> : table \begin{tabular}{lllllll} \toprule & year & chassis & engine & start & finish & team \\ \midrule 0 & 2001 & dallara & oldsmobile & 11 & 1 & team penske \\ 1 & 2002 & dallara & chevrolet & 13 & 1 & team penske \\ 2 & 2003 & dallara & toyota & 1 & 2 & team penske \\ 3 & 2004 & dallara & toyota & 8 & 9 & team penske \\ 4 & 2005 & dallara & toyota & 5 & 9 & team penske \\ 5 & 2006 & dallara & honda & 2 & 25 & team penske \\ 6 & 2007 & dallara & honda & 1 & 3 & team penske \\ 7 & 2008 & dallara & honda & 4 & 4 & team penske \\ 8 & 2009 & dallara & honda & 1 & 1 & team penske \\ 9 & 2010 & dallara & honda & 1 & 9 & team penske \\ 10 & 2011 & dallara & honda & 16 & 17 & team penske \\ 11 & 2012 & dallara & chevrolet & 6 & 10 & team penske \\ 12 & 2013 & dallara & chevrolet & 8 & 6 & team penske \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 2006 \\ 1 & 2007 \\ 2 & 2008 \\ 3 & 2009 \\ 4 & 2010 \\ 5 & 2011 \\ \bottomrule \end{tabular}	select year where engine = 'honda' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>chassis</th> <th>engine</th> <th>start</th> <th>finish</th> <th>team</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2001</td> <td>dallara</td> <td>oldsmobile</td> <td>11</td> <td>1</td> <td>team penske</td> </tr> <tr> <th>1</th> <td>2002</td> <td>dallara</td> <td>chevrolet</td> <td>13</td> <td>1</td> <td>team penske</td> </tr> <tr> <th>2</th> <td>2003</td> <td>dallara</td> <td>toyota</td> <td>1</td> <td>2</td> <td>team penske</td> </tr> <tr> <th>3</th> <td>2004</td> <td>dallara</td> <td>toyota</td> <td>8</td> <td>9</td> <td>team penske</td> </tr> <tr> <th>4</th> <td>2005</td> <td>dallara</td> <td>toyota</td> <td>5</td> <td>9</td> <td>team penske</td> </tr> <tr> <th>5</th> <td>2006</td> <td>dallara</td> <td>honda</td> <td>2</td> <td>25</td> <td>team penske</td> </tr> <tr> <th>6</th> <td>2007</td> <td>dallara</td> <td>honda</td> <td>1</td> <td>3</td> <td>team penske</td> </tr> <tr> <th>7</th> <td>2008</td> <td>dallara</td> <td>honda</td> <td>4</td> <td>4</td> <td>team penske</td> </tr> <tr> <th>8</th> <td>2009</td> <td>dallara</td> <td>honda</td> <td>1</td> <td>1</td> <td>team penske</td> </tr> <tr> <th>9</th> <td>2010</td> <td>dallara</td> <td>honda</td> <td>1</td> <td>9</td> <td>team penske</td> </tr> <tr> <th>10</th> <td>2011</td> <td>dallara</td> <td>honda</td> <td>16</td> <td>17</td> <td>team penske</td> </tr> <tr> <th>11</th> <td>2012</td> <td>dallara</td> <td>chevrolet</td> <td>6</td> <td>10</td> <td>team penske</td> </tr> <tr> <th>12</th> <td>2013</td> <td>dallara</td> <td>chevrolet</td> <td>8</td> <td>6</td> <td>team penske</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2006</td> </tr> <tr> <th>1</th> <td>2007</td> </tr> <tr> <th>2</th> <td>2008</td> </tr> <tr> <th>3</th> <td>2009</td> </tr> <tr> <th>4</th> <td>2010</td> </tr> <tr> <th>5</th> <td>2011</td> </tr> </tbody> </table>	select year where engine = 'honda' <table_name> : table \| \| year \| chassis \| engine \| start \| finish \| team \| \|---:\|-------:\|:----------\|:-----------\|--------:\|---------:\|:------------\| \| 0 \| 2001 \| dallara \| oldsmobile \| 11 \| 1 \| team penske \| \| 1 \| 2002 \| dallara \| chevrolet \| 13 \| 1 \| team penske \| \| 2 \| 2003 \| dallara \| toyota \| 1 \| 2 \| team penske \| \| 3 \| 2004 \| dallara \| toyota \| 8 \| 9 \| team penske \| \| 4 \| 2005 \| dallara \| toyota \| 5 \| 9 \| team penske \| \| 5 \| 2006 \| dallara \| honda \| 2 \| 25 \| team penske \| \| 6 \| 2007 \| dallara \| honda \| 1 \| 3 \| team penske \| \| 7 \| 2008 \| dallara \| honda \| 4 \| 4 \| team penske \| \| 8 \| 2009 \| dallara \| honda \| 1 \| 1 \| team penske \| \| 9 \| 2010 \| dallara \| honda \| 1 \| 9 \| team penske \| \| 10 \| 2011 \| dallara \| honda \| 16 \| 17 \| 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select count ( date ) where location = 'lake louise, canada' col : season \| date \| location \| discipline \| place row 1 : 2012 \| 2011-12-02 00:00:00 \| lake louise, canada \| downhill \| 2nd row 2 : 2012 \| 2012-01-28 00:00:00 \| st. moritz, switzerland \| downhill \| 3rd row 3 : 2012 \| 2012-02-04 00:00:00 \| garmisch, germany \| downhill \| 3rd row 4 : 2012 \| 2012-02-05 00:00:00 \| garmisch, germany \| super-g \| 3rd row 5 : 2012 \| 2012-02-26 00:00:00 \| bansko, bulgaria \| super-g \| 2nd row 6 : 2013 \| 2012-11-30 00:00:00 \| lake louise, canada \| downhill \| 3rd row 7 : 2013 \| 2013-03-01 00:00:00 \| garmisch, germany \| super-g \| 1st row 8 : 2014 \| 2013-11-29 00:00:00 \| beaver creek, usa \| downhill \| 2nd row 9 : 2014 \| 2013-12-01 00:00:00 \| beaver creek, usa \| giant slalom \| 3rd row 10 : 2014 \| 2013-12-07 00:00:00 \| lake louise, canada \| downhill \| 2nd row 11 : 2014 \| 2013-12-08 00:00:00 \| lake louise, canada \| super-g \| 2nd row 12 : 2014 \| 2013-12-14 00:00:00 \| st. moritz, switzerland \| super-g \| 1st row 13 : 2014 \| 2013-12-22 00:00:00 \| val-d'isere, france \| giant slalom \| 1st row 14 : 2014 \| 2014-01-24 00:00:00 \| cortina d'ampezzo, italy \| downhill \| 2nd row 15 : 2014 \| 2014-01-25 00:00:00 \| cortina d'ampezzo, italy \| downhill \| 3rd row 16 : 2014 \| 2014-01-26 00:00:00 \| cortina d'ampezzo, italy \| super-g \| 2nd	col : count ( "date" ) row 1 : 4	select count ( date ) where location = 'lake louise, canada' <table_name> : table \begin{tabular}{llllll} \toprule & season & date & location & discipline & place \\ \midrule 0 & 2012 & 2011-12-02 00:00:00 & lake louise, canada & downhill & 2nd \\ 1 & 2012 & 2012-01-28 00:00:00 & st. moritz, switzerland & downhill & 3rd \\ 2 & 2012 & 2012-02-04 00:00:00 & garmisch, germany & downhill & 3rd \\ 3 & 2012 & 2012-02-05 00:00:00 & garmisch, germany & super-g & 3rd \\ 4 & 2012 & 2012-02-26 00:00:00 & bansko, bulgaria & super-g & 2nd \\ 5 & 2013 & 2012-11-30 00:00:00 & lake louise, canada & downhill & 3rd \\ 6 & 2013 & 2013-03-01 00:00:00 & garmisch, germany & super-g & 1st \\ 7 & 2014 & 2013-11-29 00:00:00 & beaver creek, usa & downhill & 2nd \\ 8 & 2014 & 2013-12-01 00:00:00 & beaver creek, usa & giant slalom & 3rd \\ 9 & 2014 & 2013-12-07 00:00:00 & lake louise, canada & downhill & 2nd \\ 10 & 2014 & 2013-12-08 00:00:00 & lake louise, canada & super-g & 2nd \\ 11 & 2014 & 2013-12-14 00:00:00 & st. moritz, switzerland & super-g & 1st \\ 12 & 2014 & 2013-12-22 00:00:00 & val-d'isere, france & giant slalom & 1st \\ 13 & 2014 & 2014-01-24 00:00:00 & cortina d'ampezzo, italy & downhill & 2nd \\ 14 & 2014 & 2014-01-25 00:00:00 & cortina d'ampezzo, italy & downhill & 3rd \\ 15 & 2014 & 2014-01-26 00:00:00 & cortina d'ampezzo, italy & super-g & 2nd \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "date" ) \\ \midrule 0 & 4 \\ \bottomrule \end{tabular}	select count ( date ) where location = 'lake louise, canada' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>date</th> <th>location</th> <th>discipline</th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2012</td> <td>2011-12-02 00:00:00</td> <td>lake louise, canada</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>1</th> <td>2012</td> <td>2012-01-28 00:00:00</td> <td>st. moritz, switzerland</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>2</th> <td>2012</td> <td>2012-02-04 00:00:00</td> <td>garmisch, germany</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>3</th> <td>2012</td> <td>2012-02-05 00:00:00</td> <td>garmisch, germany</td> <td>super-g</td> <td>3rd</td> </tr> <tr> <th>4</th> <td>2012</td> <td>2012-02-26 00:00:00</td> <td>bansko, bulgaria</td> <td>super-g</td> <td>2nd</td> </tr> <tr> <th>5</th> <td>2013</td> <td>2012-11-30 00:00:00</td> <td>lake louise, canada</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>6</th> <td>2013</td> <td>2013-03-01 00:00:00</td> <td>garmisch, germany</td> <td>super-g</td> <td>1st</td> </tr> <tr> <th>7</th> <td>2014</td> <td>2013-11-29 00:00:00</td> <td>beaver creek, usa</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>8</th> <td>2014</td> <td>2013-12-01 00:00:00</td> <td>beaver creek, usa</td> <td>giant slalom</td> <td>3rd</td> </tr> <tr> <th>9</th> <td>2014</td> <td>2013-12-07 00:00:00</td> <td>lake louise, canada</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>10</th> <td>2014</td> <td>2013-12-08 00:00:00</td> <td>lake louise, canada</td> <td>super-g</td> <td>2nd</td> </tr> <tr> <th>11</th> <td>2014</td> <td>2013-12-14 00:00:00</td> <td>st. moritz, switzerland</td> <td>super-g</td> <td>1st</td> </tr> <tr> <th>12</th> <td>2014</td> <td>2013-12-22 00:00:00</td> <td>val-d'isere, france</td> <td>giant slalom</td> <td>1st</td> </tr> <tr> <th>13</th> <td>2014</td> <td>2014-01-24 00:00:00</td> <td>cortina d'ampezzo, italy</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>14</th> <td>2014</td> <td>2014-01-25 00:00:00</td> <td>cortina d'ampezzo, italy</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>15</th> <td>2014</td> <td>2014-01-26 00:00:00</td> <td>cortina d'ampezzo, italy</td> <td>super-g</td> <td>2nd</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "date" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>4</td> </tr> </tbody> </table>	select count ( date ) where location = 'lake louise, canada' <table_name> : table \| \| season \| date \| location \| discipline \| place \| \|---:\|---------:\|:--------------------\|:-------------------------\|:-------------\|:--------\| \| 0 \| 2012 \| 2011-12-02 00:00:00 \| lake louise, canada \| downhill \| 2nd \| \| 1 \| 2012 \| 2012-01-28 00:00:00 \| st. moritz, switzerland \| downhill \| 3rd \| \| 2 \| 2012 \| 2012-02-04 00:00:00 \| garmisch, germany \| downhill \| 3rd \| \| 3 \| 2012 \| 2012-02-05 00:00:00 \| garmisch, germany \| super-g \| 3rd \| \| 4 \| 2012 \| 2012-02-26 00:00:00 \| bansko, bulgaria \| super-g \| 2nd \| \| 5 \| 2013 \| 2012-11-30 00:00:00 \| lake louise, canada \| downhill \| 3rd \| \| 6 \| 2013 \| 2013-03-01 00:00:00 \| garmisch, germany \| super-g \| 1st \| \| 7 \| 2014 \| 2013-11-29 00:00:00 \| beaver creek, usa \| downhill \| 2nd \| \| 8 \| 2014 \| 2013-12-01 00:00:00 \| beaver creek, usa \| giant slalom \| 3rd \| \| 9 \| 2014 \| 2013-12-07 00:00:00 \| lake louise, canada \| downhill \| 2nd \| \| 10 \| 2014 \| 2013-12-08 00:00:00 \| lake louise, canada \| super-g \| 2nd \| \| 11 \| 2014 \| 2013-12-14 00:00:00 \| st. moritz, switzerland \| super-g \| 1st \| \| 12 \| 2014 \| 2013-12-22 00:00:00 \| val-d'isere, france \| giant slalom \| 1st \| \| 13 \| 2014 \| 2014-01-24 00:00:00 \| cortina d'ampezzo, italy \| downhill \| 2nd \| \| 14 \| 2014 \| 2014-01-25 00:00:00 \| cortina d'ampezzo, italy \| downhill \| 3rd \| \| 15 \| 2014 \| 2014-01-26 00:00:00 \| cortina d'ampezzo, italy \| super-g \| 2nd \|	\| \| count ( "date" ) \| 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select count ( * ) where latest public release date (edition) > 323 col : part \| number \| first public release date (first edition) \| latest public release date (edition) \| latest amendment \| title \| description row 1 : part 1 \| iso/iec 15938-1 \| 2002 \| 2002 \| 2006 \| systems \| the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim) row 2 : part 2 \| iso/iec 15938-2 \| 2002 \| 2002 \| none \| description definition language \| none row 3 : part 3 \| iso/iec 15938-3 \| 2002 \| 2002 \| 2010 \| visual \| none row 4 : part 4 \| iso/iec 15938-4 \| 2002 \| 2002 \| 2006 \| audio \| none row 5 : part 5 \| iso/iec 15938-5 \| 2003 \| 2003 \| 2008 \| multimedia description schemes \| none row 6 : part 6 \| iso/iec 15938-6 \| 2003 \| 2003 \| 2010 (2011) \| reference software \| none row 7 : part 7 \| iso/iec 15938-7 \| 2003 \| 2003 \| 2010 (2011) \| conformance testing \| none row 8 : part 8 \| iso/iec tr 15938-8 \| 2002 \| 2002 \| 2010 \| extraction and use of mpeg-7 descriptions \| none row 9 : part 9 \| iso/iec 15938-9 \| 2005 \| 2005 \| (2011) \| profiles and levels \| none row 10 : part 10 \| iso/iec 15938-10 \| 2005 \| 2005 \| none \| schema definition \| none row 11 : part 11 \| iso/iec tr 15938-11 \| 2005 \| 2005 \| none \| mpeg-7 profile schemas \| none row 12 : part 12 \| iso/iec 15938-12 \| 2008 \| 2008 \| (2011) \| query format \| none	col : count ( "*" ) row 1 : 0	select count ( * ) where latest public release date (edition) > 323 <table_name> : table \begin{tabular}{llllllll} \toprule & part & number & first public release date (first edition) & latest public release date (edition) & latest amendment & title & description \\ \midrule 0 & part 1 & iso/iec 15938-1 & 2002 & 2002 & 2006 & systems & the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim) \\ 1 & part 2 & iso/iec 15938-2 & 2002 & 2002 & none & description definition language & none \\ 2 & part 3 & iso/iec 15938-3 & 2002 & 2002 & 2010 & visual & none \\ 3 & part 4 & iso/iec 15938-4 & 2002 & 2002 & 2006 & audio & none \\ 4 & part 5 & iso/iec 15938-5 & 2003 & 2003 & 2008 & multimedia description schemes & none \\ 5 & part 6 & iso/iec 15938-6 & 2003 & 2003 & 2010 (2011) & reference software & none \\ 6 & part 7 & iso/iec 15938-7 & 2003 & 2003 & 2010 (2011) & conformance testing & none \\ 7 & part 8 & iso/iec tr 15938-8 & 2002 & 2002 & 2010 & extraction and use of mpeg-7 descriptions & none \\ 8 & part 9 & iso/iec 15938-9 & 2005 & 2005 & (2011) & profiles and levels & none \\ 9 & part 10 & iso/iec 15938-10 & 2005 & 2005 & none & schema definition & none \\ 10 & part 11 & iso/iec tr 15938-11 & 2005 & 2005 & none & mpeg-7 profile schemas & none \\ 11 & part 12 & iso/iec 15938-12 & 2008 & 2008 & (2011) & query format & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where latest public release date (edition) > 323 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>part</th> <th>number</th> <th>first public release date (first edition)</th> <th>latest public release date (edition)</th> <th>latest amendment</th> <th>title</th> <th>description</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>part 1</td> <td>iso/iec 15938-1</td> <td>2002</td> <td>2002</td> <td>2006</td> <td>systems</td> <td>the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim)</td> </tr> <tr> <th>1</th> <td>part 2</td> <td>iso/iec 15938-2</td> <td>2002</td> <td>2002</td> <td>none</td> <td>description definition language</td> <td>none</td> </tr> <tr> <th>2</th> <td>part 3</td> <td>iso/iec 15938-3</td> <td>2002</td> <td>2002</td> <td>2010</td> <td>visual</td> <td>none</td> </tr> <tr> <th>3</th> <td>part 4</td> <td>iso/iec 15938-4</td> <td>2002</td> <td>2002</td> <td>2006</td> <td>audio</td> <td>none</td> </tr> <tr> <th>4</th> <td>part 5</td> <td>iso/iec 15938-5</td> <td>2003</td> <td>2003</td> <td>2008</td> <td>multimedia description schemes</td> <td>none</td> </tr> <tr> <th>5</th> <td>part 6</td> <td>iso/iec 15938-6</td> <td>2003</td> <td>2003</td> <td>2010 (2011)</td> <td>reference software</td> <td>none</td> </tr> <tr> <th>6</th> <td>part 7</td> <td>iso/iec 15938-7</td> <td>2003</td> <td>2003</td> <td>2010 (2011)</td> <td>conformance testing</td> <td>none</td> </tr> <tr> <th>7</th> <td>part 8</td> <td>iso/iec tr 15938-8</td> <td>2002</td> <td>2002</td> <td>2010</td> <td>extraction and use of mpeg-7 descriptions</td> <td>none</td> </tr> <tr> <th>8</th> <td>part 9</td> <td>iso/iec 15938-9</td> <td>2005</td> <td>2005</td> <td>(2011)</td> <td>profiles and levels</td> <td>none</td> </tr> <tr> <th>9</th> <td>part 10</td> <td>iso/iec 15938-10</td> <td>2005</td> <td>2005</td> <td>none</td> <td>schema definition</td> <td>none</td> </tr> <tr> <th>10</th> <td>part 11</td> <td>iso/iec tr 15938-11</td> <td>2005</td> <td>2005</td> <td>none</td> <td>mpeg-7 profile schemas</td> <td>none</td> </tr> <tr> <th>11</th> <td>part 12</td> <td>iso/iec 15938-12</td> <td>2008</td> <td>2008</td> <td>(2011)</td> <td>query format</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where latest public release date (edition) > 323 <table_name> : table \| \| part \| number \| first public release date (first edition) \| latest public release date (edition) \| latest amendment \| title \| description \| \|---:\|:--------\|:--------------------\|--------------------------------------------:\|---------------------------------------:\|:-------------------\|:------------------------------------------\|:------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| part 1 \| iso/iec 15938-1 \| 2002 \| 2002 \| 2006 \| systems \| the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim) \| \| 1 \| part 2 \| iso/iec 15938-2 \| 2002 \| 2002 \| none \| description definition language \| none \| \| 2 \| part 3 \| iso/iec 15938-3 \| 2002 \| 2002 \| 2010 \| visual \| none \| \| 3 \| part 4 \| iso/iec 15938-4 \| 2002 \| 2002 \| 2006 \| audio \| none \| \| 4 \| part 5 \| iso/iec 15938-5 \| 2003 \| 2003 \| 2008 \| multimedia description schemes \| none \| \| 5 \| part 6 \| iso/iec 15938-6 \| 2003 \| 2003 \| 2010 (2011) \| reference software \| none \| \| 6 \| part 7 \| iso/iec 15938-7 \| 2003 \| 2003 \| 2010 (2011) \| conformance testing \| none \| \| 7 \| part 8 \| iso/iec tr 15938-8 \| 2002 \| 2002 \| 2010 \| extraction and use of mpeg-7 descriptions \| none \| \| 8 \| part 9 \| iso/iec 15938-9 \| 2005 \| 2005 \| (2011) \| profiles and levels \| none \| \| 9 \| part 10 \| iso/iec 15938-10 \| 2005 \| 2005 \| none \| schema definition \| none \| \| 10 \| part 11 \| iso/iec tr 15938-11 \| 2005 \| 2005 \| none \| mpeg-7 profile schemas \| none \| \| 11 \| part 12 \| iso/iec 15938-12 \| 2008 \| 2008 \| (2011) \| query format \| none \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 4891, 1071, 3992, 1509, 261, 329, 608, 13, 405, 3847, 23, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 2680, 1757, 451, 34, 203, 1377, 411, 451, 34, 2696, 1757, 451, 34, 203, 1377, 411, 451, 34, 3645, 1071, 3992, 1509, 261, 3645, 28432, 13, 1757, 451, 34, 203, 1377, 411, 451, 34, 13550, 1071, 3992, 1509, 261, 329, 608, 13, 1757, 451, 34, 203, 1377, 411, 451, 34, 13550, 2125, 409, 475, 1757, 451, 34, 203, 1377, 411, 451, 34, 2649, 1757, 451, 34, 203, 1377, 411, 451, 34, 3384, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 2680, 404, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 9699, 19, 77, 557, 4711, 29, 7414, 17, 21, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6976, 22, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6976, 22, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6976, 26, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 4299, 87, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 5787, 6637, 15004, 3766, 8257, 434, 312, 9001, 17, 27, 16, 326, 5926, 27935, 434, 312, 9001, 17, 27, 913, 300, 1022, 261, 955, 1462, 740, 364, 312, 9001, 17, 27, 13, 471, 326, 3112, 740, 364, 312, 9001, 17, 27, 15550, 261, 70, 381, 13, 1757, 4465, 34, 203, 565, 7765, 313, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 21, 1757, 451, 34, 203, 1377, 411, 4465, 34, 2680, 576, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 9699, 19, 77, 557, 4711, 29, 7414, 17, 22, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6976, 22, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6976, 22, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6102, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 3384, 2379, 2653, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6102, 1757, 4465, 34, 203, 565, 7765, 313, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 22, 1757, 451, 34, 203, 1377, 411, 4465, 34, 2680, 890, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 9699, 19, 77, 557, 4711, 29, 7414, 17, 23, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 6976, 22, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 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select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' col : year \| laureate(s) \| citizenship \| institution \| citation row 1 : 2003 \| jean-pierre serre \| french \| college de france \| "for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory" row 2 : 2004 \| michael atiyah isadore singer \| british american \| university of edinburgh massachusetts institute of technology \| "for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics" row 3 : 2005 \| peter lax \| american \| courant institute \| "for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions" row 4 : 2006 \| lennart carleson \| swedish \| royal institute of technology \| "for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems" row 5 : 2007 \| s. r. srinivasa varadhan \| indian/american \| courant institute \| "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation" row 6 : 2008 \| john g. thompson jacques tits \| american belgian/french \| university of florida college de france \| "for their profound achievements in algebra and in particular for shaping modern group theory" row 7 : 2009 \| mikhail gromov \| russian/french \| institut des hautes etudes scientifiques courant institute \| "for his revolutionary contributions to geometry" row 8 : 2010 \| john t. tate \| american \| university of texas at austin \| "for his vast and lasting impact on the theory of numbers" row 9 : 2011 \| john milnor \| american \| stony brook university \| "for pioneering discoveries in topology, geometry, and algebra" row 10 : 2012 \| endre szemeredi \| hungarian/american \| alfred renyi institute and rutgers university \| "for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory" row 11 : 2013 \| pierre deligne \| belgian \| institute for advanced study \| "for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields" row 12 : 2014 \| yakov g. sinai \| russian/american \| landau institute for theoretical physics and princeton university \| "for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics"	col : count ( "citizenship" ) row 1 : 1	select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' <table_name> : table \begin{tabular}{llllll} \toprule & year & laureate(s) & citizenship & institution & citation \\ \midrule 0 & 2003 & jean-pierre serre & french & college de france & "for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory" \\ 1 & 2004 & michael atiyah isadore singer & british american & university of edinburgh massachusetts institute of technology & "for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics" \\ 2 & 2005 & peter lax & american & courant institute & "for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions" \\ 3 & 2006 & lennart carleson & swedish & royal institute of technology & "for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems" \\ 4 & 2007 & s. r. srinivasa varadhan & indian/american & courant institute & "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation" \\ 5 & 2008 & john g. thompson jacques tits & american belgian/french & university of florida college de france & "for their profound achievements in algebra and in particular for shaping modern group theory" \\ 6 & 2009 & mikhail gromov & russian/french & institut des hautes etudes scientifiques courant institute & "for his revolutionary contributions to geometry" \\ 7 & 2010 & john t. tate & american & university of texas at austin & "for his vast and lasting impact on the theory of numbers" \\ 8 & 2011 & john milnor & american & stony brook university & "for pioneering discoveries in topology, geometry, and algebra" \\ 9 & 2012 & endre szemeredi & hungarian/american & alfred renyi institute and rutgers university & "for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory" \\ 10 & 2013 & pierre deligne & belgian & institute for advanced study & "for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields" \\ 11 & 2014 & yakov g. sinai & russian/american & landau institute for theoretical physics and princeton university & "for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics" \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "citizenship" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>laureate(s)</th> <th>citizenship</th> <th>institution</th> <th>citation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2003</td> <td>jean-pierre serre</td> <td>french</td> <td>college de france</td> <td>"for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory"</td> </tr> <tr> <th>1</th> <td>2004</td> <td>michael atiyah isadore singer</td> <td>british american</td> <td>university of edinburgh massachusetts institute of technology</td> <td>"for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics"</td> </tr> <tr> <th>2</th> <td>2005</td> <td>peter lax</td> <td>american</td> <td>courant institute</td> <td>"for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions"</td> </tr> <tr> <th>3</th> <td>2006</td> <td>lennart carleson</td> <td>swedish</td> <td>royal institute of technology</td> <td>"for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems"</td> </tr> <tr> <th>4</th> <td>2007</td> <td>s. r. srinivasa varadhan</td> <td>indian/american</td> <td>courant institute</td> <td>"for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation"</td> </tr> <tr> <th>5</th> <td>2008</td> <td>john g. thompson jacques tits</td> <td>american belgian/french</td> <td>university of florida college de france</td> <td>"for their profound achievements in algebra and in particular for shaping modern group theory"</td> </tr> <tr> <th>6</th> <td>2009</td> <td>mikhail gromov</td> <td>russian/french</td> <td>institut des hautes etudes scientifiques courant institute</td> <td>"for his revolutionary contributions to geometry"</td> </tr> <tr> <th>7</th> <td>2010</td> <td>john t. tate</td> <td>american</td> <td>university of texas at austin</td> <td>"for his vast and lasting impact on the theory of numbers"</td> </tr> <tr> <th>8</th> <td>2011</td> <td>john milnor</td> <td>american</td> <td>stony brook university</td> <td>"for pioneering discoveries in topology, geometry, and algebra"</td> </tr> <tr> <th>9</th> <td>2012</td> <td>endre szemeredi</td> <td>hungarian/american</td> <td>alfred renyi institute and rutgers university</td> <td>"for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory"</td> </tr> <tr> <th>10</th> <td>2013</td> <td>pierre deligne</td> <td>belgian</td> <td>institute for advanced study</td> <td>"for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields"</td> </tr> <tr> <th>11</th> <td>2014</td> <td>yakov g. sinai</td> <td>russian/american</td> <td>landau institute for theoretical physics and princeton university</td> <td>"for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics"</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "citizenship" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' <table_name> : table \| \| year \| laureate(s) \| citizenship \| institution \| citation \| \|---:\|-------:\|:------------------------------\|:------------------------\|:------------------------------------------------------------------\|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 2003 \| jean-pierre serre \| french \| college de france \| "for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory" \| \| 1 \| 2004 \| michael atiyah isadore singer \| british american \| university of edinburgh massachusetts institute of technology \| "for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics" \| \| 2 \| 2005 \| peter lax \| american \| courant institute \| "for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions" \| \| 3 \| 2006 \| lennart carleson \| swedish \| royal institute of technology \| "for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems" \| \| 4 \| 2007 \| s. r. srinivasa varadhan \| indian/american \| courant institute \| "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation" \| \| 5 \| 2008 \| john g. thompson jacques tits \| american belgian/french \| university of florida college de france \| "for their profound achievements in algebra and in particular for shaping modern group theory" \| \| 6 \| 2009 \| mikhail gromov \| russian/french \| institut des hautes etudes scientifiques courant institute \| "for his revolutionary contributions to geometry" \| \| 7 \| 2010 \| john t. tate \| american \| university of texas at austin \| "for his vast and lasting impact on the theory of numbers" \| \| 8 \| 2011 \| john milnor \| american \| stony brook university \| "for pioneering discoveries in topology, geometry, and algebra" \| \| 9 \| 2012 \| endre szemeredi \| hungarian/american \| alfred renyi institute and rutgers university \| "for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory" \| \| 10 \| 2013 \| pierre deligne \| belgian \| institute for advanced study \| "for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields" \| \| 11 \| 2014 \| yakov g. sinai \| russian/american \| landau institute for theoretical physics and princeton university \| "for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics" \|	\| \| count ( "citizenship" ) \| \|---:\|--------------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 276, 305, 452, 275, 3261, 262, 1625, 7125, 594, 340, 12, 87, 13, 273, 296, 87, 18, 436, 18, 9133, 267, 427, 345, 69, 569, 361, 25842, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 11821, 594, 340, 12, 87, 13, 1757, 451, 34, 203, 1377, 411, 451, 34, 71, 305, 452, 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select count ( place ) where tier = 4 col : season \| tier \| division \| place row 1 : 1928-84 \| 5 \| regional \| none row 2 : 1984/85 \| 4 \| 3a \| 6th row 3 : 1985/86 \| 4 \| 3a \| 9th row 4 : 1986/87 \| 4 \| 3a \| 11th row 5 : 1987/88 \| 4 \| 3a \| 15th row 6 : 1988/89 \| 4 \| 3a \| 4th row 7 : 1989/90 \| 4 \| 3a \| 9th row 8 : 1990/91 \| 4 \| 3a \| 9th row 9 : 1991/92 \| 4 \| 3a \| 5th row 10 : 1992/93 \| 4 \| 3a \| 17th row 11 : 1993/94 \| 4 \| 3a \| 7th row 12 : 1994/95 \| 4 \| 3a \| 4th row 13 : 1995/96 \| 4 \| 3a \| 1st row 14 : 1996/97 \| 3 \| 2ab \| 19th row 15 : 1997/98 \| 4 \| 3a \| 2nd	col : count ( "place" ) row 1 : 13	select count ( place ) where tier = 4 <table_name> : table \begin{tabular}{lllll} \toprule & season & tier & division & place \\ \midrule 0 & 1928-84 & 5 & regional & none \\ 1 & 1984/85 & 4 & 3a & 6th \\ 2 & 1985/86 & 4 & 3a & 9th \\ 3 & 1986/87 & 4 & 3a & 11th \\ 4 & 1987/88 & 4 & 3a & 15th \\ 5 & 1988/89 & 4 & 3a & 4th \\ 6 & 1989/90 & 4 & 3a & 9th \\ 7 & 1990/91 & 4 & 3a & 9th \\ 8 & 1991/92 & 4 & 3a & 5th \\ 9 & 1992/93 & 4 & 3a & 17th \\ 10 & 1993/94 & 4 & 3a & 7th \\ 11 & 1994/95 & 4 & 3a & 4th \\ 12 & 1995/96 & 4 & 3a & 1st \\ 13 & 1996/97 & 3 & 2ab & 19th \\ 14 & 1997/98 & 4 & 3a & 2nd \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "place" ) \\ \midrule 0 & 13 \\ \bottomrule \end{tabular}	select count ( place ) where tier = 4 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>tier</th> <th>division</th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1928-84</td> <td>5</td> <td>regional</td> <td>none</td> </tr> <tr> <th>1</th> <td>1984/85</td> <td>4</td> <td>3a</td> <td>6th</td> </tr> <tr> <th>2</th> <td>1985/86</td> <td>4</td> <td>3a</td> <td>9th</td> </tr> <tr> <th>3</th> <td>1986/87</td> <td>4</td> <td>3a</td> <td>11th</td> </tr> <tr> <th>4</th> <td>1987/88</td> <td>4</td> <td>3a</td> <td>15th</td> </tr> <tr> <th>5</th> <td>1988/89</td> <td>4</td> <td>3a</td> <td>4th</td> </tr> <tr> <th>6</th> <td>1989/90</td> <td>4</td> <td>3a</td> <td>9th</td> </tr> <tr> <th>7</th> <td>1990/91</td> <td>4</td> <td>3a</td> <td>9th</td> </tr> <tr> <th>8</th> <td>1991/92</td> <td>4</td> <td>3a</td> <td>5th</td> </tr> <tr> <th>9</th> <td>1992/93</td> <td>4</td> <td>3a</td> <td>17th</td> </tr> <tr> <th>10</th> <td>1993/94</td> <td>4</td> <td>3a</td> <td>7th</td> </tr> <tr> <th>11</th> <td>1994/95</td> <td>4</td> <td>3a</td> <td>4th</td> </tr> <tr> <th>12</th> <td>1995/96</td> <td>4</td> <td>3a</td> <td>1st</td> </tr> <tr> <th>13</th> <td>1996/97</td> <td>3</td> <td>2ab</td> <td>19th</td> </tr> <tr> <th>14</th> <td>1997/98</td> <td>4</td> <td>3a</td> <td>2nd</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "place" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>13</td> </tr> </tbody> </table>	select count ( place ) where tier = 4 <table_name> : table \| \| season \| tier \| division \| place \| \|---:\|:---------\|-------:\|:-----------\|:--------\| \| 0 \| 1928-84 \| 5 \| regional \| none \| \| 1 \| 1984/85 \| 4 \| 3a \| 6th \| \| 2 \| 1985/86 \| 4 \| 3a \| 9th \| \| 3 \| 1986/87 \| 4 \| 3a \| 11th \| \| 4 \| 1987/88 \| 4 \| 3a \| 15th \| \| 5 \| 1988/89 \| 4 \| 3a \| 4th \| \| 6 \| 1989/90 \| 4 \| 3a \| 9th \| \| 7 \| 1990/91 \| 4 \| 3a \| 9th \| \| 8 \| 1991/92 \| 4 \| 3a \| 5th \| \| 9 \| 1992/93 \| 4 \| 3a \| 17th \| \| 10 \| 1993/94 \| 4 \| 3a \| 7th \| \| 11 \| 1994/95 \| 4 \| 3a \| 4th \| \| 12 \| 1995/96 \| 4 \| 3a \| 1st \| \| 13 \| 1996/97 \| 3 \| 2ab \| 19th \| \| 14 \| 1997/98 \| 4 \| 3a \| 2nd \|	\| \| count ( "place" ) \| \|---:\|--------------------:\| \| 0 \| 13 \|	[ [ 1, 4025, 1056, 261, 3166, 262, 1625, 17742, 273, 1059, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 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select co-driver where car = 'toyota corolla' col : pos. \| driver \| co-driver \| car \| time \| difference \| points row 1 : 1 \| raffaele pinto \| arnaldo bernacchini \| fiat abarth 124 rallye \| 6:26:15 \| 0 \| 20 row 2 : 2 \| alcide paganelli \| ninni russo \| fiat abarth 124 rallye \| 6:30:12 \| 3.57 \| none row 3 : 3 \| markku alen \| ilkka kivimaki \| fiat abarth 124 rallye \| 6:37:17 \| 11.02 \| none row 4 : 4 \| ove andersson \| arne hertz \| toyota corolla \| 6:40:54 \| 14.39 \| 10 row 5 : 5 \| harry kallstrom \| claes billstam \| datsun 260z \| 6:54:27 \| 28.12 \| 8 row 6 : 6 \| bob neyret \| yveline vanoni \| alpine-renault a110 1800 \| 7:04:18 \| 38.03 \| 6 row 7 : 7 \| georg fischer \| harald gottlieb \| bmw 2002 \| 7:05:02 \| 38.47 \| 4 row 8 : 8 \| francisco romaozinho \| jose bernardo \| citroen gs \| 7:17:04 \| 50.49 \| 3 row 9 : 9 \| chris sclater \| neil wilson \| ford escort rs1600 \| 7:26:59 \| 1:00.44 \| 2 row 10 : 10 \| antonio borges \| miguel sottomayor \| fiat 124 sport spyder \| 7:27:55 \| 1:01.40 \| none	col : co-driver row 1 : arne hertz	select co-driver where car = 'toyota corolla' <table_name> : table \begin{tabular}{llllllll} \toprule & pos. & driver & co-driver & car & time & difference & points \\ \midrule 0 & 1 & raffaele pinto & arnaldo bernacchini & fiat abarth 124 rallye & 6:26:15 & 0 & 20 \\ 1 & 2 & alcide paganelli & ninni russo & fiat abarth 124 rallye & 6:30:12 & 3.57 & none \\ 2 & 3 & markku alen & ilkka kivimaki & fiat abarth 124 rallye & 6:37:17 & 11.02 & none \\ 3 & 4 & ove andersson & arne hertz & toyota corolla & 6:40:54 & 14.39 & 10 \\ 4 & 5 & harry kallstrom & claes billstam & datsun 260z & 6:54:27 & 28.12 & 8 \\ 5 & 6 & bob neyret & yveline vanoni & alpine-renault a110 1800 & 7:04:18 & 38.03 & 6 \\ 6 & 7 & georg fischer & harald gottlieb & bmw 2002 & 7:05:02 & 38.47 & 4 \\ 7 & 8 & francisco romaozinho & jose bernardo & citroen gs & 7:17:04 & 50.49 & 3 \\ 8 & 9 & chris sclater & neil wilson & ford escort rs1600 & 7:26:59 & 1:00.44 & 2 \\ 9 & 10 & antonio borges & miguel sottomayor & fiat 124 sport spyder & 7:27:55 & 1:01.40 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & co-driver \\ \midrule 0 & arne hertz \\ \bottomrule \end{tabular}	select co-driver where car = 'toyota corolla' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pos.</th> <th>driver</th> <th>co-driver</th> <th>car</th> <th>time</th> <th>difference</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>raffaele pinto</td> <td>arnaldo bernacchini</td> <td>fiat abarth 124 rallye</td> <td>6:26:15</td> <td>0</td> <td>20</td> </tr> <tr> <th>1</th> <td>2</td> <td>alcide paganelli</td> <td>ninni russo</td> <td>fiat abarth 124 rallye</td> <td>6:30:12</td> <td>3.57</td> <td>none</td> </tr> <tr> <th>2</th> <td>3</td> <td>markku alen</td> <td>ilkka kivimaki</td> <td>fiat abarth 124 rallye</td> <td>6:37:17</td> <td>11.02</td> <td>none</td> </tr> <tr> <th>3</th> <td>4</td> <td>ove andersson</td> <td>arne hertz</td> <td>toyota corolla</td> <td>6:40:54</td> <td>14.39</td> <td>10</td> </tr> <tr> <th>4</th> <td>5</td> <td>harry kallstrom</td> <td>claes billstam</td> <td>datsun 260z</td> <td>6:54:27</td> <td>28.12</td> <td>8</td> </tr> <tr> <th>5</th> <td>6</td> <td>bob neyret</td> <td>yveline vanoni</td> <td>alpine-renault a110 1800</td> <td>7:04:18</td> <td>38.03</td> <td>6</td> </tr> <tr> <th>6</th> <td>7</td> <td>georg fischer</td> <td>harald gottlieb</td> <td>bmw 2002</td> <td>7:05:02</td> <td>38.47</td> <td>4</td> </tr> <tr> <th>7</th> <td>8</td> <td>francisco romaozinho</td> <td>jose bernardo</td> <td>citroen gs</td> <td>7:17:04</td> <td>50.49</td> <td>3</td> </tr> <tr> <th>8</th> <td>9</td> <td>chris sclater</td> <td>neil wilson</td> <td>ford escort rs1600</td> <td>7:26:59</td> <td>1:00.44</td> <td>2</td> </tr> <tr> <th>9</th> <td>10</td> <td>antonio borges</td> <td>miguel sottomayor</td> <td>fiat 124 sport spyder</td> <td>7:27:55</td> <td>1:01.40</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>co-driver</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>arne hertz</td> </tr> </tbody> </table>	select co-driver where car = 'toyota corolla' <table_name> : table \| \| pos. \| driver \| co-driver \| car \| time \| difference \| points \| \|---:\|-------:\|:---------------------\|:--------------------\|:-------------------------\|:--------\|:-------------\|:---------\| \| 0 \| 1 \| raffaele pinto \| arnaldo bernacchini \| fiat abarth 124 rallye \| 6:26:15 \| 0 \| 20 \| \| 1 \| 2 \| alcide paganelli \| ninni russo \| fiat abarth 124 rallye \| 6:30:12 \| 3.57 \| none \| \| 2 \| 3 \| markku alen \| ilkka kivimaki \| fiat abarth 124 rallye \| 6:37:17 \| 11.02 \| none \| \| 3 \| 4 \| ove andersson \| arne hertz \| toyota corolla \| 6:40:54 \| 14.39 \| 10 \| \| 4 \| 5 \| harry kallstrom \| claes billstam \| datsun 260z \| 6:54:27 \| 28.12 \| 8 \| \| 5 \| 6 \| bob neyret \| yveline vanoni \| alpine-renault a110 1800 \| 7:04:18 \| 38.03 \| 6 \| \| 6 \| 7 \| georg fischer \| harald gottlieb \| bmw 2002 \| 7:05:02 \| 38.47 \| 4 \| \| 7 \| 8 \| francisco romaozinho \| jose bernardo \| citroen gs \| 7:17:04 \| 50.49 \| 3 \| \| 8 \| 9 \| chris sclater \| neil wilson \| ford escort rs1600 \| 7:26:59 \| 1:00.44 \| 2 \| \| 9 \| 10 \| antonio borges \| miguel sottomayor \| fiat 124 sport spyder \| 7:27:55 \| 1:01.40 \| none \|	\| \| co-driver \| \|---:\|:------------\| \| 0 \| arne hertz \|	[ [ 1, 4025, 1825, 17, 7407, 1625, 5926, 273, 296, 869, 93, 25441, 1858, 355, 11821, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 917, 17347, 451, 34, 203, 1377, 411, 451, 34, 7407, 1757, 451, 34, 203, 1377, 411, 451, 34, 2894, 17, 7407, 1757, 451, 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select abs ( year - year ) where title = '24 hour party people' col : year \| title \| role \| notes row 1 : 1991 \| let him have it \| derek bentley \| none row 2 : 1992 \| death and the compass \| alonso zunz \| none row 3 : 1993 \| anchoress \| priest \| none row 4 : 1994 \| shallow grave \| david \| none row 5 : 1996 \| jude \| jude fawley \| none row 6 : 1998 \| elizabeth \| duke of norfolk \| none row 7 : 1998 \| a price above rubies \| sender horowitz \| none row 8 : 1999 \| heart \| gary ellis \| none row 9 : 1999 \| existenz \| seminar leader \| none row 10 : 1999 \| with or without you \| vincent boyd \| none row 11 : 2000 \| gone in 60 seconds \| raymond calitri \| none row 12 : 2000 \| the tyre \| salesman \| short film row 13 : 2001 \| the others \| charles stewart \| none row 14 : 2001 \| the invisible circus \| wolf \| none row 15 : 2001 \| this little piggy \| cabbie \| short film row 16 : 2002 \| 24 hour party people \| boethius \| none row 17 : 2002 \| i am dina \| leo zhukovsky \| none row 18 : 2002 \| revengers tragedy \| vindici \| none row 19 : 2002 \| 28 days later \| major henry west \| none row 20 : 2007 \| the dark is rising \| the rider \| none row 21 : 2008 \| new orleans, mon amour \| dr. henry \| none row 22 : 2009 \| g.i. joe: the rise of cobra \| james mccullen / destro \| none row 23 : 2009 \| amelia \| fred noonan \| none row 24 : 2009 \| the happiness salesman \| salesman \| short film row 25 : 2012 \| song for marion \| james harris \| none row 26 : 2013 \| thor: the dark world \| malekith \| none	col : "abs ( year - year )" row 1 : abs ( year - year )	select abs ( year - year ) where title = '24 hour party people' <table_name> : table \begin{tabular}{lllll} \toprule & year & title & role & notes \\ \midrule 0 & 1991 & let him have it & derek bentley & none \\ 1 & 1992 & death and the compass & alonso zunz & none \\ 2 & 1993 & anchoress & priest & none \\ 3 & 1994 & shallow grave & david & none \\ 4 & 1996 & jude & jude fawley & none \\ 5 & 1998 & elizabeth & duke of norfolk & none \\ 6 & 1998 & a price above rubies & sender horowitz & none \\ 7 & 1999 & heart & gary ellis & none \\ 8 & 1999 & existenz & seminar leader & none \\ 9 & 1999 & with or without you & vincent boyd & none \\ 10 & 2000 & gone in 60 seconds & raymond calitri & none \\ 11 & 2000 & the tyre & salesman & short film \\ 12 & 2001 & the others & charles stewart & none \\ 13 & 2001 & the invisible circus & wolf & none \\ 14 & 2001 & this little piggy & cabbie & short film \\ 15 & 2002 & 24 hour party people & boethius & none \\ 16 & 2002 & i am dina & leo zhukovsky & none \\ 17 & 2002 & revengers tragedy & vindici & none \\ 18 & 2002 & 28 days later & major henry west & none \\ 19 & 2007 & the dark is rising & the rider & none \\ 20 & 2008 & new orleans, mon amour & dr. henry & none \\ 21 & 2009 & g.i. joe: the rise of cobra & james mccullen / destro & none \\ 22 & 2009 & amelia & fred noonan & none \\ 23 & 2009 & the happiness salesman & salesman & short film \\ 24 & 2012 & song for marion & james harris & none \\ 25 & 2013 & thor: the dark world & malekith & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & "abs ( year - year )" \\ \midrule 0 & abs ( year - year ) \\ \bottomrule \end{tabular}	select abs ( year - year ) where title = '24 hour party people' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>title</th> <th>role</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1991</td> <td>let him have it</td> <td>derek bentley</td> <td>none</td> </tr> <tr> <th>1</th> <td>1992</td> <td>death and the compass</td> <td>alonso zunz</td> <td>none</td> </tr> <tr> <th>2</th> <td>1993</td> <td>anchoress</td> <td>priest</td> <td>none</td> </tr> <tr> <th>3</th> <td>1994</td> <td>shallow grave</td> <td>david</td> <td>none</td> </tr> <tr> <th>4</th> <td>1996</td> <td>jude</td> <td>jude fawley</td> <td>none</td> </tr> <tr> <th>5</th> <td>1998</td> <td>elizabeth</td> <td>duke of norfolk</td> <td>none</td> </tr> <tr> <th>6</th> <td>1998</td> <td>a price above rubies</td> <td>sender horowitz</td> <td>none</td> </tr> <tr> <th>7</th> <td>1999</td> <td>heart</td> <td>gary ellis</td> <td>none</td> </tr> <tr> <th>8</th> <td>1999</td> <td>existenz</td> <td>seminar leader</td> <td>none</td> </tr> <tr> <th>9</th> <td>1999</td> <td>with or without you</td> <td>vincent boyd</td> <td>none</td> </tr> <tr> <th>10</th> <td>2000</td> <td>gone in 60 seconds</td> <td>raymond calitri</td> <td>none</td> </tr> <tr> <th>11</th> <td>2000</td> <td>the tyre</td> <td>salesman</td> <td>short film</td> </tr> <tr> <th>12</th> <td>2001</td> <td>the others</td> <td>charles stewart</td> <td>none</td> </tr> <tr> <th>13</th> <td>2001</td> <td>the invisible circus</td> <td>wolf</td> <td>none</td> </tr> <tr> <th>14</th> <td>2001</td> <td>this little piggy</td> <td>cabbie</td> <td>short film</td> </tr> <tr> <th>15</th> <td>2002</td> <td>24 hour party people</td> <td>boethius</td> <td>none</td> </tr> <tr> <th>16</th> <td>2002</td> <td>i am dina</td> <td>leo zhukovsky</td> <td>none</td> </tr> <tr> <th>17</th> <td>2002</td> <td>revengers tragedy</td> <td>vindici</td> <td>none</td> </tr> <tr> <th>18</th> <td>2002</td> <td>28 days later</td> <td>major henry west</td> <td>none</td> </tr> <tr> <th>19</th> <td>2007</td> <td>the dark is rising</td> <td>the rider</td> <td>none</td> </tr> <tr> <th>20</th> <td>2008</td> <td>new orleans, mon amour</td> <td>dr. henry</td> <td>none</td> </tr> <tr> <th>21</th> <td>2009</td> <td>g.i. joe: the rise of cobra</td> <td>james mccullen / destro</td> <td>none</td> </tr> <tr> <th>22</th> <td>2009</td> <td>amelia</td> <td>fred noonan</td> <td>none</td> </tr> <tr> <th>23</th> <td>2009</td> <td>the happiness salesman</td> <td>salesman</td> <td>short film</td> </tr> <tr> <th>24</th> <td>2012</td> <td>song for marion</td> <td>james harris</td> <td>none</td> </tr> <tr> <th>25</th> <td>2013</td> <td>thor: the dark world</td> <td>malekith</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"abs ( year - year )"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>abs ( year - year )</td> </tr> </tbody> </table>	select abs ( year - year ) where title = '24 hour party people' <table_name> : table \| \| year \| title \| role \| notes \| \|---:\|-------:\|:----------------------------\|:------------------------\|:-----------\| \| 0 \| 1991 \| let him have it \| derek bentley \| none \| \| 1 \| 1992 \| death and the compass \| alonso zunz \| none \| \| 2 \| 1993 \| anchoress \| priest \| none \| \| 3 \| 1994 \| shallow grave \| david \| none \| \| 4 \| 1996 \| jude \| jude fawley \| none \| \| 5 \| 1998 \| elizabeth \| duke of norfolk \| none \| \| 6 \| 1998 \| a price above rubies \| sender horowitz \| none \| \| 7 \| 1999 \| heart \| gary ellis \| none \| \| 8 \| 1999 \| existenz \| seminar leader \| none \| \| 9 \| 1999 \| with or without you \| vincent boyd \| none \| \| 10 \| 2000 \| gone in 60 seconds \| raymond calitri \| none \| \| 11 \| 2000 \| the tyre \| salesman \| short film \| \| 12 \| 2001 \| the others \| charles stewart \| none \| \| 13 \| 2001 \| the invisible circus \| wolf \| none \| \| 14 \| 2001 \| this little piggy \| cabbie \| short film \| \| 15 \| 2002 \| 24 hour party people \| boethius \| none \| \| 16 \| 2002 \| i am dina \| leo zhukovsky \| none \| \| 17 \| 2002 \| revengers tragedy \| vindici \| none \| \| 18 \| 2002 \| 28 days later \| major henry west \| none \| \| 19 \| 2007 \| the dark is rising \| the rider \| none \| \| 20 \| 2008 \| new orleans, mon amour \| dr. henry \| none \| \| 21 \| 2009 \| g.i. joe: the rise of cobra \| james mccullen / destro \| none \| \| 22 \| 2009 \| amelia \| fred noonan \| none \| \| 23 \| 2009 \| the happiness salesman \| salesman \| short film \| \| 24 \| 2012 \| song for marion \| james harris \| none \| \| 25 \| 2013 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select place - division where place = '20th' col : season \| tier \| division \| place row 1 : 1970-01 \| 6 \| regional \| none row 2 : 2001/02 \| 6 \| 1a reg \| none row 3 : 2002/03 \| 5 \| reg. pref \| 11th row 4 : 2003/04 \| 5 \| reg. pref \| 9th row 5 : 2004/05 \| 5 \| reg. pref \| 1st row 6 : 2005/06 \| 4 \| 3a \| 20th row 7 : 2006/07 \| 5 \| reg. pref \| 3rd row 8 : 2007/08 \| 5 \| reg. pref \| 1st row 9 : 2008/09 \| 4 \| 3a \| 16th row 10 : 2009/10 \| 4 \| 3a \| 17th row 11 : 2010/11 \| 4 \| 3a \| 18th row 12 : 2011/12 \| 5 \| reg. pref \| 2nd	col : "place - division" row 1 : place - division	select place - division where place = '20th' <table_name> : table \begin{tabular}{lllll} \toprule & season & tier & division & place \\ \midrule 0 & 1970-01 & 6 & regional & none \\ 1 & 2001/02 & 6 & 1a reg & none \\ 2 & 2002/03 & 5 & reg. pref & 11th \\ 3 & 2003/04 & 5 & reg. pref & 9th \\ 4 & 2004/05 & 5 & reg. pref & 1st \\ 5 & 2005/06 & 4 & 3a & 20th \\ 6 & 2006/07 & 5 & reg. pref & 3rd \\ 7 & 2007/08 & 5 & reg. pref & 1st \\ 8 & 2008/09 & 4 & 3a & 16th \\ 9 & 2009/10 & 4 & 3a & 17th \\ 10 & 2010/11 & 4 & 3a & 18th \\ 11 & 2011/12 & 5 & reg. pref & 2nd \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & "place - division" \\ \midrule 0 & place - division \\ \bottomrule \end{tabular}	select place - division where place = '20th' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>tier</th> <th>division</th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1970-01</td> <td>6</td> <td>regional</td> <td>none</td> </tr> <tr> <th>1</th> <td>2001/02</td> <td>6</td> <td>1a reg</td> <td>none</td> </tr> <tr> <th>2</th> <td>2002/03</td> <td>5</td> <td>reg. pref</td> <td>11th</td> </tr> <tr> <th>3</th> <td>2003/04</td> <td>5</td> <td>reg. pref</td> <td>9th</td> </tr> <tr> <th>4</th> <td>2004/05</td> <td>5</td> <td>reg. pref</td> <td>1st</td> </tr> <tr> <th>5</th> <td>2005/06</td> <td>4</td> <td>3a</td> <td>20th</td> </tr> <tr> <th>6</th> <td>2006/07</td> <td>5</td> <td>reg. pref</td> <td>3rd</td> </tr> <tr> <th>7</th> <td>2007/08</td> <td>5</td> <td>reg. pref</td> <td>1st</td> </tr> <tr> <th>8</th> <td>2008/09</td> <td>4</td> <td>3a</td> <td>16th</td> </tr> <tr> <th>9</th> <td>2009/10</td> <td>4</td> <td>3a</td> <td>17th</td> </tr> <tr> <th>10</th> <td>2010/11</td> <td>4</td> <td>3a</td> <td>18th</td> </tr> <tr> <th>11</th> <td>2011/12</td> <td>5</td> <td>reg. pref</td> <td>2nd</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"place - division"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>place - division</td> </tr> </tbody> </table>	select place - division where place = '20th' <table_name> : table \| \| season \| tier \| division \| place \| \|---:\|:---------\|-------:\|:-----------\|:--------\| \| 0 \| 1970-01 \| 6 \| regional \| none \| \| 1 \| 2001/02 \| 6 \| 1a reg \| none \| \| 2 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select rank where tally = '3-1' col : rank \| player \| county \| tally \| total \| opposition row 1 : 1 \| eamonn flynn \| dublin \| 3-5 \| 14 \| wexford row 2 : 1 \| charlie mccarthy \| cork \| 2-8 \| 14 \| galway row 3 : 3 \| paddy fahy \| galway \| 2-7 \| 13 \| kildare row 4 : 3 \| t. morrissey \| wicklow \| 2-7 \| 13 \| laois row 5 : 5 \| charlie mccarthy \| cork \| 3-3 \| 12 \| offaly row 6 : 5 \| michael moroney \| clare \| 2-6 \| 12 \| dublin row 7 : 5 \| declan lovett \| kerry \| 1-9 \| 12 \| galway row 8 : 5 \| charlie mccarthy \| cork \| 1-9 \| 12 \| tipperary row 9 : 9 \| ger cuddy \| laois \| 3-2 \| 11 \| wicklow row 10 : 9 \| pat enright \| waterford \| 2-5 \| 11 \| kerry row 11 : 9 \| pat enright \| waterford \| 1-8 \| 11 \| laois row 12 : 9 \| johnny walsh \| kildare \| 0-11 \| 11 \| waterford row 13 : 9 \| eddie keher \| kilkenny \| 0-11 \| 11 \| wexford row 14 : 14 \| brendan cummins \| cork \| 3-1 \| 10 \| wexford row 15 : 14 \| p. j. molloy \| galway \| 3-1 \| 10 \| kerry row 16 : 14 \| nick behan \| kildare \| 3-1 \| 10 \| kerry row 17 : 14 \| seanie o'leary \| cork \| 3-1 \| 10 \| limerick row 18 : 14 \| michael keating \| tipperary \| 2-4 \| 10 \| wexford row 19 : 14 \| seamus richmond \| antrim \| 2-4 \| 10 \| westmeath row 20 : 14 \| declan lovett \| kerry \| 2-4 \| 10 \| waterford row 21 : 14 \| michael keating \| tipperary \| 2-4 \| 10 \| dublin row 22 : 14 \| eddie keher \| kilkenny \| 2-4 \| 10 \| dublin row 23 : 14 \| mick dwan \| kildare \| 2-4 \| 10 \| antrim row 24 : 14 \| charlie mccarthy \| cork \| 1-7 \| 10 \| kilkenny row 25 : 14 \| paddy fahy \| galway \| 0-10 \| 10 \| kerry row 26 : 14 \| johnny walsh \| kildare \| 0-10 \| 10 \| westmeath row 27 : 27 \| p flynn \| wexford \| 3-0 \| 9 \| offaly row 28 : 27 \| n casey \| clare \| 3-0 \| 9 \| cork row 29 : 27 \| willie moore \| limerick \| 3-0 \| 9 \| cork row 30 : 27 \| ger cuddy \| laois \| 3-0 \| 9 \| westmeath row 31 : 27 \| tom ryan \| galway \| 3-0 \| 9 \| laois row 32 : 27 \| seanie o'leary \| cork \| 3-0 \| 9 \| offaly row 33 : 27 \| p flynn \| wexford \| 2-3 \| 9 \| cork row 34 : 27 \| eddie keher \| kilkenny \| 2-3 \| 9 \| limerick row 35 : 27 \| johnny walsh \| kildare \| 1-6 \| 9 \| galway row 36 : 27 \| francis loughnane \| tipperary \| 1-6 \| 9 \| cork row 37 : 27 \| richie bennis \| limerick \| 1-6 \| 9 \| cork row 38 : 27 \| pat enright \| waterford \| 0-9 \| 9 \| kildare row 39 : 27 \| johnny walsh \| kildare \| 0-9 \| 9 \| kerry	col : rank row 1 : 14 row 2 : 14 row 3 : 14 row 4 : 14	select rank where tally = '3-1' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & player & county & tally & total & opposition \\ \midrule 0 & 1 & eamonn flynn & dublin & 3-5 & 14 & wexford \\ 1 & 1 & charlie mccarthy & cork & 2-8 & 14 & galway \\ 2 & 3 & paddy fahy & galway & 2-7 & 13 & kildare \\ 3 & 3 & t. morrissey & wicklow & 2-7 & 13 & laois \\ 4 & 5 & charlie mccarthy & cork & 3-3 & 12 & offaly \\ 5 & 5 & michael moroney & clare & 2-6 & 12 & dublin \\ 6 & 5 & declan lovett & kerry & 1-9 & 12 & galway \\ 7 & 5 & charlie mccarthy & cork & 1-9 & 12 & tipperary \\ 8 & 9 & ger cuddy & laois & 3-2 & 11 & wicklow \\ 9 & 9 & pat enright & waterford & 2-5 & 11 & kerry \\ 10 & 9 & pat enright & waterford & 1-8 & 11 & laois \\ 11 & 9 & johnny walsh & kildare & 0-11 & 11 & waterford \\ 12 & 9 & eddie keher & kilkenny & 0-11 & 11 & wexford \\ 13 & 14 & brendan cummins & cork & 3-1 & 10 & wexford \\ 14 & 14 & p. j. molloy & galway & 3-1 & 10 & kerry \\ 15 & 14 & nick behan & kildare & 3-1 & 10 & kerry \\ 16 & 14 & seanie o'leary & cork & 3-1 & 10 & limerick \\ 17 & 14 & michael keating & tipperary & 2-4 & 10 & wexford \\ 18 & 14 & seamus richmond & antrim & 2-4 & 10 & westmeath \\ 19 & 14 & declan lovett & kerry & 2-4 & 10 & waterford \\ 20 & 14 & michael keating & tipperary & 2-4 & 10 & dublin \\ 21 & 14 & eddie keher & kilkenny & 2-4 & 10 & dublin \\ 22 & 14 & mick dwan & kildare & 2-4 & 10 & antrim \\ 23 & 14 & charlie mccarthy & cork & 1-7 & 10 & kilkenny \\ 24 & 14 & paddy fahy & galway & 0-10 & 10 & kerry \\ 25 & 14 & johnny walsh & kildare & 0-10 & 10 & westmeath \\ 26 & 27 & p flynn & wexford & 3-0 & 9 & offaly \\ 27 & 27 & n casey & clare & 3-0 & 9 & cork \\ 28 & 27 & willie moore & limerick & 3-0 & 9 & cork \\ 29 & 27 & ger cuddy & laois & 3-0 & 9 & westmeath \\ 30 & 27 & tom ryan & galway & 3-0 & 9 & laois \\ 31 & 27 & seanie o'leary & cork & 3-0 & 9 & offaly \\ 32 & 27 & p flynn & wexford & 2-3 & 9 & cork \\ 33 & 27 & eddie keher & kilkenny & 2-3 & 9 & limerick \\ 34 & 27 & johnny walsh & kildare & 1-6 & 9 & galway \\ 35 & 27 & francis loughnane & tipperary & 1-6 & 9 & cork \\ 36 & 27 & richie bennis & limerick & 1-6 & 9 & cork \\ 37 & 27 & pat enright & waterford & 0-9 & 9 & kildare \\ 38 & 27 & johnny walsh & kildare & 0-9 & 9 & kerry \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & rank \\ \midrule 0 & 14 \\ 1 & 14 \\ 2 & 14 \\ 3 & 14 \\ \bottomrule \end{tabular}	select rank where tally = '3-1' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>player</th> <th>county</th> <th>tally</th> <th>total</th> <th>opposition</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>eamonn flynn</td> <td>dublin</td> <td>3-5</td> <td>14</td> <td>wexford</td> </tr> <tr> <th>1</th> <td>1</td> <td>charlie mccarthy</td> <td>cork</td> <td>2-8</td> <td>14</td> <td>galway</td> </tr> <tr> <th>2</th> <td>3</td> <td>paddy fahy</td> <td>galway</td> <td>2-7</td> <td>13</td> <td>kildare</td> </tr> <tr> <th>3</th> <td>3</td> <td>t. morrissey</td> <td>wicklow</td> <td>2-7</td> <td>13</td> <td>laois</td> </tr> <tr> <th>4</th> <td>5</td> <td>charlie mccarthy</td> <td>cork</td> <td>3-3</td> <td>12</td> <td>offaly</td> </tr> <tr> <th>5</th> <td>5</td> <td>michael moroney</td> <td>clare</td> <td>2-6</td> <td>12</td> <td>dublin</td> </tr> <tr> <th>6</th> <td>5</td> <td>declan lovett</td> <td>kerry</td> <td>1-9</td> <td>12</td> <td>galway</td> </tr> <tr> <th>7</th> <td>5</td> <td>charlie mccarthy</td> <td>cork</td> <td>1-9</td> <td>12</td> <td>tipperary</td> </tr> <tr> <th>8</th> <td>9</td> <td>ger cuddy</td> <td>laois</td> <td>3-2</td> <td>11</td> <td>wicklow</td> </tr> <tr> <th>9</th> <td>9</td> <td>pat enright</td> <td>waterford</td> <td>2-5</td> <td>11</td> <td>kerry</td> </tr> <tr> <th>10</th> <td>9</td> <td>pat enright</td> <td>waterford</td> <td>1-8</td> <td>11</td> <td>laois</td> </tr> <tr> <th>11</th> <td>9</td> <td>johnny walsh</td> <td>kildare</td> <td>0-11</td> <td>11</td> <td>waterford</td> </tr> <tr> <th>12</th> <td>9</td> <td>eddie keher</td> <td>kilkenny</td> <td>0-11</td> <td>11</td> <td>wexford</td> </tr> <tr> <th>13</th> <td>14</td> <td>brendan cummins</td> <td>cork</td> <td>3-1</td> <td>10</td> <td>wexford</td> </tr> <tr> <th>14</th> <td>14</td> <td>p. j. molloy</td> <td>galway</td> <td>3-1</td> <td>10</td> <td>kerry</td> </tr> <tr> <th>15</th> <td>14</td> <td>nick behan</td> <td>kildare</td> <td>3-1</td> <td>10</td> <td>kerry</td> </tr> <tr> <th>16</th> <td>14</td> <td>seanie o'leary</td> <td>cork</td> <td>3-1</td> <td>10</td> <td>limerick</td> </tr> <tr> <th>17</th> <td>14</td> <td>michael keating</td> <td>tipperary</td> <td>2-4</td> <td>10</td> <td>wexford</td> </tr> <tr> <th>18</th> <td>14</td> <td>seamus richmond</td> <td>antrim</td> <td>2-4</td> <td>10</td> <td>westmeath</td> </tr> <tr> <th>19</th> <td>14</td> <td>declan lovett</td> <td>kerry</td> <td>2-4</td> <td>10</td> <td>waterford</td> </tr> <tr> <th>20</th> <td>14</td> <td>michael keating</td> <td>tipperary</td> <td>2-4</td> <td>10</td> <td>dublin</td> </tr> <tr> <th>21</th> <td>14</td> <td>eddie keher</td> <td>kilkenny</td> <td>2-4</td> <td>10</td> <td>dublin</td> </tr> <tr> <th>22</th> <td>14</td> <td>mick dwan</td> <td>kildare</td> <td>2-4</td> <td>10</td> <td>antrim</td> </tr> <tr> <th>23</th> <td>14</td> <td>charlie mccarthy</td> <td>cork</td> <td>1-7</td> <td>10</td> <td>kilkenny</td> </tr> <tr> <th>24</th> <td>14</td> <td>paddy fahy</td> <td>galway</td> <td>0-10</td> <td>10</td> <td>kerry</td> </tr> <tr> <th>25</th> <td>14</td> <td>johnny walsh</td> <td>kildare</td> <td>0-10</td> <td>10</td> <td>westmeath</td> </tr> <tr> <th>26</th> <td>27</td> <td>p flynn</td> <td>wexford</td> <td>3-0</td> <td>9</td> <td>offaly</td> </tr> <tr> <th>27</th> <td>27</td> <td>n casey</td> <td>clare</td> <td>3-0</td> <td>9</td> <td>cork</td> </tr> <tr> <th>28</th> <td>27</td> <td>willie moore</td> <td>limerick</td> <td>3-0</td> <td>9</td> <td>cork</td> </tr> <tr> <th>29</th> <td>27</td> <td>ger cuddy</td> <td>laois</td> <td>3-0</td> <td>9</td> <td>westmeath</td> </tr> <tr> <th>30</th> <td>27</td> <td>tom ryan</td> <td>galway</td> <td>3-0</td> <td>9</td> <td>laois</td> </tr> <tr> <th>31</th> <td>27</td> <td>seanie o'leary</td> <td>cork</td> <td>3-0</td> <td>9</td> <td>offaly</td> </tr> <tr> <th>32</th> <td>27</td> <td>p flynn</td> <td>wexford</td> <td>2-3</td> <td>9</td> <td>cork</td> </tr> <tr> <th>33</th> <td>27</td> <td>eddie keher</td> <td>kilkenny</td> <td>2-3</td> <td>9</td> <td>limerick</td> </tr> <tr> <th>34</th> <td>27</td> <td>johnny walsh</td> <td>kildare</td> <td>1-6</td> <td>9</td> <td>galway</td> </tr> <tr> <th>35</th> <td>27</td> <td>francis loughnane</td> <td>tipperary</td> <td>1-6</td> <td>9</td> <td>cork</td> </tr> <tr> <th>36</th> <td>27</td> <td>richie bennis</td> <td>limerick</td> <td>1-6</td> <td>9</td> <td>cork</td> </tr> <tr> <th>37</th> <td>27</td> <td>pat enright</td> <td>waterford</td> <td>0-9</td> <td>9</td> <td>kildare</td> </tr> <tr> <th>38</th> <td>27</td> <td>johnny walsh</td> <td>kildare</td> <td>0-9</td> <td>9</td> <td>kerry</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>14</td> </tr> <tr> <th>1</th> <td>14</td> </tr> <tr> <th>2</th> <td>14</td> </tr> <tr> <th>3</th> <td>14</td> </tr> </tbody> </table>	select rank where tally = '3-1' <table_name> : table \| \| rank \| player \| county \| tally \| total \| opposition \| \|---:\|-------:\|:------------------\|:----------\|:--------\|--------:\|:-------------\| \| 0 \| 1 \| eamonn flynn \| dublin \| 3-5 \| 14 \| wexford \| \| 1 \| 1 \| charlie mccarthy \| cork \| 2-8 \| 14 \| galway \| \| 2 \| 3 \| paddy fahy \| galway \| 2-7 \| 13 \| kildare \| \| 3 \| 3 \| t. morrissey \| wicklow \| 2-7 \| 13 \| laois \| \| 4 \| 5 \| charlie mccarthy \| cork \| 3-3 \| 12 \| offaly \| \| 5 \| 5 \| michael moroney \| clare \| 2-6 \| 12 \| dublin \| \| 6 \| 5 \| declan lovett \| kerry \| 1-9 \| 12 \| galway \| \| 7 \| 5 \| charlie mccarthy \| cork \| 1-9 \| 12 \| tipperary \| \| 8 \| 9 \| ger cuddy \| laois \| 3-2 \| 11 \| wicklow \| \| 9 \| 9 \| pat enright \| waterford \| 2-5 \| 11 \| kerry \| \| 10 \| 9 \| pat enright \| waterford \| 1-8 \| 11 \| laois \| \| 11 \| 9 \| johnny walsh \| kildare \| 0-11 \| 11 \| waterford \| \| 12 \| 9 \| eddie keher \| kilkenny \| 0-11 \| 11 \| wexford \| \| 13 \| 14 \| brendan cummins \| cork \| 3-1 \| 10 \| wexford \| \| 14 \| 14 \| p. j. molloy \| galway \| 3-1 \| 10 \| kerry \| \| 15 \| 14 \| nick behan \| kildare \| 3-1 \| 10 \| kerry \| \| 16 \| 14 \| seanie o'leary \| cork \| 3-1 \| 10 \| limerick \| \| 17 \| 14 \| michael keating \| tipperary \| 2-4 \| 10 \| wexford \| \| 18 \| 14 \| seamus richmond \| antrim \| 2-4 \| 10 \| westmeath \| \| 19 \| 14 \| declan lovett \| kerry \| 2-4 \| 10 \| waterford \| \| 20 \| 14 \| michael keating \| tipperary \| 2-4 \| 10 \| dublin \| \| 21 \| 14 \| eddie keher \| kilkenny \| 2-4 \| 10 \| dublin \| \| 22 \| 14 \| mick dwan \| kildare \| 2-4 \| 10 \| antrim \| \| 23 \| 14 \| charlie mccarthy \| cork \| 1-7 \| 10 \| kilkenny \| \| 24 \| 14 \| paddy fahy \| galway \| 0-10 \| 10 \| kerry \| \| 25 \| 14 \| johnny walsh \| kildare \| 0-10 \| 10 \| westmeath \| \| 26 \| 27 \| p flynn \| wexford \| 3-0 \| 9 \| offaly \| \| 27 \| 27 \| n casey \| clare \| 3-0 \| 9 \| cork \| \| 28 \| 27 \| willie moore \| limerick \| 3-0 \| 9 \| cork \| \| 29 \| 27 \| ger cuddy \| laois \| 3-0 \| 9 \| westmeath \| \| 30 \| 27 \| tom ryan \| galway \| 3-0 \| 9 \| laois \| \| 31 \| 27 \| seanie o'leary \| cork \| 3-0 \| 9 \| offaly \| \| 32 \| 27 \| p flynn \| wexford \| 2-3 \| 9 \| cork \| \| 33 \| 27 \| eddie keher \| kilkenny \| 2-3 \| 9 \| limerick \| \| 34 \| 27 \| johnny walsh \| kildare \| 1-6 \| 9 \| galway \| \| 35 \| 27 \| francis loughnane \| tipperary \| 1-6 \| 9 \| cork \| \| 36 \| 27 \| richie bennis \| limerick \| 1-6 \| 9 \| cork \| \| 37 \| 27 \| pat enright \| waterford \| 0-9 \| 9 \| kildare \| \| 38 \| 27 \| johnny walsh \| kildare \| 0-9 \| 9 \| kerry \|	\| \| rank \| \|---:\|-------:\| \| 0 \| 14 \| \| 1 \| 14 \| \| 2 \| 14 \| \| 3 \| 14 \|	[ [ 1, 4025, 6171, 1625, 268, 1230, 273, 296, 23, 17, 21, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 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select length where version = 'axwell remix' col : version \| length \| album \| remixed by \| year \| comment row 1 : single version / radio edit \| 3:39 \| go - the very best of moby \| mhc aka philip larsen and chis smith \| 2006 \| remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one row 2 : extended remix \| 6:48 \| none \| mhc aka philip larsen and chis smith \| 2006 \| similar to the previous but longer row 3 : axwell remix \| 7:24 \| none \| axwell \| 2006 \| used in a scene in the 2008 movie 21 row 4 : enzo mori & stephan clark remix \| 7:10 \| none \| enzo mori and stephan clark \| 2006 \| none row 5 : mhc club remix \| 7:31 \| none \| mhc aka philip larsen and chis smith \| 2006 \| none row 6 : zloot remix \| 4:36 \| none \| toni toolz \| 2006 \| none row 7 : music video \| 3:58 \| none \| none \| 2006 \| none	col : length row 1 : 7:24	select length where version = 'axwell remix' <table_name> : table \begin{tabular}{lllllll} \toprule & version & length & album & remixed by & year & comment \\ \midrule 0 & single version / radio edit & 3:39 & go - the very best of moby & mhc aka philip larsen and chis smith & 2006 & remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one \\ 1 & extended remix & 6:48 & none & mhc aka philip larsen and chis smith & 2006 & similar to the previous but longer \\ 2 & axwell remix & 7:24 & none & axwell & 2006 & used in a scene in the 2008 movie 21 \\ 3 & enzo mori & stephan clark remix & 7:10 & none & enzo mori and stephan clark & 2006 & none \\ 4 & mhc club remix & 7:31 & none & mhc aka philip larsen and chis smith & 2006 & none \\ 5 & zloot remix & 4:36 & none & toni toolz & 2006 & none \\ 6 & music video & 3:58 & none & none & 2006 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & length \\ \midrule 0 & 7:24 \\ \bottomrule \end{tabular}	select length where version = 'axwell remix' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>version</th> <th>length</th> <th>album</th> <th>remixed by</th> <th>year</th> <th>comment</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>single version / radio edit</td> <td>3:39</td> <td>go - the very best of moby</td> <td>mhc aka philip larsen and chis smith</td> <td>2006</td> <td>remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one</td> </tr> <tr> <th>1</th> <td>extended remix</td> <td>6:48</td> <td>none</td> <td>mhc aka philip larsen and chis smith</td> <td>2006</td> <td>similar to the previous but longer</td> </tr> <tr> <th>2</th> <td>axwell remix</td> <td>7:24</td> <td>none</td> <td>axwell</td> <td>2006</td> <td>used in a scene in the 2008 movie 21</td> </tr> <tr> <th>3</th> <td>enzo mori & stephan clark remix</td> <td>7:10</td> <td>none</td> <td>enzo mori and stephan clark</td> <td>2006</td> <td>none</td> </tr> <tr> <th>4</th> <td>mhc club remix</td> <td>7:31</td> <td>none</td> <td>mhc aka philip larsen and chis smith</td> <td>2006</td> <td>none</td> </tr> <tr> <th>5</th> <td>zloot remix</td> <td>4:36</td> <td>none</td> <td>toni toolz</td> <td>2006</td> <td>none</td> </tr> <tr> <th>6</th> <td>music video</td> <td>3:58</td> <td>none</td> <td>none</td> <td>2006</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>length</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7:24</td> </tr> </tbody> </table>	select length where version = 'axwell remix' <table_name> : table \| \| version \| length \| album \| remixed by \| year \| comment \| \|---:\|:--------------------------------\|:---------\|:---------------------------\|:-------------------------------------\|-------:\|:-------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| single version / radio edit \| 3:39 \| go - the very best of moby \| mhc aka philip larsen and chis smith \| 2006 \| remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one \| \| 1 \| extended remix \| 6:48 \| none \| mhc aka philip larsen and chis smith \| 2006 \| similar to the previous but longer \| \| 2 \| axwell remix \| 7:24 \| none \| axwell \| 2006 \| used in a scene in the 2008 movie 21 \| \| 3 \| enzo mori & stephan clark remix \| 7:10 \| none \| enzo mori and stephan clark \| 2006 \| none \| \| 4 \| mhc club remix \| 7:31 \| none \| mhc aka philip larsen and chis smith \| 2006 \| none \| \| 5 \| zloot remix \| 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select month where month = 'precipitation inches (mm)' col : month \| jan \| feb \| mar \| apr \| may \| jun \| jul \| aug \| sep \| oct \| nov \| dec \| year row 1 : record high °f (°c) \| 76 (24) \| 86 (30) \| 96 (36) \| 96 (36) \| 95 (35) \| 104 (40) \| 111 (44) \| 109 (43) \| 105 (41) \| 96 (36) \| 90 (32) \| 78 (26) \| 111 (44) row 2 : average high °f (°c) \| 46.2 (7.9) \| 50.4 (10.2) \| 59.1 (15.1) \| 68.7 (20.4) \| 75.5 (24.2) \| 83.5 (28.6) \| 88.7 (31.5) \| 89.4 (31.9) \| 80.8 (27.1) \| 70.3 (21.3) \| 59.2 (15.1) \| 48.0 (8.9) \| 68.3 (20.2) row 3 : average low °f (°c) \| 26.1 (-3.3) \| 29.0 (-1.7) \| 37.8 (3.2) \| 46.9 (8.3) \| 55.7 (13.2) \| 64.1 (17.8) \| 68.7 (20.4) \| 67.7 (19.8) \| 58.9 (14.9) \| 47.6 (8.7) \| 39.2 (4) \| 28.1 (-2.2) \| 47.5 (8.6) row 4 : record low °f (°c) \| -23 (-31) \| -24 (-31) \| -11 (-24) \| 18 (-8) \| 28 (-2) \| 41 (5) \| 48 (9) \| 44 (7) \| 29 (-2) \| 17 (-8) \| 5 (-15) \| -12 (-24) \| -24 (-31) row 5 : precipitation inches (mm) \| 1.99 (50.5) \| 2.43 (61.7) \| 3.54 (89.9) \| 4.05 (102.9) \| 4.99 (126.7) \| 4.59 (116.6) \| 3.18 (80.8) \| 2.75 (69.9) \| 4.43 (112.5) \| 3.83 (97.3) \| 4.19 (106.4) \| 2.73 (69.3) \| 42.7 (1,084.6) row 6 : snowfall inches (cm) \| 1.6 (4.1) \| 2.0 (5.1) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| .7 (1.8) \| 4.4 (11.2) row 7 : avg. precipitation days (≥ 0.01 in) \| 5.4 \| 6.6 \| 8.2 \| 9.0 \| 11.2 \| 8.9 \| 7.0 \| 6.4 \| 7.6 \| 7.9 \| 7.0 \| 6.3 \| 91.4 row 8 : avg. snowy days (≥ 0.1 in) \| .7 \| .9 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| .5 \| 2.3	col : month row 1 : precipitation inches (mm)	select month where month = 'precipitation inches (mm)' <table_name> : table \begin{tabular}{lllllllllllllll} \toprule & month & jan & feb & mar & apr & may & jun & jul & aug & sep & oct & nov & dec & year \\ \midrule 0 & record high °f (°c) & 76 (24) & 86 (30) & 96 (36) & 96 (36) & 95 (35) & 104 (40) & 111 (44) & 109 (43) & 105 (41) & 96 (36) & 90 (32) & 78 (26) & 111 (44) \\ 1 & average high °f (°c) & 46.2 (7.9) & 50.4 (10.2) & 59.1 (15.1) & 68.7 (20.4) & 75.5 (24.2) & 83.5 (28.6) & 88.7 (31.5) & 89.4 (31.9) & 80.8 (27.1) & 70.3 (21.3) & 59.2 (15.1) & 48.0 (8.9) & 68.3 (20.2) \\ 2 & average low °f (°c) & 26.1 (-3.3) & 29.0 (-1.7) & 37.8 (3.2) & 46.9 (8.3) & 55.7 (13.2) & 64.1 (17.8) & 68.7 (20.4) & 67.7 (19.8) & 58.9 (14.9) & 47.6 (8.7) & 39.2 (4) & 28.1 (-2.2) & 47.5 (8.6) \\ 3 & record low °f (°c) & -23 (-31) & -24 (-31) & -11 (-24) & 18 (-8) & 28 (-2) & 41 (5) & 48 (9) & 44 (7) & 29 (-2) & 17 (-8) & 5 (-15) & -12 (-24) & -24 (-31) \\ 4 & precipitation inches (mm) & 1.99 (50.5) & 2.43 (61.7) & 3.54 (89.9) & 4.05 (102.9) & 4.99 (126.7) & 4.59 (116.6) & 3.18 (80.8) & 2.75 (69.9) & 4.43 (112.5) & 3.83 (97.3) & 4.19 (106.4) & 2.73 (69.3) & 42.7 (1,084.6) \\ 5 & snowfall inches (cm) & 1.6 (4.1) & 2.0 (5.1) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & .7 (1.8) & 4.4 (11.2) \\ 6 & avg. precipitation days (≥ 0.01 in) & 5.4 & 6.6 & 8.2 & 9.0 & 11.2 & 8.9 & 7.0 & 6.4 & 7.6 & 7.9 & 7.0 & 6.3 & 91.4 \\ 7 & avg. snowy days (≥ 0.1 in) & .7 & .9 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & .5 & 2.3 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & month \\ \midrule 0 & precipitation inches (mm) \\ \bottomrule \end{tabular}	select month where month = 'precipitation inches (mm)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>month</th> <th>jan</th> <th>feb</th> <th>mar</th> <th>apr</th> <th>may</th> <th>jun</th> <th>jul</th> <th>aug</th> <th>sep</th> <th>oct</th> <th>nov</th> <th>dec</th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>record high °f (°c)</td> <td>76 (24)</td> <td>86 (30)</td> <td>96 (36)</td> <td>96 (36)</td> <td>95 (35)</td> <td>104 (40)</td> <td>111 (44)</td> <td>109 (43)</td> <td>105 (41)</td> <td>96 (36)</td> <td>90 (32)</td> <td>78 (26)</td> <td>111 (44)</td> </tr> <tr> <th>1</th> <td>average high °f (°c)</td> <td>46.2 (7.9)</td> <td>50.4 (10.2)</td> <td>59.1 (15.1)</td> <td>68.7 (20.4)</td> <td>75.5 (24.2)</td> <td>83.5 (28.6)</td> <td>88.7 (31.5)</td> <td>89.4 (31.9)</td> <td>80.8 (27.1)</td> <td>70.3 (21.3)</td> <td>59.2 (15.1)</td> <td>48.0 (8.9)</td> <td>68.3 (20.2)</td> </tr> <tr> <th>2</th> <td>average low °f (°c)</td> <td>26.1 (-3.3)</td> <td>29.0 (-1.7)</td> <td>37.8 (3.2)</td> <td>46.9 (8.3)</td> <td>55.7 (13.2)</td> <td>64.1 (17.8)</td> <td>68.7 (20.4)</td> <td>67.7 (19.8)</td> <td>58.9 (14.9)</td> <td>47.6 (8.7)</td> <td>39.2 (4)</td> <td>28.1 (-2.2)</td> <td>47.5 (8.6)</td> </tr> <tr> <th>3</th> <td>record low °f (°c)</td> <td>-23 (-31)</td> <td>-24 (-31)</td> <td>-11 (-24)</td> <td>18 (-8)</td> <td>28 (-2)</td> <td>41 (5)</td> <td>48 (9)</td> <td>44 (7)</td> <td>29 (-2)</td> <td>17 (-8)</td> <td>5 (-15)</td> <td>-12 (-24)</td> <td>-24 (-31)</td> </tr> <tr> <th>4</th> <td>precipitation inches (mm)</td> <td>1.99 (50.5)</td> <td>2.43 (61.7)</td> <td>3.54 (89.9)</td> <td>4.05 (102.9)</td> <td>4.99 (126.7)</td> <td>4.59 (116.6)</td> <td>3.18 (80.8)</td> <td>2.75 (69.9)</td> <td>4.43 (112.5)</td> <td>3.83 (97.3)</td> <td>4.19 (106.4)</td> <td>2.73 (69.3)</td> <td>42.7 (1,084.6)</td> </tr> <tr> <th>5</th> <td>snowfall inches (cm)</td> <td>1.6 (4.1)</td> <td>2.0 (5.1)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>.7 (1.8)</td> <td>4.4 (11.2)</td> </tr> <tr> <th>6</th> <td>avg. precipitation days (≥ 0.01 in)</td> <td>5.4</td> <td>6.6</td> <td>8.2</td> <td>9.0</td> <td>11.2</td> <td>8.9</td> <td>7.0</td> <td>6.4</td> <td>7.6</td> <td>7.9</td> <td>7.0</td> <td>6.3</td> <td>91.4</td> </tr> <tr> <th>7</th> <td>avg. snowy days (≥ 0.1 in)</td> <td>.7</td> <td>.9</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>.5</td> <td>2.3</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>month</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>precipitation inches (mm)</td> </tr> </tbody> </table>	select month where month = 'precipitation inches (mm)' <table_name> : table \| \| month \| jan \| feb \| mar \| apr \| may \| jun \| jul \| aug \| sep \| oct \| nov \| dec \| year \| \|---:\|:------------------------------------\|:------------\|:------------\|:------------\|:-------------\|:-------------\|:-------------\|:------------\|:------------\|:-------------\|:------------\|:-------------\|:------------\|:---------------\| \| 0 \| record high °f (°c) \| 76 (24) \| 86 (30) \| 96 (36) \| 96 (36) \| 95 (35) \| 104 (40) \| 111 (44) \| 109 (43) \| 105 (41) \| 96 (36) \| 90 (32) \| 78 (26) \| 111 (44) \| \| 1 \| average high °f (°c) \| 46.2 (7.9) \| 50.4 (10.2) \| 59.1 (15.1) \| 68.7 (20.4) \| 75.5 (24.2) \| 83.5 (28.6) \| 88.7 (31.5) \| 89.4 (31.9) \| 80.8 (27.1) \| 70.3 (21.3) \| 59.2 (15.1) \| 48.0 (8.9) \| 68.3 (20.2) \| \| 2 \| average low °f (°c) \| 26.1 (-3.3) \| 29.0 (-1.7) \| 37.8 (3.2) \| 46.9 (8.3) \| 55.7 (13.2) \| 64.1 (17.8) \| 68.7 (20.4) \| 67.7 (19.8) \| 58.9 (14.9) \| 47.6 (8.7) \| 39.2 (4) \| 28.1 (-2.2) \| 47.5 (8.6) \| \| 3 \| record low °f (°c) \| -23 (-31) \| -24 (-31) \| -11 (-24) \| 18 (-8) \| 28 (-2) \| 41 (5) \| 48 (9) \| 44 (7) \| 29 (-2) \| 17 (-8) \| 5 (-15) \| -12 (-24) \| -24 (-31) \| \| 4 \| precipitation inches (mm) \| 1.99 (50.5) \| 2.43 (61.7) \| 3.54 (89.9) \| 4.05 (102.9) \| 4.99 (126.7) \| 4.59 (116.6) \| 3.18 (80.8) \| 2.75 (69.9) \| 4.43 (112.5) \| 3.83 (97.3) \| 4.19 (106.4) \| 2.73 (69.3) \| 42.7 (1,084.6) \| \| 5 \| snowfall inches (cm) \| 1.6 (4.1) \| 2.0 (5.1) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| 0 (0) \| .7 (1.8) \| 4.4 (11.2) \| \| 6 \| avg. precipitation days (≥ 0.01 in) \| 5.4 \| 6.6 \| 8.2 \| 9.0 \| 11.2 \| 8.9 \| 7.0 \| 6.4 \| 7.6 \| 7.9 \| 7.0 \| 6.3 \| 91.4 \| \| 7 \| avg. snowy days (≥ 0.1 in) \| .7 \| .9 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| 0 \| .5 \| 2.3 \|	\| \| month \| \|---:\|:--------------------------\| \| 0 \| precipitation inches (mm) \|	[ [ 1, 4025, 3138, 1625, 3138, 273, 296, 1484, 3449, 8773, 316, 11163, 261, 7020, 2506, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 7496, 1757, 451, 34, 203, 1377, 411, 451, 34, 78, 304, 1757, 451, 34, 203, 1377, 411, 451, 34, 3030, 70, 1757, 451, 34, 203, 1377, 411, 451, 34, 3684, 1757, 451, 34, 203, 1377, 411, 451, 34, 438, 86, 1757, 451, 34, 203, 1377, 411, 451, 34, 24877, 1757, 451, 34, 203, 1377, 411, 451, 34, 78, 318, 1757, 451, 34, 203, 1377, 411, 451, 34, 78, 332, 1757, 451, 34, 203, 1377, 411, 451, 34, 6480, 1757, 451, 34, 203, 1377, 411, 451, 34, 10814, 1757, 451, 34, 203, 1377, 411, 451, 34, 13410, 1757, 451, 34, 203, 1377, 411, 451, 34, 82, 1527, 1757, 451, 34, 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select gold where rank = 5 col : rank \| nation \| gold \| silver \| bronze \| total row 1 : 1 \| cuba \| 4 \| 3 \| 2 \| 9 row 2 : 2 \| canada \| 4 \| 2 \| 1 \| 7 row 3 : 3 \| united states \| 2 \| 0 \| 2 \| 4 row 4 : 4 \| mexico \| 1 \| 1 \| 0 \| 2 row 5 : 5 \| ecuador \| 1 \| 0 \| 0 \| 1 row 6 : 6 \| argentina \| 0 \| 4 \| 3 \| 7 row 7 : 7 \| brazil \| 0 \| 2 \| 2 \| 4 row 8 : 8 \| chile \| 0 \| 0 \| 1 \| 1 row 9 : 8 \| venezuela \| 0 \| 0 \| 1 \| 1 row 10 : total \| total \| 12 \| 12 \| 12 \| 36	col : gold row 1 : 1	select gold where rank = 5 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & cuba & 4 & 3 & 2 & 9 \\ 1 & 2 & canada & 4 & 2 & 1 & 7 \\ 2 & 3 & united states & 2 & 0 & 2 & 4 \\ 3 & 4 & mexico & 1 & 1 & 0 & 2 \\ 4 & 5 & ecuador & 1 & 0 & 0 & 1 \\ 5 & 6 & argentina & 0 & 4 & 3 & 7 \\ 6 & 7 & brazil & 0 & 2 & 2 & 4 \\ 7 & 8 & chile & 0 & 0 & 1 & 1 \\ 8 & 8 & venezuela & 0 & 0 & 1 & 1 \\ 9 & total & total & 12 & 12 & 12 & 36 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & gold \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select gold where rank = 5 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>cuba</td> <td>4</td> <td>3</td> <td>2</td> <td>9</td> </tr> <tr> <th>1</th> <td>2</td> <td>canada</td> <td>4</td> <td>2</td> <td>1</td> <td>7</td> </tr> <tr> <th>2</th> <td>3</td> <td>united states</td> <td>2</td> <td>0</td> <td>2</td> <td>4</td> </tr> <tr> <th>3</th> <td>4</td> <td>mexico</td> <td>1</td> <td>1</td> <td>0</td> <td>2</td> </tr> <tr> <th>4</th> <td>5</td> <td>ecuador</td> <td>1</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>5</th> <td>6</td> <td>argentina</td> <td>0</td> <td>4</td> <td>3</td> <td>7</td> </tr> <tr> <th>6</th> <td>7</td> <td>brazil</td> <td>0</td> <td>2</td> <td>2</td> <td>4</td> </tr> <tr> <th>7</th> <td>8</td> <td>chile</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>8</th> <td>8</td> <td>venezuela</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>9</th> <td>total</td> <td>total</td> <td>12</td> <td>12</td> <td>12</td> <td>36</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>gold</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select gold where rank = 5 <table_name> : table \| \| rank \| nation \| gold \| silver \| bronze \| total \| \|---:\|:-------\|:--------------\|-------:\|---------:\|---------:\|--------:\| \| 0 \| 1 \| cuba \| 4 \| 3 \| 2 \| 9 \| \| 1 \| 2 \| canada \| 4 \| 2 \| 1 \| 7 \| \| 2 \| 3 \| united states \| 2 \| 0 \| 2 \| 4 \| \| 3 \| 4 \| mexico \| 1 \| 1 \| 0 \| 2 \| \| 4 \| 5 \| ecuador \| 1 \| 0 \| 0 \| 1 \| \| 5 \| 6 \| argentina \| 0 \| 4 \| 3 \| 7 \| \| 6 \| 7 \| brazil \| 0 \| 2 \| 2 \| 4 \| \| 7 \| 8 \| chile \| 0 \| 0 \| 1 \| 1 \| \| 8 \| 8 \| venezuela \| 0 \| 0 \| 1 \| 1 \| \| 9 \| total \| total \| 12 \| 12 \| 12 \| 36 \|	\| \| gold \| \|---:\|-------:\| \| 0 \| 1 \|	[ [ 1, 4025, 20465, 1625, 6171, 273, 1381, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 82, 367, 1757, 451, 34, 203, 1377, 411, 451, 34, 75, 1673, 1757, 451, 34, 203, 1377, 411, 451, 34, 25119, 502, 1757, 451, 34, 203, 1377, 411, 451, 34, 70, 1949, 8489, 1757, 451, 34, 203, 1377, 411, 451, 34, 4963, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 21, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 71, 373, 69, 1757, 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select runners-up + runners-up where team = 'swindon town' col : team \| winners \| runners-up \| years won \| years runner-up row 1 : liverpool \| 8 \| 3 \| 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 \| 1978, 1987, 2005 row 2 : aston villa \| 5 \| 3 \| 1961, 1975, 1977, 1994, 1996 \| 1963, 1971, 2010 row 3 : manchester united \| 4 \| 4 \| 1992, 2006, 2009, 2010 \| 1983, 1991, 1994, 2003 row 4 : tottenham hotspur \| 4 \| 3 \| 1971, 1973, 1999, 2008 \| 1982, 2002, 2009 row 5 : chelsea \| 4 \| 2 \| 1965, 1998, 2005, 2007 \| 1972, 2008 row 6 : nottingham forest \| 4 \| 2 \| 1978, 1979, 1989, 1990 \| 1980, 1992 row 7 : leicester city \| 3 \| 2 \| 1964, 1997, 2000 \| 1965, 1999 row 8 : manchester city \| 3 \| 1 \| 1970, 1976, 2014 \| 1974 row 9 : arsenal \| 2 \| 5 \| 1987, 1993 \| 1968, 1969, 1988, 2007, 2011 row 10 : norwich city \| 2 \| 2 \| 1962, 1985 \| 1973, 1975 row 11 : birmingham city \| 2 \| 1 \| 1963, 2011 \| 2001 row 12 : wolverhampton wanderers \| 2 \| 0 \| 1974, 1980 \| none row 13 : west bromwich albion \| 1 \| 2 \| 1966 \| 1967, 1970 row 14 : middlesbrough \| 1 \| 2 \| 2004 \| 1997, 1998 row 15 : queens park rangers \| 1 \| 1 \| 1967 \| 1986 row 16 : leeds united \| 1 \| 1 \| 1968 \| 1996 row 17 : stoke city \| 1 \| 1 \| 1972 \| 1964 row 18 : luton town \| 1 \| 1 \| 1988 \| 1989 row 19 : sheffield wednesday \| 1 \| 1 \| 1991 \| 1993 row 20 : swindon town \| 1 \| 0 \| 1969 \| none row 21 : oxford united \| 1 \| 0 \| 1986 \| none row 22 : blackburn rovers \| 1 \| 0 \| 2002 \| none row 23 : swansea city \| 1 \| 0 \| 2013 \| none row 24 : west ham united \| 0 \| 2 \| none \| 1966, 1981 row 25 : everton \| 0 \| 2 \| none \| 1977, 1984 row 26 : bolton wanderers \| 0 \| 2 \| none \| 1995, 2004 row 27 : sunderland \| 0 \| 2 \| none \| 1985, 2014 row 28 : rotherham united \| 0 \| 1 \| none \| 1961 row 29 : rochdale \| 0 \| 1 \| none \| 1962 row 30 : newcastle united \| 0 \| 1 \| none \| 1976 row 31 : southampton \| 0 \| 1 \| none \| 1979 row 32 : oldham athletic \| 0 \| 1 \| none \| 1990 row 33 : tranmere rovers \| 0 \| 1 \| none \| 2000 row 34 : wigan athletic \| 0 \| 1 \| none \| 2006 row 35 : cardiff city \| 0 \| 1 \| none \| 2012 row 36 : bradford city \| 0 \| 1 \| none \| 2013	col : "runners-up + runners-up" row 1 : runners-up + runners-up	select runners-up + runners-up where team = 'swindon town' <table_name> : table \begin{tabular}{llllll} \toprule & team & winners & runners-up & years won & years runner-up \\ \midrule 0 & liverpool & 8 & 3 & 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 & 1978, 1987, 2005 \\ 1 & aston villa & 5 & 3 & 1961, 1975, 1977, 1994, 1996 & 1963, 1971, 2010 \\ 2 & manchester united & 4 & 4 & 1992, 2006, 2009, 2010 & 1983, 1991, 1994, 2003 \\ 3 & tottenham hotspur & 4 & 3 & 1971, 1973, 1999, 2008 & 1982, 2002, 2009 \\ 4 & chelsea & 4 & 2 & 1965, 1998, 2005, 2007 & 1972, 2008 \\ 5 & nottingham forest & 4 & 2 & 1978, 1979, 1989, 1990 & 1980, 1992 \\ 6 & leicester city & 3 & 2 & 1964, 1997, 2000 & 1965, 1999 \\ 7 & manchester city & 3 & 1 & 1970, 1976, 2014 & 1974 \\ 8 & arsenal & 2 & 5 & 1987, 1993 & 1968, 1969, 1988, 2007, 2011 \\ 9 & norwich city & 2 & 2 & 1962, 1985 & 1973, 1975 \\ 10 & birmingham city & 2 & 1 & 1963, 2011 & 2001 \\ 11 & wolverhampton wanderers & 2 & 0 & 1974, 1980 & none \\ 12 & west bromwich albion & 1 & 2 & 1966 & 1967, 1970 \\ 13 & middlesbrough & 1 & 2 & 2004 & 1997, 1998 \\ 14 & queens park rangers & 1 & 1 & 1967 & 1986 \\ 15 & leeds united & 1 & 1 & 1968 & 1996 \\ 16 & stoke city & 1 & 1 & 1972 & 1964 \\ 17 & luton town & 1 & 1 & 1988 & 1989 \\ 18 & sheffield wednesday & 1 & 1 & 1991 & 1993 \\ 19 & swindon town & 1 & 0 & 1969 & none \\ 20 & oxford united & 1 & 0 & 1986 & none \\ 21 & blackburn rovers & 1 & 0 & 2002 & none \\ 22 & swansea city & 1 & 0 & 2013 & none \\ 23 & west ham united & 0 & 2 & none & 1966, 1981 \\ 24 & everton & 0 & 2 & none & 1977, 1984 \\ 25 & bolton wanderers & 0 & 2 & none & 1995, 2004 \\ 26 & sunderland & 0 & 2 & none & 1985, 2014 \\ 27 & rotherham united & 0 & 1 & none & 1961 \\ 28 & rochdale & 0 & 1 & none & 1962 \\ 29 & newcastle united & 0 & 1 & none & 1976 \\ 30 & southampton & 0 & 1 & none & 1979 \\ 31 & oldham athletic & 0 & 1 & none & 1990 \\ 32 & tranmere rovers & 0 & 1 & none & 2000 \\ 33 & wigan athletic & 0 & 1 & none & 2006 \\ 34 & cardiff city & 0 & 1 & none & 2012 \\ 35 & bradford city & 0 & 1 & none & 2013 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & "runners-up + runners-up" \\ \midrule 0 & runners-up + runners-up \\ \bottomrule \end{tabular}	select runners-up + runners-up where team = 'swindon town' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>winners</th> <th>runners-up</th> <th>years won</th> <th>years runner-up</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>liverpool</td> <td>8</td> <td>3</td> <td>1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012</td> <td>1978, 1987, 2005</td> </tr> <tr> <th>1</th> <td>aston villa</td> <td>5</td> <td>3</td> <td>1961, 1975, 1977, 1994, 1996</td> <td>1963, 1971, 2010</td> </tr> <tr> <th>2</th> <td>manchester united</td> <td>4</td> <td>4</td> <td>1992, 2006, 2009, 2010</td> <td>1983, 1991, 1994, 2003</td> </tr> <tr> <th>3</th> <td>tottenham hotspur</td> <td>4</td> <td>3</td> <td>1971, 1973, 1999, 2008</td> <td>1982, 2002, 2009</td> </tr> <tr> <th>4</th> <td>chelsea</td> <td>4</td> <td>2</td> <td>1965, 1998, 2005, 2007</td> <td>1972, 2008</td> </tr> <tr> <th>5</th> <td>nottingham forest</td> <td>4</td> <td>2</td> <td>1978, 1979, 1989, 1990</td> <td>1980, 1992</td> </tr> <tr> <th>6</th> <td>leicester city</td> <td>3</td> <td>2</td> <td>1964, 1997, 2000</td> <td>1965, 1999</td> </tr> <tr> <th>7</th> <td>manchester city</td> <td>3</td> <td>1</td> <td>1970, 1976, 2014</td> <td>1974</td> </tr> <tr> <th>8</th> <td>arsenal</td> <td>2</td> <td>5</td> <td>1987, 1993</td> <td>1968, 1969, 1988, 2007, 2011</td> </tr> <tr> <th>9</th> <td>norwich city</td> <td>2</td> <td>2</td> <td>1962, 1985</td> <td>1973, 1975</td> </tr> <tr> <th>10</th> <td>birmingham city</td> <td>2</td> <td>1</td> <td>1963, 2011</td> <td>2001</td> </tr> <tr> <th>11</th> <td>wolverhampton wanderers</td> <td>2</td> <td>0</td> <td>1974, 1980</td> <td>none</td> </tr> <tr> <th>12</th> <td>west bromwich albion</td> <td>1</td> <td>2</td> <td>1966</td> <td>1967, 1970</td> </tr> <tr> <th>13</th> <td>middlesbrough</td> <td>1</td> <td>2</td> <td>2004</td> <td>1997, 1998</td> </tr> <tr> <th>14</th> <td>queens park rangers</td> <td>1</td> <td>1</td> <td>1967</td> <td>1986</td> </tr> <tr> <th>15</th> <td>leeds united</td> <td>1</td> <td>1</td> <td>1968</td> <td>1996</td> </tr> <tr> <th>16</th> <td>stoke city</td> <td>1</td> <td>1</td> <td>1972</td> <td>1964</td> </tr> <tr> <th>17</th> <td>luton town</td> <td>1</td> <td>1</td> <td>1988</td> <td>1989</td> </tr> <tr> <th>18</th> <td>sheffield wednesday</td> <td>1</td> <td>1</td> <td>1991</td> <td>1993</td> </tr> <tr> <th>19</th> <td>swindon town</td> <td>1</td> <td>0</td> <td>1969</td> <td>none</td> </tr> <tr> <th>20</th> <td>oxford united</td> <td>1</td> <td>0</td> <td>1986</td> <td>none</td> </tr> <tr> <th>21</th> <td>blackburn rovers</td> <td>1</td> <td>0</td> <td>2002</td> <td>none</td> </tr> <tr> <th>22</th> <td>swansea city</td> <td>1</td> <td>0</td> <td>2013</td> <td>none</td> </tr> <tr> <th>23</th> <td>west ham united</td> <td>0</td> <td>2</td> <td>none</td> <td>1966, 1981</td> </tr> <tr> <th>24</th> <td>everton</td> <td>0</td> <td>2</td> <td>none</td> <td>1977, 1984</td> </tr> <tr> <th>25</th> <td>bolton wanderers</td> <td>0</td> <td>2</td> <td>none</td> <td>1995, 2004</td> </tr> <tr> <th>26</th> <td>sunderland</td> <td>0</td> <td>2</td> <td>none</td> <td>1985, 2014</td> </tr> <tr> <th>27</th> <td>rotherham united</td> <td>0</td> <td>1</td> <td>none</td> <td>1961</td> </tr> <tr> <th>28</th> <td>rochdale</td> <td>0</td> <td>1</td> <td>none</td> <td>1962</td> </tr> <tr> <th>29</th> <td>newcastle united</td> <td>0</td> <td>1</td> <td>none</td> <td>1976</td> </tr> <tr> <th>30</th> <td>southampton</td> <td>0</td> <td>1</td> <td>none</td> <td>1979</td> </tr> <tr> <th>31</th> <td>oldham athletic</td> <td>0</td> <td>1</td> <td>none</td> <td>1990</td> </tr> <tr> <th>32</th> <td>tranmere rovers</td> <td>0</td> <td>1</td> <td>none</td> <td>2000</td> </tr> <tr> <th>33</th> <td>wigan athletic</td> <td>0</td> <td>1</td> <td>none</td> <td>2006</td> </tr> <tr> <th>34</th> <td>cardiff city</td> <td>0</td> <td>1</td> <td>none</td> <td>2012</td> </tr> <tr> <th>35</th> <td>bradford city</td> <td>0</td> <td>1</td> <td>none</td> <td>2013</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"runners-up + runners-up"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>runners-up + runners-up</td> </tr> </tbody> </table>	select runners-up + runners-up where team = 'swindon town' <table_name> : table \| \| team \| winners \| runners-up \| years won \| years runner-up \| \|---:\|:------------------------\|----------:\|-------------:\|:-----------------------------------------------\|:-----------------------------\| \| 0 \| liverpool \| 8 \| 3 \| 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 \| 1978, 1987, 2005 \| \| 1 \| aston villa \| 5 \| 3 \| 1961, 1975, 1977, 1994, 1996 \| 1963, 1971, 2010 \| \| 2 \| manchester united \| 4 \| 4 \| 1992, 2006, 2009, 2010 \| 1983, 1991, 1994, 2003 \| \| 3 \| tottenham hotspur \| 4 \| 3 \| 1971, 1973, 1999, 2008 \| 1982, 2002, 2009 \| \| 4 \| chelsea \| 4 \| 2 \| 1965, 1998, 2005, 2007 \| 1972, 2008 \| \| 5 \| nottingham forest \| 4 \| 2 \| 1978, 1979, 1989, 1990 \| 1980, 1992 \| \| 6 \| leicester city \| 3 \| 2 \| 1964, 1997, 2000 \| 1965, 1999 \| \| 7 \| manchester city \| 3 \| 1 \| 1970, 1976, 2014 \| 1974 \| \| 8 \| arsenal \| 2 \| 5 \| 1987, 1993 \| 1968, 1969, 1988, 2007, 2011 \| \| 9 \| norwich city \| 2 \| 2 \| 1962, 1985 \| 1973, 1975 \| \| 10 \| birmingham city \| 2 \| 1 \| 1963, 2011 \| 2001 \| \| 11 \| wolverhampton wanderers \| 2 \| 0 \| 1974, 1980 \| none \| \| 12 \| west bromwich albion \| 1 \| 2 \| 1966 \| 1967, 1970 \| \| 13 \| middlesbrough \| 1 \| 2 \| 2004 \| 1997, 1998 \| \| 14 \| queens park rangers \| 1 \| 1 \| 1967 \| 1986 \| \| 15 \| leeds united \| 1 \| 1 \| 1968 \| 1996 \| \| 16 \| stoke city \| 1 \| 1 \| 1972 \| 1964 \| \| 17 \| luton town \| 1 \| 1 \| 1988 \| 1989 \| \| 18 \| sheffield wednesday \| 1 \| 1 \| 1991 \| 1993 \| \| 19 \| swindon town \| 1 \| 0 \| 1969 \| none \| \| 20 \| oxford united \| 1 \| 0 \| 1986 \| none \| \| 21 \| blackburn rovers \| 1 \| 0 \| 2002 \| none \| \| 22 \| swansea city \| 1 \| 0 \| 2013 \| none \| \| 23 \| west ham united \| 0 \| 2 \| none \| 1966, 1981 \| \| 24 \| everton \| 0 \| 2 \| none \| 1977, 1984 \| \| 25 \| bolton wanderers \| 0 \| 2 \| none \| 1995, 2004 \| \| 26 \| sunderland \| 0 \| 2 \| none \| 1985, 2014 \| \| 27 \| rotherham united \| 0 \| 1 \| none \| 1961 \| \| 28 \| rochdale \| 0 \| 1 \| none \| 1962 \| \| 29 \| newcastle united \| 0 \| 1 \| none \| 1976 \| \| 30 \| southampton \| 0 \| 1 \| none \| 1979 \| \| 31 \| oldham athletic \| 0 \| 1 \| none \| 1990 \| \| 32 \| tranmere rovers \| 0 \| 1 \| none \| 2000 \| \| 33 \| wigan athletic \| 0 \| 1 \| none \| 2006 \| \| 34 \| cardiff city \| 0 \| 1 \| none \| 2012 \| \| 35 \| bradford city \| 0 \| 1 \| none \| 2013 \|	\| \| "runners-up + runners-up" \| \|---:\|:----------------------------\| \| 0 \| runners-up + runners-up \|	[ [ 1, 4025, 1086, 9646, 17, 416, 397, 1086, 9646, 17, 416, 1625, 5927, 273, 296, 5328, 728, 265, 358, 91, 82, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 10035, 1757, 451, 34, 203, 1377, 411, 451, 34, 8082, 9646, 1757, 451, 34, 203, 1377, 411, 451, 34, 2681, 9646, 17, 416, 1757, 451, 34, 203, 1377, 411, 451, 34, 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select year where role = 'scott' col : year \| title \| role \| notes row 1 : 1999 \| bob rizzo's simply funk with suzanne \| himself \| as matthew j. morrison row 2 : 2003 \| marci x \| boyz r us \| as matthew j. morrison row 3 : 2005 \| once upon a mattress \| sir harry \| none row 4 : 2006 \| blinders \| scott \| none row 5 : 2007 \| music and lyrics \| ray \| none row 6 : 2007 \| dan in real life \| policeman \| none row 7 : 2007 \| i think i love my wife \| salesman #2 \| none row 8 : 2011 \| the muppets \| mahna mahna host \| none row 9 : 2012 \| what to expect when you're expecting \| evan \| none	col : year row 1 : 2006	select year where role = 'scott' <table_name> : table \begin{tabular}{lllll} \toprule & year & title & role & notes \\ \midrule 0 & 1999 & bob rizzo's simply funk with suzanne & himself & as matthew j. morrison \\ 1 & 2003 & marci x & boyz r us & as matthew j. morrison \\ 2 & 2005 & once upon a mattress & sir harry & none \\ 3 & 2006 & blinders & scott & none \\ 4 & 2007 & music and lyrics & ray & none \\ 5 & 2007 & dan in real life & policeman & none \\ 6 & 2007 & i think i love my wife & salesman #2 & none \\ 7 & 2011 & the muppets & mahna mahna host & none \\ 8 & 2012 & what to expect when you're expecting & evan & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 2006 \\ \bottomrule \end{tabular}	select year where role = 'scott' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>title</th> <th>role</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>bob rizzo's simply funk with suzanne</td> <td>himself</td> <td>as matthew j. morrison</td> </tr> <tr> <th>1</th> <td>2003</td> <td>marci x</td> <td>boyz r us</td> <td>as matthew j. morrison</td> </tr> <tr> <th>2</th> <td>2005</td> <td>once upon a mattress</td> <td>sir harry</td> <td>none</td> </tr> <tr> <th>3</th> <td>2006</td> <td>blinders</td> <td>scott</td> <td>none</td> </tr> <tr> <th>4</th> <td>2007</td> <td>music and lyrics</td> <td>ray</td> <td>none</td> </tr> <tr> <th>5</th> <td>2007</td> <td>dan in real life</td> <td>policeman</td> <td>none</td> </tr> <tr> <th>6</th> <td>2007</td> <td>i think i love my wife</td> <td>salesman #2</td> <td>none</td> </tr> <tr> <th>7</th> <td>2011</td> <td>the muppets</td> <td>mahna mahna host</td> <td>none</td> </tr> <tr> <th>8</th> <td>2012</td> <td>what to expect when you're expecting</td> <td>evan</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2006</td> </tr> </tbody> </table>	select year where role = 'scott' <table_name> : table \| \| year \| title \| role \| notes \| \|---:\|-------:\|:-------------------------------------\|:-----------------\|:-----------------------\| \| 0 \| 1999 \| bob rizzo's simply funk with suzanne \| himself \| as matthew j. morrison \| \| 1 \| 2003 \| marci x \| boyz r us \| as matthew j. morrison \| \| 2 \| 2005 \| once upon a mattress \| sir harry \| none \| \| 3 \| 2006 \| blinders \| scott \| none \| \| 4 \| 2007 \| music and lyrics \| ray \| none \| \| 5 \| 2007 \| dan in real life \| policeman \| none \| \| 6 \| 2007 \| i think i love my wife \| salesman #2 \| none \| \| 7 \| 2011 \| the muppets \| mahna mahna host \| none \| \| 8 \| 2012 \| what to expect when you're expecting \| evan \| none \|	\| \| year \| \|---:\|-------:\| \| 0 \| 2006 \|	[ [ 1, 4025, 3286, 1625, 2478, 273, 296, 1017, 352, 88, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 2649, 1757, 451, 34, 203, 1377, 411, 451, 34, 4615, 1757, 451, 34, 203, 1377, 411, 451, 34, 12903, 1757, 451, 34, 203, 565, 7765, 313, 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select count ( result ) where date = 'none' col : week \| date \| tv time \| opponent \| result \| attendance \| bye row 1 : 1 \| september 6, 1998 \| fox 1:05 pm mt \| at dallas cowboys \| l 38-10 \| 63602 \| 0 row 2 : 2 \| september 13, 1998 \| fox 1:15 pm mt \| at seattle seahawks \| l 33-14 \| 57678 \| 0 row 3 : 3 \| september 20, 1998 \| espn 5:15 pm mt \| philadelphia eagles \| w 17-3 \| 39782 \| 0 row 4 : 4 \| september 27, 1998 \| fox 10:00 am mt \| at st. louis rams \| w 20-17 \| 55832 \| 0 row 5 : 5 \| october 4, 1998 \| cbs 1:05 pm mt \| oakland raiders \| l 23-20 \| 53,24 \| 0 row 6 : 6 \| october 11, 1998 \| fox 1:05 pm mt \| chicago bears \| w 20-7 \| 50495 \| 0 row 7 : 7 \| october 18, 1998 \| fox 10:00 am mt \| at new york giants \| l 34-7 \| 70456 \| 0 row 8 : 8 \| none \| none \| none \| none \| none \| 1 row 9 : 9 \| november 1, 1998 \| fox 11:00 am mt \| at detroit lions \| w 17-15 \| 66087 \| 0 row 10 : 10 \| november 8, 1998 \| fox 2:15 pm mt \| washington redskins \| w 29-27 \| 45,95 \| 0 row 11 : 11 \| november 15, 1998 \| fox 2:15 pm mt \| dallas cowboys \| l 35-28 \| 71,67 \| 0 row 12 : 12 \| november 22, 1998 \| fox 11:00 am mt \| at washington redskins \| w 45-42 \| 63435 \| 0 row 13 : 13 \| november 29, 1998 \| fox 11:00 am mt \| at kansas city chiefs \| l 34-24 \| 69613 \| 0 row 14 : 14 \| december 6, 1998 \| fox 2:15 pm mt \| new york giants \| l 23-19 \| 46128 \| 0 row 15 : 15 \| december 13, 1998 \| fox 11:00 am mt \| at philadelphia eagles \| w 20-17 \| 62176 \| 0 row 16 : 16 \| december 20, 1998 \| fox 2:05 pm mt \| new orleans saints \| w 19-17 \| 51617 \| 0 row 17 : 17 \| december 27, 1998 \| cbs 2:05 pm mt \| san diego chargers \| w 16-13 \| 71,67 \| 0	col : count ( "result" ) row 1 : 1	select count ( result ) where date = 'none' <table_name> : table \begin{tabular}{llllllll} \toprule & week & date & tv time & opponent & result & attendance & bye \\ \midrule 0 & 1 & september 6, 1998 & fox 1:05 pm mt & at dallas cowboys & l 38-10 & 63602 & 0 \\ 1 & 2 & september 13, 1998 & fox 1:15 pm mt & at seattle seahawks & l 33-14 & 57678 & 0 \\ 2 & 3 & september 20, 1998 & espn 5:15 pm mt & philadelphia eagles & w 17-3 & 39782 & 0 \\ 3 & 4 & september 27, 1998 & fox 10:00 am mt & at st. louis rams & w 20-17 & 55832 & 0 \\ 4 & 5 & october 4, 1998 & cbs 1:05 pm mt & oakland raiders & l 23-20 & 53,24 & 0 \\ 5 & 6 & october 11, 1998 & fox 1:05 pm mt & chicago bears & w 20-7 & 50495 & 0 \\ 6 & 7 & october 18, 1998 & fox 10:00 am mt & at new york giants & l 34-7 & 70456 & 0 \\ 7 & 8 & none & none & none & none & none & 1 \\ 8 & 9 & november 1, 1998 & fox 11:00 am mt & at detroit lions & w 17-15 & 66087 & 0 \\ 9 & 10 & november 8, 1998 & fox 2:15 pm mt & washington redskins & w 29-27 & 45,95 & 0 \\ 10 & 11 & november 15, 1998 & fox 2:15 pm mt & dallas cowboys & l 35-28 & 71,67 & 0 \\ 11 & 12 & november 22, 1998 & fox 11:00 am mt & at washington redskins & w 45-42 & 63435 & 0 \\ 12 & 13 & november 29, 1998 & fox 11:00 am mt & at kansas city chiefs & l 34-24 & 69613 & 0 \\ 13 & 14 & december 6, 1998 & fox 2:15 pm mt & new york giants & l 23-19 & 46128 & 0 \\ 14 & 15 & december 13, 1998 & fox 11:00 am mt & at philadelphia eagles & w 20-17 & 62176 & 0 \\ 15 & 16 & december 20, 1998 & fox 2:05 pm mt & new orleans saints & w 19-17 & 51617 & 0 \\ 16 & 17 & december 27, 1998 & cbs 2:05 pm mt & san diego chargers & w 16-13 & 71,67 & 0 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "result" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( result ) where date = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>week</th> <th>date</th> <th>tv time</th> <th>opponent</th> <th>result</th> <th>attendance</th> <th>bye</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>september 6, 1998</td> <td>fox 1:05 pm mt</td> <td>at dallas cowboys</td> <td>l 38-10</td> <td>63602</td> <td>0</td> </tr> <tr> <th>1</th> <td>2</td> <td>september 13, 1998</td> <td>fox 1:15 pm mt</td> <td>at seattle seahawks</td> <td>l 33-14</td> <td>57678</td> <td>0</td> </tr> <tr> <th>2</th> <td>3</td> <td>september 20, 1998</td> <td>espn 5:15 pm mt</td> <td>philadelphia eagles</td> <td>w 17-3</td> <td>39782</td> <td>0</td> </tr> <tr> <th>3</th> <td>4</td> <td>september 27, 1998</td> <td>fox 10:00 am mt</td> <td>at st. louis rams</td> <td>w 20-17</td> <td>55832</td> <td>0</td> </tr> <tr> <th>4</th> <td>5</td> <td>october 4, 1998</td> <td>cbs 1:05 pm mt</td> <td>oakland raiders</td> <td>l 23-20</td> <td>53,24</td> <td>0</td> </tr> <tr> <th>5</th> <td>6</td> <td>october 11, 1998</td> <td>fox 1:05 pm mt</td> <td>chicago bears</td> <td>w 20-7</td> <td>50495</td> <td>0</td> </tr> <tr> <th>6</th> <td>7</td> <td>october 18, 1998</td> <td>fox 10:00 am mt</td> <td>at new york giants</td> <td>l 34-7</td> <td>70456</td> <td>0</td> </tr> <tr> <th>7</th> <td>8</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>1</td> </tr> <tr> <th>8</th> <td>9</td> <td>november 1, 1998</td> <td>fox 11:00 am mt</td> <td>at detroit lions</td> <td>w 17-15</td> <td>66087</td> <td>0</td> </tr> <tr> <th>9</th> <td>10</td> <td>november 8, 1998</td> <td>fox 2:15 pm mt</td> <td>washington redskins</td> <td>w 29-27</td> <td>45,95</td> <td>0</td> </tr> <tr> <th>10</th> <td>11</td> <td>november 15, 1998</td> <td>fox 2:15 pm mt</td> <td>dallas cowboys</td> <td>l 35-28</td> <td>71,67</td> <td>0</td> </tr> <tr> <th>11</th> <td>12</td> <td>november 22, 1998</td> <td>fox 11:00 am mt</td> <td>at washington redskins</td> <td>w 45-42</td> <td>63435</td> <td>0</td> </tr> <tr> <th>12</th> <td>13</td> <td>november 29, 1998</td> <td>fox 11:00 am mt</td> <td>at kansas city chiefs</td> <td>l 34-24</td> <td>69613</td> <td>0</td> </tr> <tr> <th>13</th> <td>14</td> <td>december 6, 1998</td> <td>fox 2:15 pm mt</td> <td>new york giants</td> <td>l 23-19</td> <td>46128</td> <td>0</td> </tr> <tr> <th>14</th> <td>15</td> <td>december 13, 1998</td> <td>fox 11:00 am mt</td> <td>at philadelphia eagles</td> <td>w 20-17</td> <td>62176</td> <td>0</td> </tr> <tr> <th>15</th> <td>16</td> <td>december 20, 1998</td> <td>fox 2:05 pm mt</td> <td>new orleans saints</td> <td>w 19-17</td> <td>51617</td> <td>0</td> </tr> <tr> <th>16</th> <td>17</td> <td>december 27, 1998</td> <td>cbs 2:05 pm mt</td> <td>san diego chargers</td> <td>w 16-13</td> <td>71,67</td> <td>0</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "result" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( result ) where date = 'none' <table_name> : table \| \| week \| date \| tv time \| opponent \| result \| attendance \| bye \| \|---:\|-------:\|:-------------------\|:----------------\|:-----------------------\|:---------\|:-------------\|------:\| \| 0 \| 1 \| september 6, 1998 \| fox 1:05 pm mt \| at dallas cowboys \| l 38-10 \| 63602 \| 0 \| \| 1 \| 2 \| september 13, 1998 \| fox 1:15 pm mt \| at seattle seahawks \| l 33-14 \| 57678 \| 0 \| \| 2 \| 3 \| september 20, 1998 \| espn 5:15 pm mt \| philadelphia eagles \| w 17-3 \| 39782 \| 0 \| \| 3 \| 4 \| september 27, 1998 \| fox 10:00 am mt \| at st. louis rams \| w 20-17 \| 55832 \| 0 \| \| 4 \| 5 \| october 4, 1998 \| cbs 1:05 pm mt \| oakland raiders \| l 23-20 \| 53,24 \| 0 \| \| 5 \| 6 \| october 11, 1998 \| fox 1:05 pm mt \| chicago bears \| w 20-7 \| 50495 \| 0 \| \| 6 \| 7 \| october 18, 1998 \| fox 10:00 am mt \| at new york giants \| l 34-7 \| 70456 \| 0 \| \| 7 \| 8 \| none \| none \| none \| none \| none \| 1 \| \| 8 \| 9 \| november 1, 1998 \| fox 11:00 am mt \| at detroit lions \| w 17-15 \| 66087 \| 0 \| \| 9 \| 10 \| november 8, 1998 \| fox 2:15 pm mt \| washington redskins \| w 29-27 \| 45,95 \| 0 \| \| 10 \| 11 \| november 15, 1998 \| fox 2:15 pm mt \| dallas cowboys \| l 35-28 \| 71,67 \| 0 \| \| 11 \| 12 \| november 22, 1998 \| fox 11:00 am mt \| at washington redskins \| w 45-42 \| 63435 \| 0 \| \| 12 \| 13 \| november 29, 1998 \| fox 11:00 am mt \| at kansas city chiefs \| l 34-24 \| 69613 \| 0 \| \| 13 \| 14 \| december 6, 1998 \| fox 2:15 pm mt \| new york giants \| l 23-19 \| 46128 \| 0 \| \| 14 \| 15 \| december 13, 1998 \| fox 11:00 am mt \| at philadelphia eagles \| w 20-17 \| 62176 \| 0 \| \| 15 \| 16 \| december 20, 1998 \| fox 2:05 pm mt \| new orleans saints \| w 19-17 \| 51617 \| 0 \| \| 16 \| 17 \| december 27, 1998 \| cbs 2:05 pm mt \| san diego chargers \| w 16-13 \| 71,67 \| 0 \|	\| \| count ( "result" ) \| \|---:\|---------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 563, 262, 1625, 1509, 273, 296, 6102, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 10741, 1757, 451, 34, 203, 1377, 411, 451, 34, 712, 1757, 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select year where award = 'capital awards' col : year \| award \| nominated work \| category \| result row 1 : 2007 \| cosmopolitan ultimate woman of the year \| leona lewis \| newcomer of the year \| won row 2 : 2007 \| the record of the year \| "bleeding love" \| the record of the year \| won row 3 : 2008 \| capital awards \| leona lewis \| favourite uk female artist \| won row 4 : 2008 \| britain's best \| leona lewis \| music award \| won row 5 : 2008 \| newnownext awards \| leona lewis \| the kylie award: next international crossover \| won row 6 : 2008 \| glamour woman of the year awards \| leona lewis \| uk solo artist \| won row 7 : 2008 \| nickelodeon uk kids choice awards \| "bleeding love" \| favourite song \| won row 8 : 2008 \| uk music video awards \| "bleeding love" \| people's choice award \| won row 9 : 2008 \| bambi award \| leona lewis \| shooting star \| won row 10 : 2008 \| new music weekly awards \| leona lewis \| top 40 new artist of the year \| won row 11 : 2008 \| billboard 2008 year end award \| leona lewis \| best new artist \| won row 12 : 2008 \| vh1 video of the year \| "bleeding love" \| best video \| won row 13 : 2008 \| nme best album \| "spirit" \| best album \| nominated row 14 : 2008 \| peta \| leona lewis \| person of the year \| won row 15 : 2009 \| naacp image awards \| leona lewis \| outstanding new artist \| nominated row 16 : 2009 \| swiss music awards \| leona lewis \| best international newcomer \| won row 17 : 2009 \| japan gold disc awards \| leona lewis \| new artist of the year \| won row 18 : 2009 \| hito pop music awards \| "bleeding love" \| best western song \| won row 19 : 2009 \| peta - sexiest vegetarian alive awards \| leona lewis \| sexiest vegetarian celebrity 2009 \| won row 20 : 2009 \| apra awards \| "bleeding love" \| most played foreign work \| won row 21 : 2009 \| beffta awards \| leona lewis \| best female act \| won row 22 : 2009 \| cosmopolitan awards \| leona lewis \| ultimate music star \| won	col : year row 1 : 2008	select year where award = 'capital awards' <table_name> : table \begin{tabular}{llllll} \toprule & year & award & nominated work & category & result \\ \midrule 0 & 2007 & cosmopolitan ultimate woman of the year & leona lewis & newcomer of the year & won \\ 1 & 2007 & the record of the year & "bleeding love" & the record of the year & won \\ 2 & 2008 & capital awards & leona lewis & favourite uk female artist & won \\ 3 & 2008 & britain's best & leona lewis & music award & won \\ 4 & 2008 & newnownext awards & leona lewis & the kylie award: next international crossover & won \\ 5 & 2008 & glamour woman of the year awards & leona lewis & uk solo artist & won \\ 6 & 2008 & nickelodeon uk kids choice awards & "bleeding love" & favourite song & won \\ 7 & 2008 & uk music video awards & "bleeding love" & people's choice award & won \\ 8 & 2008 & bambi award & leona lewis & shooting star & won \\ 9 & 2008 & new music weekly awards & leona lewis & top 40 new artist of the year & won \\ 10 & 2008 & billboard 2008 year end award & leona lewis & best new artist & won \\ 11 & 2008 & vh1 video of the year & "bleeding love" & best video & won \\ 12 & 2008 & nme best album & "spirit" & best album & nominated \\ 13 & 2008 & peta & leona lewis & person of the year & won \\ 14 & 2009 & naacp image awards & leona lewis & outstanding new artist & nominated \\ 15 & 2009 & swiss music awards & leona lewis & best international newcomer & won \\ 16 & 2009 & japan gold disc awards & leona lewis & new artist of the year & won \\ 17 & 2009 & hito pop music awards & "bleeding love" & best western song & won \\ 18 & 2009 & peta - sexiest vegetarian alive awards & leona lewis & sexiest vegetarian celebrity 2009 & won \\ 19 & 2009 & apra awards & "bleeding love" & most played foreign work & won \\ 20 & 2009 & beffta awards & leona lewis & best female act & won \\ 21 & 2009 & cosmopolitan awards & leona lewis & ultimate music star & won \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 2008 \\ \bottomrule \end{tabular}	select year where award = 'capital awards' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>award</th> <th>nominated work</th> <th>category</th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2007</td> <td>cosmopolitan ultimate woman of the year</td> <td>leona lewis</td> <td>newcomer of the year</td> <td>won</td> </tr> <tr> <th>1</th> <td>2007</td> <td>the record of the year</td> <td>"bleeding love"</td> <td>the record of the year</td> <td>won</td> </tr> <tr> <th>2</th> <td>2008</td> <td>capital awards</td> <td>leona lewis</td> <td>favourite uk female artist</td> <td>won</td> </tr> <tr> <th>3</th> <td>2008</td> <td>britain's best</td> <td>leona lewis</td> <td>music award</td> <td>won</td> </tr> <tr> <th>4</th> <td>2008</td> <td>newnownext awards</td> <td>leona lewis</td> <td>the kylie award: next international crossover</td> <td>won</td> </tr> <tr> <th>5</th> <td>2008</td> <td>glamour woman of the year awards</td> <td>leona lewis</td> <td>uk solo artist</td> <td>won</td> </tr> <tr> <th>6</th> <td>2008</td> <td>nickelodeon uk kids choice awards</td> <td>"bleeding love"</td> <td>favourite song</td> <td>won</td> </tr> <tr> <th>7</th> <td>2008</td> <td>uk music video awards</td> <td>"bleeding love"</td> <td>people's choice award</td> <td>won</td> </tr> <tr> <th>8</th> <td>2008</td> <td>bambi award</td> <td>leona lewis</td> <td>shooting star</td> <td>won</td> </tr> <tr> <th>9</th> <td>2008</td> <td>new music weekly awards</td> <td>leona lewis</td> <td>top 40 new artist of the year</td> <td>won</td> </tr> <tr> <th>10</th> <td>2008</td> <td>billboard 2008 year end award</td> <td>leona lewis</td> <td>best new artist</td> <td>won</td> </tr> <tr> <th>11</th> <td>2008</td> <td>vh1 video of the year</td> <td>"bleeding love"</td> <td>best video</td> <td>won</td> </tr> <tr> <th>12</th> <td>2008</td> <td>nme best album</td> <td>"spirit"</td> <td>best album</td> <td>nominated</td> </tr> <tr> <th>13</th> <td>2008</td> <td>peta</td> <td>leona lewis</td> <td>person of the year</td> <td>won</td> </tr> <tr> <th>14</th> <td>2009</td> <td>naacp image awards</td> <td>leona lewis</td> <td>outstanding new artist</td> <td>nominated</td> </tr> <tr> <th>15</th> <td>2009</td> <td>swiss music awards</td> <td>leona lewis</td> <td>best international newcomer</td> <td>won</td> </tr> <tr> <th>16</th> <td>2009</td> <td>japan gold disc awards</td> <td>leona lewis</td> <td>new artist of the year</td> <td>won</td> </tr> <tr> <th>17</th> <td>2009</td> <td>hito pop music awards</td> <td>"bleeding love"</td> <td>best western song</td> <td>won</td> </tr> <tr> <th>18</th> <td>2009</td> <td>peta - sexiest vegetarian alive awards</td> <td>leona lewis</td> <td>sexiest vegetarian celebrity 2009</td> <td>won</td> </tr> <tr> <th>19</th> <td>2009</td> <td>apra awards</td> <td>"bleeding love"</td> <td>most played foreign work</td> <td>won</td> </tr> <tr> <th>20</th> <td>2009</td> <td>beffta awards</td> <td>leona lewis</td> <td>best female act</td> <td>won</td> </tr> <tr> <th>21</th> <td>2009</td> <td>cosmopolitan awards</td> <td>leona lewis</td> <td>ultimate music star</td> <td>won</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2008</td> </tr> </tbody> </table>	select year where award = 'capital awards' <table_name> : table \| \| year \| award \| nominated work \| category \| result \| \|---:\|-------:\|:----------------------------------------\|:-----------------\|:----------------------------------------------\|:----------\| \| 0 \| 2007 \| cosmopolitan ultimate woman of the year \| leona lewis \| newcomer of the year \| won \| \| 1 \| 2007 \| the record of the year \| "bleeding love" \| the record of the year \| won \| \| 2 \| 2008 \| capital awards \| leona lewis \| favourite uk female artist \| won \| \| 3 \| 2008 \| britain's best \| leona lewis \| music award \| won \| \| 4 \| 2008 \| newnownext awards \| leona lewis \| the kylie award: next international crossover \| won \| \| 5 \| 2008 \| glamour woman of the year awards \| leona lewis \| uk solo artist \| won \| \| 6 \| 2008 \| nickelodeon uk kids choice awards \| "bleeding love" \| favourite song \| won \| \| 7 \| 2008 \| uk music video awards \| "bleeding love" \| people's choice award \| won \| \| 8 \| 2008 \| bambi award \| leona lewis \| shooting star \| won \| \| 9 \| 2008 \| new music weekly awards \| leona lewis \| top 40 new artist of the year \| won \| \| 10 \| 2008 \| billboard 2008 year end award \| leona lewis \| best new artist \| won \| \| 11 \| 2008 \| vh1 video of the year \| "bleeding love" \| best video \| won \| \| 12 \| 2008 \| nme best album \| "spirit" \| best album \| nominated \| \| 13 \| 2008 \| peta \| leona lewis \| person of the year \| won \| \| 14 \| 2009 \| naacp image awards \| leona lewis \| outstanding new artist \| nominated \| \| 15 \| 2009 \| swiss music awards \| leona lewis \| best international newcomer \| won \| \| 16 \| 2009 \| japan gold disc awards \| leona lewis \| new artist of the year \| won \| \| 17 \| 2009 \| hito pop music awards \| "bleeding love" \| best western song \| won \| \| 18 \| 2009 \| peta - sexiest vegetarian alive awards \| leona lewis \| sexiest vegetarian celebrity 2009 \| won \| \| 19 \| 2009 \| apra awards \| "bleeding love" \| most played foreign work \| won \| \| 20 \| 2009 \| beffta awards \| leona lewis \| best female act \| won \| \| 21 \| 2009 \| cosmopolitan awards \| leona lewis \| ultimate music star \| won \|	\| \| year \| \|---:\|-------:\| \| 0 \| 2008 \|	[ [ 1, 4025, 3286, 1625, 279, 2913, 273, 296, 5909, 7053, 279, 6397, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 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select count ( * ) where player = 336 col : place \| player \| country \| score \| to par \| money ($) row 1 : 1 \| ralph guldahl \| united states \| 72-68-70-69=279 \| -9 \| 1,500 row 2 : 2 \| sam snead \| united states \| 70-70-72-68=280 \| -8 \| 800 row 3 : t3 \| billy burke \| united states \| 69-72-71-70=282 \| -6 \| 550 row 4 : t3 \| lawson little \| united states \| 72-72-68-70=282 \| -6 \| 550 row 5 : 5 \| gene sarazen \| united states \| 73-66-72-72=283 \| -5 \| 400 row 6 : 6 \| craig wood \| united states \| 72-73-71-68=284 \| -4 \| 300 row 7 : 7 \| byron nelson \| united states \| 71-69-72-75=287 \| -1 \| 250 row 8 : 8 \| henry picard \| united states \| 71-71-76-71=289 \| 1 \| 175 row 9 : 9 \| ben hogan \| united states \| 75-71-72-72=290 \| 2 \| 125 row 10 : t10 \| ed dudley \| united states \| 75-75-69-72=291 \| 3 \| 100 row 11 : t10 \| toney penna \| united states \| 72-75-72-72=291 \| 3 \| 100	col : count ( "*" ) row 1 : 0	select count ( * ) where player = 336 <table_name> : table \begin{tabular}{lllllll} \toprule & place & player & country & score & to par & money ($) \\ \midrule 0 & 1 & ralph guldahl & united states & 72-68-70-69=279 & -9 & 1,500 \\ 1 & 2 & sam snead & united states & 70-70-72-68=280 & -8 & 800 \\ 2 & t3 & billy burke & united states & 69-72-71-70=282 & -6 & 550 \\ 3 & t3 & lawson little & united states & 72-72-68-70=282 & -6 & 550 \\ 4 & 5 & gene sarazen & united states & 73-66-72-72=283 & -5 & 400 \\ 5 & 6 & craig wood & united states & 72-73-71-68=284 & -4 & 300 \\ 6 & 7 & byron nelson & united states & 71-69-72-75=287 & -1 & 250 \\ 7 & 8 & henry picard & united states & 71-71-76-71=289 & 1 & 175 \\ 8 & 9 & ben hogan & united states & 75-71-72-72=290 & 2 & 125 \\ 9 & t10 & ed dudley & united states & 75-75-69-72=291 & 3 & 100 \\ 10 & t10 & toney penna & united states & 72-75-72-72=291 & 3 & 100 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select count ( * ) where player = 336 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> <th>player</th> <th>country</th> <th>score</th> <th>to par</th> <th>money ($)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>ralph guldahl</td> <td>united states</td> <td>72-68-70-69=279</td> <td>-9</td> <td>1,500</td> </tr> <tr> <th>1</th> <td>2</td> <td>sam snead</td> <td>united states</td> <td>70-70-72-68=280</td> <td>-8</td> <td>800</td> </tr> <tr> <th>2</th> <td>t3</td> <td>billy burke</td> <td>united states</td> <td>69-72-71-70=282</td> <td>-6</td> <td>550</td> </tr> <tr> <th>3</th> <td>t3</td> <td>lawson little</td> <td>united states</td> <td>72-72-68-70=282</td> <td>-6</td> <td>550</td> </tr> <tr> <th>4</th> <td>5</td> <td>gene sarazen</td> <td>united states</td> <td>73-66-72-72=283</td> <td>-5</td> <td>400</td> </tr> <tr> <th>5</th> <td>6</td> <td>craig wood</td> <td>united states</td> <td>72-73-71-68=284</td> <td>-4</td> <td>300</td> </tr> <tr> <th>6</th> <td>7</td> <td>byron nelson</td> <td>united states</td> <td>71-69-72-75=287</td> <td>-1</td> <td>250</td> </tr> <tr> <th>7</th> <td>8</td> <td>henry picard</td> <td>united states</td> <td>71-71-76-71=289</td> <td>1</td> <td>175</td> </tr> <tr> <th>8</th> <td>9</td> <td>ben hogan</td> <td>united states</td> <td>75-71-72-72=290</td> <td>2</td> <td>125</td> </tr> <tr> <th>9</th> <td>t10</td> <td>ed dudley</td> <td>united states</td> <td>75-75-69-72=291</td> <td>3</td> <td>100</td> </tr> <tr> <th>10</th> <td>t10</td> <td>toney penna</td> <td>united states</td> <td>72-75-72-72=291</td> <td>3</td> <td>100</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select count ( * ) where player = 336 <table_name> : table \| \| place \| player \| country \| score \| to par \| money ($) \| \|---:\|:--------\|:--------------\|:--------------\|:----------------\|---------:\|:------------\| \| 0 \| 1 \| ralph guldahl \| united states \| 72-68-70-69=279 \| -9 \| 1,500 \| \| 1 \| 2 \| sam snead \| united states \| 70-70-72-68=280 \| -8 \| 800 \| \| 2 \| t3 \| billy burke \| united states \| 69-72-71-70=282 \| -6 \| 550 \| \| 3 \| t3 \| lawson little \| united states \| 72-72-68-70=282 \| -6 \| 550 \| \| 4 \| 5 \| gene sarazen \| united states \| 73-66-72-72=283 \| -5 \| 400 \| \| 5 \| 6 \| craig wood \| united states \| 72-73-71-68=284 \| -4 \| 300 \| \| 6 \| 7 \| byron nelson \| united states \| 71-69-72-75=287 \| -1 \| 250 \| \| 7 \| 8 \| henry picard \| united states \| 71-71-76-71=289 \| 1 \| 175 \| \| 8 \| 9 \| ben hogan \| united states \| 75-71-72-72=290 \| 2 \| 125 \| \| 9 \| t10 \| ed dudley \| united states \| 75-75-69-72=291 \| 3 \| 100 \| \| 10 \| t10 \| toney penna \| united states \| 72-75-72-72=291 \| 3 \| 100 \|	\| \| count ( "*" ) \| 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select venue where capacity = 4000 col : team \| location \| venue \| capacity \| position in 1993-94 row 1 : dinamo minsk \| minsk \| dinamo, minsk \| 41040 \| 1 row 2 : dinamo-93 \| minsk \| dinamo, minsk \| 41040 \| 2 row 3 : dvina \| vitebsk \| central, vitebsk \| 8300 \| 3 row 4 : dnepr \| mogilev \| spartak, mogilev \| 11200 \| 4 row 5 : bobruisk \| bobruisk \| spartak, bobruisk \| 3550 \| 5 row 6 : torpedo minsk \| minsk \| torpedo, minsk \| 5200 \| 6 row 7 : shinnik \| bobruisk \| spartak, bobruisk \| 3550 \| 7 row 8 : dinamo brest \| brest \| dinamo, brest \| 10080 \| 8 row 9 : molodechno \| molodechno \| city stadium, molodechno \| 5500 \| 9 row 10 : lokomotiv \| vitebsk \| central, vitebsk \| 8300 \| 10 row 11 : neman \| grodno \| neman \| 6300 \| 11 row 12 : vedrich \| rechytsa \| central, rechytsa \| 3550 \| 12 row 13 : shakhtyor \| soligorsk \| stroitel \| 5000 \| 13 row 14 : torpedo mogilev \| mogilev \| torpedo, mogilev \| 3500 \| 14 row 15 : gomselmash \| gomel \| central, gomel \| 11800 \| 15 row 16 : obuvshchik \| lida \| city stadium, lida \| 4000 \| first league, 1	col : venue row 1 : city stadium, lida	select venue where capacity = 4000 <table_name> : table \begin{tabular}{llllll} \toprule & team & location & venue & capacity & position in 1993-94 \\ \midrule 0 & dinamo minsk & minsk & dinamo, minsk & 41040 & 1 \\ 1 & dinamo-93 & minsk & dinamo, minsk & 41040 & 2 \\ 2 & dvina & vitebsk & central, vitebsk & 8300 & 3 \\ 3 & dnepr & mogilev & spartak, mogilev & 11200 & 4 \\ 4 & bobruisk & bobruisk & spartak, bobruisk & 3550 & 5 \\ 5 & torpedo minsk & minsk & torpedo, minsk & 5200 & 6 \\ 6 & shinnik & bobruisk & spartak, bobruisk & 3550 & 7 \\ 7 & dinamo brest & brest & dinamo, brest & 10080 & 8 \\ 8 & molodechno & molodechno & city stadium, molodechno & 5500 & 9 \\ 9 & lokomotiv & vitebsk & central, vitebsk & 8300 & 10 \\ 10 & neman & grodno & neman & 6300 & 11 \\ 11 & vedrich & rechytsa & central, rechytsa & 3550 & 12 \\ 12 & shakhtyor & soligorsk & stroitel & 5000 & 13 \\ 13 & torpedo mogilev & mogilev & torpedo, mogilev & 3500 & 14 \\ 14 & gomselmash & gomel & central, gomel & 11800 & 15 \\ 15 & obuvshchik & lida & city stadium, lida & 4000 & first league, 1 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & venue \\ \midrule 0 & city stadium, lida \\ \bottomrule \end{tabular}	select venue where capacity = 4000 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>location</th> <th>venue</th> <th>capacity</th> <th>position in 1993-94</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>dinamo minsk</td> <td>minsk</td> <td>dinamo, minsk</td> <td>41040</td> <td>1</td> </tr> <tr> <th>1</th> <td>dinamo-93</td> <td>minsk</td> <td>dinamo, minsk</td> <td>41040</td> <td>2</td> </tr> <tr> <th>2</th> <td>dvina</td> <td>vitebsk</td> <td>central, vitebsk</td> <td>8300</td> <td>3</td> </tr> <tr> <th>3</th> <td>dnepr</td> <td>mogilev</td> <td>spartak, mogilev</td> <td>11200</td> <td>4</td> </tr> <tr> <th>4</th> <td>bobruisk</td> <td>bobruisk</td> <td>spartak, bobruisk</td> <td>3550</td> <td>5</td> </tr> <tr> <th>5</th> <td>torpedo minsk</td> <td>minsk</td> <td>torpedo, minsk</td> <td>5200</td> <td>6</td> </tr> <tr> <th>6</th> <td>shinnik</td> <td>bobruisk</td> <td>spartak, bobruisk</td> <td>3550</td> <td>7</td> </tr> <tr> <th>7</th> <td>dinamo brest</td> <td>brest</td> <td>dinamo, brest</td> <td>10080</td> <td>8</td> </tr> <tr> <th>8</th> <td>molodechno</td> <td>molodechno</td> <td>city stadium, molodechno</td> <td>5500</td> <td>9</td> </tr> <tr> <th>9</th> <td>lokomotiv</td> <td>vitebsk</td> <td>central, vitebsk</td> <td>8300</td> <td>10</td> </tr> <tr> <th>10</th> <td>neman</td> <td>grodno</td> <td>neman</td> <td>6300</td> <td>11</td> </tr> <tr> <th>11</th> <td>vedrich</td> <td>rechytsa</td> <td>central, rechytsa</td> <td>3550</td> <td>12</td> </tr> <tr> <th>12</th> <td>shakhtyor</td> <td>soligorsk</td> <td>stroitel</td> <td>5000</td> <td>13</td> </tr> <tr> <th>13</th> <td>torpedo mogilev</td> <td>mogilev</td> <td>torpedo, mogilev</td> <td>3500</td> <td>14</td> </tr> <tr> <th>14</th> <td>gomselmash</td> <td>gomel</td> <td>central, gomel</td> <td>11800</td> <td>15</td> </tr> <tr> <th>15</th> <td>obuvshchik</td> <td>lida</td> <td>city stadium, lida</td> <td>4000</td> <td>first league, 1</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>venue</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>city stadium, lida</td> </tr> </tbody> </table>	select venue where capacity = 4000 <table_name> : table \| \| team \| location \| venue \| capacity \| position in 1993-94 \| \|---:\|:----------------\|:-----------\|:-------------------------\|-----------:\|:----------------------\| \| 0 \| dinamo minsk \| minsk \| dinamo, minsk \| 41040 \| 1 \| \| 1 \| dinamo-93 \| minsk \| dinamo, minsk \| 41040 \| 2 \| \| 2 \| dvina \| vitebsk \| central, vitebsk \| 8300 \| 3 \| \| 3 \| dnepr \| mogilev \| spartak, mogilev \| 11200 \| 4 \| \| 4 \| bobruisk \| bobruisk \| spartak, bobruisk \| 3550 \| 5 \| \| 5 \| torpedo minsk \| minsk \| torpedo, minsk \| 5200 \| 6 \| \| 6 \| shinnik \| bobruisk \| spartak, bobruisk \| 3550 \| 7 \| \| 7 \| dinamo brest \| brest \| dinamo, brest \| 10080 \| 8 \| \| 8 \| molodechno \| molodechno \| city stadium, molodechno \| 5500 \| 9 \| \| 9 \| lokomotiv \| vitebsk \| central, vitebsk \| 8300 \| 10 \| \| 10 \| neman \| grodno \| neman \| 6300 \| 11 \| \| 11 \| vedrich \| rechytsa \| central, rechytsa \| 3550 \| 12 \| \| 12 \| shakhtyor \| soligorsk \| stroitel \| 5000 \| 13 \| \| 13 \| torpedo mogilev \| mogilev \| torpedo, mogilev \| 3500 \| 14 \| \| 14 \| gomselmash \| gomel \| central, gomel \| 11800 \| 15 \| \| 15 \| obuvshchik \| lida \| city stadium, lida \| 4000 \| first league, 1 \|	\| \| venue \| \|---:\|:-------------------\| \| 0 \| city stadium, lida \|	[ [ 1, 4025, 331, 275, 344, 1625, 7519, 273, 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select min ( attendance ) where venue = 'lambeau field' col : week \| date \| opponent \| result \| venue \| attendance row 1 : 1 \| 1978-09-03 00:00:00 \| at detroit lions \| w 13-7 \| pontiac silverdome \| 51187 row 2 : 2 \| 1978-09-10 00:00:00 \| new orleans saints \| w 28-17 \| milwaukee county stadium \| 54336 row 3 : 3 \| 1978-09-17 00:00:00 \| oakland raiders \| l 28-3 \| lambeau field \| 55903 row 4 : 4 \| 1978-09-24 00:00:00 \| at san diego chargers \| w 24-3 \| san diego stadium \| 42755 row 5 : 5 \| 1978-10-01 00:00:00 \| detroit lions \| w 35-14 \| milwaukee county stadium \| 54601 row 6 : 6 \| 1978-10-08 00:00:00 \| chicago bears \| w 24-14 \| lambeau field \| 56267 row 7 : 7 \| 1978-10-15 00:00:00 \| seattle seahawks \| w 45-28 \| milwaukee county stadium \| 52712 row 8 : 8 \| 1978-10-22 00:00:00 \| at minnesota vikings \| l 21-7 \| metropolitan stadium \| 47411 row 9 : 9 \| 1978-10-29 00:00:00 \| tampa bay buccaneers \| w 9-7 \| lambeau field \| 55108 row 10 : 10 \| 1978-11-05 00:00:00 \| at philadelphia eagles \| l 10-3 \| veterans stadium \| 64214 row 11 : 11 \| 1978-11-12 00:00:00 \| dallas cowboys \| l 42-14 \| milwaukee county stadium \| 55256 row 12 : 12 \| 1978-11-19 00:00:00 \| at denver broncos \| l 16-3 \| mile high stadium \| 74965 row 13 : 13 \| 1978-11-26 00:00:00 \| minnesota vikings \| t 10-10 (ot) \| lambeau field \| 51737 row 14 : 14 \| 1978-12-03 00:00:00 \| at tampa bay buccaneers \| w 17-7 \| tampa stadium \| 67754 row 15 : 15 \| 1978-12-10 00:00:00 \| at chicago bears \| l 14-0 \| soldier field \| 34306 row 16 : 16 \| 1978-12-17 00:00:00 \| at los angeles rams \| l 31-14 \| los angeles memorial coliseum \| 42500	col : min ( "attendance" ) row 1 : 51737	select min ( attendance ) where venue = 'lambeau field' <table_name> : table \begin{tabular}{lllllll} \toprule & week & date & opponent & result & venue & attendance \\ \midrule 0 & 1 & 1978-09-03 00:00:00 & at detroit lions & w 13-7 & pontiac silverdome & 51187 \\ 1 & 2 & 1978-09-10 00:00:00 & new orleans saints & w 28-17 & milwaukee county stadium & 54336 \\ 2 & 3 & 1978-09-17 00:00:00 & oakland raiders & l 28-3 & lambeau field & 55903 \\ 3 & 4 & 1978-09-24 00:00:00 & at san diego chargers & w 24-3 & san diego stadium & 42755 \\ 4 & 5 & 1978-10-01 00:00:00 & detroit lions & w 35-14 & milwaukee county stadium & 54601 \\ 5 & 6 & 1978-10-08 00:00:00 & chicago bears & w 24-14 & lambeau field & 56267 \\ 6 & 7 & 1978-10-15 00:00:00 & seattle seahawks & w 45-28 & milwaukee county stadium & 52712 \\ 7 & 8 & 1978-10-22 00:00:00 & at minnesota vikings & l 21-7 & metropolitan stadium & 47411 \\ 8 & 9 & 1978-10-29 00:00:00 & tampa bay buccaneers & w 9-7 & lambeau field & 55108 \\ 9 & 10 & 1978-11-05 00:00:00 & at philadelphia eagles & l 10-3 & veterans stadium & 64214 \\ 10 & 11 & 1978-11-12 00:00:00 & dallas cowboys & l 42-14 & milwaukee county stadium & 55256 \\ 11 & 12 & 1978-11-19 00:00:00 & at denver broncos & l 16-3 & mile high stadium & 74965 \\ 12 & 13 & 1978-11-26 00:00:00 & minnesota vikings & t 10-10 (ot) & lambeau field & 51737 \\ 13 & 14 & 1978-12-03 00:00:00 & at tampa bay buccaneers & w 17-7 & tampa stadium & 67754 \\ 14 & 15 & 1978-12-10 00:00:00 & at chicago bears & l 14-0 & soldier field & 34306 \\ 15 & 16 & 1978-12-17 00:00:00 & at los angeles rams & l 31-14 & los angeles memorial coliseum & 42500 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & min ( "attendance" ) \\ \midrule 0 & 51737 \\ \bottomrule \end{tabular}	select min ( attendance ) where venue = 'lambeau field' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>week</th> <th>date</th> <th>opponent</th> <th>result</th> <th>venue</th> <th>attendance</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>1978-09-03 00:00:00</td> <td>at detroit lions</td> <td>w 13-7</td> <td>pontiac silverdome</td> <td>51187</td> </tr> <tr> <th>1</th> <td>2</td> <td>1978-09-10 00:00:00</td> <td>new orleans saints</td> <td>w 28-17</td> <td>milwaukee county stadium</td> <td>54336</td> </tr> <tr> <th>2</th> <td>3</td> <td>1978-09-17 00:00:00</td> <td>oakland raiders</td> <td>l 28-3</td> <td>lambeau field</td> <td>55903</td> </tr> <tr> <th>3</th> <td>4</td> <td>1978-09-24 00:00:00</td> <td>at san diego chargers</td> <td>w 24-3</td> <td>san diego stadium</td> <td>42755</td> </tr> <tr> <th>4</th> <td>5</td> <td>1978-10-01 00:00:00</td> <td>detroit lions</td> <td>w 35-14</td> <td>milwaukee county stadium</td> <td>54601</td> </tr> <tr> <th>5</th> <td>6</td> <td>1978-10-08 00:00:00</td> <td>chicago bears</td> <td>w 24-14</td> <td>lambeau field</td> <td>56267</td> </tr> <tr> <th>6</th> <td>7</td> <td>1978-10-15 00:00:00</td> <td>seattle seahawks</td> <td>w 45-28</td> <td>milwaukee county stadium</td> <td>52712</td> </tr> <tr> <th>7</th> <td>8</td> <td>1978-10-22 00:00:00</td> <td>at minnesota vikings</td> <td>l 21-7</td> <td>metropolitan stadium</td> <td>47411</td> </tr> <tr> <th>8</th> <td>9</td> <td>1978-10-29 00:00:00</td> <td>tampa bay buccaneers</td> <td>w 9-7</td> <td>lambeau field</td> <td>55108</td> </tr> <tr> <th>9</th> <td>10</td> <td>1978-11-05 00:00:00</td> <td>at philadelphia eagles</td> <td>l 10-3</td> <td>veterans stadium</td> <td>64214</td> </tr> <tr> <th>10</th> <td>11</td> <td>1978-11-12 00:00:00</td> <td>dallas cowboys</td> <td>l 42-14</td> <td>milwaukee county stadium</td> <td>55256</td> </tr> <tr> <th>11</th> <td>12</td> <td>1978-11-19 00:00:00</td> <td>at denver broncos</td> <td>l 16-3</td> <td>mile high stadium</td> <td>74965</td> </tr> <tr> <th>12</th> <td>13</td> <td>1978-11-26 00:00:00</td> <td>minnesota vikings</td> <td>t 10-10 (ot)</td> <td>lambeau field</td> <td>51737</td> </tr> <tr> <th>13</th> <td>14</td> <td>1978-12-03 00:00:00</td> <td>at tampa bay buccaneers</td> <td>w 17-7</td> <td>tampa stadium</td> <td>67754</td> </tr> <tr> <th>14</th> <td>15</td> <td>1978-12-10 00:00:00</td> <td>at chicago bears</td> <td>l 14-0</td> <td>soldier field</td> <td>34306</td> </tr> <tr> <th>15</th> <td>16</td> <td>1978-12-17 00:00:00</td> <td>at los angeles rams</td> <td>l 31-14</td> <td>los angeles memorial coliseum</td> <td>42500</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>min ( "attendance" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>51737</td> </tr> </tbody> </table>	select min ( attendance ) where venue = 'lambeau field' <table_name> : table \| \| week \| date \| opponent \| result \| venue \| attendance \| \|---:\|-------:\|:--------------------\|:------------------------\|:-------------\|:------------------------------\|-------------:\| \| 0 \| 1 \| 1978-09-03 00:00:00 \| at detroit lions \| w 13-7 \| pontiac silverdome \| 51187 \| \| 1 \| 2 \| 1978-09-10 00:00:00 \| new orleans saints \| w 28-17 \| milwaukee county stadium \| 54336 \| \| 2 \| 3 \| 1978-09-17 00:00:00 \| oakland raiders \| l 28-3 \| lambeau field \| 55903 \| \| 3 \| 4 \| 1978-09-24 00:00:00 \| at san diego chargers \| w 24-3 \| san diego stadium \| 42755 \| \| 4 \| 5 \| 1978-10-01 00:00:00 \| detroit lions \| w 35-14 \| milwaukee county stadium \| 54601 \| \| 5 \| 6 \| 1978-10-08 00:00:00 \| chicago bears \| w 24-14 \| lambeau field \| 56267 \| \| 6 \| 7 \| 1978-10-15 00:00:00 \| seattle seahawks \| w 45-28 \| milwaukee county stadium \| 52712 \| \| 7 \| 8 \| 1978-10-22 00:00:00 \| at minnesota vikings \| l 21-7 \| metropolitan stadium \| 47411 \| \| 8 \| 9 \| 1978-10-29 00:00:00 \| tampa bay buccaneers \| w 9-7 \| lambeau field \| 55108 \| \| 9 \| 10 \| 1978-11-05 00:00:00 \| at philadelphia eagles \| l 10-3 \| veterans stadium \| 64214 \| \| 10 \| 11 \| 1978-11-12 00:00:00 \| dallas cowboys \| l 42-14 \| milwaukee county stadium \| 55256 \| \| 11 \| 12 \| 1978-11-19 00:00:00 \| at denver broncos \| l 16-3 \| mile high stadium \| 74965 \| \| 12 \| 13 \| 1978-11-26 00:00:00 \| minnesota vikings \| t 10-10 (ot) \| lambeau field \| 51737 \| \| 13 \| 14 \| 1978-12-03 00:00:00 \| at tampa bay buccaneers \| w 17-7 \| tampa stadium \| 67754 \| \| 14 \| 15 \| 1978-12-10 00:00:00 \| at chicago bears \| l 14-0 \| soldier field \| 34306 \| \| 15 \| 16 \| 1978-12-17 00:00:00 \| at los angeles rams \| l 31-14 \| los angeles memorial coliseum \| 42500 \|	\| \| min ( "attendance" ) \| \|---:\|-----------------------:\| \| 0 \| 51737 \|	[ [ 1, 4025, 1131, 261, 2403, 409, 1359, 262, 1625, 331, 275, 344, 273, 296, 28448, 2196, 8377, 652, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 10741, 1757, 451, 34, 203, 1377, 411, 451, 34, 712, 1757, 451, 34, 203, 1377, 411, 451, 34, 556, 1029, 1757, 451, 34, 203, 1377, 411, 451, 34, 2088, 1757, 451, 34, 203, 1377, 411, 451, 34, 24612, 1757, 451, 34, 203, 1377, 411, 451, 34, 4558, 409, 1359, 1757, 451, 34, 203, 565, 7765, 313, 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select abs ( distance (km) - distance (km) ) where location = 'soja' col : name \| japanese \| distance (km) \| connections \| location row 1 : okayama \| 岡山 \| 0.0 \| sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line \| kita-ku, okayama row 2 : bizen-mikado \| 備前三門 \| 1.9 \| none \| kita-ku, okayama row 3 : daianji \| 大安寺 \| 3.3 \| none \| kita-ku, okayama row 4 : bizen-ichinomiya \| 備前一宮 \| 6.5 \| none \| kita-ku, okayama row 5 : kibitsu \| 吉備津 \| 8.4 \| none \| kita-ku, okayama row 6 : bitchu-takamatsu \| 備中高松 \| 11.0 \| none \| kita-ku, okayama row 7 : ashimori \| 足守 \| 13.4 \| none \| kita-ku, okayama row 8 : hattori \| 服部 \| 16.2 \| none \| soja row 9 : higashi-soja \| 東総社 \| 18.8 \| none \| soja row 10 : soja \| 総社 \| 20.4 \| hakubi line ibara railway ibara line \| soja	col : "abs ( distance (km) - distance (km) )" row 1 : abs ( distance (km) - distance (km) ) row 2 : abs ( distance (km) - distance (km) ) row 3 : abs ( distance (km) - distance (km) )	select abs ( distance (km) - distance (km) ) where location = 'soja' <table_name> : table \begin{tabular}{llllll} \toprule & name & japanese & distance (km) & connections & location \\ \midrule 0 & okayama & 岡山 & 0.0 & sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line & kita-ku, okayama \\ 1 & bizen-mikado & 備前三門 & 1.9 & none & kita-ku, okayama \\ 2 & daianji & 大安寺 & 3.3 & none & kita-ku, okayama \\ 3 & bizen-ichinomiya & 備前一宮 & 6.5 & none & kita-ku, okayama \\ 4 & kibitsu & 吉備津 & 8.4 & none & kita-ku, okayama \\ 5 & bitchu-takamatsu & 備中高松 & 11.0 & none & kita-ku, okayama \\ 6 & ashimori & 足守 & 13.4 & none & kita-ku, okayama \\ 7 & hattori & 服部 & 16.2 & none & soja \\ 8 & higashi-soja & 東総社 & 18.8 & none & soja \\ 9 & soja & 総社 & 20.4 & hakubi line ibara railway ibara line & soja \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & "abs ( distance (km) - distance (km) )" \\ \midrule 0 & abs ( distance (km) - distance (km) ) \\ 1 & abs ( distance (km) - distance (km) ) \\ 2 & abs ( distance (km) - distance (km) ) \\ \bottomrule \end{tabular}	select abs ( distance (km) - distance (km) ) where location = 'soja' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>japanese</th> <th>distance (km)</th> <th>connections</th> <th>location</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>okayama</td> <td>岡山</td> <td>0.0</td> <td>sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line</td> <td>kita-ku, okayama</td> </tr> <tr> <th>1</th> <td>bizen-mikado</td> <td>備前三門</td> <td>1.9</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>2</th> <td>daianji</td> <td>大安寺</td> <td>3.3</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>3</th> <td>bizen-ichinomiya</td> <td>備前一宮</td> <td>6.5</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>4</th> <td>kibitsu</td> <td>吉備津</td> <td>8.4</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>5</th> <td>bitchu-takamatsu</td> <td>備中高松</td> <td>11.0</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>6</th> <td>ashimori</td> <td>足守</td> <td>13.4</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>7</th> <td>hattori</td> <td>服部</td> <td>16.2</td> <td>none</td> <td>soja</td> </tr> <tr> <th>8</th> <td>higashi-soja</td> <td>東総社</td> <td>18.8</td> <td>none</td> <td>soja</td> </tr> <tr> <th>9</th> <td>soja</td> <td>総社</td> <td>20.4</td> <td>hakubi line ibara railway ibara line</td> <td>soja</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"abs ( distance (km) - distance (km) )"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>abs ( distance (km) - distance (km) )</td> </tr> <tr> <th>1</th> <td>abs ( distance (km) - distance (km) )</td> </tr> <tr> <th>2</th> <td>abs ( distance (km) - distance (km) )</td> </tr> </tbody> </table>	select abs ( distance (km) - distance (km) ) where location = 'soja' <table_name> : table \| \| name \| japanese \| distance (km) \| connections \| location \| \|---:\|:-----------------\|:-----------\|----------------:\|:----------------------------------------------------------------------------------------------------------------------------------------------------------------\|:-----------------\| \| 0 \| okayama \| 岡山 \| 0 \| sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line \| kita-ku, okayama \| \| 1 \| bizen-mikado \| 備前三門 \| 1.9 \| none \| kita-ku, okayama \| \| 2 \| daianji \| 大安寺 \| 3.3 \| none \| kita-ku, okayama \| \| 3 \| bizen-ichinomiya \| 備前一宮 \| 6.5 \| none \| kita-ku, okayama \| \| 4 \| kibitsu \| 吉備津 \| 8.4 \| none \| kita-ku, okayama \| \| 5 \| bitchu-takamatsu \| 備中高松 \| 11 \| none \| kita-ku, okayama \| \| 6 \| ashimori \| 足守 \| 13.4 \| none \| kita-ku, okayama \| \| 7 \| hattori \| 服部 \| 16.2 \| none \| soja \| \| 8 \| higashi-soja \| 東総社 \| 18.8 \| none \| soja \| \| 9 \| soja \| 総社 \| 20.4 \| hakubi line ibara railway ibara line \| soja \|	\| \| "abs ( distance (km) - distance (km) )" \| \|---:\|:------------------------------------------\| \| 0 \| abs ( distance (km) - distance (km) ) \| \| 1 \| abs ( distance (km) - distance (km) ) \| \| 2 \| abs ( distance (km) - distance (km) ) \|	[ [ 1, 4025, 2417, 261, 3888, 261, 18353, 13, 300, 3888, 261, 18353, 13, 262, 1625, 2117, 273, 296, 2048, 12333, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 529, 1757, 451, 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select count ( * ) where player = 'dustin johnson' col : place \| player \| country \| score \| to par row 1 : 1 \| dustin johnson \| united states \| 71-70-66=207 \| -6 row 2 : 2 \| graeme mcdowell \| northern ireland \| 71-68-71=210 \| -3 row 3 : 3 \| tiger woods \| united states \| 74-72-66=212 \| -1 row 4 : t4 \| ernie els \| south africa \| 73-68-72=213 \| e row 5 : t4 \| gregory havret \| france \| 73-71-69=213 \| e row 6 : 6 \| phil mickelson \| united states \| 75-66-73=214 \| 1 row 7 : t7 \| alex cejka \| germany \| 70-72-74=216 \| 3 row 8 : t7 \| tim clark \| south africa \| 72-72-72=216 \| 3 row 9 : t7 \| ryo ishikawa \| japan \| 70-71-75=216 \| 3 row 10 : t10 \| martin kaymer \| germany \| 74-71-72=217 \| 4 row 11 : t10 \| davis love iii \| united states \| 75-74-68=217 \| 4 row 12 : t10 \| sean o'hair \| united states \| 76-71-70=217 \| 4	col : count ( "*" ) row 1 : 1	select count ( * ) where player = 'dustin johnson' <table_name> : table \begin{tabular}{llllll} \toprule & place & player & country & score & to par \\ \midrule 0 & 1 & dustin johnson & united states & 71-70-66=207 & -6 \\ 1 & 2 & graeme mcdowell & northern ireland & 71-68-71=210 & -3 \\ 2 & 3 & tiger woods & united states & 74-72-66=212 & -1 \\ 3 & t4 & ernie els & south africa & 73-68-72=213 & e \\ 4 & t4 & gregory havret & france & 73-71-69=213 & e \\ 5 & 6 & phil mickelson & united states & 75-66-73=214 & 1 \\ 6 & t7 & alex cejka & germany & 70-72-74=216 & 3 \\ 7 & t7 & tim clark & south africa & 72-72-72=216 & 3 \\ 8 & t7 & ryo ishikawa & japan & 70-71-75=216 & 3 \\ 9 & t10 & martin kaymer & germany & 74-71-72=217 & 4 \\ 10 & t10 & davis love iii & united states & 75-74-68=217 & 4 \\ 11 & t10 & sean o'hair & united states & 76-71-70=217 & 4 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where player = 'dustin johnson' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> <th>player</th> <th>country</th> <th>score</th> <th>to par</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>dustin johnson</td> <td>united states</td> <td>71-70-66=207</td> <td>-6</td> </tr> <tr> <th>1</th> <td>2</td> <td>graeme mcdowell</td> <td>northern ireland</td> <td>71-68-71=210</td> <td>-3</td> </tr> <tr> <th>2</th> <td>3</td> <td>tiger woods</td> <td>united states</td> <td>74-72-66=212</td> <td>-1</td> </tr> <tr> <th>3</th> <td>t4</td> <td>ernie els</td> <td>south africa</td> <td>73-68-72=213</td> <td>e</td> </tr> <tr> <th>4</th> <td>t4</td> <td>gregory havret</td> <td>france</td> <td>73-71-69=213</td> <td>e</td> </tr> <tr> <th>5</th> <td>6</td> <td>phil mickelson</td> <td>united states</td> <td>75-66-73=214</td> <td>1</td> </tr> <tr> <th>6</th> <td>t7</td> <td>alex cejka</td> <td>germany</td> <td>70-72-74=216</td> <td>3</td> </tr> <tr> <th>7</th> <td>t7</td> <td>tim clark</td> <td>south africa</td> <td>72-72-72=216</td> <td>3</td> </tr> <tr> <th>8</th> <td>t7</td> <td>ryo ishikawa</td> <td>japan</td> <td>70-71-75=216</td> <td>3</td> </tr> <tr> <th>9</th> <td>t10</td> <td>martin kaymer</td> <td>germany</td> <td>74-71-72=217</td> <td>4</td> </tr> <tr> <th>10</th> <td>t10</td> <td>davis love iii</td> <td>united states</td> <td>75-74-68=217</td> <td>4</td> </tr> <tr> <th>11</th> <td>t10</td> <td>sean o'hair</td> <td>united states</td> <td>76-71-70=217</td> <td>4</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where player = 'dustin johnson' <table_name> : table \| \| place \| player \| country \| score \| to par \| \|---:\|:--------\|:----------------\|:-----------------\|:-------------\|:---------\| \| 0 \| 1 \| dustin johnson \| united states \| 71-70-66=207 \| -6 \| \| 1 \| 2 \| graeme mcdowell \| northern ireland \| 71-68-71=210 \| -3 \| \| 2 \| 3 \| tiger woods \| united states \| 74-72-66=212 \| -1 \| \| 3 \| t4 \| ernie els \| south africa \| 73-68-72=213 \| e \| \| 4 \| t4 \| gregory havret \| france \| 73-71-69=213 \| e \| \| 5 \| 6 \| phil mickelson \| united states \| 75-66-73=214 \| 1 \| \| 6 \| t7 \| alex cejka \| germany \| 70-72-74=216 \| 3 \| \| 7 \| t7 \| tim clark \| south africa \| 72-72-72=216 \| 3 \| \| 8 \| t7 \| ryo ishikawa \| japan \| 70-71-75=216 \| 3 \| \| 9 \| t10 \| martin kaymer \| germany \| 74-71-72=217 \| 4 \| \| 10 \| t10 \| davis love iii \| united states \| 75-74-68=217 \| 4 \| \| 11 \| t10 \| sean o'hair \| united states \| 76-71-70=217 \| 4 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 7291, 273, 296, 72, 641, 267, 525, 22223, 816, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 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select count ( * ) where division one > 881 col : season \| division one \| division two \| division three row 1 : 1983-84 \| whitehawk \| portfield \| east preston row 2 : 1984-85 \| steyning town \| shoreham \| oakwood row 3 : 1985-86 \| steyning town \| wick \| seaford town row 4 : 1986-87 \| arundel \| pagham \| langney sports row 5 : 1987-88 \| pagham \| langney sports \| midway row 6 : 1988-89 \| pagham \| seaford town \| saltdean united row 7 : 1989-90 \| wick \| bexhill town \| worthing united row 8 : 1990-91 \| littlehampton town \| newhaven \| ifield row 9 : 1991-92 \| peacehaven & telscombe \| portfield \| hassocks row 10 : 1992-93 \| peacehaven & telscombe \| crowborough athletic \| withdean row 11 : 1993-94 \| wick \| shoreham \| bosham row 12 : 1994-95 \| peacehaven & telscombe \| mile oak \| midhurst & easebourne row 13 : 1995-96 \| peacehaven & telscombe \| saltdean united \| ifield row 14 : 1996-97 \| burgess hill town \| littlehampton town \| sidlesham row 15 : 1997-98 \| burgess hill town \| east preston \| lingfield row 16 : 1998-99 \| burgess hill town \| sidley united \| oving social club row 17 : 1999-2000 \| langney sports \| sidlesham \| bosham row 18 : 2000-01 \| sidley united \| southwick \| rye united row 19 : 2001-02 \| burgess hill town \| rye & iden united \| pease pottage village row 20 : 2002-03 \| burgess hill town \| rye & iden united \| midhurst & easebourne row 21 : 2003-04 \| chichester city united \| littlehampton town \| crowborough athletic row 22 : 2004-05 \| horsham y m c a \| crowborough athletic \| storrington row 23 : 2005-06 \| horsham y m c a \| oakwood \| peacehaven & telscombe row 24 : 2006-07 \| eastbourne town \| pagham \| rustington row 25 : 2007-08 \| crowborough athletic \| east grinstead town \| loxwood row 26 : 2008-09 \| eastbourne united association \| peacehaven & telscombe \| clymping row 27 : 2009-10 \| whitehawk \| rye united \| bosham row 28 : 2010-11 \| crawley down \| a.f.c. uckfield \| dorking wanderers row 29 : 2011-12 \| three bridges \| east preston \| newhaven row 30 : 2012-13 \| peacehaven & telscombe \| littlehampton town \| sidlesham	col : count ( "*" ) row 1 : 30	select count ( * ) where division one > 881 <table_name> : table \begin{tabular}{lllll} \toprule & season & division one & division two & division three \\ \midrule 0 & 1983-84 & whitehawk & portfield & east preston \\ 1 & 1984-85 & steyning town & shoreham & oakwood \\ 2 & 1985-86 & steyning town & wick & seaford town \\ 3 & 1986-87 & arundel & pagham & langney sports \\ 4 & 1987-88 & pagham & langney sports & midway \\ 5 & 1988-89 & pagham & seaford town & saltdean united \\ 6 & 1989-90 & wick & bexhill town & worthing united \\ 7 & 1990-91 & littlehampton town & newhaven & ifield \\ 8 & 1991-92 & peacehaven & telscombe & portfield & hassocks \\ 9 & 1992-93 & peacehaven & telscombe & crowborough athletic & withdean \\ 10 & 1993-94 & wick & shoreham & bosham \\ 11 & 1994-95 & peacehaven & telscombe & mile oak & midhurst & easebourne \\ 12 & 1995-96 & peacehaven & telscombe & saltdean united & ifield \\ 13 & 1996-97 & burgess hill town & littlehampton town & sidlesham \\ 14 & 1997-98 & burgess hill town & east preston & lingfield \\ 15 & 1998-99 & burgess hill town & sidley united & oving social club \\ 16 & 1999-2000 & langney sports & sidlesham & bosham \\ 17 & 2000-01 & sidley united & southwick & rye united \\ 18 & 2001-02 & burgess hill town & rye & iden united & pease pottage village \\ 19 & 2002-03 & burgess hill town & rye & iden united & midhurst & easebourne \\ 20 & 2003-04 & chichester city united & littlehampton town & crowborough athletic \\ 21 & 2004-05 & horsham y m c a & crowborough athletic & storrington \\ 22 & 2005-06 & horsham y m c a & oakwood & peacehaven & telscombe \\ 23 & 2006-07 & eastbourne town & pagham & rustington \\ 24 & 2007-08 & crowborough athletic & east grinstead town & loxwood \\ 25 & 2008-09 & eastbourne united association & peacehaven & telscombe & clymping \\ 26 & 2009-10 & whitehawk & rye united & bosham \\ 27 & 2010-11 & crawley down & a.f.c. uckfield & dorking wanderers \\ 28 & 2011-12 & three bridges & east preston & newhaven \\ 29 & 2012-13 & peacehaven & telscombe & littlehampton town & sidlesham \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 30 \\ \bottomrule \end{tabular}	select count ( * ) where division one > 881 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>division one</th> <th>division two</th> <th>division three</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1983-84</td> <td>whitehawk</td> <td>portfield</td> <td>east preston</td> </tr> <tr> <th>1</th> <td>1984-85</td> <td>steyning town</td> <td>shoreham</td> <td>oakwood</td> </tr> <tr> <th>2</th> <td>1985-86</td> <td>steyning town</td> <td>wick</td> <td>seaford town</td> </tr> <tr> <th>3</th> <td>1986-87</td> <td>arundel</td> <td>pagham</td> <td>langney sports</td> </tr> <tr> <th>4</th> <td>1987-88</td> <td>pagham</td> <td>langney sports</td> <td>midway</td> </tr> <tr> <th>5</th> <td>1988-89</td> <td>pagham</td> <td>seaford town</td> <td>saltdean united</td> </tr> <tr> <th>6</th> <td>1989-90</td> <td>wick</td> <td>bexhill town</td> <td>worthing united</td> </tr> <tr> <th>7</th> <td>1990-91</td> <td>littlehampton town</td> <td>newhaven</td> <td>ifield</td> </tr> <tr> <th>8</th> <td>1991-92</td> <td>peacehaven & telscombe</td> <td>portfield</td> <td>hassocks</td> </tr> <tr> <th>9</th> <td>1992-93</td> <td>peacehaven & telscombe</td> <td>crowborough athletic</td> <td>withdean</td> </tr> <tr> <th>10</th> <td>1993-94</td> <td>wick</td> <td>shoreham</td> <td>bosham</td> </tr> <tr> <th>11</th> <td>1994-95</td> <td>peacehaven & telscombe</td> <td>mile oak</td> <td>midhurst & easebourne</td> </tr> <tr> <th>12</th> <td>1995-96</td> <td>peacehaven & telscombe</td> <td>saltdean united</td> <td>ifield</td> </tr> <tr> <th>13</th> <td>1996-97</td> <td>burgess hill town</td> <td>littlehampton town</td> <td>sidlesham</td> </tr> <tr> <th>14</th> <td>1997-98</td> <td>burgess hill town</td> <td>east preston</td> <td>lingfield</td> </tr> <tr> <th>15</th> <td>1998-99</td> <td>burgess hill town</td> <td>sidley united</td> <td>oving social club</td> </tr> <tr> <th>16</th> <td>1999-2000</td> <td>langney sports</td> <td>sidlesham</td> <td>bosham</td> </tr> <tr> <th>17</th> <td>2000-01</td> <td>sidley united</td> <td>southwick</td> <td>rye united</td> </tr> <tr> <th>18</th> <td>2001-02</td> <td>burgess hill town</td> <td>rye & iden united</td> <td>pease pottage village</td> </tr> <tr> <th>19</th> <td>2002-03</td> <td>burgess hill town</td> <td>rye & iden united</td> <td>midhurst & easebourne</td> </tr> <tr> <th>20</th> <td>2003-04</td> <td>chichester city united</td> <td>littlehampton town</td> <td>crowborough athletic</td> </tr> <tr> <th>21</th> <td>2004-05</td> <td>horsham y m c a</td> <td>crowborough athletic</td> <td>storrington</td> </tr> <tr> <th>22</th> <td>2005-06</td> <td>horsham y m c a</td> <td>oakwood</td> <td>peacehaven & telscombe</td> </tr> <tr> <th>23</th> <td>2006-07</td> <td>eastbourne town</td> <td>pagham</td> <td>rustington</td> </tr> <tr> <th>24</th> <td>2007-08</td> <td>crowborough athletic</td> <td>east grinstead town</td> <td>loxwood</td> </tr> <tr> <th>25</th> <td>2008-09</td> <td>eastbourne united association</td> <td>peacehaven & telscombe</td> <td>clymping</td> </tr> <tr> <th>26</th> <td>2009-10</td> <td>whitehawk</td> <td>rye united</td> <td>bosham</td> </tr> <tr> <th>27</th> <td>2010-11</td> <td>crawley down</td> <td>a.f.c. uckfield</td> <td>dorking wanderers</td> </tr> <tr> <th>28</th> <td>2011-12</td> <td>three bridges</td> <td>east preston</td> <td>newhaven</td> </tr> <tr> <th>29</th> <td>2012-13</td> <td>peacehaven & telscombe</td> <td>littlehampton town</td> <td>sidlesham</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>30</td> </tr> </tbody> </table>	select count ( * ) where division one > 881 <table_name> : table \| \| season \| division one \| division two \| division three \| \|---:\|:----------\|:------------------------------\|:-----------------------\|:-----------------------\| \| 0 \| 1983-84 \| whitehawk \| portfield \| east preston \| \| 1 \| 1984-85 \| steyning town \| shoreham \| oakwood \| \| 2 \| 1985-86 \| steyning town \| wick \| seaford town \| \| 3 \| 1986-87 \| arundel \| pagham \| langney sports \| \| 4 \| 1987-88 \| pagham \| langney sports \| midway \| \| 5 \| 1988-89 \| pagham \| seaford town \| saltdean united \| \| 6 \| 1989-90 \| wick \| bexhill town \| worthing united \| \| 7 \| 1990-91 \| littlehampton town \| newhaven \| ifield \| \| 8 \| 1991-92 \| peacehaven & telscombe \| portfield \| hassocks \| \| 9 \| 1992-93 \| peacehaven & telscombe \| crowborough athletic \| withdean \| \| 10 \| 1993-94 \| wick \| shoreham \| bosham \| \| 11 \| 1994-95 \| peacehaven & telscombe \| mile oak \| midhurst & easebourne \| \| 12 \| 1995-96 \| peacehaven & telscombe \| saltdean united \| ifield \| \| 13 \| 1996-97 \| burgess hill town \| littlehampton town \| sidlesham \| \| 14 \| 1997-98 \| burgess hill town \| east preston \| lingfield \| \| 15 \| 1998-99 \| burgess hill town \| sidley united \| oving social club \| \| 16 \| 1999-2000 \| langney sports \| sidlesham \| bosham \| \| 17 \| 2000-01 \| sidley united \| southwick \| rye united \| \| 18 \| 2001-02 \| burgess hill town \| rye & iden united \| pease pottage village \| \| 19 \| 2002-03 \| burgess hill town \| rye & iden united \| midhurst & easebourne \| \| 20 \| 2003-04 \| chichester city united \| littlehampton town \| crowborough athletic \| \| 21 \| 2004-05 \| horsham y m c a \| crowborough athletic \| storrington \| \| 22 \| 2005-06 \| horsham y m c a \| oakwood \| peacehaven & telscombe \| \| 23 \| 2006-07 \| eastbourne town \| pagham \| rustington \| \| 24 \| 2007-08 \| crowborough athletic \| east grinstead town \| loxwood \| \| 25 \| 2008-09 \| eastbourne united association \| peacehaven & telscombe \| clymping \| \| 26 \| 2009-10 \| whitehawk \| rye united \| bosham \| \| 27 \| 2010-11 \| crawley down \| a.f.c. uckfield \| dorking wanderers \| \| 28 \| 2011-12 \| three bridges \| east preston \| newhaven \| \| 29 \| 2012-13 \| peacehaven & telscombe \| littlehampton town \| sidlesham \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 30 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 16536, 1245, 405, 1725, 11861, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 30321, 1757, 451, 34, 203, 1377, 411, 451, 34, 2892, 1951, 1245, 1757, 451, 34, 203, 1377, 411, 451, 34, 2892, 1951, 2795, 1757, 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select count ( * ) where host city = 'salt lake city, utah' col : games \| host city \| dates \| nations \| participants \| events row 1 : 1904 summer olympics \| st. louis, missouri \| 1 july - 23 november \| 12 \| 651 \| 91 row 2 : 1932 winter olympics \| lake placid, new york \| 7 - 15 february \| 17 \| 252 \| 14 row 3 : 1932 summer olympics \| los angeles, california \| 30 july - 14 august \| 37 \| 1332 \| 117 row 4 : 1960 winter olympics \| squaw valley, california \| 2 - 20 february \| 30 \| 665 \| 27 row 5 : 1980 winter olympics \| lake placid, new york \| 13 - 24 february \| 37 \| 1072 \| 38 row 6 : 1984 summer olympics \| los angeles, california \| 20 july - 18 august \| 140 \| 6829 \| 221 row 7 : 1996 summer olympics \| atlanta, georgia \| 18 july - 4 august \| 197 \| 1318 \| 271 row 8 : 2002 winter olympics \| salt lake city, utah \| 8 - 24 february \| 77 \| 2399 \| 78	col : count ( "*" ) row 1 : 1	select count ( * ) where host city = 'salt lake city, utah' <table_name> : table \begin{tabular}{lllllll} \toprule & games & host city & dates & nations & participants & events \\ \midrule 0 & 1904 summer olympics & st. louis, missouri & 1 july - 23 november & 12 & 651 & 91 \\ 1 & 1932 winter olympics & lake placid, new york & 7 - 15 february & 17 & 252 & 14 \\ 2 & 1932 summer olympics & los angeles, california & 30 july - 14 august & 37 & 1332 & 117 \\ 3 & 1960 winter olympics & squaw valley, california & 2 - 20 february & 30 & 665 & 27 \\ 4 & 1980 winter olympics & lake placid, new york & 13 - 24 february & 37 & 1072 & 38 \\ 5 & 1984 summer olympics & los angeles, california & 20 july - 18 august & 140 & 6829 & 221 \\ 6 & 1996 summer olympics & atlanta, georgia & 18 july - 4 august & 197 & 1318 & 271 \\ 7 & 2002 winter olympics & salt lake city, utah & 8 - 24 february & 77 & 2399 & 78 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where host city = 'salt lake city, utah' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>games</th> <th>host city</th> <th>dates</th> <th>nations</th> <th>participants</th> <th>events</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1904 summer olympics</td> <td>st. louis, missouri</td> <td>1 july - 23 november</td> <td>12</td> <td>651</td> <td>91</td> </tr> <tr> <th>1</th> <td>1932 winter olympics</td> <td>lake placid, new york</td> <td>7 - 15 february</td> <td>17</td> <td>252</td> <td>14</td> </tr> <tr> <th>2</th> <td>1932 summer olympics</td> <td>los angeles, california</td> <td>30 july - 14 august</td> <td>37</td> <td>1332</td> <td>117</td> </tr> <tr> <th>3</th> <td>1960 winter olympics</td> <td>squaw valley, california</td> <td>2 - 20 february</td> <td>30</td> <td>665</td> <td>27</td> </tr> <tr> <th>4</th> <td>1980 winter olympics</td> <td>lake placid, new york</td> <td>13 - 24 february</td> <td>37</td> <td>1072</td> <td>38</td> </tr> <tr> <th>5</th> <td>1984 summer olympics</td> <td>los angeles, california</td> <td>20 july - 18 august</td> <td>140</td> <td>6829</td> <td>221</td> </tr> <tr> <th>6</th> <td>1996 summer olympics</td> <td>atlanta, georgia</td> <td>18 july - 4 august</td> <td>197</td> <td>1318</td> <td>271</td> </tr> <tr> <th>7</th> <td>2002 winter olympics</td> <td>salt lake city, utah</td> <td>8 - 24 february</td> <td>77</td> <td>2399</td> <td>78</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where host city = 'salt lake city, utah' <table_name> : table \| \| games \| host city \| dates \| nations \| participants \| events \| \|---:\|:---------------------\|:-------------------------\|:---------------------\|----------:\|---------------:\|---------:\| \| 0 \| 1904 summer olympics \| st. louis, missouri \| 1 july - 23 november \| 12 \| 651 \| 91 \| \| 1 \| 1932 winter olympics \| lake placid, new york \| 7 - 15 february \| 17 \| 252 \| 14 \| \| 2 \| 1932 summer olympics \| los angeles, california \| 30 july - 14 august \| 37 \| 1332 \| 117 \| \| 3 \| 1960 winter olympics \| squaw valley, california \| 2 - 20 february \| 30 \| 665 \| 27 \| \| 4 \| 1980 winter olympics \| lake placid, new york \| 13 - 24 february \| 37 \| 1072 \| 38 \| \| 5 \| 1984 summer olympics \| los angeles, california \| 20 july - 18 august \| 140 \| 6829 \| 221 \| \| 6 \| 1996 summer olympics \| atlanta, georgia \| 18 july - 4 august \| 197 \| 1318 \| 271 \| \| 7 \| 2002 winter olympics \| salt lake city, utah \| 8 - 24 february \| 77 \| 2399 \| 78 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 1479, 12797, 273, 296, 5759, 328, 911, 12797, 16, 5218, 9795, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 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select time where athlete = 'sylvia filipsson' col : rank \| athlete \| country \| time \| notes row 1 : none \| nataliya petrusyova \| soviet union \| 1:24.10 \| or row 2 : none \| leah poulos \| united states \| 1:25.41 \| none row 3 : none \| sylvia albrecht \| east germany \| 1:26.46 \| none row 4 : 4 \| karin enke \| east germany \| 1:26.66 \| none row 5 : 5 \| beth heiden \| united states \| 1:27.01 \| none row 6 : 6 \| annie borckink \| netherlands \| 1:27.24 \| none row 7 : 7 \| sylvia burka \| canada \| 1:27.50 \| none row 8 : 8 \| ann-sofie jarnstrom \| sweden \| 1:28.10 \| none row 9 : 9 \| sylvia filipsson \| sweden \| 1:28.18 \| none row 10 : 10 \| annette carlen-karlsson \| sweden \| 1:28.25 \| none row 11 : 11 \| valentina lalenkova \| soviet union \| 1:28.27 \| none row 12 : 12 \| bjørg eva jensen \| norway \| 1:28.55 \| none row 13 : 13 \| sijtje van der lende \| netherlands \| 1:28.72 \| none row 14 : 14 \| sarah docter \| united states \| 1:28.80 \| none row 15 : 14 \| haitske valentijn-pijlman \| netherlands \| 1:28.80 \| none row 16 : 16 \| erwina rys-ferens \| poland \| 1:28.82 \| none row 17 : 17 \| miyoshi kato \| japan \| 1:28.97 \| none row 18 : 18 \| christa rothenburger \| east germany \| 1:29.69 \| none row 19 : 19 \| brenda webster \| canada \| 1:29.84 \| none row 20 : 20 \| irina kuleshova-kovrova \| soviet union \| 1:29.94 \| none row 21 : 21 \| monika pflug \| west germany \| 1:30.13 \| none row 22 : 22 \| makiko nagaya \| japan \| 1:30.27 \| none row 23 : 23 \| sigrid smuda \| west germany \| 1:30.29 \| none row 24 : 24 \| kathy vogt \| canada \| 1:30.33 \| none row 25 : 25 \| yuko yaegashi-ota \| japan \| 1:30.72 \| none row 26 : 26 \| lee nam-sun \| south korea \| 1:31.30 \| none row 27 : 27 \| cao guifeng \| china \| 1:31.74 \| none row 28 : 28 \| anneli repola \| finland \| 1:31.76 \| none row 29 : 29 \| silvia brunner \| switzerland \| 1:31.79 \| none row 30 : 30 \| lee seong-ae \| south korea \| 1:32.04 \| none row 31 : 31 \| zhang li \| china \| 1:32.20 \| none row 32 : 32 \| shen zhenshu \| china \| 1:32.49 \| none row 33 : 33 \| brigitte flierl \| west germany \| 1:33.61 \| none row 34 : 34 \| kim yeong-hui \| south korea \| 1:34.17 \| none row 35 : 35 \| kim ferran \| great britain \| 1:34.19 \| none row 36 : 36 \| marzia peretti \| italy \| 1:35.66 \| none row 37 : 37 \| mandy horsepool \| great britain \| 1:36.31 \| none	col : time row 1 : 1:28.18	select time where athlete = 'sylvia filipsson' <table_name> : table \begin{tabular}{llllll} \toprule & rank & athlete & country & time & notes \\ \midrule 0 & none & nataliya petrusyova & soviet union & 1:24.10 & or \\ 1 & none & leah poulos & united states & 1:25.41 & none \\ 2 & none & sylvia albrecht & east germany & 1:26.46 & none \\ 3 & 4 & karin enke & east germany & 1:26.66 & none \\ 4 & 5 & beth heiden & united states & 1:27.01 & none \\ 5 & 6 & annie borckink & netherlands & 1:27.24 & none \\ 6 & 7 & sylvia burka & canada & 1:27.50 & none \\ 7 & 8 & ann-sofie jarnstrom & sweden & 1:28.10 & none \\ 8 & 9 & sylvia filipsson & sweden & 1:28.18 & none \\ 9 & 10 & annette carlen-karlsson & sweden & 1:28.25 & none \\ 10 & 11 & valentina lalenkova & soviet union & 1:28.27 & none \\ 11 & 12 & bjørg eva jensen & norway & 1:28.55 & none \\ 12 & 13 & sijtje van der lende & netherlands & 1:28.72 & none \\ 13 & 14 & sarah docter & united states & 1:28.80 & none \\ 14 & 14 & haitske valentijn-pijlman & netherlands & 1:28.80 & none \\ 15 & 16 & erwina rys-ferens & poland & 1:28.82 & none \\ 16 & 17 & miyoshi kato & japan & 1:28.97 & none \\ 17 & 18 & christa rothenburger & east germany & 1:29.69 & none \\ 18 & 19 & brenda webster & canada & 1:29.84 & none \\ 19 & 20 & irina kuleshova-kovrova & soviet union & 1:29.94 & none \\ 20 & 21 & monika pflug & west germany & 1:30.13 & none \\ 21 & 22 & makiko nagaya & japan & 1:30.27 & none \\ 22 & 23 & sigrid smuda & west germany & 1:30.29 & none \\ 23 & 24 & kathy vogt & canada & 1:30.33 & none \\ 24 & 25 & yuko yaegashi-ota & japan & 1:30.72 & none \\ 25 & 26 & lee nam-sun & south korea & 1:31.30 & none \\ 26 & 27 & cao guifeng & china & 1:31.74 & none \\ 27 & 28 & anneli repola & finland & 1:31.76 & none \\ 28 & 29 & silvia brunner & switzerland & 1:31.79 & none \\ 29 & 30 & lee seong-ae & south korea & 1:32.04 & none \\ 30 & 31 & zhang li & china & 1:32.20 & none \\ 31 & 32 & shen zhenshu & china & 1:32.49 & none \\ 32 & 33 & brigitte flierl & west germany & 1:33.61 & none \\ 33 & 34 & kim yeong-hui & south korea & 1:34.17 & none \\ 34 & 35 & kim ferran & great britain & 1:34.19 & none \\ 35 & 36 & marzia peretti & italy & 1:35.66 & none \\ 36 & 37 & mandy horsepool & great britain & 1:36.31 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & time \\ \midrule 0 & 1:28.18 \\ \bottomrule \end{tabular}	select time where athlete = 'sylvia filipsson' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>athlete</th> <th>country</th> <th>time</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>none</td> <td>nataliya petrusyova</td> <td>soviet union</td> <td>1:24.10</td> <td>or</td> </tr> <tr> <th>1</th> <td>none</td> <td>leah poulos</td> <td>united states</td> <td>1:25.41</td> <td>none</td> </tr> <tr> <th>2</th> <td>none</td> <td>sylvia albrecht</td> <td>east germany</td> <td>1:26.46</td> <td>none</td> </tr> <tr> <th>3</th> <td>4</td> <td>karin enke</td> <td>east germany</td> <td>1:26.66</td> <td>none</td> </tr> <tr> <th>4</th> <td>5</td> <td>beth heiden</td> <td>united states</td> <td>1:27.01</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>annie borckink</td> <td>netherlands</td> <td>1:27.24</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>sylvia burka</td> <td>canada</td> <td>1:27.50</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>ann-sofie jarnstrom</td> <td>sweden</td> <td>1:28.10</td> <td>none</td> </tr> <tr> <th>8</th> <td>9</td> <td>sylvia filipsson</td> <td>sweden</td> <td>1:28.18</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>annette carlen-karlsson</td> <td>sweden</td> <td>1:28.25</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>valentina lalenkova</td> <td>soviet union</td> <td>1:28.27</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>bjørg eva jensen</td> <td>norway</td> <td>1:28.55</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>sijtje van der lende</td> <td>netherlands</td> <td>1:28.72</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>sarah docter</td> <td>united states</td> <td>1:28.80</td> <td>none</td> </tr> <tr> <th>14</th> <td>14</td> <td>haitske valentijn-pijlman</td> <td>netherlands</td> <td>1:28.80</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>erwina rys-ferens</td> <td>poland</td> <td>1:28.82</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>miyoshi kato</td> <td>japan</td> <td>1:28.97</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>christa rothenburger</td> <td>east germany</td> <td>1:29.69</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>brenda webster</td> <td>canada</td> <td>1:29.84</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>irina kuleshova-kovrova</td> <td>soviet union</td> <td>1:29.94</td> <td>none</td> </tr> <tr> <th>20</th> <td>21</td> <td>monika pflug</td> <td>west germany</td> <td>1:30.13</td> <td>none</td> </tr> <tr> <th>21</th> <td>22</td> <td>makiko nagaya</td> <td>japan</td> <td>1:30.27</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>sigrid smuda</td> <td>west germany</td> <td>1:30.29</td> <td>none</td> </tr> <tr> <th>23</th> <td>24</td> <td>kathy vogt</td> <td>canada</td> <td>1:30.33</td> <td>none</td> </tr> <tr> <th>24</th> <td>25</td> <td>yuko yaegashi-ota</td> <td>japan</td> <td>1:30.72</td> <td>none</td> </tr> <tr> <th>25</th> <td>26</td> <td>lee nam-sun</td> <td>south korea</td> <td>1:31.30</td> <td>none</td> </tr> <tr> <th>26</th> <td>27</td> <td>cao guifeng</td> <td>china</td> <td>1:31.74</td> <td>none</td> </tr> <tr> <th>27</th> <td>28</td> <td>anneli repola</td> <td>finland</td> <td>1:31.76</td> <td>none</td> </tr> <tr> <th>28</th> <td>29</td> <td>silvia brunner</td> <td>switzerland</td> <td>1:31.79</td> <td>none</td> </tr> <tr> <th>29</th> <td>30</td> <td>lee seong-ae</td> <td>south korea</td> <td>1:32.04</td> <td>none</td> </tr> <tr> <th>30</th> <td>31</td> <td>zhang li</td> <td>china</td> <td>1:32.20</td> <td>none</td> </tr> <tr> <th>31</th> <td>32</td> <td>shen zhenshu</td> <td>china</td> <td>1:32.49</td> <td>none</td> </tr> <tr> <th>32</th> <td>33</td> <td>brigitte flierl</td> <td>west germany</td> <td>1:33.61</td> <td>none</td> </tr> <tr> <th>33</th> <td>34</td> <td>kim yeong-hui</td> <td>south korea</td> <td>1:34.17</td> <td>none</td> </tr> <tr> <th>34</th> <td>35</td> <td>kim ferran</td> <td>great britain</td> <td>1:34.19</td> <td>none</td> </tr> <tr> <th>35</th> <td>36</td> <td>marzia peretti</td> <td>italy</td> <td>1:35.66</td> <td>none</td> </tr> <tr> <th>36</th> <td>37</td> <td>mandy horsepool</td> <td>great britain</td> <td>1:36.31</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>time</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1:28.18</td> </tr> </tbody> </table>	select time where athlete = 'sylvia filipsson' <table_name> : table \| \| rank \| athlete \| country \| time \| notes \| \|---:\|:-------\|:--------------------------\|:--------------\|:--------\|:--------\| \| 0 \| none \| nataliya petrusyova \| soviet union \| 1:24.10 \| or \| \| 1 \| none \| leah poulos \| united states \| 1:25.41 \| none \| \| 2 \| none \| sylvia albrecht \| east germany \| 1:26.46 \| none \| \| 3 \| 4 \| karin enke \| east germany \| 1:26.66 \| none \| \| 4 \| 5 \| beth heiden \| united states \| 1:27.01 \| none \| \| 5 \| 6 \| annie borckink \| netherlands \| 1:27.24 \| none \| \| 6 \| 7 \| sylvia burka \| canada \| 1:27.50 \| none \| \| 7 \| 8 \| ann-sofie jarnstrom \| sweden \| 1:28.10 \| none \| \| 8 \| 9 \| sylvia filipsson \| sweden \| 1:28.18 \| none \| \| 9 \| 10 \| annette carlen-karlsson \| sweden \| 1:28.25 \| none \| \| 10 \| 11 \| valentina lalenkova \| soviet union \| 1:28.27 \| none \| \| 11 \| 12 \| bjørg eva jensen \| norway \| 1:28.55 \| none \| \| 12 \| 13 \| sijtje van der lende \| netherlands \| 1:28.72 \| none \| \| 13 \| 14 \| sarah docter \| united states \| 1:28.80 \| none \| \| 14 \| 14 \| haitske valentijn-pijlman \| netherlands \| 1:28.80 \| none \| \| 15 \| 16 \| erwina rys-ferens \| poland \| 1:28.82 \| none \| \| 16 \| 17 \| miyoshi kato \| japan \| 1:28.97 \| none \| \| 17 \| 18 \| christa rothenburger \| east germany \| 1:29.69 \| none \| \| 18 \| 19 \| brenda webster \| canada \| 1:29.84 \| none \| \| 19 \| 20 \| irina kuleshova-kovrova \| soviet union \| 1:29.94 \| none \| \| 20 \| 21 \| monika pflug \| west germany \| 1:30.13 \| none \| \| 21 \| 22 \| makiko nagaya \| japan \| 1:30.27 \| none \| \| 22 \| 23 \| sigrid smuda \| west germany \| 1:30.29 \| none \| \| 23 \| 24 \| kathy vogt \| canada \| 1:30.33 \| none \| \| 24 \| 25 \| yuko yaegashi-ota \| japan \| 1:30.72 \| none \| \| 25 \| 26 \| lee nam-sun \| south korea \| 1:31.30 \| none \| \| 26 \| 27 \| cao guifeng \| china \| 1:31.74 \| none \| \| 27 \| 28 \| anneli repola \| finland \| 1:31.76 \| none \| \| 28 \| 29 \| silvia brunner \| switzerland \| 1:31.79 \| none \| \| 29 \| 30 \| lee seong-ae \| south korea \| 1:32.04 \| none \| \| 30 \| 31 \| zhang li \| china \| 1:32.20 \| none \| \| 31 \| 32 \| shen zhenshu \| china \| 1:32.49 \| none \| \| 32 \| 33 \| brigitte flierl \| west germany \| 1:33.61 \| none \| \| 33 \| 34 \| kim yeong-hui \| south korea \| 1:34.17 \| none \| \| 34 \| 35 \| kim ferran \| great britain \| 1:34.19 \| none \| \| 35 \| 36 \| marzia peretti \| italy \| 1:35.66 \| none \| \| 36 \| 37 \| mandy horsepool \| great britain \| 1:36.31 \| none \|	\| \| time \| 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select count ( country ) where country = 'sweden' col : season \| team \| country \| competition \| matches \| goals row 1 : 1999 \| djurgardens if \| sweden \| allsvenskan \| 15 \| 1 row 2 : 2000 \| djurgardens if \| sweden \| superettan \| 15 \| 3 row 3 : 2001 \| djurgardens if \| sweden \| allsvenskan \| 22 \| 7 row 4 : 2002-2003 \| grazer ak \| austria \| bundesliga \| 24 \| 6 row 5 : 2003 \| denizlispor \| turkey \| super lig \| 3 \| 0 row 6 : 2003 \| landskrona bois \| sweden \| allsvenskan \| 11 \| 3 row 7 : 2004 \| landskrona bois \| sweden \| allsvenskan \| 22 \| 4 row 8 : 2005 \| djurgardens if \| sweden \| allsvenskan \| 24 \| 12 row 9 : 2006 \| djurgardens if \| sweden \| allsvenskan \| 17 \| 6 row 10 : 2007 \| djurgardens if \| sweden \| allsvenskan \| 23 \| 4 row 11 : 2008 \| djurgardens if \| sweden \| allsvenskan \| 29 \| 6 row 12 : 2008-09 \| esbjerg fb \| denmark \| superliga \| 6 \| 0 row 13 : 2010 \| aab \| denmark \| superliga \| 3 \| 1 row 14 : 2011 \| assyriska ff \| sweden \| superettan \| 19 \| 5 row 15 : total \| total \| total \| total \| 233 \| 58	col : count ( "country" ) row 1 : 10	select count ( country ) where country = 'sweden' <table_name> : table \begin{tabular}{lllllll} \toprule & season & team & country & competition & matches & goals \\ \midrule 0 & 1999 & djurgardens if & sweden & allsvenskan & 15 & 1 \\ 1 & 2000 & djurgardens if & sweden & superettan & 15 & 3 \\ 2 & 2001 & djurgardens if & sweden & allsvenskan & 22 & 7 \\ 3 & 2002-2003 & grazer ak & austria & bundesliga & 24 & 6 \\ 4 & 2003 & denizlispor & turkey & super lig & 3 & 0 \\ 5 & 2003 & landskrona bois & sweden & allsvenskan & 11 & 3 \\ 6 & 2004 & landskrona bois & sweden & allsvenskan & 22 & 4 \\ 7 & 2005 & djurgardens if & sweden & allsvenskan & 24 & 12 \\ 8 & 2006 & djurgardens if & sweden & allsvenskan & 17 & 6 \\ 9 & 2007 & djurgardens if & sweden & allsvenskan & 23 & 4 \\ 10 & 2008 & djurgardens if & sweden & allsvenskan & 29 & 6 \\ 11 & 2008-09 & esbjerg fb & denmark & superliga & 6 & 0 \\ 12 & 2010 & aab & denmark & superliga & 3 & 1 \\ 13 & 2011 & assyriska ff & sweden & superettan & 19 & 5 \\ 14 & total & total & total & total & 233 & 58 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "country" ) \\ \midrule 0 & 10 \\ \bottomrule \end{tabular}	select count ( country ) where country = 'sweden' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>team</th> <th>country</th> <th>competition</th> <th>matches</th> <th>goals</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>15</td> <td>1</td> </tr> <tr> <th>1</th> <td>2000</td> <td>djurgardens if</td> <td>sweden</td> <td>superettan</td> <td>15</td> <td>3</td> </tr> <tr> <th>2</th> <td>2001</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>22</td> <td>7</td> </tr> <tr> <th>3</th> <td>2002-2003</td> <td>grazer ak</td> <td>austria</td> <td>bundesliga</td> <td>24</td> <td>6</td> </tr> <tr> <th>4</th> <td>2003</td> <td>denizlispor</td> <td>turkey</td> <td>super lig</td> <td>3</td> <td>0</td> </tr> <tr> <th>5</th> <td>2003</td> <td>landskrona bois</td> <td>sweden</td> <td>allsvenskan</td> <td>11</td> <td>3</td> </tr> <tr> <th>6</th> <td>2004</td> <td>landskrona bois</td> <td>sweden</td> <td>allsvenskan</td> <td>22</td> <td>4</td> </tr> <tr> <th>7</th> <td>2005</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>24</td> <td>12</td> </tr> <tr> <th>8</th> <td>2006</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>17</td> <td>6</td> </tr> <tr> <th>9</th> <td>2007</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>23</td> <td>4</td> </tr> <tr> <th>10</th> <td>2008</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>29</td> <td>6</td> </tr> <tr> <th>11</th> <td>2008-09</td> <td>esbjerg fb</td> <td>denmark</td> <td>superliga</td> <td>6</td> <td>0</td> </tr> <tr> <th>12</th> <td>2010</td> <td>aab</td> <td>denmark</td> <td>superliga</td> <td>3</td> <td>1</td> </tr> <tr> <th>13</th> <td>2011</td> <td>assyriska ff</td> <td>sweden</td> <td>superettan</td> <td>19</td> <td>5</td> </tr> <tr> <th>14</th> <td>total</td> <td>total</td> <td>total</td> <td>total</td> <td>233</td> <td>58</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "country" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>10</td> </tr> </tbody> </table>	select count ( country ) where country = 'sweden' <table_name> : table \| \| season \| team \| country \| competition \| matches \| goals \| \|---:\|:----------\|:----------------\|:----------\|:--------------\|----------:\|--------:\| \| 0 \| 1999 \| djurgardens if \| sweden \| allsvenskan \| 15 \| 1 \| \| 1 \| 2000 \| djurgardens if \| sweden \| superettan \| 15 \| 3 \| \| 2 \| 2001 \| djurgardens if \| sweden \| allsvenskan \| 22 \| 7 \| \| 3 \| 2002-2003 \| grazer ak \| austria \| bundesliga \| 24 \| 6 \| \| 4 \| 2003 \| denizlispor \| turkey \| super lig \| 3 \| 0 \| \| 5 \| 2003 \| landskrona bois \| sweden \| allsvenskan \| 11 \| 3 \| \| 6 \| 2004 \| landskrona bois \| sweden \| allsvenskan \| 22 \| 4 \| \| 7 \| 2005 \| djurgardens if \| sweden \| allsvenskan \| 24 \| 12 \| \| 8 \| 2006 \| djurgardens if \| sweden \| allsvenskan \| 17 \| 6 \| \| 9 \| 2007 \| djurgardens if \| sweden \| allsvenskan \| 23 \| 4 \| \| 10 \| 2008 \| djurgardens if \| sweden \| allsvenskan \| 29 \| 6 \| \| 11 \| 2008-09 \| esbjerg fb \| denmark \| superliga \| 6 \| 0 \| \| 12 \| 2010 \| aab \| denmark \| superliga \| 3 \| 1 \| \| 13 \| 2011 \| assyriska ff \| sweden \| superettan \| 19 \| 5 \| \| 14 \| total \| total \| total \| total \| 233 \| 58 \|	\| \| count ( "country" ) \| \|---:\|----------------------:\| \| 0 \| 10 \|	[ [ 1, 4025, 1056, 261, 5251, 262, 1625, 5251, 273, 296, 5328, 329, 275, 11, 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select count ( * ) where percentage = '1.9%' col : governorate \| percentage \| seats won \| total seats row 1 : al-anbar \| none \| 0 \| 29 row 2 : babil \| 8.2% \| 5 \| 30 row 3 : baghdad \| 5.4% \| 3 \| 57 row 4 : basra \| 11.6% \| 5 \| 35 row 5 : dhi qar \| 11.1% \| 5 \| 31 row 6 : diyala \| none \| 0 \| 29 row 7 : karbala \| 6.4% \| 4 \| 27 row 8 : maysan \| 15.2% \| 7 \| 27 row 9 : al-muthanna \| 9.3% \| 5 \| 26 row 10 : najaf \| 14.8% \| 7 \| 28 row 11 : ninawa \| 1.9% \| 0 \| 37 row 12 : al-qadisiyyah \| 11.7% \| 4 \| 28 row 13 : salah ad-din \| 2.9% \| 1 \| 28 row 14 : wassit \| 10.0% \| 6 \| 28 row 15 : total \| 6.6% \| 52 \| 440	col : count ( "*" ) row 1 : 1	select count ( * ) where percentage = '1.9%' <table_name> : table \begin{tabular}{lllll} \toprule & governorate & percentage & seats won & total seats \\ \midrule 0 & al-anbar & none & 0 & 29 \\ 1 & babil & 8.2% & 5 & 30 \\ 2 & baghdad & 5.4% & 3 & 57 \\ 3 & basra & 11.6% & 5 & 35 \\ 4 & dhi qar & 11.1% & 5 & 31 \\ 5 & diyala & none & 0 & 29 \\ 6 & karbala & 6.4% & 4 & 27 \\ 7 & maysan & 15.2% & 7 & 27 \\ 8 & al-muthanna & 9.3% & 5 & 26 \\ 9 & najaf & 14.8% & 7 & 28 \\ 10 & ninawa & 1.9% & 0 & 37 \\ 11 & al-qadisiyyah & 11.7% & 4 & 28 \\ 12 & salah ad-din & 2.9% & 1 & 28 \\ 13 & wassit & 10.0% & 6 & 28 \\ 14 & total & 6.6% & 52 & 440 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where percentage = '1.9%' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>governorate</th> <th>percentage</th> <th>seats won</th> <th>total seats</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>al-anbar</td> <td>none</td> <td>0</td> <td>29</td> </tr> <tr> <th>1</th> <td>babil</td> <td>8.2%</td> <td>5</td> <td>30</td> </tr> <tr> <th>2</th> <td>baghdad</td> <td>5.4%</td> <td>3</td> <td>57</td> </tr> <tr> <th>3</th> <td>basra</td> <td>11.6%</td> <td>5</td> <td>35</td> </tr> <tr> <th>4</th> <td>dhi qar</td> <td>11.1%</td> <td>5</td> <td>31</td> </tr> <tr> <th>5</th> <td>diyala</td> <td>none</td> <td>0</td> <td>29</td> </tr> <tr> <th>6</th> <td>karbala</td> <td>6.4%</td> <td>4</td> <td>27</td> </tr> <tr> <th>7</th> <td>maysan</td> <td>15.2%</td> <td>7</td> <td>27</td> </tr> <tr> <th>8</th> <td>al-muthanna</td> <td>9.3%</td> <td>5</td> <td>26</td> </tr> <tr> <th>9</th> <td>najaf</td> <td>14.8%</td> <td>7</td> <td>28</td> </tr> <tr> <th>10</th> <td>ninawa</td> <td>1.9%</td> <td>0</td> <td>37</td> </tr> <tr> <th>11</th> <td>al-qadisiyyah</td> <td>11.7%</td> <td>4</td> <td>28</td> </tr> <tr> <th>12</th> <td>salah ad-din</td> <td>2.9%</td> <td>1</td> <td>28</td> </tr> <tr> <th>13</th> <td>wassit</td> <td>10.0%</td> <td>6</td> <td>28</td> </tr> <tr> <th>14</th> <td>total</td> <td>6.6%</td> <td>52</td> <td>440</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where percentage = '1.9%' <table_name> : table \| \| governorate \| percentage \| seats won \| total seats \| \|---:\|:--------------\|:-------------\|------------:\|--------------:\| \| 0 \| al-anbar \| none \| 0 \| 29 \| \| 1 \| babil \| 8.2% \| 5 \| 30 \| \| 2 \| baghdad \| 5.4% \| 3 \| 57 \| \| 3 \| basra \| 11.6% \| 5 \| 35 \| \| 4 \| dhi qar \| 11.1% \| 5 \| 31 \| \| 5 \| diyala \| none \| 0 \| 29 \| \| 6 \| karbala \| 6.4% \| 4 \| 27 \| \| 7 \| maysan \| 15.2% \| 7 \| 27 \| \| 8 \| al-muthanna \| 9.3% \| 5 \| 26 \| \| 9 \| najaf \| 14.8% \| 7 \| 28 \| \| 10 \| ninawa \| 1.9% \| 0 \| 37 \| \| 11 \| al-qadisiyyah \| 11.7% \| 4 \| 28 \| \| 12 \| salah ad-din \| 2.9% \| 1 \| 28 \| \| 13 \| wassit \| 10.0% \| 6 \| 28 \| \| 14 \| total \| 6.6% \| 52 \| 440 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 11622, 273, 296, 21, 18, 29, 8604, 411, 2121, 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select nation where nation = 'germany' col : rank \| heat \| nation \| competitors \| time \| notes row 1 : 1 \| 2 \| united states \| kelly willie, derrick brew, andrew rock, darold williamson \| 2:59.30 \| q row 2 : 2 \| 2 \| nigeria \| james godday, musa audu, saul weigopwa, enefiok udo-obong \| 3:01.60 \| q, sb row 3 : 3 \| 2 \| bahamas \| andrae williams, dennis darling, nathaniel mckinney, christopher brown \| 3:01.74 \| q, sb row 4 : 4 \| 1 \| great britain \| timothy benjamin, sean baldock, malachi davis, matthew elias \| 3:02.40 \| q, sb row 5 : 5 \| 1 \| japan \| yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato \| 3:02.71 \| q row 6 : 6 \| 1 \| germany \| ingo schultz, kamghe gaba, ruwen faller, bastian swillims \| 3:02.77 \| q row 7 : 7 \| 1 \| australia \| john steffensen, clinton hill, patrick dwyer, mark ormrod \| 3:03.06 \| q row 8 : 8 \| 1 \| botswana \| oganeditse moseki, johnson kubisa, california molefe, kagiso kilego \| 3:03.32 \| q, sb row 9 : 9 \| 2 \| russia \| aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko \| 3:03.35 \| none row 10 : 10 \| 2 \| poland \| piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo \| 3:03.69 \| none row 11 : 11 \| 2 \| ukraine \| volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup \| 3:04.01 \| none row 12 : 12 \| 1 \| greece \| stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis \| 3:04.27 \| sb row 13 : 13 \| 1 \| france \| ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone \| 3:04.39 \| none row 14 : 14 \| 2 \| spain \| eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina \| 3:05.03 \| sb row 15 : none \| 2 \| south africa \| marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe \| dnf \| none row 16 : none \| 1 \| jamaica \| michael campbell, michael blackwood, jermaine gonzales, davian clarke \| dsq \| none	col : nation row 1 : germany	select nation where nation = 'germany' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & heat & nation & competitors & time & notes \\ \midrule 0 & 1 & 2 & united states & kelly willie, derrick brew, andrew rock, darold williamson & 2:59.30 & q \\ 1 & 2 & 2 & nigeria & james godday, musa audu, saul weigopwa, enefiok udo-obong & 3:01.60 & q, sb \\ 2 & 3 & 2 & bahamas & andrae williams, dennis darling, nathaniel mckinney, christopher brown & 3:01.74 & q, sb \\ 3 & 4 & 1 & great britain & timothy benjamin, sean baldock, malachi davis, matthew elias & 3:02.40 & q, sb \\ 4 & 5 & 1 & japan & yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato & 3:02.71 & q \\ 5 & 6 & 1 & germany & ingo schultz, kamghe gaba, ruwen faller, bastian swillims & 3:02.77 & q \\ 6 & 7 & 1 & australia & john steffensen, clinton hill, patrick dwyer, mark ormrod & 3:03.06 & q \\ 7 & 8 & 1 & botswana & oganeditse moseki, johnson kubisa, california molefe, kagiso kilego & 3:03.32 & q, sb \\ 8 & 9 & 2 & russia & aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko & 3:03.35 & none \\ 9 & 10 & 2 & poland & piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo & 3:03.69 & none \\ 10 & 11 & 2 & ukraine & volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup & 3:04.01 & none \\ 11 & 12 & 1 & greece & stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis & 3:04.27 & sb \\ 12 & 13 & 1 & france & ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone & 3:04.39 & none \\ 13 & 14 & 2 & spain & eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina & 3:05.03 & sb \\ 14 & none & 2 & south africa & marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe & dnf & none \\ 15 & none & 1 & jamaica & michael campbell, michael blackwood, jermaine gonzales, davian clarke & dsq & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & germany \\ \bottomrule \end{tabular}	select nation where nation = 'germany' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>heat</th> <th>nation</th> <th>competitors</th> <th>time</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>2</td> <td>united states</td> <td>kelly willie, derrick brew, andrew rock, darold williamson</td> <td>2:59.30</td> <td>q</td> </tr> <tr> <th>1</th> <td>2</td> <td>2</td> <td>nigeria</td> <td>james godday, musa audu, saul weigopwa, enefiok udo-obong</td> <td>3:01.60</td> <td>q, sb</td> </tr> <tr> <th>2</th> <td>3</td> <td>2</td> <td>bahamas</td> <td>andrae williams, dennis darling, nathaniel mckinney, christopher brown</td> <td>3:01.74</td> <td>q, sb</td> </tr> <tr> <th>3</th> <td>4</td> <td>1</td> <td>great britain</td> <td>timothy benjamin, sean baldock, malachi davis, matthew elias</td> <td>3:02.40</td> <td>q, sb</td> </tr> <tr> <th>4</th> <td>5</td> <td>1</td> <td>japan</td> <td>yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato</td> <td>3:02.71</td> <td>q</td> </tr> <tr> <th>5</th> <td>6</td> <td>1</td> <td>germany</td> <td>ingo schultz, kamghe gaba, ruwen faller, bastian swillims</td> <td>3:02.77</td> <td>q</td> </tr> <tr> <th>6</th> <td>7</td> <td>1</td> <td>australia</td> <td>john steffensen, clinton hill, patrick dwyer, mark ormrod</td> <td>3:03.06</td> <td>q</td> </tr> <tr> <th>7</th> <td>8</td> <td>1</td> <td>botswana</td> <td>oganeditse moseki, johnson kubisa, california molefe, kagiso kilego</td> <td>3:03.32</td> <td>q, sb</td> </tr> <tr> <th>8</th> <td>9</td> <td>2</td> <td>russia</td> <td>aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko</td> <td>3:03.35</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>2</td> <td>poland</td> <td>piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo</td> <td>3:03.69</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>2</td> <td>ukraine</td> <td>volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup</td> <td>3:04.01</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>1</td> <td>greece</td> <td>stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis</td> <td>3:04.27</td> <td>sb</td> </tr> <tr> <th>12</th> <td>13</td> <td>1</td> <td>france</td> <td>ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone</td> <td>3:04.39</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>2</td> <td>spain</td> <td>eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina</td> <td>3:05.03</td> <td>sb</td> </tr> <tr> <th>14</th> <td>none</td> <td>2</td> <td>south africa</td> <td>marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>15</th> <td>none</td> <td>1</td> <td>jamaica</td> <td>michael campbell, michael blackwood, jermaine gonzales, davian clarke</td> <td>dsq</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>germany</td> </tr> </tbody> </table>	select nation where nation = 'germany' <table_name> : table \| \| rank \| heat \| nation \| competitors \| time \| notes \| \|---:\|:-------\|-------:\|:--------------\|:------------------------------------------------------------------------------\|:--------\|:--------\| \| 0 \| 1 \| 2 \| united states \| kelly willie, derrick brew, andrew rock, darold williamson \| 2:59.30 \| q \| \| 1 \| 2 \| 2 \| nigeria \| james godday, musa audu, saul weigopwa, enefiok udo-obong \| 3:01.60 \| q, sb \| \| 2 \| 3 \| 2 \| bahamas \| andrae williams, dennis darling, nathaniel mckinney, christopher brown \| 3:01.74 \| q, sb \| \| 3 \| 4 \| 1 \| great britain \| timothy benjamin, sean baldock, malachi davis, matthew elias \| 3:02.40 \| q, sb \| \| 4 \| 5 \| 1 \| japan \| yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato \| 3:02.71 \| q \| \| 5 \| 6 \| 1 \| germany \| ingo schultz, kamghe gaba, ruwen faller, bastian swillims \| 3:02.77 \| q \| \| 6 \| 7 \| 1 \| australia \| john steffensen, clinton hill, patrick dwyer, mark ormrod \| 3:03.06 \| q \| \| 7 \| 8 \| 1 \| botswana \| oganeditse moseki, johnson kubisa, california molefe, kagiso kilego \| 3:03.32 \| q, sb \| \| 8 \| 9 \| 2 \| russia \| aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko \| 3:03.35 \| none \| \| 9 \| 10 \| 2 \| poland \| piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo \| 3:03.69 \| none \| \| 10 \| 11 \| 2 \| ukraine \| volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup \| 3:04.01 \| none \| \| 11 \| 12 \| 1 \| greece \| stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis \| 3:04.27 \| sb \| \| 12 \| 13 \| 1 \| france \| ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone \| 3:04.39 \| none \| \| 13 \| 14 \| 2 \| spain \| eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina \| 3:05.03 \| sb \| \| 14 \| none \| 2 \| south africa \| marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe \| dnf \| none \| \| 15 \| none \| 1 \| jamaica \| michael campbell, michael blackwood, jermaine gonzales, davian clarke \| dsq \| none \|	\| \| nation \| \|---:\|:---------\| \| 0 \| germany \|	[ [ 1, 4025, 290, 367, 1625, 290, 367, 273, 296, 693, 9353, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 580, 270, 1757, 451, 34, 203, 1377, 411, 451, 34, 82, 367, 1757, 451, 34, 203, 1377, 411, 451, 34, 31942, 13704, 1757, 451, 34, 203, 1377, 411, 451, 34, 957, 1757, 451, 34, 203, 1377, 411, 451, 34, 12903, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 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select round where method = 'unanimous decision' col : record \| date \| result \| opponent \| location \| method \| round row 1 : 13-0 \| 2013-07-12 00:00:00 \| win \| igor pylypenko \| porsche arena, stuttgart, germany \| unanimous decision \| 6 row 2 : 12-0 \| 2013-10-27 00:00:00 \| win \| alphonce mchumiatumbo \| sarajevo, bosnia and herzegovina \| decision \| 8 row 3 : 11-0 \| 2013-06-07 00:00:00 \| win \| alexander vasiliev \| westfalenhalle, dortmund, germany \| tko \| 2 row 4 : 10-0 \| 2013-02-02 00:00:00 \| win \| niko falin \| iss dome, dusseldorf, germany \| unanimous decision \| 6 row 5 : 9-0 \| 2012-02-12 00:00:00 \| win \| ladislav kovarik \| esprit arena, dusseldorf, germany \| unanimous decision \| 6 row 6 : 8-0 \| 2012-06-08 00:00:00 \| win \| ivica perkovic \| sarajevo, bosnia and herzegovina \| unanimous decision \| 12 row 7 : 7-0 \| 2012-04-13 00:00:00 \| win \| aliaksandr makaranka \| lanxess arena, cologne, germany \| ko \| 1 row 8 : 6-0 \| 2011-12-17 00:00:00 \| win \| ferenc zsalek \| sarajevo, bosnia and herzegovina \| ko \| 3 row 9 : 5-0 \| 2011-12-02 00:00:00 \| win \| liridon memishi \| sap arena, mannheim, germany \| unanimous decision \| 6 row 10 : 4-0 \| 2011-06-25 00:00:00 \| win \| werner kreiskott \| lanxess arena, cologne, germany \| unanimous decision \| 6 row 11 : 3-0 \| 2011-02-19 00:00:00 \| win \| ergin solmaz \| porsche arena, stuttgart, germany \| unanimous decision \| 4 row 12 : 2-0 \| 2004-09-03 00:00:00 \| win \| tomasz zeprzalka \| gorazde, bosnia and herzegovina \| tko \| 2 row 13 : 1-0 \| 2004-02-07 00:00:00 \| win \| ergin solmaz \| sarajevo, bosnia and herzegovina \| unanimous decision \| 4	col : round row 1 : 6 row 2 : 6 row 3 : 6 row 4 : 12 row 5 : 6 row 6 : 6 row 7 : 4 row 8 : 4	select round where method = 'unanimous decision' <table_name> : table \begin{tabular}{llllllll} \toprule & record & date & result & opponent & location & method & round \\ \midrule 0 & 13-0 & 2013-07-12 00:00:00 & win & igor pylypenko & porsche arena, stuttgart, germany & unanimous decision & 6 \\ 1 & 12-0 & 2013-10-27 00:00:00 & win & alphonce mchumiatumbo & sarajevo, bosnia and herzegovina & decision & 8 \\ 2 & 11-0 & 2013-06-07 00:00:00 & win & alexander vasiliev & westfalenhalle, dortmund, germany & tko & 2 \\ 3 & 10-0 & 2013-02-02 00:00:00 & win & niko falin & iss dome, dusseldorf, germany & unanimous decision & 6 \\ 4 & 9-0 & 2012-02-12 00:00:00 & win & ladislav kovarik & esprit arena, dusseldorf, germany & unanimous decision & 6 \\ 5 & 8-0 & 2012-06-08 00:00:00 & win & ivica perkovic & sarajevo, bosnia and herzegovina & unanimous decision & 12 \\ 6 & 7-0 & 2012-04-13 00:00:00 & win & aliaksandr makaranka & lanxess arena, cologne, germany & ko & 1 \\ 7 & 6-0 & 2011-12-17 00:00:00 & win & ferenc zsalek & sarajevo, bosnia and herzegovina & ko & 3 \\ 8 & 5-0 & 2011-12-02 00:00:00 & win & liridon memishi & sap arena, mannheim, germany & unanimous decision & 6 \\ 9 & 4-0 & 2011-06-25 00:00:00 & win & werner kreiskott & lanxess arena, cologne, germany & unanimous decision & 6 \\ 10 & 3-0 & 2011-02-19 00:00:00 & win & ergin solmaz & porsche arena, stuttgart, germany & unanimous decision & 4 \\ 11 & 2-0 & 2004-09-03 00:00:00 & win & tomasz zeprzalka & gorazde, bosnia and herzegovina & tko & 2 \\ 12 & 1-0 & 2004-02-07 00:00:00 & win & ergin solmaz & sarajevo, bosnia and herzegovina & unanimous decision & 4 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & round \\ \midrule 0 & 6 \\ 1 & 6 \\ 2 & 6 \\ 3 & 12 \\ 4 & 6 \\ 5 & 6 \\ 6 & 4 \\ 7 & 4 \\ \bottomrule \end{tabular}	select round where method = 'unanimous decision' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>record</th> <th>date</th> <th>result</th> <th>opponent</th> <th>location</th> <th>method</th> <th>round</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>13-0</td> <td>2013-07-12 00:00:00</td> <td>win</td> <td>igor pylypenko</td> <td>porsche arena, stuttgart, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>1</th> <td>12-0</td> <td>2013-10-27 00:00:00</td> <td>win</td> <td>alphonce mchumiatumbo</td> <td>sarajevo, bosnia and herzegovina</td> <td>decision</td> <td>8</td> </tr> <tr> <th>2</th> <td>11-0</td> <td>2013-06-07 00:00:00</td> <td>win</td> <td>alexander vasiliev</td> <td>westfalenhalle, dortmund, germany</td> <td>tko</td> <td>2</td> </tr> <tr> <th>3</th> <td>10-0</td> <td>2013-02-02 00:00:00</td> <td>win</td> <td>niko falin</td> <td>iss dome, dusseldorf, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>4</th> <td>9-0</td> <td>2012-02-12 00:00:00</td> <td>win</td> <td>ladislav kovarik</td> <td>esprit arena, dusseldorf, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>5</th> <td>8-0</td> <td>2012-06-08 00:00:00</td> <td>win</td> <td>ivica perkovic</td> <td>sarajevo, bosnia and herzegovina</td> <td>unanimous decision</td> <td>12</td> </tr> <tr> <th>6</th> <td>7-0</td> <td>2012-04-13 00:00:00</td> <td>win</td> <td>aliaksandr makaranka</td> <td>lanxess arena, cologne, germany</td> <td>ko</td> <td>1</td> </tr> <tr> <th>7</th> <td>6-0</td> <td>2011-12-17 00:00:00</td> <td>win</td> <td>ferenc zsalek</td> <td>sarajevo, bosnia and herzegovina</td> <td>ko</td> <td>3</td> </tr> <tr> <th>8</th> <td>5-0</td> <td>2011-12-02 00:00:00</td> <td>win</td> <td>liridon memishi</td> <td>sap arena, mannheim, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>9</th> <td>4-0</td> <td>2011-06-25 00:00:00</td> <td>win</td> <td>werner kreiskott</td> <td>lanxess arena, cologne, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>10</th> <td>3-0</td> <td>2011-02-19 00:00:00</td> <td>win</td> <td>ergin solmaz</td> <td>porsche arena, stuttgart, germany</td> <td>unanimous decision</td> <td>4</td> </tr> <tr> <th>11</th> <td>2-0</td> <td>2004-09-03 00:00:00</td> <td>win</td> <td>tomasz zeprzalka</td> <td>gorazde, bosnia and herzegovina</td> <td>tko</td> <td>2</td> </tr> <tr> <th>12</th> <td>1-0</td> <td>2004-02-07 00:00:00</td> <td>win</td> <td>ergin solmaz</td> <td>sarajevo, bosnia and herzegovina</td> <td>unanimous decision</td> <td>4</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>round</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>6</td> </tr> <tr> <th>1</th> <td>6</td> </tr> <tr> <th>2</th> <td>6</td> </tr> <tr> <th>3</th> <td>12</td> </tr> <tr> <th>4</th> <td>6</td> </tr> <tr> <th>5</th> <td>6</td> </tr> <tr> <th>6</th> <td>4</td> </tr> <tr> <th>7</th> <td>4</td> </tr> </tbody> </table>	select round where method = 'unanimous decision' <table_name> : table \| \| record \| date \| result \| opponent \| location \| method \| round \| \|---:\|:---------\|:--------------------\|:---------\|:----------------------\|:----------------------------------\|:-------------------\|--------:\| \| 0 \| 13-0 \| 2013-07-12 00:00:00 \| win \| igor pylypenko \| porsche arena, stuttgart, germany \| unanimous decision \| 6 \| \| 1 \| 12-0 \| 2013-10-27 00:00:00 \| win \| alphonce mchumiatumbo \| sarajevo, bosnia and herzegovina \| decision \| 8 \| \| 2 \| 11-0 \| 2013-06-07 00:00:00 \| win \| alexander vasiliev \| westfalenhalle, dortmund, germany \| tko \| 2 \| \| 3 \| 10-0 \| 2013-02-02 00:00:00 \| win \| niko falin \| iss dome, dusseldorf, germany \| unanimous decision \| 6 \| \| 4 \| 9-0 \| 2012-02-12 00:00:00 \| win \| ladislav kovarik \| esprit arena, dusseldorf, germany \| unanimous decision \| 6 \| \| 5 \| 8-0 \| 2012-06-08 00:00:00 \| win \| ivica perkovic \| sarajevo, bosnia and herzegovina \| unanimous decision \| 12 \| \| 6 \| 7-0 \| 2012-04-13 00:00:00 \| win \| aliaksandr makaranka \| lanxess arena, cologne, germany \| ko \| 1 \| \| 7 \| 6-0 \| 2011-12-17 00:00:00 \| win \| ferenc zsalek \| sarajevo, bosnia and herzegovina \| ko \| 3 \| \| 8 \| 5-0 \| 2011-12-02 00:00:00 \| win \| liridon memishi \| sap arena, mannheim, germany \| unanimous decision \| 6 \| \| 9 \| 4-0 \| 2011-06-25 00:00:00 \| win \| werner kreiskott \| lanxess arena, cologne, germany \| unanimous decision \| 6 \| \| 10 \| 3-0 \| 2011-02-19 00:00:00 \| win \| ergin solmaz \| porsche arena, stuttgart, germany \| unanimous decision \| 4 \| \| 11 \| 2-0 \| 2004-09-03 00:00:00 \| win \| tomasz zeprzalka \| gorazde, bosnia and herzegovina \| tko \| 2 \| \| 12 \| 1-0 \| 2004-02-07 00:00:00 \| win \| ergin solmaz \| sarajevo, bosnia and herzegovina \| unanimous decision \| 4 \|	\| \| round \| \|---:\|--------:\| \| 0 \| 6 \| \| 1 \| 6 \| \| 2 \| 6 \| \| 3 \| 12 \| \| 4 \| 6 \| \| 5 \| 6 \| \| 6 \| 4 \| \| 7 \| 4 \|	[ [ 1, 4025, 3643, 1625, 707, 273, 296, 318, 304, 381, 1481, 14604, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 3366, 1757, 451, 34, 203, 1377, 411, 451, 34, 712, 1757, 451, 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select count ( japanese title ) where year > 2010 col : year \| japanese title \| english title \| role \| network row 1 : 1997 \| あくり \| agri \| none \| nhk row 2 : 1998 \| ラフアントヒース \| love & peace \| yohei horiguchi \| ntv row 3 : 2001 \| ネハーラント \| neverland \| osamu seto \| tbs row 4 : 2002 \| hito ni yasashiku (人にやさしく / 3ヒース ) \| be nice to people \| yusuke \| fuji tv row 5 : 2002 \| engimono (演技者) \| acting by \| hachida \| fuji tv row 6 : 2004 \| kino wa tomo kyo no teki \| none \| none \| none row 7 : 2005 \| dekabeya (六本木おかしな捜査班) \| funny roppongi squad \| yukio ochi \| tv asahi row 8 : 2005 \| asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ) \| to asuka and to the unseen child \| sawamura kazuya \| fuji tv row 9 : 2005 \| nemureru mori no shitai (眠れる森の死体) \| sleeping corpse \| eiji/yamazaki \| fuji tv row 10 : 2006 \| アキハハラ@deep \| akihabara@deep \| box \| tbs row 11 : 2007 \| hana yori dango returns \| boys over flowers 2 \| junpei oribe \| tbs row 12 : 2007 \| hanazakari no kimitachi e \| ikemen paradise \| shuichi nakatsu \| fuji tv row 13 : 2008 \| hachimitsu to clover (ハチミツとクローハー) \| honey & clover \| yuta takemoto \| fuji tv row 14 : 2008 \| hanazakari no kimitachi e \| ikemen paradise \| shuichi nakatsu \| fuji tv row 15 : 2008 \| mao \| devil \| naoto serizawa \| tbs row 16 : 2009 \| inochi naki mono no koe (ウォイス) \| voice \| ryosuke ishimatsu \| fuji tv row 17 : 2009 \| majo saiban (魔女裁判) \| the witch trial \| toru yoshioka \| fuji tv row 18 : 2009 \| yonimo \"kim\" yo na monogatari \| the law of recycling suicides \| r 8427 \| none row 19 : 2010 \| unobore deka (うぬほれ刑事) \| conceited detective \| sadame honjo \| tbs row 20 : 2010 \| kyuukei no kouya \| spherical wilderness \| shoichi soeda \| fuji tv row 21 : 2012 \| osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~) \| late blooming sunflower -my life renewed- \| jotaro kodaira \| fuji tv row 22 : 2014 \| gunshi kanbei \| none \| dom justo takayama \| nhk	col : count ( "japanese title" ) row 1 : 2	select count ( japanese title ) where year > 2010 <table_name> : table \begin{tabular}{llllll} \toprule & year & japanese title & english title & role & network \\ \midrule 0 & 1997 & あくり & agri & none & nhk \\ 1 & 1998 & ラフアントヒース & love & peace & yohei horiguchi & ntv \\ 2 & 2001 & ネハーラント & neverland & osamu seto & tbs \\ 3 & 2002 & hito ni yasashiku (人にやさしく / 3ヒース ) & be nice to people & yusuke & fuji tv \\ 4 & 2002 & engimono (演技者) & acting by & hachida & fuji tv \\ 5 & 2004 & kino wa tomo kyo no teki & none & none & none \\ 6 & 2005 & dekabeya (六本木おかしな捜査班) & funny roppongi squad & yukio ochi & tv asahi \\ 7 & 2005 & asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ) & to asuka and to the unseen child & sawamura kazuya & fuji tv \\ 8 & 2005 & nemureru mori no shitai (眠れる森の死体) & sleeping corpse & eiji/yamazaki & fuji tv \\ 9 & 2006 & アキハハラ@deep & akihabara@deep & box & tbs \\ 10 & 2007 & hana yori dango returns & boys over flowers 2 & junpei oribe & tbs \\ 11 & 2007 & hanazakari no kimitachi e & ikemen paradise & shuichi nakatsu & fuji tv \\ 12 & 2008 & hachimitsu to clover (ハチミツとクローハー) & honey & clover & yuta takemoto & fuji tv \\ 13 & 2008 & hanazakari no kimitachi e & ikemen paradise & shuichi nakatsu & fuji tv \\ 14 & 2008 & mao & devil & naoto serizawa & tbs \\ 15 & 2009 & inochi naki mono no koe (ウォイス) & voice & ryosuke ishimatsu & fuji tv \\ 16 & 2009 & majo saiban (魔女裁判) & the witch trial & toru yoshioka & fuji tv \\ 17 & 2009 & yonimo \"kim\" yo na monogatari & the law of recycling suicides & r 8427 & none \\ 18 & 2010 & unobore deka (うぬほれ刑事) & conceited detective & sadame honjo & tbs \\ 19 & 2010 & kyuukei no kouya & spherical wilderness & shoichi soeda & fuji tv \\ 20 & 2012 & osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~) & late blooming sunflower -my life renewed- & jotaro kodaira & fuji tv \\ 21 & 2014 & gunshi kanbei & none & dom justo takayama & nhk \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "japanese title" ) \\ \midrule 0 & 2 \\ \bottomrule \end{tabular}	select count ( japanese title ) where year > 2010 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>japanese title</th> <th>english title</th> <th>role</th> <th>network</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1997</td> <td>あくり</td> <td>agri</td> <td>none</td> <td>nhk</td> </tr> <tr> <th>1</th> <td>1998</td> <td>ラフアントヒース</td> <td>love & peace</td> <td>yohei horiguchi</td> <td>ntv</td> </tr> <tr> <th>2</th> <td>2001</td> <td>ネハーラント</td> <td>neverland</td> <td>osamu seto</td> <td>tbs</td> </tr> <tr> <th>3</th> <td>2002</td> <td>hito ni yasashiku (人にやさしく / 3ヒース )</td> <td>be nice to people</td> <td>yusuke</td> <td>fuji tv</td> </tr> <tr> <th>4</th> <td>2002</td> <td>engimono (演技者)</td> <td>acting by</td> <td>hachida</td> <td>fuji tv</td> </tr> <tr> <th>5</th> <td>2004</td> <td>kino wa tomo kyo no teki</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>6</th> <td>2005</td> <td>dekabeya (六本木おかしな捜査班)</td> <td>funny roppongi squad</td> <td>yukio ochi</td> <td>tv asahi</td> </tr> <tr> <th>7</th> <td>2005</td> <td>asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ)</td> <td>to asuka and to the unseen child</td> <td>sawamura kazuya</td> <td>fuji tv</td> </tr> <tr> <th>8</th> <td>2005</td> <td>nemureru mori no shitai (眠れる森の死体)</td> <td>sleeping corpse</td> <td>eiji/yamazaki</td> <td>fuji tv</td> </tr> <tr> <th>9</th> <td>2006</td> <td>アキハハラ@deep</td> <td>akihabara@deep</td> <td>box</td> <td>tbs</td> </tr> <tr> <th>10</th> <td>2007</td> <td>hana yori dango returns</td> <td>boys over flowers 2</td> <td>junpei oribe</td> <td>tbs</td> </tr> <tr> <th>11</th> <td>2007</td> <td>hanazakari no kimitachi e</td> <td>ikemen paradise</td> <td>shuichi nakatsu</td> <td>fuji tv</td> </tr> <tr> <th>12</th> <td>2008</td> <td>hachimitsu to clover (ハチミツとクローハー)</td> <td>honey & clover</td> <td>yuta takemoto</td> <td>fuji tv</td> </tr> <tr> <th>13</th> <td>2008</td> <td>hanazakari no kimitachi e</td> <td>ikemen paradise</td> <td>shuichi nakatsu</td> <td>fuji tv</td> </tr> <tr> <th>14</th> <td>2008</td> <td>mao</td> <td>devil</td> <td>naoto serizawa</td> <td>tbs</td> </tr> <tr> <th>15</th> <td>2009</td> <td>inochi naki mono no koe (ウォイス)</td> <td>voice</td> <td>ryosuke ishimatsu</td> <td>fuji tv</td> </tr> <tr> <th>16</th> <td>2009</td> <td>majo saiban (魔女裁判)</td> <td>the witch trial</td> <td>toru yoshioka</td> <td>fuji tv</td> </tr> <tr> <th>17</th> <td>2009</td> <td>yonimo \"kim\" yo na monogatari</td> <td>the law of recycling suicides</td> <td>r 8427</td> <td>none</td> </tr> <tr> <th>18</th> <td>2010</td> <td>unobore deka (うぬほれ刑事)</td> <td>conceited detective</td> <td>sadame honjo</td> <td>tbs</td> </tr> <tr> <th>19</th> <td>2010</td> <td>kyuukei no kouya</td> <td>spherical wilderness</td> <td>shoichi soeda</td> <td>fuji tv</td> </tr> <tr> <th>20</th> <td>2012</td> <td>osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~)</td> <td>late blooming sunflower -my life renewed-</td> <td>jotaro kodaira</td> <td>fuji tv</td> </tr> <tr> <th>21</th> <td>2014</td> <td>gunshi kanbei</td> <td>none</td> <td>dom justo takayama</td> <td>nhk</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "japanese title" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> </tbody> </table>	select count ( japanese title ) where year > 2010 <table_name> : table \| \| year \| japanese title \| english title \| role \| network \| \|---:\|-------:\|:--------------------------------------------------------------------------------------------\|:------------------------------------------\|:-------------------\|:----------\| \| 0 \| 1997 \| あくり \| agri \| none \| nhk \| \| 1 \| 1998 \| ラフアントヒース \| love & peace \| yohei horiguchi \| ntv \| \| 2 \| 2001 \| ネハーラント \| neverland \| osamu seto \| tbs \| \| 3 \| 2002 \| hito ni yasashiku (人にやさしく / 3ヒース ) \| be nice to people \| yusuke \| fuji tv \| \| 4 \| 2002 \| engimono (演技者) \| acting by \| hachida \| fuji tv \| \| 5 \| 2004 \| kino wa tomo kyo no teki \| none \| none \| none \| \| 6 \| 2005 \| dekabeya (六本木おかしな捜査班) \| funny roppongi squad \| yukio ochi \| tv asahi \| \| 7 \| 2005 \| asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ) \| to asuka and to the unseen child \| sawamura kazuya \| fuji tv \| \| 8 \| 2005 \| nemureru mori no shitai (眠れる森の死体) \| sleeping corpse \| eiji/yamazaki \| fuji tv \| \| 9 \| 2006 \| アキハハラ@deep \| akihabara@deep \| box \| tbs \| \| 10 \| 2007 \| hana yori dango returns \| boys over flowers 2 \| junpei oribe \| tbs \| \| 11 \| 2007 \| hanazakari no kimitachi e \| ikemen paradise \| shuichi nakatsu \| fuji tv \| \| 12 \| 2008 \| hachimitsu to clover (ハチミツとクローハー) \| honey & clover \| yuta takemoto \| fuji tv \| \| 13 \| 2008 \| hanazakari no kimitachi e \| ikemen paradise \| shuichi nakatsu \| fuji tv \| \| 14 \| 2008 \| mao \| devil \| naoto serizawa \| tbs \| \| 15 \| 2009 \| inochi naki mono no koe (ウォイス) \| voice \| ryosuke ishimatsu \| fuji tv \| \| 16 \| 2009 \| majo saiban (魔女裁判) \| the witch trial \| toru yoshioka \| fuji tv \| \| 17 \| 2009 \| yonimo \"kim\" yo na monogatari \| the law of recycling suicides \| r 8427 \| none \| \| 18 \| 2010 \| unobore deka (うぬほれ刑事) \| conceited detective \| sadame honjo \| tbs \| \| 19 \| 2010 \| kyuukei no kouya \| spherical wilderness \| shoichi soeda \| fuji tv \| \| 20 \| 2012 \| osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~) \| late blooming sunflower -my life renewed- \| jotaro kodaira \| fuji tv \| \| 21 \| 2014 \| gunshi kanbei \| none \| dom justo takayama \| nhk \|	\| \| count ( "japanese title" ) \| \|---:\|-----------------------------:\| \| 0 \| 2 \|	[ [ 1, 4025, 1056, 261, 525, 30472, 3392, 2077, 262, 1625, 3286, 405, 18965, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 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select year where label = 'emi' col : year \| title \| label \| uk singles chart \| u.s. billboard hot 100 chart row 1 : 1969 \| "melting pot" \| philips \| 3 \| none row 2 : 1970 \| "good morning freedom" \| philips \| 10 \| none row 3 : 1970 \| "our world" \| philips \| 17 \| 64 row 4 : 1971 \| "the banner man" \| regal zonophone \| 3 \| none row 5 : 1972 \| "stay with me" \| regal zonophone \| 11 \| none row 6 : 1973 \| "by the devil (i was tempted)" \| emi \| 26 \| none row 7 : 1973 \| "randy" \| emi \| 9 \| none	col : year row 1 : 1973 row 2 : 1973	select year where label = 'emi' <table_name> : table \begin{tabular}{llllll} \toprule & year & title & label & uk singles chart & u.s. billboard hot 100 chart \\ \midrule 0 & 1969 & "melting pot" & philips & 3 & none \\ 1 & 1970 & "good morning freedom" & philips & 10 & none \\ 2 & 1970 & "our world" & philips & 17 & 64 \\ 3 & 1971 & "the banner man" & regal zonophone & 3 & none \\ 4 & 1972 & "stay with me" & regal zonophone & 11 & none \\ 5 & 1973 & "by the devil (i was tempted)" & emi & 26 & none \\ 6 & 1973 & "randy" & emi & 9 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 1973 \\ 1 & 1973 \\ \bottomrule \end{tabular}	select year where label = 'emi' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>title</th> <th>label</th> <th>uk singles chart</th> <th>u.s. billboard hot 100 chart</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1969</td> <td>"melting pot"</td> <td>philips</td> <td>3</td> <td>none</td> </tr> <tr> <th>1</th> <td>1970</td> <td>"good morning freedom"</td> <td>philips</td> <td>10</td> <td>none</td> </tr> <tr> <th>2</th> <td>1970</td> <td>"our world"</td> <td>philips</td> <td>17</td> <td>64</td> </tr> <tr> <th>3</th> <td>1971</td> <td>"the banner man"</td> <td>regal zonophone</td> <td>3</td> <td>none</td> </tr> <tr> <th>4</th> <td>1972</td> <td>"stay with me"</td> <td>regal zonophone</td> <td>11</td> <td>none</td> </tr> <tr> <th>5</th> <td>1973</td> <td>"by the devil (i was tempted)"</td> <td>emi</td> <td>26</td> <td>none</td> </tr> <tr> <th>6</th> <td>1973</td> <td>"randy"</td> <td>emi</td> <td>9</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1973</td> </tr> <tr> <th>1</th> <td>1973</td> </tr> </tbody> </table>	select year where label = 'emi' <table_name> : table \| \| year \| title \| label \| uk singles chart \| u.s. billboard hot 100 chart \| \|---:\|-------:\|:-------------------------------\|:----------------\|-------------------:\|:-------------------------------\| \| 0 \| 1969 \| "melting pot" \| philips \| 3 \| none \| \| 1 \| 1970 \| "good morning freedom" \| philips \| 10 \| none \| \| 2 \| 1970 \| "our world" \| philips \| 17 \| 64 \| \| 3 \| 1971 \| "the banner man" \| regal zonophone \| 3 \| none \| \| 4 \| 1972 \| "stay with me" \| regal zonophone \| 11 \| none \| \| 5 \| 1973 \| "by the devil (i was tempted)" \| emi \| 26 \| none \| \| 6 \| 1973 \| "randy" \| emi \| 9 \| none \|	\| \| year \| \|---:\|-------:\| \| 0 \| 1973 \| \| 1 \| 1973 \|	[ [ 1, 4025, 3286, 1625, 1433, 273, 296, 351, 77, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 2649, 1757, 451, 34, 203, 1377, 411, 451, 34, 1925, 1757, 451, 34, 203, 1377, 411, 451, 34, 19445, 4864, 1040, 4980, 1757, 451, 34, 203, 1377, 411, 451, 34, 89, 18, 87, 18, 20714, 3752, 12811, 2130, 4980, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 3657, 8148, 1757, 4465, 34, 203, 1377, 411, 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select sum ( competition ) where venue = 'osaka, japan' col : year \| competition \| venue \| position \| event \| notes row 1 : 1998 \| turin marathon \| turin, italy \| 3rd \| marathon \| 2:12:59 row 2 : 2003 \| lisbon marathon \| lisbon, portugal \| 1st \| marathon \| 2:15:31 row 3 : 2004 \| vienna marathon \| vienna, austria \| 3rd \| marathon \| 2:11:24 row 4 : 2004 \| berlin marathon \| berlin, germany \| 5th \| marathon \| 2:09:08 row 5 : 2005 \| world championships \| helsinki, finland \| 18th \| marathon \| 2:16:33 row 6 : 2006 \| paris marathon \| paris, france \| 4th \| marathon \| 2:08:55 row 7 : 2006 \| lisbon marathon \| lisbon, portugal \| 1st \| marathon \| 2:21:08 row 8 : 2007 \| world championships \| osaka, japan \| none \| marathon \| dns	col : sum ( "competition" ) row 1 : 0	select sum ( competition ) where venue = 'osaka, japan' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 1998 & turin marathon & turin, italy & 3rd & marathon & 2:12:59 \\ 1 & 2003 & lisbon marathon & lisbon, portugal & 1st & marathon & 2:15:31 \\ 2 & 2004 & vienna marathon & vienna, austria & 3rd & marathon & 2:11:24 \\ 3 & 2004 & berlin marathon & berlin, germany & 5th & marathon & 2:09:08 \\ 4 & 2005 & world championships & helsinki, finland & 18th & marathon & 2:16:33 \\ 5 & 2006 & paris marathon & paris, france & 4th & marathon & 2:08:55 \\ 6 & 2006 & lisbon marathon & lisbon, portugal & 1st & marathon & 2:21:08 \\ 7 & 2007 & world championships & osaka, japan & none & marathon & dns \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & sum ( "competition" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}	select sum ( competition ) where venue = 'osaka, japan' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1998</td> <td>turin marathon</td> <td>turin, italy</td> <td>3rd</td> <td>marathon</td> <td>2:12:59</td> </tr> <tr> <th>1</th> <td>2003</td> <td>lisbon marathon</td> <td>lisbon, portugal</td> <td>1st</td> <td>marathon</td> <td>2:15:31</td> </tr> <tr> <th>2</th> <td>2004</td> <td>vienna marathon</td> <td>vienna, austria</td> <td>3rd</td> <td>marathon</td> <td>2:11:24</td> </tr> <tr> <th>3</th> <td>2004</td> <td>berlin marathon</td> <td>berlin, germany</td> <td>5th</td> <td>marathon</td> <td>2:09:08</td> </tr> <tr> <th>4</th> <td>2005</td> <td>world championships</td> <td>helsinki, finland</td> <td>18th</td> <td>marathon</td> <td>2:16:33</td> </tr> <tr> <th>5</th> <td>2006</td> <td>paris marathon</td> <td>paris, france</td> <td>4th</td> <td>marathon</td> <td>2:08:55</td> </tr> <tr> <th>6</th> <td>2006</td> <td>lisbon marathon</td> <td>lisbon, portugal</td> <td>1st</td> <td>marathon</td> <td>2:21:08</td> </tr> <tr> <th>7</th> <td>2007</td> <td>world championships</td> <td>osaka, japan</td> <td>none</td> <td>marathon</td> <td>dns</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>sum ( "competition" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>	select sum ( competition ) where venue = 'osaka, japan' <table_name> : table \| \| year \| competition \| venue \| position \| event \| notes \| \|---:\|-------:\|:--------------------\|:------------------\|:-----------\|:---------\|:--------\| \| 0 \| 1998 \| turin marathon \| turin, italy \| 3rd \| marathon \| 2:12:59 \| \| 1 \| 2003 \| lisbon marathon \| lisbon, portugal \| 1st \| marathon \| 2:15:31 \| \| 2 \| 2004 \| vienna marathon \| vienna, austria \| 3rd \| marathon \| 2:11:24 \| \| 3 \| 2004 \| berlin marathon \| berlin, germany \| 5th \| marathon \| 2:09:08 \| \| 4 \| 2005 \| world championships \| helsinki, finland \| 18th \| marathon \| 2:16:33 \| \| 5 \| 2006 \| paris marathon \| paris, france \| 4th \| marathon \| 2:08:55 \| \| 6 \| 2006 \| lisbon marathon \| lisbon, portugal \| 1st \| marathon \| 2:21:08 \| \| 7 \| 2007 \| world championships \| osaka, japan \| none \| marathon \| dns \|	\| \| sum ( "competition" ) \| \|---:\|------------------------:\| \| 0 \| 0 \|	[ [ 1, 4025, 2142, 261, 25163, 608, 262, 1625, 331, 275, 344, 273, 296, 538, 581, 69, 16, 525, 30472, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 31942, 608, 1757, 451, 34, 203, 1377, 411, 451, 34, 24612, 1757, 451, 34, 203, 1377, 411, 451, 34, 3276, 1757, 451, 34, 203, 1377, 411, 451, 34, 2575, 1757, 451, 34, 203, 1377, 411, 451, 34, 12903, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 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select package where flash size = '4k' col : chip \| flash size \| eeprom \| sram \| frequency [mhz] \| package row 1 : at90s1200 \| 1k \| 64 \| 0 \| 12 \| pdip-20 row 2 : at90s2313 \| 2k \| 128 \| 128 \| 10 \| pdip-20 row 3 : at90s/ls2323 \| 2k \| 128 \| 128 \| 10 \| pdip-8 row 4 : at90s/ls2343 \| 2k \| 128 \| 128 \| 10 \| pdip-8 row 5 : at90s4414 \| 4k \| 256 \| 256 \| 8 \| pdip-40 row 6 : at90s/ls4434 \| 4k \| 256 \| 256 \| 8 \| pdip-40 row 7 : at90s8515 \| 8k \| 512 \| 512 \| 8 \| pdip-40 row 8 : at90s/ls8535 \| 8k \| 512 \| 512 \| 8 \| pdip-40	col : package row 1 : pdip-40 row 2 : pdip-40	select package where flash size = '4k' <table_name> : table \begin{tabular}{lllllll} \toprule & chip & flash size & eeprom & sram & frequency [mhz] & package \\ \midrule 0 & at90s1200 & 1k & 64 & 0 & 12 & pdip-20 \\ 1 & at90s2313 & 2k & 128 & 128 & 10 & pdip-20 \\ 2 & at90s/ls2323 & 2k & 128 & 128 & 10 & pdip-8 \\ 3 & at90s/ls2343 & 2k & 128 & 128 & 10 & pdip-8 \\ 4 & at90s4414 & 4k & 256 & 256 & 8 & pdip-40 \\ 5 & at90s/ls4434 & 4k & 256 & 256 & 8 & pdip-40 \\ 6 & at90s8515 & 8k & 512 & 512 & 8 & pdip-40 \\ 7 & at90s/ls8535 & 8k & 512 & 512 & 8 & pdip-40 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & package \\ \midrule 0 & pdip-40 \\ 1 & pdip-40 \\ \bottomrule \end{tabular}	select package where flash size = '4k' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>chip</th> <th>flash size</th> <th>eeprom</th> <th>sram</th> <th>frequency [mhz]</th> <th>package</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>at90s1200</td> <td>1k</td> <td>64</td> <td>0</td> <td>12</td> <td>pdip-20</td> </tr> <tr> <th>1</th> <td>at90s2313</td> <td>2k</td> <td>128</td> <td>128</td> <td>10</td> <td>pdip-20</td> </tr> <tr> <th>2</th> <td>at90s/ls2323</td> <td>2k</td> <td>128</td> <td>128</td> <td>10</td> <td>pdip-8</td> </tr> <tr> <th>3</th> <td>at90s/ls2343</td> <td>2k</td> <td>128</td> <td>128</td> <td>10</td> <td>pdip-8</td> </tr> <tr> <th>4</th> <td>at90s4414</td> <td>4k</td> <td>256</td> <td>256</td> <td>8</td> <td>pdip-40</td> </tr> <tr> <th>5</th> <td>at90s/ls4434</td> <td>4k</td> <td>256</td> <td>256</td> <td>8</td> <td>pdip-40</td> </tr> <tr> <th>6</th> <td>at90s8515</td> <td>8k</td> <td>512</td> <td>512</td> <td>8</td> <td>pdip-40</td> </tr> <tr> <th>7</th> <td>at90s/ls8535</td> <td>8k</td> <td>512</td> <td>512</td> <td>8</td> <td>pdip-40</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>package</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>pdip-40</td> </tr> <tr> <th>1</th> <td>pdip-40</td> </tr> </tbody> </table>	select package where flash size = '4k' <table_name> : table \| \| chip \| flash size \| eeprom \| sram \| frequency [mhz] \| package \| \|---:\|:-------------\|:-------------\|---------:\|-------:\|------------------:\|:----------\| \| 0 \| at90s1200 \| 1k \| 64 \| 0 \| 12 \| pdip-20 \| \| 1 \| at90s2313 \| 2k \| 128 \| 128 \| 10 \| pdip-20 \| \| 2 \| at90s/ls2323 \| 2k \| 128 \| 128 \| 10 \| pdip-8 \| \| 3 \| at90s/ls2343 \| 2k \| 128 \| 128 \| 10 \| pdip-8 \| \| 4 \| at90s4414 \| 4k \| 256 \| 256 \| 8 \| pdip-40 \| \| 5 \| at90s/ls4434 \| 4k \| 256 \| 256 \| 8 \| pdip-40 \| \| 6 \| at90s8515 \| 8k \| 512 \| 512 \| 8 \| pdip-40 \| \| 7 \| at90s/ls8535 \| 8k \| 512 \| 512 \| 8 \| pdip-40 \|	\| \| package \| \|---:\|:----------\| \| 0 \| pdip-40 \| \| 1 \| pdip-40 \|	[ [ 1, 4025, 2181, 1625, 9563, 963, 273, 296, 24, 79, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 343, 625, 1757, 451, 34, 203, 1377, 411, 451, 34, 13440, 963, 1757, 451, 34, 203, 1377, 411, 451, 34, 2661, 520, 1757, 451, 34, 203, 1377, 411, 451, 34, 87, 1940, 1757, 451, 34, 203, 1377, 411, 451, 34, 14092, 306, 81, 76, 94, 65, 1757, 451, 34, 203, 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select count ( * ) where partner = 'jim mcmanus' col : outcome \| no. \| date \| tournament \| surface \| partner \| opponents in the final \| score in the final row 1 : runner-up \| 1 \| 1969 \| los angeles, u.s \| hard \| jim mcmanus \| pancho gonzales ron holmberg \| 3-6, 4-6 row 2 : runner-up \| 2 \| 1970 \| merion, u.s \| hard \| jim mcmanus \| william bowrey ray ruffels \| 6-3, 2-6, 5-7 row 3 : winner \| 1 \| 1971 \| columbus, u.s \| hard \| jim mcmanus \| jimmy connors roscoe tanner \| 4-6, 7-5, 6-2 row 4 : winner \| 2 \| 1971 \| merion, u.s \| hard \| clark graebner \| robert mckinley dick stockton \| 7-6, 6-3 row 5 : winner \| 3 \| 1971 \| sacramento, u.s \| hard \| jim mcmanus \| bob maud frew mcmillan \| 7-6, 6-3 row 6 : winner \| 4 \| 1972 \| los angeles, u.s \| outdoor \| jim mcmanus \| ilie nastase ion tiriac \| 6-2, 5-7, 6-4 row 7 : winner \| 5 \| 1972 \| london/queen's club, england \| grass \| jim mcmanus \| jurgen fassbender karl meiler \| 4-6, 6-3, 7-5 row 8 : runner-up \| 3 \| 1972 \| tanglewood, u.s \| other \| jim mcmanus \| bob hewitt andrew pattison \| 4-6, 4-6	col : count ( "*" ) row 1 : 7	select count ( * ) where partner = 'jim mcmanus' <table_name> : table \begin{tabular}{lllllllll} \toprule & outcome & no. & date & tournament & surface & partner & opponents in the final & score in the final \\ \midrule 0 & runner-up & 1 & 1969 & los angeles, u.s & hard & jim mcmanus & pancho gonzales ron holmberg & 3-6, 4-6 \\ 1 & runner-up & 2 & 1970 & merion, u.s & hard & jim mcmanus & william bowrey ray ruffels & 6-3, 2-6, 5-7 \\ 2 & winner & 1 & 1971 & columbus, u.s & hard & jim mcmanus & jimmy connors roscoe tanner & 4-6, 7-5, 6-2 \\ 3 & winner & 2 & 1971 & merion, u.s & hard & clark graebner & robert mckinley dick stockton & 7-6, 6-3 \\ 4 & winner & 3 & 1971 & sacramento, u.s & hard & jim mcmanus & bob maud frew mcmillan & 7-6, 6-3 \\ 5 & winner & 4 & 1972 & los angeles, u.s & outdoor & jim mcmanus & ilie nastase ion tiriac & 6-2, 5-7, 6-4 \\ 6 & winner & 5 & 1972 & london/queen's club, england & grass & jim mcmanus & jurgen fassbender karl meiler & 4-6, 6-3, 7-5 \\ 7 & runner-up & 3 & 1972 & tanglewood, u.s & other & jim mcmanus & bob hewitt andrew pattison & 4-6, 4-6 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 7 \\ \bottomrule \end{tabular}	select count ( * ) where partner = 'jim mcmanus' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>outcome</th> <th>no.</th> <th>date</th> <th>tournament</th> <th>surface</th> <th>partner</th> <th>opponents in the final</th> <th>score in the final</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>runner-up</td> <td>1</td> <td>1969</td> <td>los angeles, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>pancho gonzales ron holmberg</td> <td>3-6, 4-6</td> </tr> <tr> <th>1</th> <td>runner-up</td> <td>2</td> <td>1970</td> <td>merion, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>william bowrey ray ruffels</td> <td>6-3, 2-6, 5-7</td> </tr> <tr> <th>2</th> <td>winner</td> <td>1</td> <td>1971</td> <td>columbus, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>jimmy connors roscoe tanner</td> <td>4-6, 7-5, 6-2</td> </tr> <tr> <th>3</th> <td>winner</td> <td>2</td> <td>1971</td> <td>merion, u.s</td> <td>hard</td> <td>clark graebner</td> <td>robert mckinley dick stockton</td> <td>7-6, 6-3</td> </tr> <tr> <th>4</th> <td>winner</td> <td>3</td> <td>1971</td> <td>sacramento, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>bob maud frew mcmillan</td> <td>7-6, 6-3</td> </tr> <tr> <th>5</th> <td>winner</td> <td>4</td> <td>1972</td> <td>los angeles, u.s</td> <td>outdoor</td> <td>jim mcmanus</td> <td>ilie nastase ion tiriac</td> <td>6-2, 5-7, 6-4</td> </tr> <tr> <th>6</th> <td>winner</td> <td>5</td> <td>1972</td> <td>london/queen's club, england</td> <td>grass</td> <td>jim mcmanus</td> <td>jurgen fassbender karl meiler</td> <td>4-6, 6-3, 7-5</td> </tr> <tr> <th>7</th> <td>runner-up</td> <td>3</td> <td>1972</td> <td>tanglewood, u.s</td> <td>other</td> <td>jim mcmanus</td> <td>bob hewitt andrew pattison</td> <td>4-6, 4-6</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7</td> </tr> </tbody> </table>	select count ( * ) where partner = 'jim mcmanus' <table_name> : table \| \| outcome \| no. \| date \| tournament \| surface \| partner \| opponents in the final \| score in the final \| \|---:\|:----------\|------:\|-------:\|:-----------------------------\|:----------\|:---------------\|:------------------------------\|:---------------------\| \| 0 \| runner-up \| 1 \| 1969 \| los angeles, u.s \| hard \| jim mcmanus \| pancho gonzales ron holmberg \| 3-6, 4-6 \| \| 1 \| runner-up \| 2 \| 1970 \| merion, u.s \| hard \| jim mcmanus \| william bowrey ray ruffels \| 6-3, 2-6, 5-7 \| \| 2 \| winner \| 1 \| 1971 \| columbus, u.s \| hard \| jim mcmanus \| jimmy connors roscoe tanner \| 4-6, 7-5, 6-2 \| \| 3 \| winner \| 2 \| 1971 \| merion, u.s \| hard \| clark graebner \| robert mckinley dick stockton \| 7-6, 6-3 \| \| 4 \| winner \| 3 \| 1971 \| sacramento, u.s \| hard \| jim mcmanus \| bob maud frew mcmillan \| 7-6, 6-3 \| \| 5 \| winner \| 4 \| 1972 \| los angeles, u.s \| outdoor \| jim mcmanus \| ilie nastase ion tiriac \| 6-2, 5-7, 6-4 \| \| 6 \| winner \| 5 \| 1972 \| london/queen's club, england \| grass \| jim mcmanus \| jurgen fassbender karl meiler \| 4-6, 6-3, 7-5 \| \| 7 \| runner-up \| 3 \| 1972 \| tanglewood, u.s \| other \| jim mcmanus \| bob hewitt andrew pattison \| 4-6, 4-6 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 7 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 19170, 273, 296, 78, 381, 6108, 4728, 407, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 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select # where # = 14 col : # \| name \| birth and death \| office started \| office ended row 1 : 1 \| geir vidalin \| 27 october 1761 - 20 september 1823 \| 1801 \| 1823 row 2 : 2 \| steingrimur jonsson \| none \| 1824 \| 1845 row 3 : 3 \| helgi thordersen \| 8 april 1794 - 4 december 1867 \| 1846 \| 1866 row 4 : 4 \| 'petur petursson \| 3 october 1808 - 15 may 1891 \| 1866 \| 1889 row 5 : 5 \| hallgrimur sveinsson \| 5 april 1841 - 16 december 1909 \| 1889 \| 1908 row 6 : 6 \| þorhallur bjarnarson \| 2 december 1855 - 15 december 1916 \| 1908 \| 1916 row 7 : 7 \| jon helgason \| 1866 - 1942 \| 1917 \| 1939 row 8 : 8 \| sigurgeir sigurðsson \| 3 august 1890 - 13 october 1953 \| 1939 \| 1953 row 9 : 9 \| asmundur guðmundsson \| 6 october 1888 reykholt - 29 may 1969 reykjavik \| 1954 \| 1989 row 10 : 10 \| sigurbjorn einarsson \| 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik \| 1959 \| 1981 row 11 : 11 \| petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) \| 2 june 1919 - 3 june 2010 \| 1981 \| 1989 row 12 : 12 \| olafur skulason \| 29 december 1929 - 9 june 2008 \| 1989 \| 1997 row 13 : 13 \| karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) \| 5 february 1947 reykjavik \| 1998 \| 2012 row 14 : 14 \| agnes sigurðardottir \| 19 october 1954 isafjorður \| 24 june 2012 \| incumbent	col : # row 1 : 14	select # where # = 14 <table_name> : table \begin{tabular}{llllll} \toprule & # & name & birth and death & office started & office ended \\ \midrule 0 & 1 & geir vidalin & 27 october 1761 - 20 september 1823 & 1801 & 1823 \\ 1 & 2 & steingrimur jonsson & none & 1824 & 1845 \\ 2 & 3 & helgi thordersen & 8 april 1794 - 4 december 1867 & 1846 & 1866 \\ 3 & 4 & 'petur petursson & 3 october 1808 - 15 may 1891 & 1866 & 1889 \\ 4 & 5 & hallgrimur sveinsson & 5 april 1841 - 16 december 1909 & 1889 & 1908 \\ 5 & 6 & þorhallur bjarnarson & 2 december 1855 - 15 december 1916 & 1908 & 1916 \\ 6 & 7 & jon helgason & 1866 - 1942 & 1917 & 1939 \\ 7 & 8 & sigurgeir sigurðsson & 3 august 1890 - 13 october 1953 & 1939 & 1953 \\ 8 & 9 & asmundur guðmundsson & 6 october 1888 reykholt - 29 may 1969 reykjavik & 1954 & 1989 \\ 9 & 10 & sigurbjorn einarsson & 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik & 1959 & 1981 \\ 10 & 11 & petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) & 2 june 1919 - 3 june 2010 & 1981 & 1989 \\ 11 & 12 & olafur skulason & 29 december 1929 - 9 june 2008 & 1989 & 1997 \\ 12 & 13 & karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) & 5 february 1947 reykjavik & 1998 & 2012 \\ 13 & 14 & agnes sigurðardottir & 19 october 1954 isafjorður & 24 june 2012 & incumbent \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & # \\ \midrule 0 & 14 \\ \bottomrule \end{tabular}	select # where # = 14 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>name</th> <th>birth and death</th> <th>office started</th> <th>office ended</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>geir vidalin</td> <td>27 october 1761 - 20 september 1823</td> <td>1801</td> <td>1823</td> </tr> <tr> <th>1</th> <td>2</td> <td>steingrimur jonsson</td> <td>none</td> <td>1824</td> <td>1845</td> </tr> <tr> <th>2</th> <td>3</td> <td>helgi thordersen</td> <td>8 april 1794 - 4 december 1867</td> <td>1846</td> <td>1866</td> </tr> <tr> <th>3</th> <td>4</td> <td>'petur petursson</td> <td>3 october 1808 - 15 may 1891</td> <td>1866</td> <td>1889</td> </tr> <tr> <th>4</th> <td>5</td> <td>hallgrimur sveinsson</td> <td>5 april 1841 - 16 december 1909</td> <td>1889</td> <td>1908</td> </tr> <tr> <th>5</th> <td>6</td> <td>þorhallur bjarnarson</td> <td>2 december 1855 - 15 december 1916</td> <td>1908</td> <td>1916</td> </tr> <tr> <th>6</th> <td>7</td> <td>jon helgason</td> <td>1866 - 1942</td> <td>1917</td> <td>1939</td> </tr> <tr> <th>7</th> <td>8</td> <td>sigurgeir sigurðsson</td> <td>3 august 1890 - 13 october 1953</td> <td>1939</td> <td>1953</td> </tr> <tr> <th>8</th> <td>9</td> <td>asmundur guðmundsson</td> <td>6 october 1888 reykholt - 29 may 1969 reykjavik</td> <td>1954</td> <td>1989</td> </tr> <tr> <th>9</th> <td>10</td> <td>sigurbjorn einarsson</td> <td>30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik</td> <td>1959</td> <td>1981</td> </tr> <tr> <th>10</th> <td>11</td> <td>petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland)</td> <td>2 june 1919 - 3 june 2010</td> <td>1981</td> <td>1989</td> </tr> <tr> <th>11</th> <td>12</td> <td>olafur skulason</td> <td>29 december 1929 - 9 june 2008</td> <td>1989</td> <td>1997</td> </tr> <tr> <th>12</th> <td>13</td> <td>karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland)</td> <td>5 february 1947 reykjavik</td> <td>1998</td> <td>2012</td> </tr> <tr> <th>13</th> <td>14</td> <td>agnes sigurðardottir</td> <td>19 october 1954 isafjorður</td> <td>24 june 2012</td> <td>incumbent</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>14</td> </tr> </tbody> </table>	select # where # = 14 <table_name> : table \| \| # \| name \| birth and death \| office started \| office ended \| \|---:\|----:\|:--------------------------------------------------------------------------\|:----------------------------------------------------------------\|:-----------------\|:---------------\| \| 0 \| 1 \| geir vidalin \| 27 october 1761 - 20 september 1823 \| 1801 \| 1823 \| \| 1 \| 2 \| steingrimur jonsson \| none \| 1824 \| 1845 \| \| 2 \| 3 \| helgi thordersen \| 8 april 1794 - 4 december 1867 \| 1846 \| 1866 \| \| 3 \| 4 \| 'petur petursson \| 3 october 1808 - 15 may 1891 \| 1866 \| 1889 \| \| 4 \| 5 \| hallgrimur sveinsson \| 5 april 1841 - 16 december 1909 \| 1889 \| 1908 \| \| 5 \| 6 \| þorhallur bjarnarson \| 2 december 1855 - 15 december 1916 \| 1908 \| 1916 \| \| 6 \| 7 \| jon helgason \| 1866 - 1942 \| 1917 \| 1939 \| \| 7 \| 8 \| sigurgeir sigurðsson \| 3 august 1890 - 13 october 1953 \| 1939 \| 1953 \| \| 8 \| 9 \| asmundur guðmundsson \| 6 october 1888 reykholt - 29 may 1969 reykjavik \| 1954 \| 1989 \| \| 9 \| 10 \| sigurbjorn einarsson \| 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik \| 1959 \| 1981 \| \| 10 \| 11 \| petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) \| 2 june 1919 - 3 june 2010 \| 1981 \| 1989 \| \| 11 \| 12 \| olafur skulason \| 29 december 1929 - 9 june 2008 \| 1989 \| 1997 \| \| 12 \| 13 \| karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) \| 5 february 1947 reykjavik \| 1998 \| 2012 \| \| 13 \| 14 \| agnes sigurðardottir \| 19 october 1954 isafjorður \| 24 june 2012 \| incumbent \|	\| \| # \| \|---:\|----:\| \| 0 \| 14 \|	[ [ 1, 4025, 468, 1625, 468, 273, 5045, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 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select name where street address = 'central avenue southeast and main street southeast' col : name \| street address \| years as tallest \| height ft (m) \| floors row 1 : globe building \| 4th street south \| 1882-1886 \| 157 (48) \| 8 row 2 : lumber exchange building \| 10 5th street south \| 1886-1887 \| 165 (50) \| 12 row 3 : industrial exposition building \| central avenue southeast and main street southeast \| 1887-1890 \| 240 (73) \| 8 row 4 : metropolitan building \| 308 2nd avenue south \| 1890-1895 \| 258 (79) \| 12 row 5 : minneapolis city hall \| 350 5th street south \| 1895-1929 \| 341 (104) \| 14 row 6 : foshay tower \| 821 marquette avenue \| 1929-1973 \| 448 (137) \| 32 row 7 : ids tower \| 80 8th street south \| 1973-present \| 792 (241) \| 55	col : name row 1 : industrial exposition building	select name where street address = 'central avenue southeast and main street southeast' <table_name> : table \begin{tabular}{llllll} \toprule & name & street address & years as tallest & height ft (m) & floors \\ \midrule 0 & globe building & 4th street south & 1882-1886 & 157 (48) & 8 \\ 1 & lumber exchange building & 10 5th street south & 1886-1887 & 165 (50) & 12 \\ 2 & industrial exposition building & central avenue southeast and main street southeast & 1887-1890 & 240 (73) & 8 \\ 3 & metropolitan building & 308 2nd avenue south & 1890-1895 & 258 (79) & 12 \\ 4 & minneapolis city hall & 350 5th street south & 1895-1929 & 341 (104) & 14 \\ 5 & foshay tower & 821 marquette avenue & 1929-1973 & 448 (137) & 32 \\ 6 & ids tower & 80 8th street south & 1973-present & 792 (241) & 55 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & name \\ \midrule 0 & industrial exposition building \\ \bottomrule \end{tabular}	select name where street address = 'central avenue southeast and main street southeast' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>street address</th> <th>years as tallest</th> <th>height ft (m)</th> <th>floors</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>globe building</td> <td>4th street south</td> <td>1882-1886</td> <td>157 (48)</td> <td>8</td> </tr> <tr> <th>1</th> <td>lumber exchange building</td> <td>10 5th street south</td> <td>1886-1887</td> <td>165 (50)</td> <td>12</td> </tr> <tr> <th>2</th> <td>industrial exposition building</td> <td>central avenue southeast and main street southeast</td> <td>1887-1890</td> <td>240 (73)</td> <td>8</td> </tr> <tr> <th>3</th> <td>metropolitan building</td> <td>308 2nd avenue south</td> <td>1890-1895</td> <td>258 (79)</td> <td>12</td> </tr> <tr> <th>4</th> <td>minneapolis city hall</td> <td>350 5th street south</td> <td>1895-1929</td> <td>341 (104)</td> <td>14</td> </tr> <tr> <th>5</th> <td>foshay tower</td> <td>821 marquette avenue</td> <td>1929-1973</td> <td>448 (137)</td> <td>32</td> </tr> <tr> <th>6</th> <td>ids tower</td> <td>80 8th street south</td> <td>1973-present</td> <td>792 (241)</td> <td>55</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>industrial exposition building</td> </tr> </tbody> </table>	select name where street address = 'central avenue southeast and main street southeast' <table_name> : table \| \| name \| street address \| years as tallest \| height ft (m) \| floors \| \|---:\|:-------------------------------\|:---------------------------------------------------\|:-------------------\|:----------------\|---------:\| \| 0 \| globe building \| 4th street south \| 1882-1886 \| 157 (48) \| 8 \| \| 1 \| lumber exchange building \| 10 5th street south \| 1886-1887 \| 165 (50) \| 12 \| \| 2 \| industrial exposition building \| central avenue southeast and main street southeast \| 1887-1890 \| 240 (73) \| 8 \| \| 3 \| metropolitan building \| 308 2nd avenue south \| 1890-1895 \| 258 (79) \| 12 \| \| 4 \| minneapolis city hall \| 350 5th 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select count ( 2.27 ) where rank < 3 col : rank \| athlete \| nationality \| 2.15 \| 2.2 \| 2.24 \| 2.27 \| result \| notes row 1 : 1 \| yaroslav rybakov \| russia \| o \| o \| o \| o \| 2.27 \| q row 2 : 1 \| andriy sokolovskyy \| ukraine \| o \| o \| o \| o \| 2.27 \| q row 3 : 1 \| stefan holm \| sweden \| o \| o \| o \| o \| 2.27 \| q row 4 : 1 \| andrey tereshin \| russia \| o \| o \| o \| o \| 2.27 \| q row 5 : 1 \| victor moya \| cuba \| o \| o \| o \| o \| 2.27 \| q, pb row 6 : 1 \| linus thornblad \| sweden \| o \| o \| o \| o \| 2.27 \| q row 7 : 7 \| giulio ciotti \| italy \| o \| o \| o \| xxx \| 2.24 \| q row 8 : 8 \| robert wolski \| poland \| xo \| o \| o \| xxx \| 2.24 \| q row 9 : 9 \| ramsay carelse \| south africa \| xo \| xo \| o \| xxx \| 2.24 \| none row 10 : 10 \| tora harris \| united states \| o \| o \| xo \| xxx \| 2.24 \| none row 11 : 10 \| nicola ciotti \| italy \| o \| o \| xo \| xxx \| 2.24 \| none row 12 : 10 \| wojciech theiner \| poland \| o \| o \| xo \| xxx \| 2.24 \| none row 13 : 13 \| tomas janku \| czech republic \| o \| o \| xxo \| xxx \| 2.24 \| none row 14 : 13 \| mustapha raifak \| france \| o \| o \| xxo \| xxx \| 2.24 \| none row 15 : 15 \| svatoslav ton \| czech republic \| o \| xo \| xxx \| none \| 2.2 \| none row 16 : 16 \| adam shunk \| united states \| o \| xxx \| none \| 2.15 \| none \| none row 17 : 16 \| roman fricke \| germany \| o \| xxx \| none \| 2.15 \| none \| none	col : count ( "2.27" ) row 1 : 14	select count ( 2.27 ) where rank < 3 <table_name> : table \begin{tabular}{llllllllll} \toprule & rank & athlete & nationality & 2.15 & 2.2 & 2.24 & 2.27 & result & notes \\ \midrule 0 & 1 & yaroslav rybakov & russia & o & o & o & o & 2.27 & q \\ 1 & 1 & andriy sokolovskyy & ukraine & o & o & o & o & 2.27 & q \\ 2 & 1 & stefan holm & sweden & o & o & o & o & 2.27 & q \\ 3 & 1 & andrey tereshin & russia & o & o & o & o & 2.27 & q \\ 4 & 1 & victor moya & cuba & o & o & o & o & 2.27 & q, pb \\ 5 & 1 & linus thornblad & sweden & o & o & o & o & 2.27 & q \\ 6 & 7 & giulio ciotti & italy & o & o & o & xxx & 2.24 & q \\ 7 & 8 & robert wolski & poland & xo & o & o & xxx & 2.24 & q \\ 8 & 9 & ramsay carelse & south africa & xo & xo & o & xxx & 2.24 & none \\ 9 & 10 & tora harris & united states & o & o & xo & xxx & 2.24 & none \\ 10 & 10 & nicola ciotti & italy & o & o & xo & xxx & 2.24 & none \\ 11 & 10 & wojciech theiner & poland & o & o & xo & xxx & 2.24 & none \\ 12 & 13 & tomas janku & czech republic & o & o & xxo & xxx & 2.24 & none \\ 13 & 13 & mustapha raifak & france & o & o & xxo & xxx & 2.24 & none \\ 14 & 15 & svatoslav ton & czech republic & o & xo & xxx & none & 2.2 & none \\ 15 & 16 & adam shunk & united states & o & xxx & none & 2.15 & none & none \\ 16 & 16 & roman fricke & germany & o & xxx & none & 2.15 & none & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "2.27" ) \\ \midrule 0 & 14 \\ \bottomrule \end{tabular}	select count ( 2.27 ) where rank < 3 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>athlete</th> <th>nationality</th> <th>2.15</th> <th>2.2</th> <th>2.24</th> <th>2.27</th> <th>result</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>yaroslav rybakov</td> <td>russia</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>1</th> <td>1</td> <td>andriy sokolovskyy</td> <td>ukraine</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>2</th> <td>1</td> <td>stefan holm</td> <td>sweden</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>3</th> <td>1</td> <td>andrey tereshin</td> <td>russia</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>4</th> <td>1</td> <td>victor moya</td> <td>cuba</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q, pb</td> </tr> <tr> <th>5</th> <td>1</td> <td>linus thornblad</td> <td>sweden</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>6</th> <td>7</td> <td>giulio ciotti</td> <td>italy</td> <td>o</td> <td>o</td> <td>o</td> <td>xxx</td> <td>2.24</td> <td>q</td> </tr> <tr> <th>7</th> <td>8</td> <td>robert wolski</td> <td>poland</td> <td>xo</td> <td>o</td> <td>o</td> <td>xxx</td> <td>2.24</td> <td>q</td> </tr> <tr> <th>8</th> <td>9</td> <td>ramsay carelse</td> <td>south africa</td> <td>xo</td> <td>xo</td> <td>o</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>tora harris</td> <td>united states</td> <td>o</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>10</th> <td>10</td> <td>nicola ciotti</td> <td>italy</td> <td>o</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>11</th> <td>10</td> <td>wojciech theiner</td> <td>poland</td> <td>o</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>tomas janku</td> <td>czech republic</td> <td>o</td> <td>o</td> <td>xxo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>13</th> <td>13</td> <td>mustapha raifak</td> <td>france</td> <td>o</td> <td>o</td> <td>xxo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>svatoslav ton</td> <td>czech republic</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>none</td> <td>2.2</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>adam shunk</td> <td>united states</td> <td>o</td> <td>xxx</td> <td>none</td> <td>2.15</td> <td>none</td> <td>none</td> </tr> <tr> <th>16</th> <td>16</td> <td>roman fricke</td> <td>germany</td> <td>o</td> <td>xxx</td> <td>none</td> <td>2.15</td> <td>none</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "2.27" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>14</td> </tr> </tbody> </table>	select count ( 2.27 ) where rank < 3 <table_name> : table \| \| rank \| athlete \| nationality \| 2.15 \| 2.2 \| 2.24 \| 2.27 \| result \| notes \| \|---:\|-------:\|:-------------------\|:---------------\|:-------\|:------\|:-------\|:-------\|:---------\|:--------\| \| 0 \| 1 \| yaroslav rybakov \| russia \| o \| o \| o \| o \| 2.27 \| q \| \| 1 \| 1 \| andriy sokolovskyy \| ukraine \| o \| o \| o \| o \| 2.27 \| q \| \| 2 \| 1 \| stefan holm \| sweden \| o \| o \| o \| o \| 2.27 \| q \| \| 3 \| 1 \| andrey tereshin \| russia \| o \| o \| o \| o \| 2.27 \| q \| \| 4 \| 1 \| victor moya \| cuba \| o \| o \| o \| o \| 2.27 \| q, pb \| \| 5 \| 1 \| linus thornblad \| sweden \| o \| o \| o \| o \| 2.27 \| q \| \| 6 \| 7 \| giulio ciotti \| italy \| o \| o \| o \| xxx \| 2.24 \| q \| \| 7 \| 8 \| robert wolski \| poland \| xo \| o \| o \| xxx \| 2.24 \| q \| \| 8 \| 9 \| ramsay carelse \| south africa \| xo \| xo \| o \| xxx \| 2.24 \| none \| \| 9 \| 10 \| tora harris \| united states \| o \| o \| xo \| xxx \| 2.24 \| none \| \| 10 \| 10 \| nicola ciotti \| italy \| o \| o \| xo \| xxx \| 2.24 \| none \| \| 11 \| 10 \| wojciech theiner \| poland \| o \| o \| xo \| xxx \| 2.24 \| none \| \| 12 \| 13 \| tomas janku \| czech republic \| o \| o \| xxo \| xxx \| 2.24 \| none \| \| 13 \| 13 \| mustapha raifak \| france \| o \| o \| xxo \| xxx \| 2.24 \| none \| \| 14 \| 15 \| svatoslav ton \| czech republic \| o \| xo \| xxx \| none \| 2.2 \| none \| \| 15 \| 16 \| adam shunk \| united states \| o \| xxx \| none \| 2.15 \| none \| none \| \| 16 \| 16 \| roman fricke \| germany \| o \| xxx \| none \| 2.15 \| none \| none \|	\| \| count ( "2.27" ) \| \|---:\|-------------------:\| \| 0 \| 14 \|	[ [ 1, 4025, 1056, 261, 576, 18, 5324, 262, 1625, 6171, 411, 890, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 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select count ( name ) where name = 'zoltan kiss' col : position \| nation \| number \| name \| soproni liga \| uefa cup \| hungarian cup \| league cup \| total row 1 : 1 \| \| 14 \| gergely rudolf \| 16 \| 3 \| 0 \| 0 \| 19 row 2 : 2 \| \| 41 \| lorant olah \| 12 \| 1 \| 0 \| 0 \| 13 row 3 : 3 \| \| 99 \| omagbemi dudu \| 4 \| 1 \| 5 \| 0 \| 10 row 4 : 4 \| \| 55 \| peter szakaly \| 9 \| 0 \| 0 \| 0 \| 9 row 5 : 5 \| \| 77 \| peter czvitkovics \| 7 \| 0 \| 0 \| 0 \| 7 row 6 : 6 \| \| 4 \| leandro de almeida \| 5 \| 0 \| 1 \| 0 \| 6 row 7 : 7 \| \| 17 \| norbert meszaros \| 3 \| 0 \| 0 \| 0 \| 3 row 8 : 8 \| \| 8 \| zsombor kerekes \| 1 \| 0 \| 2 \| 0 \| 3 row 9 : 9 \| \| 10 \| igor bogdanovic \| 0 \| 0 \| 3 \| 0 \| 3 row 10 : 10 \| \| 2 \| istvan szucs \| 2 \| 0 \| 0 \| 0 \| 2 row 11 : 11 \| \| 30 \| zoltan kiss \| 2 \| 0 \| 0 \| 0 \| 2 row 12 : 12 \| \| 23 \| peter szilagyi \| 2 \| 0 \| 0 \| 0 \| 2 row 13 : 13 \| \| 7 \| tibor dombi \| 2 \| 0 \| 0 \| 0 \| 2 row 14 : 14 \| \| 13 \| peter biro \| 1 \| 0 \| 0 \| 0 \| 1 row 15 : 15 \| \| 27 \| gabor demjen \| 1 \| 0 \| 0 \| 0 \| 1 row 16 : 16 \| \| 19 \| vinicius galvao leal \| 1 \| 0 \| 0 \| 0 \| 1 row 17 : 17 \| \| 1 \| vukasin poleksic \| 1 \| 0 \| 0 \| 0 \| 1 row 18 : 18 \| \| 83 \| zoltan varga \| 0 \| 0 \| 1 \| 0 \| 1 row 19 : 19 \| \| 16 \| adam komlosi \| 0 \| 0 \| 1 \| 0 \| 1 row 20 : none \| \| none \| own goals \| 1 \| 0 \| 0 \| 0 \| 1 row 21 : none \| \| none \| totals \| 70 \| 5 \| 13 \| 0 \| 88	col : count ( "name" ) row 1 : 1	select count ( name ) where name = 'zoltan kiss' <table_name> : table \begin{tabular}{llllllllll} \toprule & position & nation & number & name & soproni liga & uefa cup & hungarian cup & league cup & total \\ \midrule 0 & 1 & & 14 & gergely rudolf & 16 & 3 & 0 & 0 & 19 \\ 1 & 2 & & 41 & lorant olah & 12 & 1 & 0 & 0 & 13 \\ 2 & 3 & & 99 & omagbemi dudu & 4 & 1 & 5 & 0 & 10 \\ 3 & 4 & & 55 & peter szakaly & 9 & 0 & 0 & 0 & 9 \\ 4 & 5 & & 77 & peter czvitkovics & 7 & 0 & 0 & 0 & 7 \\ 5 & 6 & & 4 & leandro de almeida & 5 & 0 & 1 & 0 & 6 \\ 6 & 7 & & 17 & norbert meszaros & 3 & 0 & 0 & 0 & 3 \\ 7 & 8 & & 8 & zsombor kerekes & 1 & 0 & 2 & 0 & 3 \\ 8 & 9 & & 10 & igor bogdanovic & 0 & 0 & 3 & 0 & 3 \\ 9 & 10 & & 2 & istvan szucs & 2 & 0 & 0 & 0 & 2 \\ 10 & 11 & & 30 & zoltan kiss & 2 & 0 & 0 & 0 & 2 \\ 11 & 12 & & 23 & peter szilagyi & 2 & 0 & 0 & 0 & 2 \\ 12 & 13 & & 7 & tibor dombi & 2 & 0 & 0 & 0 & 2 \\ 13 & 14 & & 13 & peter biro & 1 & 0 & 0 & 0 & 1 \\ 14 & 15 & & 27 & gabor demjen & 1 & 0 & 0 & 0 & 1 \\ 15 & 16 & & 19 & vinicius galvao leal & 1 & 0 & 0 & 0 & 1 \\ 16 & 17 & & 1 & vukasin poleksic & 1 & 0 & 0 & 0 & 1 \\ 17 & 18 & & 83 & zoltan varga & 0 & 0 & 1 & 0 & 1 \\ 18 & 19 & & 16 & adam komlosi & 0 & 0 & 1 & 0 & 1 \\ 19 & none & & none & own goals & 1 & 0 & 0 & 0 & 1 \\ 20 & none & & none & totals & 70 & 5 & 13 & 0 & 88 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "name" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( name ) where name = 'zoltan kiss' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>position</th> <th>nation</th> <th>number</th> <th>name</th> <th>soproni liga</th> <th>uefa cup</th> <th>hungarian cup</th> <th>league cup</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td></td> <td>14</td> <td>gergely rudolf</td> <td>16</td> <td>3</td> <td>0</td> <td>0</td> <td>19</td> </tr> <tr> <th>1</th> <td>2</td> <td></td> <td>41</td> <td>lorant olah</td> <td>12</td> <td>1</td> <td>0</td> <td>0</td> <td>13</td> </tr> <tr> <th>2</th> <td>3</td> <td></td> <td>99</td> <td>omagbemi dudu</td> <td>4</td> <td>1</td> <td>5</td> <td>0</td> <td>10</td> </tr> <tr> <th>3</th> <td>4</td> <td></td> <td>55</td> <td>peter szakaly</td> <td>9</td> <td>0</td> <td>0</td> <td>0</td> <td>9</td> </tr> <tr> <th>4</th> <td>5</td> <td></td> <td>77</td> <td>peter czvitkovics</td> <td>7</td> <td>0</td> <td>0</td> <td>0</td> <td>7</td> </tr> <tr> <th>5</th> <td>6</td> <td></td> <td>4</td> <td>leandro de almeida</td> <td>5</td> <td>0</td> <td>1</td> <td>0</td> <td>6</td> </tr> <tr> <th>6</th> <td>7</td> <td></td> <td>17</td> <td>norbert meszaros</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>3</td> </tr> <tr> <th>7</th> <td>8</td> <td></td> <td>8</td> <td>zsombor kerekes</td> <td>1</td> <td>0</td> <td>2</td> <td>0</td> <td>3</td> </tr> <tr> <th>8</th> <td>9</td> <td></td> <td>10</td> <td>igor bogdanovic</td> <td>0</td> <td>0</td> <td>3</td> <td>0</td> <td>3</td> </tr> <tr> <th>9</th> <td>10</td> <td></td> <td>2</td> <td>istvan szucs</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>10</th> <td>11</td> <td></td> <td>30</td> <td>zoltan kiss</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>11</th> <td>12</td> <td></td> <td>23</td> <td>peter szilagyi</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>12</th> <td>13</td> <td></td> <td>7</td> <td>tibor dombi</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>13</th> <td>14</td> <td></td> <td>13</td> <td>peter biro</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>14</th> <td>15</td> <td></td> <td>27</td> <td>gabor demjen</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>15</th> <td>16</td> <td></td> <td>19</td> <td>vinicius galvao leal</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>16</th> <td>17</td> <td></td> <td>1</td> <td>vukasin poleksic</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>17</th> <td>18</td> <td></td> <td>83</td> <td>zoltan varga</td> <td>0</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>18</th> <td>19</td> <td></td> <td>16</td> <td>adam komlosi</td> <td>0</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>19</th> <td>none</td> <td></td> <td>none</td> <td>own goals</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>20</th> <td>none</td> <td></td> <td>none</td> <td>totals</td> <td>70</td> <td>5</td> <td>13</td> <td>0</td> <td>88</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "name" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( name ) where name = 'zoltan kiss' <table_name> : table \| \| position \| nation \| number \| name \| soproni liga \| uefa cup \| hungarian cup \| league cup \| total \| \|---:\|:-----------\|:---------\|:---------\|:---------------------\|---------------:\|-----------:\|----------------:\|-------------:\|--------:\| \| 0 \| 1 \| \| 14 \| gergely rudolf \| 16 \| 3 \| 0 \| 0 \| 19 \| \| 1 \| 2 \| \| 41 \| lorant olah \| 12 \| 1 \| 0 \| 0 \| 13 \| \| 2 \| 3 \| \| 99 \| omagbemi dudu \| 4 \| 1 \| 5 \| 0 \| 10 \| \| 3 \| 4 \| \| 55 \| peter szakaly \| 9 \| 0 \| 0 \| 0 \| 9 \| \| 4 \| 5 \| \| 77 \| peter czvitkovics \| 7 \| 0 \| 0 \| 0 \| 7 \| \| 5 \| 6 \| \| 4 \| leandro de almeida \| 5 \| 0 \| 1 \| 0 \| 6 \| \| 6 \| 7 \| \| 17 \| norbert meszaros \| 3 \| 0 \| 0 \| 0 \| 3 \| \| 7 \| 8 \| \| 8 \| zsombor kerekes \| 1 \| 0 \| 2 \| 0 \| 3 \| \| 8 \| 9 \| \| 10 \| igor bogdanovic \| 0 \| 0 \| 3 \| 0 \| 3 \| \| 9 \| 10 \| \| 2 \| istvan szucs \| 2 \| 0 \| 0 \| 0 \| 2 \| \| 10 \| 11 \| \| 30 \| zoltan kiss \| 2 \| 0 \| 0 \| 0 \| 2 \| \| 11 \| 12 \| \| 23 \| peter szilagyi \| 2 \| 0 \| 0 \| 0 \| 2 \| \| 12 \| 13 \| \| 7 \| tibor dombi \| 2 \| 0 \| 0 \| 0 \| 2 \| \| 13 \| 14 \| \| 13 \| peter biro \| 1 \| 0 \| 0 \| 0 \| 1 \| \| 14 \| 15 \| \| 27 \| gabor demjen \| 1 \| 0 \| 0 \| 0 \| 1 \| \| 15 \| 16 \| \| 19 \| vinicius galvao leal \| 1 \| 0 \| 0 \| 0 \| 1 \| \| 16 \| 17 \| \| 1 \| vukasin poleksic \| 1 \| 0 \| 0 \| 0 \| 1 \| \| 17 \| 18 \| \| 83 \| zoltan varga \| 0 \| 0 \| 1 \| 0 \| 1 \| \| 18 \| 19 \| \| 16 \| adam komlosi \| 0 \| 0 \| 1 \| 0 \| 1 \| \| 19 \| none \| \| none \| own goals \| 1 \| 0 \| 0 \| 0 \| 1 \| \| 20 \| none \| \| none \| totals \| 70 \| 5 \| 13 \| 0 \| 88 \|	\| \| count ( "name" ) \| \|---:\|-------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 508, 262, 1625, 508, 273, 296, 94, 4397, 304, 417, 1054, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 3276, 1757, 451, 34, 203, 1377, 411, 451, 34, 82, 367, 1757, 451, 34, 203, 1377, 411, 451, 34, 2696, 1757, 451, 34, 203, 1377, 411, 451, 34, 529, 1757, 451, 34, 203, 1377, 411, 451, 34, 87, 556, 1949, 77, 16917, 69, 1757, 451, 34, 203, 1377, 411, 451, 34, 344, 507, 276, 416, 1757, 451, 34, 203, 1377, 411, 451, 34, 76, 20651, 297, 2779, 276, 416, 1757, 451, 34, 203, 1377, 411, 451, 34, 298, 20910, 276, 416, 1757, 451, 34, 203, 1377, 411, 451, 34, 4963, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 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select nation where nation = 'greece' order by silver desc limit 1 col : rank \| nation \| gold \| silver \| bronze \| total row 1 : 1 \| netherlands \| 20 \| 9 \| 0 \| 29 row 2 : 2 \| italy \| 10 \| 15 \| 3 \| 28 row 3 : 3 \| belgium \| 1 \| 2 \| 6 \| 9 row 4 : 4 \| spain \| 1 \| 1 \| 13 \| 15 row 5 : 5 \| great britain \| 0 \| 2 \| 0 \| 2 row 6 : 6 \| germany \| 0 \| 1 \| 7 \| 8 row 7 : 7 \| greece \| 0 \| 1 \| 0 \| 1 row 8 : 7 \| russia \| 0 \| 1 \| 0 \| 1 row 9 : 9 \| sweden \| 0 \| 0 \| 2 \| 2 row 10 : 10 \| france \| 0 \| 0 \| 1 \| 1	col : nation row 1 : greece	select nation where nation = 'greece' order by silver desc limit 1 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & netherlands & 20 & 9 & 0 & 29 \\ 1 & 2 & italy & 10 & 15 & 3 & 28 \\ 2 & 3 & belgium & 1 & 2 & 6 & 9 \\ 3 & 4 & spain & 1 & 1 & 13 & 15 \\ 4 & 5 & great britain & 0 & 2 & 0 & 2 \\ 5 & 6 & germany & 0 & 1 & 7 & 8 \\ 6 & 7 & greece & 0 & 1 & 0 & 1 \\ 7 & 7 & russia & 0 & 1 & 0 & 1 \\ 8 & 9 & sweden & 0 & 0 & 2 & 2 \\ 9 & 10 & france & 0 & 0 & 1 & 1 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & greece \\ \bottomrule \end{tabular}	select nation where nation = 'greece' order by silver desc limit 1 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>netherlands</td> <td>20</td> <td>9</td> <td>0</td> <td>29</td> </tr> <tr> <th>1</th> <td>2</td> <td>italy</td> <td>10</td> <td>15</td> <td>3</td> <td>28</td> </tr> <tr> <th>2</th> <td>3</td> <td>belgium</td> <td>1</td> <td>2</td> <td>6</td> <td>9</td> </tr> <tr> <th>3</th> <td>4</td> <td>spain</td> <td>1</td> <td>1</td> <td>13</td> <td>15</td> </tr> <tr> <th>4</th> <td>5</td> <td>great britain</td> <td>0</td> <td>2</td> <td>0</td> <td>2</td> </tr> <tr> <th>5</th> <td>6</td> <td>germany</td> <td>0</td> <td>1</td> <td>7</td> <td>8</td> </tr> <tr> <th>6</th> <td>7</td> <td>greece</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>7</th> <td>7</td> <td>russia</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>8</th> <td>9</td> <td>sweden</td> <td>0</td> <td>0</td> <td>2</td> <td>2</td> </tr> <tr> <th>9</th> <td>10</td> <td>france</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>greece</td> </tr> </tbody> </table>	select nation where nation = 'greece' order by silver desc limit 1 <table_name> : table \| \| rank \| nation \| gold \| silver \| bronze \| total \| \|---:\|-------:\|:--------------\|-------:\|---------:\|---------:\|--------:\| \| 0 \| 1 \| netherlands \| 20 \| 9 \| 0 \| 29 \| \| 1 \| 2 \| italy \| 10 \| 15 \| 3 \| 28 \| \| 2 \| 3 \| belgium \| 1 \| 2 \| 6 \| 9 \| \| 3 \| 4 \| spain \| 1 \| 1 \| 13 \| 15 \| \| 4 \| 5 \| great britain \| 0 \| 2 \| 0 \| 2 \| \| 5 \| 6 \| germany \| 0 \| 1 \| 7 \| 8 \| \| 6 \| 7 \| greece \| 0 \| 1 \| 0 \| 1 \| \| 7 \| 7 \| russia \| 0 \| 1 \| 0 \| 1 \| \| 8 \| 9 \| sweden \| 0 \| 0 \| 2 \| 2 \| \| 9 \| 10 \| france \| 0 \| 0 \| 1 \| 1 \|	\| \| nation \| \|---:\|:---------\| \| 0 \| greece \|	[ [ 1, 4025, 290, 367, 1625, 290, 367, 273, 296, 75, 992, 311, 11, 1353, 635, 17714, 502, 3044, 1800, 404, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 82, 367, 1757, 451, 34, 203, 1377, 411, 451, 34, 75, 1673, 1757, 451, 34, 203, 1377, 411, 451, 34, 25119, 502, 1757, 451, 34, 203, 1377, 411, 451, 34, 70, 1949, 8489, 1757, 451, 34, 203, 1377, 411, 451, 34, 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select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' col : pick # \| player \| position \| nationality \| nhl team \| college/junior/club team row 1 : 148 \| paul krake \| goalie \| canada \| quebec nordiques \| university of alaska anchorage (ncaa) row 2 : 149 \| phil huber \| center \| canada \| new york islanders \| kamloops blazers (whl) row 3 : 150 \| derek langille \| defense \| canada \| toronto maple leafs \| north bay centennials (ohl) row 4 : 151 \| jim solly \| left wing \| canada \| winnipeg jets \| bowling green state university (ncaa) row 5 : 152 \| sergei starikov \| defense \| soviet union \| new jersey devils \| cska moscow (ussr) row 6 : 153 \| milan tichy \| defense \| czechoslovakia \| chicago blackhawks \| prince albert raiders (whl) row 7 : 154 \| jon pratt \| left wing \| united states \| minnesota north stars \| pingree high school (ushs-ma) row 8 : 155 \| rob sangster \| left wing \| canada \| vancouver canucks \| kitchener rangers (ohl) row 9 : 156 \| kevin plager \| right wing \| united states \| st. louis blues \| parkway north high school (ushs-mo) row 10 : 157 \| raymond saumier \| right wing \| canada \| hartford whalers \| trois rivieres draveurs (qmjhl) row 11 : 158 \| andy suhy \| defense \| united states \| detroit red wings \| western michigan university (ncaa) row 12 : 159 \| sverre sears \| defense \| united states \| philadelphia flyers \| princeton university (ncaa) row 13 : 160 \| greg spenrath \| defense \| canada \| new york rangers \| tri-city americans (whl) row 14 : 161 \| derek plante \| center \| united states \| buffalo sabres \| cloquet high school (ushs-mn) row 15 : 162 \| darcy martini \| defense \| canada \| edmonton oilers \| michigan technological university (ncaa) row 16 : 163 \| david shute \| left wing \| united states \| pittsburgh penguins \| victoria cougars (whl) row 17 : 164 \| rick allain \| defense \| canada \| boston bruins \| kitchener rangers (ohl) row 18 : 165 \| sean whyte \| right wing \| canada \| los angeles kings \| guelph platers (ohl) row 19 : 166 \| dean holoien \| right wing \| canada \| washington capitals \| saskatoon blades (whl) row 20 : 167 \| patrick lebeau \| left wing \| canada \| montreal canadiens \| st-jean lynx (qmjhl) row 21 : 168 \| kevin wortman \| defense \| united states \| calgary flames \| american international college (ncaa)	col : count ( "distinct player" ) row 1 : 1	select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' <table_name> : table \begin{tabular}{lllllll} \toprule & pick # & player & position & nationality & nhl team & college/junior/club team \\ \midrule 0 & 148 & paul krake & goalie & canada & quebec nordiques & university of alaska anchorage (ncaa) \\ 1 & 149 & phil huber & center & canada & new york islanders & kamloops blazers (whl) \\ 2 & 150 & derek langille & defense & canada & toronto maple leafs & north bay centennials (ohl) \\ 3 & 151 & jim solly & left wing & canada & winnipeg jets & bowling green state university (ncaa) \\ 4 & 152 & sergei starikov & defense & soviet union & new jersey devils & cska moscow (ussr) \\ 5 & 153 & milan tichy & defense & czechoslovakia & chicago blackhawks & prince albert raiders (whl) \\ 6 & 154 & jon pratt & left wing & united states & minnesota north stars & pingree high school (ushs-ma) \\ 7 & 155 & rob sangster & left wing & canada & vancouver canucks & kitchener rangers (ohl) \\ 8 & 156 & kevin plager & right wing & united states & st. louis blues & parkway north high school (ushs-mo) \\ 9 & 157 & raymond saumier & right wing & canada & hartford whalers & trois rivieres draveurs (qmjhl) \\ 10 & 158 & andy suhy & defense & united states & detroit red wings & western michigan university (ncaa) \\ 11 & 159 & sverre sears & defense & united states & philadelphia flyers & princeton university (ncaa) \\ 12 & 160 & greg spenrath & defense & canada & new york rangers & tri-city americans (whl) \\ 13 & 161 & derek plante & center & united states & buffalo sabres & cloquet high school (ushs-mn) \\ 14 & 162 & darcy martini & defense & canada & edmonton oilers & michigan technological university (ncaa) \\ 15 & 163 & david shute & left wing & united states & pittsburgh penguins & victoria cougars (whl) \\ 16 & 164 & rick allain & defense & canada & boston bruins & kitchener rangers (ohl) \\ 17 & 165 & sean whyte & right wing & canada & los angeles kings & guelph platers (ohl) \\ 18 & 166 & dean holoien & right wing & canada & washington capitals & saskatoon blades (whl) \\ 19 & 167 & patrick lebeau & left wing & canada & montreal canadiens & st-jean lynx (qmjhl) \\ 20 & 168 & kevin wortman & defense & united states & calgary flames & american international college (ncaa) \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "distinct player" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pick #</th> <th>player</th> <th>position</th> <th>nationality</th> <th>nhl team</th> <th>college/junior/club team</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>148</td> <td>paul krake</td> <td>goalie</td> <td>canada</td> <td>quebec nordiques</td> <td>university of alaska anchorage (ncaa)</td> </tr> <tr> <th>1</th> <td>149</td> <td>phil huber</td> <td>center</td> <td>canada</td> <td>new york islanders</td> <td>kamloops blazers (whl)</td> </tr> <tr> <th>2</th> <td>150</td> <td>derek langille</td> <td>defense</td> <td>canada</td> <td>toronto maple leafs</td> <td>north bay centennials (ohl)</td> </tr> <tr> <th>3</th> <td>151</td> <td>jim solly</td> <td>left wing</td> <td>canada</td> <td>winnipeg jets</td> <td>bowling green state university (ncaa)</td> </tr> <tr> <th>4</th> <td>152</td> <td>sergei starikov</td> <td>defense</td> <td>soviet union</td> <td>new jersey devils</td> <td>cska moscow (ussr)</td> </tr> <tr> <th>5</th> <td>153</td> <td>milan tichy</td> <td>defense</td> <td>czechoslovakia</td> <td>chicago blackhawks</td> <td>prince albert raiders (whl)</td> </tr> <tr> <th>6</th> <td>154</td> <td>jon pratt</td> <td>left wing</td> <td>united states</td> <td>minnesota north stars</td> <td>pingree high school (ushs-ma)</td> </tr> <tr> <th>7</th> <td>155</td> <td>rob sangster</td> <td>left wing</td> <td>canada</td> <td>vancouver canucks</td> <td>kitchener rangers (ohl)</td> </tr> <tr> <th>8</th> <td>156</td> <td>kevin plager</td> <td>right wing</td> <td>united states</td> <td>st. louis blues</td> <td>parkway north high school (ushs-mo)</td> </tr> <tr> <th>9</th> <td>157</td> <td>raymond saumier</td> <td>right wing</td> <td>canada</td> <td>hartford whalers</td> <td>trois rivieres draveurs (qmjhl)</td> </tr> <tr> <th>10</th> <td>158</td> <td>andy suhy</td> <td>defense</td> <td>united states</td> <td>detroit red wings</td> <td>western michigan university (ncaa)</td> </tr> <tr> <th>11</th> <td>159</td> <td>sverre sears</td> <td>defense</td> <td>united states</td> <td>philadelphia flyers</td> <td>princeton university (ncaa)</td> </tr> <tr> <th>12</th> <td>160</td> <td>greg spenrath</td> <td>defense</td> <td>canada</td> <td>new york rangers</td> <td>tri-city americans (whl)</td> </tr> <tr> <th>13</th> <td>161</td> <td>derek plante</td> <td>center</td> <td>united states</td> <td>buffalo sabres</td> <td>cloquet high school (ushs-mn)</td> </tr> <tr> <th>14</th> <td>162</td> <td>darcy martini</td> <td>defense</td> <td>canada</td> <td>edmonton oilers</td> <td>michigan technological university (ncaa)</td> </tr> <tr> <th>15</th> <td>163</td> <td>david shute</td> <td>left wing</td> <td>united states</td> <td>pittsburgh penguins</td> <td>victoria cougars (whl)</td> </tr> <tr> <th>16</th> <td>164</td> <td>rick allain</td> <td>defense</td> <td>canada</td> <td>boston bruins</td> <td>kitchener rangers (ohl)</td> </tr> <tr> <th>17</th> <td>165</td> <td>sean whyte</td> <td>right wing</td> <td>canada</td> <td>los angeles kings</td> <td>guelph platers (ohl)</td> </tr> <tr> <th>18</th> <td>166</td> <td>dean holoien</td> <td>right wing</td> <td>canada</td> <td>washington capitals</td> <td>saskatoon blades (whl)</td> </tr> <tr> <th>19</th> <td>167</td> <td>patrick lebeau</td> <td>left wing</td> <td>canada</td> <td>montreal canadiens</td> <td>st-jean lynx (qmjhl)</td> </tr> <tr> <th>20</th> <td>168</td> <td>kevin wortman</td> <td>defense</td> <td>united states</td> <td>calgary flames</td> <td>american international college (ncaa)</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "distinct player" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' <table_name> : table \| \| pick # \| player \| position \| nationality \| nhl team \| college/junior/club team \| \|---:\|---------:\|:----------------\|:-----------\|:---------------\|:----------------------\|:-----------------------------------------\| \| 0 \| 148 \| paul krake \| goalie \| canada \| quebec nordiques \| university of alaska anchorage (ncaa) \| \| 1 \| 149 \| phil huber \| center \| canada \| new york islanders \| kamloops blazers (whl) \| \| 2 \| 150 \| derek langille \| defense \| canada \| toronto maple leafs \| north bay centennials (ohl) \| \| 3 \| 151 \| jim solly \| left wing \| canada \| winnipeg jets \| bowling green state university (ncaa) \| \| 4 \| 152 \| sergei starikov \| defense \| soviet union \| new jersey devils \| cska moscow (ussr) \| \| 5 \| 153 \| milan tichy \| defense \| czechoslovakia \| chicago blackhawks \| prince albert raiders (whl) \| \| 6 \| 154 \| jon pratt \| left wing \| united states \| minnesota north stars \| pingree high school (ushs-ma) \| \| 7 \| 155 \| rob sangster \| left wing \| canada \| vancouver canucks \| kitchener rangers (ohl) \| \| 8 \| 156 \| kevin plager \| right wing \| united states \| st. louis blues \| parkway north high school (ushs-mo) \| \| 9 \| 157 \| raymond saumier \| right wing \| canada \| hartford whalers \| trois rivieres draveurs (qmjhl) \| \| 10 \| 158 \| andy suhy \| defense \| united states \| detroit red wings \| western michigan university (ncaa) \| \| 11 \| 159 \| sverre sears \| defense \| united states \| philadelphia flyers \| princeton university (ncaa) \| \| 12 \| 160 \| greg spenrath \| defense \| canada \| new york rangers \| tri-city americans (whl) \| \| 13 \| 161 \| derek plante \| center \| united states \| buffalo sabres \| cloquet high school (ushs-mn) \| \| 14 \| 162 \| darcy martini \| defense \| canada \| edmonton oilers \| michigan technological university (ncaa) \| \| 15 \| 163 \| david shute \| left wing \| united states \| pittsburgh penguins \| victoria cougars (whl) \| \| 16 \| 164 \| rick allain \| defense \| canada \| boston bruins \| kitchener rangers (ohl) \| \| 17 \| 165 \| sean whyte \| right wing \| canada \| los angeles kings \| guelph platers (ohl) \| \| 18 \| 166 \| dean holoien \| right wing \| canada \| washington capitals \| saskatoon blades (whl) \| \| 19 \| 167 \| patrick lebeau \| left wing \| canada \| montreal canadiens \| st-jean lynx (qmjhl) \| \| 20 \| 168 \| kevin wortman \| defense \| united states \| calgary flames \| american international college (ncaa) \|	\| \| count ( "distinct player" ) \| \|---:\|------------------------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 10217, 7291, 262, 1625, 645, 298, 908, 19, 78, 318, 9659, 19, 830, 373, 5927, 273, 296, 318, 6760, 560, 434, 524, 835, 69, 392, 343, 1531, 261, 82, 5353, 69, 2506, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 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select units where petroleum coke-fired = '0.004' col : pollutant \| units \| emission standard \| coal-fired \| petroleum coke-fired row 1 : so2 \| lb/mmbtu \| ≤ 0.15 \| 0.0-0.04 \| 0.03-0.13 row 2 : nox \| lb/mmbtu \| ≤ 0.09 \| 0.04-0.06 \| 0.02 row 3 : solid particulate \| lb/mmbtu \| ≤ 0.011 \| 0.004 \| 0.007 row 4 : pm10 \| lb/mmbtu \| ≤ 0.011 \| 0.006 \| 0.004 row 5 : so3 \| lb/hour \| ≤ 1.1 \| 0.43 \| 0 row 6 : fluoride \| lb/mmbtu \| ≤ 1.57×10-4 \| 1.06×10-4 \| 0.95×10-4 row 7 : lead \| lb/mmbtu \| ≤ 2.6×10-5 \| 0.56×10-5 \| 0.59×10-5 row 8 : mercury \| lb/mmbtu \| ≤ 1.05×10-5 \| 0.095×10-5 \| 0.028×10-5	col : units row 1 : lb/mmbtu	select units where petroleum coke-fired = '0.004' <table_name> : table \begin{tabular}{llllll} \toprule & pollutant & units & emission standard & coal-fired & petroleum coke-fired \\ \midrule 0 & so2 & lb/mmbtu & ≤ 0.15 & 0.0-0.04 & 0.03-0.13 \\ 1 & nox & lb/mmbtu & ≤ 0.09 & 0.04-0.06 & 0.02 \\ 2 & solid particulate & lb/mmbtu & ≤ 0.011 & 0.004 & 0.007 \\ 3 & pm10 & lb/mmbtu & ≤ 0.011 & 0.006 & 0.004 \\ 4 & so3 & lb/hour & ≤ 1.1 & 0.43 & 0 \\ 5 & fluoride & lb/mmbtu & ≤ 1.57×10-4 & 1.06×10-4 & 0.95×10-4 \\ 6 & lead & lb/mmbtu & ≤ 2.6×10-5 & 0.56×10-5 & 0.59×10-5 \\ 7 & mercury & lb/mmbtu & ≤ 1.05×10-5 & 0.095×10-5 & 0.028×10-5 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & units \\ \midrule 0 & lb/mmbtu \\ \bottomrule \end{tabular}	select units where petroleum coke-fired = '0.004' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pollutant</th> <th>units</th> <th>emission standard</th> <th>coal-fired</th> <th>petroleum coke-fired</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>so2</td> <td>lb/mmbtu</td> <td>≤ 0.15</td> <td>0.0-0.04</td> <td>0.03-0.13</td> </tr> <tr> <th>1</th> <td>nox</td> <td>lb/mmbtu</td> <td>≤ 0.09</td> <td>0.04-0.06</td> <td>0.02</td> </tr> <tr> <th>2</th> <td>solid particulate</td> <td>lb/mmbtu</td> <td>≤ 0.011</td> <td>0.004</td> <td>0.007</td> </tr> <tr> <th>3</th> <td>pm10</td> <td>lb/mmbtu</td> <td>≤ 0.011</td> <td>0.006</td> <td>0.004</td> </tr> <tr> <th>4</th> <td>so3</td> <td>lb/hour</td> <td>≤ 1.1</td> <td>0.43</td> <td>0</td> </tr> <tr> <th>5</th> <td>fluoride</td> <td>lb/mmbtu</td> <td>≤ 1.57×10-4</td> <td>1.06×10-4</td> <td>0.95×10-4</td> </tr> <tr> <th>6</th> <td>lead</td> <td>lb/mmbtu</td> <td>≤ 2.6×10-5</td> <td>0.56×10-5</td> <td>0.59×10-5</td> </tr> <tr> <th>7</th> <td>mercury</td> <td>lb/mmbtu</td> <td>≤ 1.05×10-5</td> <td>0.095×10-5</td> <td>0.028×10-5</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>units</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>lb/mmbtu</td> </tr> </tbody> </table>	select units where petroleum coke-fired = '0.004' <table_name> : table \| \| pollutant \| units \| emission standard \| coal-fired \| petroleum coke-fired \| \|---:\|:------------------\|:---------\|:--------------------\|:-------------\|:-----------------------\| \| 0 \| so2 \| lb/mmbtu \| ≤ 0.15 \| 0.0-0.04 \| 0.03-0.13 \| \| 1 \| nox \| lb/mmbtu \| ≤ 0.09 \| 0.04-0.06 \| 0.02 \| \| 2 \| solid particulate \| lb/mmbtu \| ≤ 0.011 \| 0.004 \| 0.007 \| \| 3 \| pm10 \| lb/mmbtu \| ≤ 0.011 \| 0.006 \| 0.004 \| \| 4 \| so3 \| lb/hour \| ≤ 1.1 \| 0.43 \| 0 \| \| 5 \| fluoride \| lb/mmbtu \| ≤ 1.57×10-4 \| 1.06×10-4 \| 0.95×10-4 \| \| 6 \| lead \| lb/mmbtu \| ≤ 2.6×10-5 \| 0.56×10-5 \| 0.59×10-5 \| \| 7 \| mercury \| lb/mmbtu \| ≤ 1.05×10-5 \| 0.095×10-5 \| 0.028×10-5 \|	\| \| units \| \|---:\|:---------\| \| 0 \| lb/mmbtu \|	[ [ 1, 4025, 4971, 1625, 293, 278, 4615, 379, 276, 3056, 17, 74, 2921, 273, 296, 20, 18, 26565, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 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select count ( * ) where first tops = '202/2' col : first tops \| second tops row 1 : 102 \| 101 row 2 : 142 \| 108 row 3 : 146 \| 109 row 4 : 150 \| 122 row 5 : 163 \| 110 row 6 : 167 \| 108 row 7 : 171 \| 101 row 8 : 175 \| 116 row 9 : 179 \| 120 row 10 : 183 \| 123 row 11 : 187 \| 126 row 12 : 201/1 \| 201 row 13 : 202/2 \| 207 row 14 : 211/2 \| 207 row 15 : 221/2 \| 202 row 16 : 223/1 \| 201 row 17 : 225 \| 203 row 18 : 106 \| 105 row 19 : 143 \| 100 row 20 : 147 \| 111 row 21 : 160 \| 104 row 22 : 164 \| 101 row 23 : 168 \| 101 & 111 row 24 : 172 \| 116 row 25 : 176 \| 117 row 26 : 180 \| 124 row 27 : 184 \| 123 row 28 : 188 \| 126 row 29 : 201/2 \| 202 row 30 : 202/3 \| 205 row 31 : 211/3 \| 205 row 32 : 221/3 \| 203 row 33 : 223/2 \| 202 row 34 : 261 \| 251 row 35 : 140 \| 104 row 36 : 144 \| 101 row 37 : 148 \| 114 row 38 : 161 \| 107 & 108 row 39 : 165 \| 111 row 40 : 169 \| 104 row 41 : 173 \| 115 row 42 : 177 \| 115 row 43 : 181 \| 124 row 44 : 185 \| 125 row 45 : 189 \| 126 row 46 : 201/3 \| 203 row 47 : 203 \| 204 row 48 : 212 \| 204 row 49 : 222/1 \| 206 row 50 : 223/3 \| 203 row 51 : 141 \| 105 row 52 : 145 \| 103 row 53 : 149 \| 121 row 54 : 162 \| 101 row 55 : 166 \| 104 row 56 : 170 \| 105 row 57 : 174 \| 118 row 58 : 178 \| 119 row 59 : 182 \| 123 row 60 : 186 \| 127 row 61 : 190 \| 130 row 62 : 202/1 \| 206 row 63 : 211/1 \| 206 row 64 : 221/1 \| 201 row 65 : 222/2 \| 205 row 66 : 224 \| 207	col : count ( "*" ) row 1 : 1	select count ( * ) where first tops = '202/2' <table_name> : table \begin{tabular}{lll} \toprule & first tops & second tops \\ \midrule 0 & 102 & 101 \\ 1 & 142 & 108 \\ 2 & 146 & 109 \\ 3 & 150 & 122 \\ 4 & 163 & 110 \\ 5 & 167 & 108 \\ 6 & 171 & 101 \\ 7 & 175 & 116 \\ 8 & 179 & 120 \\ 9 & 183 & 123 \\ 10 & 187 & 126 \\ 11 & 201/1 & 201 \\ 12 & 202/2 & 207 \\ 13 & 211/2 & 207 \\ 14 & 221/2 & 202 \\ 15 & 223/1 & 201 \\ 16 & 225 & 203 \\ 17 & 106 & 105 \\ 18 & 143 & 100 \\ 19 & 147 & 111 \\ 20 & 160 & 104 \\ 21 & 164 & 101 \\ 22 & 168 & 101 & 111 \\ 23 & 172 & 116 \\ 24 & 176 & 117 \\ 25 & 180 & 124 \\ 26 & 184 & 123 \\ 27 & 188 & 126 \\ 28 & 201/2 & 202 \\ 29 & 202/3 & 205 \\ 30 & 211/3 & 205 \\ 31 & 221/3 & 203 \\ 32 & 223/2 & 202 \\ 33 & 261 & 251 \\ 34 & 140 & 104 \\ 35 & 144 & 101 \\ 36 & 148 & 114 \\ 37 & 161 & 107 & 108 \\ 38 & 165 & 111 \\ 39 & 169 & 104 \\ 40 & 173 & 115 \\ 41 & 177 & 115 \\ 42 & 181 & 124 \\ 43 & 185 & 125 \\ 44 & 189 & 126 \\ 45 & 201/3 & 203 \\ 46 & 203 & 204 \\ 47 & 212 & 204 \\ 48 & 222/1 & 206 \\ 49 & 223/3 & 203 \\ 50 & 141 & 105 \\ 51 & 145 & 103 \\ 52 & 149 & 121 \\ 53 & 162 & 101 \\ 54 & 166 & 104 \\ 55 & 170 & 105 \\ 56 & 174 & 118 \\ 57 & 178 & 119 \\ 58 & 182 & 123 \\ 59 & 186 & 127 \\ 60 & 190 & 130 \\ 61 & 202/1 & 206 \\ 62 & 211/1 & 206 \\ 63 & 221/1 & 201 \\ 64 & 222/2 & 205 \\ 65 & 224 & 207 \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where first tops = '202/2' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>first tops</th> <th>second tops</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>102</td> <td>101</td> </tr> <tr> <th>1</th> <td>142</td> <td>108</td> </tr> <tr> <th>2</th> <td>146</td> <td>109</td> </tr> <tr> <th>3</th> <td>150</td> <td>122</td> </tr> <tr> <th>4</th> <td>163</td> <td>110</td> </tr> <tr> <th>5</th> <td>167</td> <td>108</td> </tr> <tr> <th>6</th> <td>171</td> <td>101</td> </tr> <tr> <th>7</th> <td>175</td> <td>116</td> </tr> <tr> <th>8</th> <td>179</td> <td>120</td> </tr> <tr> <th>9</th> <td>183</td> <td>123</td> </tr> <tr> <th>10</th> <td>187</td> <td>126</td> </tr> <tr> <th>11</th> <td>201/1</td> <td>201</td> </tr> <tr> <th>12</th> <td>202/2</td> <td>207</td> </tr> <tr> <th>13</th> <td>211/2</td> <td>207</td> </tr> <tr> <th>14</th> <td>221/2</td> <td>202</td> </tr> <tr> <th>15</th> <td>223/1</td> <td>201</td> </tr> <tr> <th>16</th> <td>225</td> <td>203</td> </tr> <tr> <th>17</th> <td>106</td> <td>105</td> </tr> <tr> <th>18</th> <td>143</td> <td>100</td> </tr> <tr> <th>19</th> <td>147</td> <td>111</td> </tr> <tr> <th>20</th> <td>160</td> <td>104</td> </tr> <tr> <th>21</th> <td>164</td> <td>101</td> </tr> <tr> <th>22</th> <td>168</td> <td>101 & 111</td> </tr> <tr> <th>23</th> <td>172</td> <td>116</td> </tr> <tr> <th>24</th> <td>176</td> <td>117</td> </tr> <tr> <th>25</th> <td>180</td> <td>124</td> </tr> <tr> <th>26</th> <td>184</td> <td>123</td> </tr> <tr> <th>27</th> <td>188</td> <td>126</td> </tr> <tr> <th>28</th> <td>201/2</td> <td>202</td> </tr> <tr> <th>29</th> <td>202/3</td> <td>205</td> </tr> <tr> <th>30</th> <td>211/3</td> <td>205</td> </tr> <tr> <th>31</th> <td>221/3</td> <td>203</td> </tr> <tr> <th>32</th> <td>223/2</td> <td>202</td> </tr> <tr> <th>33</th> <td>261</td> <td>251</td> </tr> <tr> <th>34</th> <td>140</td> <td>104</td> </tr> <tr> <th>35</th> <td>144</td> <td>101</td> </tr> <tr> <th>36</th> <td>148</td> <td>114</td> </tr> <tr> <th>37</th> <td>161</td> <td>107 & 108</td> </tr> <tr> <th>38</th> <td>165</td> <td>111</td> </tr> <tr> <th>39</th> <td>169</td> <td>104</td> </tr> <tr> <th>40</th> <td>173</td> <td>115</td> </tr> <tr> <th>41</th> <td>177</td> <td>115</td> </tr> <tr> <th>42</th> <td>181</td> <td>124</td> </tr> <tr> <th>43</th> <td>185</td> <td>125</td> </tr> <tr> <th>44</th> <td>189</td> <td>126</td> </tr> <tr> <th>45</th> <td>201/3</td> <td>203</td> </tr> <tr> <th>46</th> <td>203</td> <td>204</td> </tr> <tr> <th>47</th> <td>212</td> <td>204</td> </tr> <tr> <th>48</th> <td>222/1</td> <td>206</td> </tr> <tr> <th>49</th> <td>223/3</td> <td>203</td> </tr> <tr> <th>50</th> <td>141</td> <td>105</td> </tr> <tr> <th>51</th> <td>145</td> <td>103</td> </tr> <tr> <th>52</th> <td>149</td> <td>121</td> </tr> <tr> <th>53</th> <td>162</td> <td>101</td> </tr> <tr> <th>54</th> <td>166</td> <td>104</td> </tr> <tr> <th>55</th> <td>170</td> <td>105</td> </tr> <tr> <th>56</th> <td>174</td> <td>118</td> </tr> <tr> <th>57</th> <td>178</td> <td>119</td> </tr> <tr> <th>58</th> <td>182</td> <td>123</td> </tr> <tr> <th>59</th> <td>186</td> <td>127</td> </tr> <tr> <th>60</th> <td>190</td> <td>130</td> </tr> <tr> <th>61</th> <td>202/1</td> <td>206</td> </tr> <tr> <th>62</th> <td>211/1</td> <td>206</td> </tr> <tr> <th>63</th> <td>221/1</td> <td>201</td> </tr> <tr> <th>64</th> <td>222/2</td> <td>205</td> </tr> <tr> <th>65</th> <td>224</td> <td>207</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where first tops = '202/2' <table_name> : table \| \| first tops \| second tops \| \|---:\|:-------------\|:--------------\| \| 0 \| 102 \| 101 \| \| 1 \| 142 \| 108 \| \| 2 \| 146 \| 109 \| \| 3 \| 150 \| 122 \| \| 4 \| 163 \| 110 \| \| 5 \| 167 \| 108 \| \| 6 \| 171 \| 101 \| \| 7 \| 175 \| 116 \| \| 8 \| 179 \| 120 \| \| 9 \| 183 \| 123 \| \| 10 \| 187 \| 126 \| \| 11 \| 201/1 \| 201 \| \| 12 \| 202/2 \| 207 \| \| 13 \| 211/2 \| 207 \| \| 14 \| 221/2 \| 202 \| \| 15 \| 223/1 \| 201 \| \| 16 \| 225 \| 203 \| \| 17 \| 106 \| 105 \| \| 18 \| 143 \| 100 \| \| 19 \| 147 \| 111 \| \| 20 \| 160 \| 104 \| \| 21 \| 164 \| 101 \| \| 22 \| 168 \| 101 & 111 \| \| 23 \| 172 \| 116 \| \| 24 \| 176 \| 117 \| \| 25 \| 180 \| 124 \| \| 26 \| 184 \| 123 \| \| 27 \| 188 \| 126 \| \| 28 \| 201/2 \| 202 \| \| 29 \| 202/3 \| 205 \| \| 30 \| 211/3 \| 205 \| \| 31 \| 221/3 \| 203 \| \| 32 \| 223/2 \| 202 \| \| 33 \| 261 \| 251 \| \| 34 \| 140 \| 104 \| \| 35 \| 144 \| 101 \| \| 36 \| 148 \| 114 \| \| 37 \| 161 \| 107 & 108 \| \| 38 \| 165 \| 111 \| \| 39 \| 169 \| 104 \| \| 40 \| 173 \| 115 \| \| 41 \| 177 \| 115 \| \| 42 \| 181 \| 124 \| \| 43 \| 185 \| 125 \| \| 44 \| 189 \| 126 \| \| 45 \| 201/3 \| 203 \| \| 46 \| 203 \| 204 \| \| 47 \| 212 \| 204 \| \| 48 \| 222/1 \| 206 \| \| 49 \| 223/3 \| 203 \| \| 50 \| 141 \| 105 \| \| 51 \| 145 \| 103 \| \| 52 \| 149 \| 121 \| \| 53 \| 162 \| 101 \| \| 54 \| 166 \| 104 \| \| 55 \| 170 \| 105 \| \| 56 \| 174 \| 118 \| \| 57 \| 178 \| 119 \| \| 58 \| 182 \| 123 \| \| 59 \| 186 \| 127 \| \| 60 \| 190 \| 130 \| \| 61 \| 202/1 \| 206 \| \| 62 \| 211/1 \| 206 \| \| 63 \| 221/1 \| 201 \| \| 64 \| 222/2 \| 205 \| \| 65 \| 224 \| 207 \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 1122, 358, 1121, 273, 296, 18212, 19, 22, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 3645, 358, 1121, 1757, 451, 34, 203, 1377, 411, 451, 34, 8538, 358, 1121, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 20481, 1757, 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select count ( * ) where no. < 2 col : no. \| name \| term of office \| president(s) served under row 1 : 1 \| william bennett \| 1989 - 1991 \| george h. w. bush row 2 : 2 \| bob martinez \| march 28, 1991 - january 20, 1993 \| george h. w. bush row 3 : 3 \| lee p. brown \| january 1993 - december 12, 1995 \| bill clinton row 4 : 4 \| barry mccaffrey \| february 29, 1996 - january 4, 2001 \| bill clinton row 5 : 5 \| john p. walters \| december 7, 2001 - january 19, 2009 \| george w. bush row 6 : 6 \| gil kerlikowske \| may 7, 2009 - march 6, 2014 \| barack obama row 7 : acting \| michael botticelli \| march 6, 2014 - \| barack obama	col : count ( "*" ) row 1 : 1	select count ( * ) where no. < 2 <table_name> : table \begin{tabular}{lllll} \toprule & no. & name & term of office & president(s) served under \\ \midrule 0 & 1 & william bennett & 1989 - 1991 & george h. w. bush \\ 1 & 2 & bob martinez & march 28, 1991 - january 20, 1993 & george h. w. bush \\ 2 & 3 & lee p. brown & january 1993 - december 12, 1995 & bill clinton \\ 3 & 4 & barry mccaffrey & february 29, 1996 - january 4, 2001 & bill clinton \\ 4 & 5 & john p. walters & december 7, 2001 - january 19, 2009 & george w. bush \\ 5 & 6 & gil kerlikowske & may 7, 2009 - march 6, 2014 & barack obama \\ 6 & acting & michael botticelli & march 6, 2014 - & barack obama \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where no. < 2 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>no.</th> <th>name</th> <th>term of office</th> <th>president(s) served under</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>william bennett</td> <td>1989 - 1991</td> <td>george h. w. bush</td> </tr> <tr> <th>1</th> <td>2</td> <td>bob martinez</td> <td>march 28, 1991 - january 20, 1993</td> <td>george h. w. bush</td> </tr> <tr> <th>2</th> <td>3</td> <td>lee p. brown</td> <td>january 1993 - december 12, 1995</td> <td>bill clinton</td> </tr> <tr> <th>3</th> <td>4</td> <td>barry mccaffrey</td> <td>february 29, 1996 - january 4, 2001</td> <td>bill clinton</td> </tr> <tr> <th>4</th> <td>5</td> <td>john p. walters</td> <td>december 7, 2001 - january 19, 2009</td> <td>george w. bush</td> </tr> <tr> <th>5</th> <td>6</td> <td>gil kerlikowske</td> <td>may 7, 2009 - march 6, 2014</td> <td>barack obama</td> </tr> <tr> <th>6</th> <td>acting</td> <td>michael botticelli</td> <td>march 6, 2014 -</td> <td>barack obama</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where no. < 2 <table_name> : table \| \| no. \| name \| term of office \| president(s) served under \| \|---:\|:-------\|:-------------------\|:------------------------------------\|:----------------------------\| \| 0 \| 1 \| william bennett \| 1989 - 1991 \| george h. w. bush \| \| 1 \| 2 \| bob martinez \| march 28, 1991 - january 20, 1993 \| george h. w. bush \| \| 2 \| 3 \| lee p. brown \| january 1993 - december 12, 1995 \| bill clinton \| \| 3 \| 4 \| barry mccaffrey \| february 29, 1996 - january 4, 2001 \| bill clinton \| \| 4 \| 5 \| john p. walters \| december 7, 2001 - january 19, 2009 \| george w. bush \| \| 5 \| 6 \| gil kerlikowske \| may 7, 2009 - march 6, 2014 \| barack obama \| \| 6 \| acting \| michael botticelli \| march 6, 2014 - \| barack obama \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 1158, 18, 411, 576, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 2135, 17347, 451, 34, 203, 1377, 411, 451, 34, 529, 1757, 451, 34, 203, 1377, 411, 451, 34, 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select rank where team = 'lithuania' col : rank \| team \| names \| time \| qualification row 1 : 1 \| france \| christophe capelle philippe ermenault jean-michel monin francis moreau \| 4:09.570 \| q row 2 : 2 \| italy \| adler capelli mauro trentini andrea collinelli cristiano citton \| 4:09.695 \| q row 3 : 3 \| australia \| bradley mcgee stuart o'grady timothy o'shannessey dean woods \| 4:09.750 \| q row 4 : 4 \| ukraine \| bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko \| 4:11.545 \| q row 5 : 5 \| russia \| eduard gritsun nikolay kuznetsov aleksey markov anton chantyr \| 4:11.665 \| q row 6 : 6 \| united states \| dirk copeland mariano friedick adam laurent michael mccarthy \| 4:11.950 \| q row 7 : 7 \| spain \| juan martinez juan llaneras santos gonzalez adolfo alperi \| 4:12.780 \| q row 8 : 8 \| new zealand \| gregory henderson brendon cameron timothy carswell julian dean \| 4:15.140 \| q row 9 : 9 \| germany \| robert bartko guido fulst danilo hondo heiko szonn \| 4:15.140 \| none row 10 : 10 \| great britain \| robert hayes matthew illingsworth bryan steel chris newton \| 4:16.510 \| none row 11 : 11 \| lithuania \| arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas \| 4:16.050 \| none row 12 : 12 \| netherlands \| jarich bakker robertus michie slippens richard rozendaal peter schep \| 4:16.175 \| none row 13 : 13 \| denmark \| frederik bertelsen jimmi madsen michael nielsen jacob piil \| 4:16.175 \| none row 14 : 14 \| argentina \| walter perez edgardo simon gonzalo garcia gabriel curuchet \| 4:20.840 \| none row 15 : 15 \| south korea \| dae-hong chun young chung jong-mo kim younk-sik noh \| 4:25.215 \| none row 16 : 16 \| chile \| jose medina luis sepulveda marco arriagada marcelo arriagada \| 4:25.960 \| none row 17 : 17 \| colombia \| john garcia marlon perez yovani lopez jos velasquez de la cuesta \| 4:26.400 \| none	col : rank row 1 : 11	select rank where team = 'lithuania' <table_name> : table \begin{tabular}{llllll} \toprule & rank & team & names & time & qualification \\ \midrule 0 & 1 & france & christophe capelle philippe ermenault jean-michel monin francis moreau & 4:09.570 & q \\ 1 & 2 & italy & adler capelli mauro trentini andrea collinelli cristiano citton & 4:09.695 & q \\ 2 & 3 & australia & bradley mcgee stuart o'grady timothy o'shannessey dean woods & 4:09.750 & q \\ 3 & 4 & ukraine & bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko & 4:11.545 & q \\ 4 & 5 & russia & eduard gritsun nikolay kuznetsov aleksey markov anton chantyr & 4:11.665 & q \\ 5 & 6 & united states & dirk copeland mariano friedick adam laurent michael mccarthy & 4:11.950 & q \\ 6 & 7 & spain & juan martinez juan llaneras santos gonzalez adolfo alperi & 4:12.780 & q \\ 7 & 8 & new zealand & gregory henderson brendon cameron timothy carswell julian dean & 4:15.140 & q \\ 8 & 9 & germany & robert bartko guido fulst danilo hondo heiko szonn & 4:15.140 & none \\ 9 & 10 & great britain & robert hayes matthew illingsworth bryan steel chris newton & 4:16.510 & none \\ 10 & 11 & lithuania & arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas & 4:16.050 & none \\ 11 & 12 & netherlands & jarich bakker robertus michie slippens richard rozendaal peter schep & 4:16.175 & none \\ 12 & 13 & denmark & frederik bertelsen jimmi madsen michael nielsen jacob piil & 4:16.175 & none \\ 13 & 14 & argentina & walter perez edgardo simon gonzalo garcia gabriel curuchet & 4:20.840 & none \\ 14 & 15 & south korea & dae-hong chun young chung jong-mo kim younk-sik noh & 4:25.215 & none \\ 15 & 16 & chile & jose medina luis sepulveda marco arriagada marcelo arriagada & 4:25.960 & none \\ 16 & 17 & colombia & john garcia marlon perez yovani lopez jos velasquez de la cuesta & 4:26.400 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & rank \\ \midrule 0 & 11 \\ \bottomrule \end{tabular}	select rank where team = 'lithuania' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>team</th> <th>names</th> <th>time</th> <th>qualification</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>france</td> <td>christophe capelle philippe ermenault jean-michel monin francis moreau</td> <td>4:09.570</td> <td>q</td> </tr> <tr> <th>1</th> <td>2</td> <td>italy</td> <td>adler capelli mauro trentini andrea collinelli cristiano citton</td> <td>4:09.695</td> <td>q</td> </tr> <tr> <th>2</th> <td>3</td> <td>australia</td> <td>bradley mcgee stuart o'grady timothy o'shannessey dean woods</td> <td>4:09.750</td> <td>q</td> </tr> <tr> <th>3</th> <td>4</td> <td>ukraine</td> <td>bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko</td> <td>4:11.545</td> <td>q</td> </tr> <tr> <th>4</th> <td>5</td> <td>russia</td> <td>eduard gritsun nikolay kuznetsov aleksey markov anton chantyr</td> <td>4:11.665</td> <td>q</td> </tr> <tr> <th>5</th> <td>6</td> <td>united states</td> <td>dirk copeland mariano friedick adam laurent michael mccarthy</td> <td>4:11.950</td> <td>q</td> </tr> <tr> <th>6</th> <td>7</td> <td>spain</td> <td>juan martinez juan llaneras santos gonzalez adolfo alperi</td> <td>4:12.780</td> <td>q</td> </tr> <tr> <th>7</th> <td>8</td> <td>new zealand</td> <td>gregory henderson brendon cameron timothy carswell julian dean</td> <td>4:15.140</td> <td>q</td> </tr> <tr> <th>8</th> <td>9</td> <td>germany</td> <td>robert bartko guido fulst danilo hondo heiko szonn</td> <td>4:15.140</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>great britain</td> <td>robert hayes matthew illingsworth bryan steel chris newton</td> <td>4:16.510</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>lithuania</td> <td>arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas</td> <td>4:16.050</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>netherlands</td> <td>jarich bakker robertus michie slippens richard rozendaal peter schep</td> <td>4:16.175</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>denmark</td> <td>frederik bertelsen jimmi madsen michael nielsen jacob piil</td> <td>4:16.175</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>argentina</td> <td>walter perez edgardo simon gonzalo garcia gabriel curuchet</td> <td>4:20.840</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>south korea</td> <td>dae-hong chun young chung jong-mo kim younk-sik noh</td> <td>4:25.215</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>chile</td> <td>jose medina luis sepulveda marco arriagada marcelo arriagada</td> <td>4:25.960</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>colombia</td> <td>john garcia marlon perez yovani lopez jos velasquez de la cuesta</td> <td>4:26.400</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>11</td> </tr> </tbody> </table>	select rank where team = 'lithuania' <table_name> : table \| \| rank \| team \| names \| time \| qualification \| \|---:\|-------:\|:--------------\|:-------------------------------------------------------------------------\|:---------\|:----------------\| \| 0 \| 1 \| france \| christophe capelle philippe ermenault jean-michel monin francis moreau \| 4:09.570 \| q \| \| 1 \| 2 \| italy \| adler capelli mauro trentini andrea collinelli cristiano citton \| 4:09.695 \| q \| \| 2 \| 3 \| australia \| bradley mcgee stuart o'grady timothy o'shannessey dean woods \| 4:09.750 \| q \| \| 3 \| 4 \| ukraine \| bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko \| 4:11.545 \| q \| \| 4 \| 5 \| russia \| eduard gritsun nikolay kuznetsov aleksey markov anton chantyr \| 4:11.665 \| q \| \| 5 \| 6 \| united states \| dirk copeland mariano friedick adam laurent michael mccarthy \| 4:11.950 \| q \| \| 6 \| 7 \| spain \| juan martinez juan llaneras santos gonzalez adolfo alperi \| 4:12.780 \| q \| \| 7 \| 8 \| new zealand \| gregory henderson brendon cameron timothy carswell julian dean \| 4:15.140 \| q \| \| 8 \| 9 \| germany \| robert bartko guido fulst danilo hondo heiko szonn \| 4:15.140 \| none \| \| 9 \| 10 \| great britain \| robert hayes matthew illingsworth bryan steel chris newton \| 4:16.510 \| none \| \| 10 \| 11 \| lithuania \| arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas \| 4:16.050 \| none \| \| 11 \| 12 \| netherlands \| jarich bakker robertus michie slippens richard rozendaal peter schep \| 4:16.175 \| none \| \| 12 \| 13 \| denmark \| frederik bertelsen jimmi madsen michael nielsen jacob piil \| 4:16.175 \| none \| \| 13 \| 14 \| argentina \| walter perez edgardo simon gonzalo garcia gabriel curuchet \| 4:20.840 \| none \| \| 14 \| 15 \| south korea \| dae-hong chun young chung jong-mo kim younk-sik noh \| 4:25.215 \| none \| \| 15 \| 16 \| chile \| jose medina luis sepulveda marco arriagada marcelo arriagada \| 4:25.960 \| none \| \| 16 \| 17 \| colombia \| john garcia marlon perez yovani lopez jos velasquez de la cuesta \| 4:26.400 \| none \|	\| \| rank \| \|---:\|-------:\| \| 0 \| 11 \|	[ [ 1, 4025, 6171, 1625, 5927, 273, 296, 80, 483, 89, 304, 1155, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 10035, 1757, 451, 34, 203, 1377, 411, 451, 34, 1973, 1757, 451, 34, 203, 1377, 411, 451, 34, 957, 1757, 451, 34, 203, 1377, 411, 451, 34, 3369, 1480, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 21, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 4840, 1359, 1757, 4465, 34, 203, 1377, 411, 4465, 34, 15182, 376, 556, 580, 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select count ( * ) where name = 'the condominiums at north bank park' col : rank \| name \| height ft / m \| floors \| year \| notes row 1 : 1 \| rhodes state office tower \| 629 / 192 \| 41 \| 1973 \| has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s row 2 : 2 \| leveque tower \| 555 / 169 \| 47 \| 1927 \| tallest building constructed in columbus in the 1920s row 3 : 3 \| william green building \| 530 / 162 \| 33 \| 1990 \| tallest building constructed in columbus in the 1990s row 4 : 4 \| huntington center \| 512 / 156 \| 37 \| 1984 \| tallest building constructed in columbus in the 1980s row 5 : 5 \| vern riffe state office tower \| 503 / 153 \| 32 \| 1988 \| none row 6 : 6 \| one nationwide plaza \| 485 / 148 \| 40 \| 1976 \| none row 7 : 7 \| franklin county courthouse \| 464 / 141 \| 27 \| 1991 \| none row 8 : 8 \| aep building \| 456 / 139 \| 31 \| 1983 \| none row 9 : 9 \| borden building \| 438 / 134 \| 34 \| 1974 \| none row 10 : 10 \| three nationwide plaza \| 408 / 124 \| 27 \| 1989 \| none row 11 : 11 \| one columbus center \| 366 / 112 \| 26 \| 1987 \| none row 12 : 12 \| columbus center \| 357 / 109 \| 25 \| 1964 \| tallest building constructed in columbus in the 1960s. was built as the bank one tower row 13 : 13 \| capitol square \| 350 / 107 \| 26 \| 1984 \| none row 14 : 14 \| continental center \| 348 / 106 \| 26 \| 1973 \| none row 15 : 15 \| pnc bank building \| 317 / 97 \| 25 \| 1977 \| none row 16 : 16 \| miranova condominiums \| 314 / 96 \| 26 \| 2001 \| tallest residential building in the state of ohio. tallest building built in the 2000s row 17 : 17 \| fifth third center \| 302 / 92 \| 25 \| 1998 \| none row 18 : 18 \| motorists mutual building \| 286 / 87 \| 21 \| 1973 \| none row 19 : 19 \| midland building \| 280 / 85 \| 21 \| 1970 \| none row 20 : 20 \| the condominiums at north bank park \| 267 / 81 \| 20 \| 2007 \| none row 21 : 21= \| lincoln tower dormitory \| 260 / 79 \| 26 \| 1967 \| none row 22 : 21= \| morrill tower dormitory \| 260 / 79 \| 26 \| 1967 \| none row 23 : 23 \| hyatt regency columbus \| 256 / 78 \| 20 \| 1980 \| none row 24 : 24 \| key bank building \| 253 / 77 \| 20 \| 1963 \| none row 25 : 25 \| adam's mark hotel \| 243 / 74 \| 16 \| 1961 \| none row 26 : 26 \| town center \| 226 / 69 \| 17 \| 1974 \| none row 27 : 27 \| 8 east broad street \| 212 / 64.6 \| 17 \| 1906 \| none row 28 : 28 \| huntington building \| 202 / 59.4 \| 13 \| 1926 \| none row 29 : 29 \| ohio judicial center \| 200 / 57.9 \| 14 \| 1933 \| none row 30 : 30 \| 16 east broad street \| 180 / 64.4 \| 13 \| 1900 \| none	col : count ( "*" ) row 1 : 1	select count ( * ) where name = 'the condominiums at north bank park' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & name & height ft / m & floors & year & notes \\ \midrule 0 & 1 & rhodes state office tower & 629 / 192 & 41 & 1973 & has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s \\ 1 & 2 & leveque tower & 555 / 169 & 47 & 1927 & tallest building constructed in columbus in the 1920s \\ 2 & 3 & william green building & 530 / 162 & 33 & 1990 & tallest building constructed in columbus in the 1990s \\ 3 & 4 & huntington center & 512 / 156 & 37 & 1984 & tallest building constructed in columbus in the 1980s \\ 4 & 5 & vern riffe state office tower & 503 / 153 & 32 & 1988 & none \\ 5 & 6 & one nationwide plaza & 485 / 148 & 40 & 1976 & none \\ 6 & 7 & franklin county courthouse & 464 / 141 & 27 & 1991 & none \\ 7 & 8 & aep building & 456 / 139 & 31 & 1983 & none \\ 8 & 9 & borden building & 438 / 134 & 34 & 1974 & none \\ 9 & 10 & three nationwide plaza & 408 / 124 & 27 & 1989 & none \\ 10 & 11 & one columbus center & 366 / 112 & 26 & 1987 & none \\ 11 & 12 & columbus center & 357 / 109 & 25 & 1964 & tallest building constructed in columbus in the 1960s. was built as the bank one tower \\ 12 & 13 & capitol square & 350 / 107 & 26 & 1984 & none \\ 13 & 14 & continental center & 348 / 106 & 26 & 1973 & none \\ 14 & 15 & pnc bank building & 317 / 97 & 25 & 1977 & none \\ 15 & 16 & miranova condominiums & 314 / 96 & 26 & 2001 & tallest residential building in the state of ohio. tallest building built in the 2000s \\ 16 & 17 & fifth third center & 302 / 92 & 25 & 1998 & none \\ 17 & 18 & motorists mutual building & 286 / 87 & 21 & 1973 & none \\ 18 & 19 & midland building & 280 / 85 & 21 & 1970 & none \\ 19 & 20 & the condominiums at north bank park & 267 / 81 & 20 & 2007 & none \\ 20 & 21= & lincoln tower dormitory & 260 / 79 & 26 & 1967 & none \\ 21 & 21= & morrill tower dormitory & 260 / 79 & 26 & 1967 & none \\ 22 & 23 & hyatt regency columbus & 256 / 78 & 20 & 1980 & none \\ 23 & 24 & key bank building & 253 / 77 & 20 & 1963 & none \\ 24 & 25 & adam's mark hotel & 243 / 74 & 16 & 1961 & none \\ 25 & 26 & town center & 226 / 69 & 17 & 1974 & none \\ 26 & 27 & 8 east broad street & 212 / 64.6 & 17 & 1906 & none \\ 27 & 28 & huntington building & 202 / 59.4 & 13 & 1926 & none \\ 28 & 29 & ohio judicial center & 200 / 57.9 & 14 & 1933 & none \\ 29 & 30 & 16 east broad street & 180 / 64.4 & 13 & 1900 & none \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}	select count ( * ) where name = 'the condominiums at north bank park' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>name</th> <th>height ft / m</th> <th>floors</th> <th>year</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>rhodes state office tower</td> <td>629 / 192</td> <td>41</td> <td>1973</td> <td>has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s</td> </tr> <tr> <th>1</th> <td>2</td> <td>leveque tower</td> <td>555 / 169</td> <td>47</td> <td>1927</td> <td>tallest building constructed in columbus in the 1920s</td> </tr> <tr> <th>2</th> <td>3</td> <td>william green building</td> <td>530 / 162</td> <td>33</td> <td>1990</td> <td>tallest building constructed in columbus in the 1990s</td> </tr> <tr> <th>3</th> <td>4</td> <td>huntington center</td> <td>512 / 156</td> <td>37</td> <td>1984</td> <td>tallest building constructed in columbus in the 1980s</td> </tr> <tr> <th>4</th> <td>5</td> <td>vern riffe state office tower</td> <td>503 / 153</td> <td>32</td> <td>1988</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>one nationwide plaza</td> <td>485 / 148</td> <td>40</td> <td>1976</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>franklin county courthouse</td> <td>464 / 141</td> <td>27</td> <td>1991</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>aep building</td> <td>456 / 139</td> <td>31</td> <td>1983</td> <td>none</td> </tr> <tr> <th>8</th> <td>9</td> <td>borden building</td> <td>438 / 134</td> <td>34</td> <td>1974</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>three nationwide plaza</td> <td>408 / 124</td> <td>27</td> <td>1989</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>one columbus center</td> <td>366 / 112</td> <td>26</td> <td>1987</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>columbus center</td> <td>357 / 109</td> <td>25</td> <td>1964</td> <td>tallest building constructed in columbus in the 1960s. was built as the bank one tower</td> </tr> <tr> <th>12</th> <td>13</td> <td>capitol square</td> <td>350 / 107</td> <td>26</td> <td>1984</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>continental center</td> <td>348 / 106</td> <td>26</td> <td>1973</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>pnc bank building</td> <td>317 / 97</td> <td>25</td> <td>1977</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>miranova condominiums</td> <td>314 / 96</td> <td>26</td> <td>2001</td> <td>tallest residential building in the state of ohio. tallest building built in the 2000s</td> </tr> <tr> <th>16</th> <td>17</td> <td>fifth third center</td> <td>302 / 92</td> <td>25</td> <td>1998</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>motorists mutual building</td> <td>286 / 87</td> <td>21</td> <td>1973</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>midland building</td> <td>280 / 85</td> <td>21</td> <td>1970</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>the condominiums at north bank park</td> <td>267 / 81</td> <td>20</td> <td>2007</td> <td>none</td> </tr> <tr> <th>20</th> <td>21=</td> <td>lincoln tower dormitory</td> <td>260 / 79</td> <td>26</td> <td>1967</td> <td>none</td> </tr> <tr> <th>21</th> <td>21=</td> <td>morrill tower dormitory</td> <td>260 / 79</td> <td>26</td> <td>1967</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>hyatt regency columbus</td> <td>256 / 78</td> <td>20</td> <td>1980</td> <td>none</td> </tr> <tr> <th>23</th> <td>24</td> <td>key bank building</td> <td>253 / 77</td> <td>20</td> <td>1963</td> <td>none</td> </tr> <tr> <th>24</th> <td>25</td> <td>adam's mark hotel</td> <td>243 / 74</td> <td>16</td> <td>1961</td> <td>none</td> </tr> <tr> <th>25</th> <td>26</td> <td>town center</td> <td>226 / 69</td> <td>17</td> <td>1974</td> <td>none</td> </tr> <tr> <th>26</th> <td>27</td> <td>8 east broad street</td> <td>212 / 64.6</td> <td>17</td> <td>1906</td> <td>none</td> </tr> <tr> <th>27</th> <td>28</td> <td>huntington building</td> <td>202 / 59.4</td> <td>13</td> <td>1926</td> <td>none</td> </tr> <tr> <th>28</th> <td>29</td> <td>ohio judicial center</td> <td>200 / 57.9</td> <td>14</td> <td>1933</td> <td>none</td> </tr> <tr> <th>29</th> <td>30</td> <td>16 east broad street</td> <td>180 / 64.4</td> <td>13</td> <td>1900</td> <td>none</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>	select count ( * ) where name = 'the condominiums at north bank park' <table_name> : table \| \| rank \| name \| height ft / m \| floors \| year \| notes \| \|---:\|:-------\|:------------------------------------\|:----------------\|---------:\|-------:\|:---------------------------------------------------------------------------------------------------------------------------------------------------------\| \| 0 \| 1 \| rhodes state office tower \| 629 / 192 \| 41 \| 1973 \| has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s \| \| 1 \| 2 \| leveque tower \| 555 / 169 \| 47 \| 1927 \| tallest building constructed in columbus in the 1920s \| \| 2 \| 3 \| william green building \| 530 / 162 \| 33 \| 1990 \| tallest building constructed in columbus in the 1990s \| \| 3 \| 4 \| huntington center \| 512 / 156 \| 37 \| 1984 \| tallest building constructed in columbus in the 1980s \| \| 4 \| 5 \| vern riffe state office tower \| 503 / 153 \| 32 \| 1988 \| none \| \| 5 \| 6 \| one nationwide plaza \| 485 / 148 \| 40 \| 1976 \| none \| \| 6 \| 7 \| franklin county courthouse \| 464 / 141 \| 27 \| 1991 \| none \| \| 7 \| 8 \| aep building \| 456 / 139 \| 31 \| 1983 \| none \| \| 8 \| 9 \| borden building \| 438 / 134 \| 34 \| 1974 \| none \| \| 9 \| 10 \| three nationwide plaza \| 408 / 124 \| 27 \| 1989 \| none \| \| 10 \| 11 \| one columbus center \| 366 / 112 \| 26 \| 1987 \| none \| \| 11 \| 12 \| columbus center \| 357 / 109 \| 25 \| 1964 \| tallest building constructed in columbus in the 1960s. was built as the bank one tower \| \| 12 \| 13 \| capitol square \| 350 / 107 \| 26 \| 1984 \| none \| \| 13 \| 14 \| continental center \| 348 / 106 \| 26 \| 1973 \| none \| \| 14 \| 15 \| pnc bank building \| 317 / 97 \| 25 \| 1977 \| none \| \| 15 \| 16 \| miranova condominiums \| 314 / 96 \| 26 \| 2001 \| tallest residential building in the state of ohio. tallest building built in the 2000s \| \| 16 \| 17 \| fifth third center \| 302 / 92 \| 25 \| 1998 \| none \| \| 17 \| 18 \| motorists mutual building \| 286 / 87 \| 21 \| 1973 \| none \| \| 18 \| 19 \| midland building \| 280 / 85 \| 21 \| 1970 \| none \| \| 19 \| 20 \| the condominiums at north bank park \| 267 / 81 \| 20 \| 2007 \| none \| \| 20 \| 21= \| lincoln tower dormitory \| 260 / 79 \| 26 \| 1967 \| none \| \| 21 \| 21= \| morrill tower dormitory \| 260 / 79 \| 26 \| 1967 \| none \| \| 22 \| 23 \| hyatt regency columbus \| 256 / 78 \| 20 \| 1980 \| none \| \| 23 \| 24 \| key bank building \| 253 / 77 \| 20 \| 1963 \| none \| \| 24 \| 25 \| adam's mark hotel \| 243 / 74 \| 16 \| 1961 \| none \| \| 25 \| 26 \| town center \| 226 / 69 \| 17 \| 1974 \| none \| \| 26 \| 27 \| 8 east broad street \| 212 / 64.6 \| 17 \| 1906 \| none \| \| 27 \| 28 \| huntington building \| 202 / 59.4 \| 13 \| 1926 \| none \| \| 28 \| 29 \| ohio judicial center \| 200 / 57.9 \| 14 \| 1933 \| none \| \| 29 \| 30 \| 16 east broad street \| 180 / 64.4 \| 13 \| 1900 \| none \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 1 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 508, 273, 296, 5787, 6941, 362, 267, 5077, 87, 622, 21435, 11218, 779, 79, 11, 411, 2121, 67, 529, 34, 294, 1014, 411, 2121, 5795, 33, 21, 667, 33, 18858, 34, 203, 225, 411, 24604, 34, 203, 565, 411, 313, 2154, 33, 955, 17, 7989, 30, 2145, 31, 34, 203, 1377, 411, 451, 4695, 451, 34, 203, 1377, 411, 451, 34, 11500, 1757, 451, 34, 203, 1377, 411, 451, 34, 529, 1757, 451, 34, 203, 1377, 411, 451, 34, 4210, 11038, 342, 312, 1757, 451, 34, 203, 1377, 411, 451, 34, 74, 383, 1383, 1757, 451, 34, 203, 1377, 411, 451, 34, 6874, 1757, 451, 34, 203, 1377, 411, 451, 34, 12903, 1757, 451, 34, 203, 565, 7765, 313, 34, 203, 225, 7765, 24604, 34, 203, 225, 411, 20779, 34, 203, 565, 411, 313, 34, 203, 1377, 411, 451, 34, 20, 1757, 451, 34, 203, 1377, 411, 4465, 34, 21, 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select count ( * ) where size (in kb) = 'none' col : version \| date \| development cycle \| size (in kb) \| download \| notes row 1 : 0.1 \| 9 june 1993 \| beta \| none \| evolt \| none row 2 : 0.2 \| 14 june 1993 \| beta \| none \| none \| changelog row 3 : 0.3 \| 16 june 1993 \| beta \| none \| none \| changelog row 4 : 0.4 \| 18 june 1993 \| beta \| none \| none \| changelog row 5 : 0.5 \| 24 june 1993 \| beta \| none \| none \| changelog row 6 : 0.6 \| 30 june 1993 \| beta \| none \| none \| changelog row 7 : 0.8 \| 5 november 1993 \| beta \| none \| none \| changelog (distinct version discontinued) row 8 : 0.9 \| 12 november 1993 \| beta-pre \| none \| none \| none row 9 : 0.9 \| 16 november 1993 \| beta \| none \| none \| changelog row 10 : 0.9 \| 22 november 1993 \| winsock alpha r9.2 \| none \| none \| none row 11 : 1 \| 17 february 1994 \| release \| none \| evolt \| none row 12 : 1.01 \| none \| release \| none \| none \| none row 13 : 1.01a \| 17 march 1994 \| release \| 521 \| [5], evolt \| changelog row 14 : 2 \| none \| alpha \| none \| none \| development ceased	col : count ( "*" ) row 1 : 13	select count ( * ) where size (in kb) = 'none' <table_name> : table \begin{tabular}{lllllll} \toprule & version & date & development cycle & size (in kb) & download & notes \\ \midrule 0 & 0.1 & 9 june 1993 & beta & none & evolt & none \\ 1 & 0.2 & 14 june 1993 & beta & none & none & changelog \\ 2 & 0.3 & 16 june 1993 & beta & none & none & changelog \\ 3 & 0.4 & 18 june 1993 & beta & none & none & changelog \\ 4 & 0.5 & 24 june 1993 & beta & none & none & changelog \\ 5 & 0.6 & 30 june 1993 & beta & none & none & changelog \\ 6 & 0.8 & 5 november 1993 & beta & none & none & changelog (distinct version discontinued) \\ 7 & 0.9 & 12 november 1993 & beta-pre & none & none & none \\ 8 & 0.9 & 16 november 1993 & beta & none & none & changelog \\ 9 & 0.9 & 22 november 1993 & winsock alpha r9.2 & none & none & none \\ 10 & 1 & 17 february 1994 & release & none & evolt & none \\ 11 & 1.01 & none & release & none & none & none \\ 12 & 1.01a & 17 march 1994 & release & 521 & [5], evolt & changelog \\ 13 & 2 & none & alpha & none & none & development ceased \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 13 \\ \bottomrule \end{tabular}	select count ( * ) where size (in kb) = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>version</th> <th>date</th> <th>development cycle</th> <th>size (in kb)</th> <th>download</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0.1</td> <td>9 june 1993</td> <td>beta</td> <td>none</td> <td>evolt</td> <td>none</td> </tr> <tr> <th>1</th> <td>0.2</td> <td>14 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>2</th> <td>0.3</td> <td>16 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>3</th> <td>0.4</td> <td>18 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>4</th> <td>0.5</td> <td>24 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>5</th> <td>0.6</td> <td>30 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>6</th> <td>0.8</td> <td>5 november 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog (distinct version discontinued)</td> </tr> <tr> <th>7</th> <td>0.9</td> <td>12 november 1993</td> <td>beta-pre</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>8</th> <td>0.9</td> <td>16 november 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>9</th> <td>0.9</td> <td>22 november 1993</td> <td>winsock alpha r9.2</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>10</th> <td>1</td> <td>17 february 1994</td> <td>release</td> <td>none</td> <td>evolt</td> <td>none</td> </tr> <tr> <th>11</th> <td>1.01</td> <td>none</td> <td>release</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>12</th> <td>1.01a</td> <td>17 march 1994</td> <td>release</td> <td>521</td> <td>[5], evolt</td> <td>changelog</td> </tr> <tr> <th>13</th> <td>2</td> <td>none</td> <td>alpha</td> <td>none</td> <td>none</td> <td>development ceased</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>13</td> </tr> </tbody> </table>	select count ( * ) where size (in kb) = 'none' <table_name> : table \| \| version \| date \| development cycle \| size (in kb) \| download \| notes \| \|---:\|:----------\|:-----------------\|:--------------------\|:---------------\|:-----------\|:------------------------------------------\| \| 0 \| 0.1 \| 9 june 1993 \| beta \| none \| evolt \| none \| \| 1 \| 0.2 \| 14 june 1993 \| beta \| none \| none \| changelog \| \| 2 \| 0.3 \| 16 june 1993 \| beta \| none \| none \| changelog \| \| 3 \| 0.4 \| 18 june 1993 \| beta \| none \| none \| changelog \| \| 4 \| 0.5 \| 24 june 1993 \| beta \| none \| none \| changelog \| \| 5 \| 0.6 \| 30 june 1993 \| beta \| none \| none \| changelog \| \| 6 \| 0.8 \| 5 november 1993 \| beta \| none \| none \| changelog (distinct version discontinued) \| \| 7 \| 0.9 \| 12 november 1993 \| beta-pre \| none \| none \| none \| \| 8 \| 0.9 \| 16 november 1993 \| beta \| none \| none \| changelog \| \| 9 \| 0.9 \| 22 november 1993 \| winsock alpha r9.2 \| none \| none \| none \| \| 10 \| 1 \| 17 february 1994 \| release \| none \| evolt \| none \| \| 11 \| 1.01 \| none \| release \| none \| none \| none \| \| 12 \| 1.01a \| 17 march 1994 \| release \| 521 \| [5], evolt \| changelog \| \| 13 \| 2 \| none \| alpha \| none \| none \| development ceased \|	\| \| count ( "*" ) \| \|---:\|----------------:\| \| 0 \| 13 \|	[ [ 1, 4025, 1056, 261, 380, 262, 1625, 963, 261, 267, 9182, 13, 273, 296, 6102, 11, 411, 2121, 67, 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select score where season = 2003 col : season \| winner \| score \| runners-up \| venue row 1 : 2000 \| san juan jabloteh \| 1-0 \| defence force \| marvin lee stadium row 2 : 2001 \| w connection \| 1-0 \| caledonia aia \| manny ramjohn stadium row 3 : 2002 \| defence force \| 2-0 \| w connection \| hasely crawford stadium row 4 : 2003 \| san juan jabloteh \| 1-1 \| w connection \| manny ramjohn stadium row 5 : 2004 \| w connection \| 2-2 \| defence force \| manny ramjohn stadium row 6 : 2005 \| w connection \| 3-1 \| san juan jabloteh \| manny ramjohn stadium row 7 : 2006 \| w connection \| 3-1 \| north east stars \| manny ramjohn stadium row 8 : 2007 \| w connection \| 2-0 \| caledonia aia \| manny ramjohn stadium row 9 : 2008 \| w connection \| 2-2 \| joe public \| manny ramjohn stadium row 10 : 2009 \| defence force \| 1-0 \| joe public \| marvin lee stadium row 11 : 2010 \| joe public \| 1-1 \| defence force \| marvin lee stadium row 12 : 2011 \| caledonia aia \| 2-1 \| t&tec \| hasely crawford stadium row 13 : 2012 \| caledonia aia \| 2-1 \| defence force \| hasely crawford stadium row 14 : 2013 \| central fc \| 2-1 \| defence force \| hasely crawford stadium	col : score row 1 : 1-1	select score where season = 2003 <table_name> : table \begin{tabular}{llllll} \toprule & season & winner & score & runners-up & venue \\ \midrule 0 & 2000 & san juan jabloteh & 1-0 & defence force & marvin lee stadium \\ 1 & 2001 & w connection & 1-0 & caledonia aia & manny ramjohn stadium \\ 2 & 2002 & defence force & 2-0 & w connection & hasely crawford stadium \\ 3 & 2003 & san juan jabloteh & 1-1 & w connection & manny ramjohn stadium \\ 4 & 2004 & w connection & 2-2 & defence force & manny ramjohn stadium \\ 5 & 2005 & w connection & 3-1 & san juan jabloteh & manny ramjohn stadium \\ 6 & 2006 & w connection & 3-1 & north east stars & manny ramjohn stadium \\ 7 & 2007 & w connection & 2-0 & caledonia aia & manny ramjohn stadium \\ 8 & 2008 & w connection & 2-2 & joe public & manny ramjohn stadium \\ 9 & 2009 & defence force & 1-0 & joe public & marvin lee stadium \\ 10 & 2010 & joe public & 1-1 & defence force & marvin lee stadium \\ 11 & 2011 & caledonia aia & 2-1 & t&tec & hasely crawford stadium \\ 12 & 2012 & caledonia aia & 2-1 & defence force & hasely crawford stadium \\ 13 & 2013 & central fc & 2-1 & defence force & hasely crawford stadium \\ \bottomrule \end{tabular}	\begin{tabular}{ll} \toprule & score \\ \midrule 0 & 1-1 \\ \bottomrule \end{tabular}	select score where season = 2003 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>winner</th> <th>score</th> <th>runners-up</th> <th>venue</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2000</td> <td>san juan jabloteh</td> <td>1-0</td> <td>defence force</td> <td>marvin lee stadium</td> </tr> <tr> <th>1</th> <td>2001</td> <td>w connection</td> <td>1-0</td> <td>caledonia aia</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>2</th> <td>2002</td> <td>defence force</td> <td>2-0</td> <td>w connection</td> <td>hasely crawford stadium</td> </tr> <tr> <th>3</th> <td>2003</td> <td>san juan jabloteh</td> <td>1-1</td> <td>w connection</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>4</th> <td>2004</td> <td>w connection</td> <td>2-2</td> <td>defence force</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>5</th> <td>2005</td> <td>w connection</td> <td>3-1</td> <td>san juan jabloteh</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>6</th> <td>2006</td> <td>w connection</td> <td>3-1</td> <td>north east stars</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>7</th> <td>2007</td> <td>w connection</td> <td>2-0</td> <td>caledonia aia</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>8</th> <td>2008</td> <td>w connection</td> <td>2-2</td> <td>joe public</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>9</th> <td>2009</td> <td>defence force</td> <td>1-0</td> <td>joe public</td> <td>marvin lee stadium</td> </tr> <tr> <th>10</th> <td>2010</td> <td>joe public</td> <td>1-1</td> <td>defence force</td> <td>marvin lee stadium</td> </tr> <tr> <th>11</th> <td>2011</td> <td>caledonia aia</td> <td>2-1</td> <td>t&tec</td> <td>hasely crawford stadium</td> </tr> <tr> <th>12</th> <td>2012</td> <td>caledonia aia</td> <td>2-1</td> <td>defence force</td> <td>hasely crawford stadium</td> </tr> <tr> <th>13</th> <td>2013</td> <td>central fc</td> <td>2-1</td> <td>defence force</td> <td>hasely crawford stadium</td> </tr> </tbody> </table>	<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>score</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1-1</td> </tr> </tbody> </table>	select score where season = 2003 <table_name> : table \| \| season \| winner \| score \| runners-up \| venue \| \|---:\|---------:\|:------------------\|:--------\|:------------------\|:------------------------\| \| 0 \| 2000 \| san juan jabloteh \| 1-0 \| defence force \| marvin lee stadium \| \| 1 \| 2001 \| w connection \| 1-0 \| caledonia aia \| manny ramjohn stadium \| \| 2 \| 2002 \| defence force \| 2-0 \| w connection \| hasely crawford stadium \| \| 3 \| 2003 \| san juan jabloteh \| 1-1 \| w connection \| manny ramjohn stadium \| \| 4 \| 2004 \| w connection \| 2-2 \| defence force \| manny ramjohn stadium \| \| 5 \| 2005 \| w connection \| 3-1 \| san juan jabloteh \| manny ramjohn stadium \| \| 6 \| 2006 \| w connection \| 3-1 \| north east stars \| manny ramjohn stadium \| \| 7 \| 2007 \| w connection \| 2-0 \| caledonia aia \| manny ramjohn stadium \| \| 8 \| 2008 \| w connection \| 2-2 \| joe public \| manny ramjohn stadium \| \| 9 \| 2009 \| defence force \| 1-0 \| joe public \| marvin lee stadium \| \| 10 \| 2010 \| joe public \| 1-1 \| defence force \| marvin lee stadium \| \| 11 \| 2011 \| caledonia aia \| 2-1 \| t&tec \| hasely crawford stadium \| \| 12 \| 2012 \| caledonia aia \| 2-1 \| defence force \| hasely crawford stadium \| \| 13 \| 2013 \| central fc \| 2-1 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select opp. where venue = 'anz stadium' col : round | opponent | result | bro. | opp. | date | venue | crowd | position row 1 : 1 | auckland warriors | win | 14 | 2 | 1 mar | anz stadium | 42361 | 2/10 row 2 : 2 | adelaide rams | win | 28 | 12 | 9 mar | anz stadium | 16279 | 1/10 row 3 : 3 | perth reds | win | 26 | 16 | 16 mar | waca ground | 11109 | 2/10 row 4 : 4 | canberra raiders | win | 24 | 8 | 24 mar | anz stadium | 26103 | 2/10 row 5 : 5 | cronulla sharks | win | 14 | 12 | 31 mar | anz stadium | 17294 | 1/10 row 6 : 6 | north queensland cowboys | win | 42 | 16 | 5 apr | stockland stadium | 30122 | 1/10 row 7 : 7 | adelaide rams | win | 20 | 10 | 13 apr | adelaide oval | 17633 | 1/10 row 8 : 8 | penrith panthers | loss | 26 | 27 | 21 apr | penrith football stadium | 12648 | 1/10 row 9 : 9 | canterbury bulldogs | win | 34 | 16 | 28 apr | anz stadium | 17921 | 1/10 row 10 : 10 | auckland warriors | win | 34 | 18 | 4 may | mt smart stadium | 16471 | 1/10 row 11 : 11 | north queensland cowboys | draw | 20 | 20 | 25 may | anz stadium | 14167 | 1/10 row 12 : 12 | hunter mariners | loss | 6 | 24 | 30 may | topper stadium | 7124 | 1/10 row 13 : 13 | cronulla sharks | loss | 4 | 32 | 30 jun | endeavour field | 12240 | 1/10 row 14 : 14 | perth reds | win | 50 | 14 | 6 jul | anz stadium | 11806 | 1/10 row 15 : 15 | canberra raiders | win | 19 | 4 | 14 jul | bruce stadium | 13067 | 1/10 row 16 : 16 | penrith panthers | win | 54 | 12 | 10 aug | anz stadium | 13921 | 1/10 row 17 : 17 | hunter mariners | win | 34 | 16 | 18 aug | anz stadium | 13830 | 1/10 row 18 : 18 | canterbury bulldogs | win | 32 | 24 | 25 aug | belmore oval | 9781 | 1/10 row 19 : semi final | cronulla sharks | win | 34 | 2 | 6 sep | stockland stadium | 26256 | none row 20 : grand final | cronulla sharks | win | 26 | 8 | 20 sep | anz stadium | 58912 | none

col : opp. row 1 : 2 row 2 : 12 row 3 : 8 row 4 : 12 row 5 : 16 row 6 : 20 row 7 : 14 row 8 : 12 row 9 : 16 row 10 : 8

select opp. where venue = 'anz stadium' <table_name> : table \begin{tabular}{llllllllll} \toprule & round & opponent & result & bro. & opp. & date & venue & crowd & position \\ \midrule 0 & 1 & auckland warriors & win & 14 & 2 & 1 mar & anz stadium & 42361 & 2/10 \\ 1 & 2 & adelaide rams & win & 28 & 12 & 9 mar & anz stadium & 16279 & 1/10 \\ 2 & 3 & perth reds & win & 26 & 16 & 16 mar & waca ground & 11109 & 2/10 \\ 3 & 4 & canberra raiders & win & 24 & 8 & 24 mar & anz stadium & 26103 & 2/10 \\ 4 & 5 & cronulla sharks & win & 14 & 12 & 31 mar & anz stadium & 17294 & 1/10 \\ 5 & 6 & north queensland cowboys & win & 42 & 16 & 5 apr & stockland stadium & 30122 & 1/10 \\ 6 & 7 & adelaide rams & win & 20 & 10 & 13 apr & adelaide oval & 17633 & 1/10 \\ 7 & 8 & penrith panthers & loss & 26 & 27 & 21 apr & penrith football stadium & 12648 & 1/10 \\ 8 & 9 & canterbury bulldogs & win & 34 & 16 & 28 apr & anz stadium & 17921 & 1/10 \\ 9 & 10 & auckland warriors & win & 34 & 18 & 4 may & mt smart stadium & 16471 & 1/10 \\ 10 & 11 & north queensland cowboys & draw & 20 & 20 & 25 may & anz stadium & 14167 & 1/10 \\ 11 & 12 & hunter mariners & loss & 6 & 24 & 30 may & topper stadium & 7124 & 1/10 \\ 12 & 13 & cronulla sharks & loss & 4 & 32 & 30 jun & endeavour field & 12240 & 1/10 \\ 13 & 14 & perth reds & win & 50 & 14 & 6 jul & anz stadium & 11806 & 1/10 \\ 14 & 15 & canberra raiders & win & 19 & 4 & 14 jul & bruce stadium & 13067 & 1/10 \\ 15 & 16 & penrith panthers & win & 54 & 12 & 10 aug & anz stadium & 13921 & 1/10 \\ 16 & 17 & hunter mariners & win & 34 & 16 & 18 aug & anz stadium & 13830 & 1/10 \\ 17 & 18 & canterbury bulldogs & win & 32 & 24 & 25 aug & belmore oval & 9781 & 1/10 \\ 18 & semi final & cronulla sharks & win & 34 & 2 & 6 sep & stockland stadium & 26256 & none \\ 19 & grand final & cronulla sharks & win & 26 & 8 & 20 sep & anz stadium & 58912 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & opp. \\ \midrule 0 & 2 \\ 1 & 12 \\ 2 & 8 \\ 3 & 12 \\ 4 & 16 \\ 5 & 20 \\ 6 & 14 \\ 7 & 12 \\ 8 & 16 \\ 9 & 8 \\ \bottomrule \end{tabular}

select opp. where venue = 'anz stadium' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>round</th> <th>opponent</th> <th>result</th> <th>bro.</th> <th>opp.</th> <th>date</th> <th>venue</th> <th>crowd</th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>auckland warriors</td> <td>win</td> <td>14</td> <td>2</td> <td>1 mar</td> <td>anz stadium</td> <td>42361</td> <td>2/10</td> </tr> <tr> <th>1</th> <td>2</td> <td>adelaide rams</td> <td>win</td> <td>28</td> <td>12</td> <td>9 mar</td> <td>anz stadium</td> <td>16279</td> <td>1/10</td> </tr> <tr> <th>2</th> <td>3</td> <td>perth reds</td> <td>win</td> <td>26</td> <td>16</td> <td>16 mar</td> <td>waca ground</td> <td>11109</td> <td>2/10</td> </tr> <tr> <th>3</th> <td>4</td> <td>canberra raiders</td> <td>win</td> <td>24</td> <td>8</td> <td>24 mar</td> <td>anz stadium</td> <td>26103</td> <td>2/10</td> </tr> <tr> <th>4</th> <td>5</td> <td>cronulla sharks</td> <td>win</td> <td>14</td> <td>12</td> <td>31 mar</td> <td>anz stadium</td> <td>17294</td> <td>1/10</td> </tr> <tr> <th>5</th> <td>6</td> <td>north queensland cowboys</td> <td>win</td> <td>42</td> <td>16</td> <td>5 apr</td> <td>stockland stadium</td> <td>30122</td> <td>1/10</td> </tr> <tr> <th>6</th> <td>7</td> <td>adelaide rams</td> <td>win</td> <td>20</td> <td>10</td> <td>13 apr</td> <td>adelaide oval</td> <td>17633</td> <td>1/10</td> </tr> <tr> <th>7</th> <td>8</td> <td>penrith panthers</td> <td>loss</td> <td>26</td> <td>27</td> <td>21 apr</td> <td>penrith football stadium</td> <td>12648</td> <td>1/10</td> </tr> <tr> <th>8</th> <td>9</td> <td>canterbury bulldogs</td> <td>win</td> <td>34</td> <td>16</td> <td>28 apr</td> <td>anz stadium</td> <td>17921</td> <td>1/10</td> </tr> <tr> <th>9</th> <td>10</td> <td>auckland warriors</td> <td>win</td> <td>34</td> <td>18</td> <td>4 may</td> <td>mt smart stadium</td> <td>16471</td> <td>1/10</td> </tr> <tr> <th>10</th> <td>11</td> <td>north queensland cowboys</td> <td>draw</td> <td>20</td> <td>20</td> <td>25 may</td> <td>anz stadium</td> <td>14167</td> <td>1/10</td> </tr> <tr> <th>11</th> <td>12</td> <td>hunter mariners</td> <td>loss</td> <td>6</td> <td>24</td> <td>30 may</td> <td>topper stadium</td> <td>7124</td> <td>1/10</td> </tr> <tr> <th>12</th> <td>13</td> <td>cronulla sharks</td> <td>loss</td> <td>4</td> <td>32</td> <td>30 jun</td> <td>endeavour field</td> <td>12240</td> <td>1/10</td> </tr> <tr> <th>13</th> <td>14</td> <td>perth reds</td> <td>win</td> <td>50</td> <td>14</td> <td>6 jul</td> <td>anz stadium</td> <td>11806</td> <td>1/10</td> </tr> <tr> <th>14</th> <td>15</td> <td>canberra raiders</td> <td>win</td> <td>19</td> <td>4</td> <td>14 jul</td> <td>bruce stadium</td> <td>13067</td> <td>1/10</td> </tr> <tr> <th>15</th> <td>16</td> <td>penrith panthers</td> <td>win</td> <td>54</td> <td>12</td> <td>10 aug</td> <td>anz stadium</td> <td>13921</td> <td>1/10</td> </tr> <tr> <th>16</th> <td>17</td> <td>hunter mariners</td> <td>win</td> <td>34</td> <td>16</td> <td>18 aug</td> <td>anz stadium</td> <td>13830</td> <td>1/10</td> </tr> <tr> <th>17</th> <td>18</td> <td>canterbury bulldogs</td> <td>win</td> <td>32</td> <td>24</td> <td>25 aug</td> <td>belmore oval</td> <td>9781</td> <td>1/10</td> </tr> <tr> <th>18</th> <td>semi final</td> <td>cronulla sharks</td> <td>win</td> <td>34</td> <td>2</td> <td>6 sep</td> <td>stockland stadium</td> <td>26256</td> <td>none</td> </tr> <tr> <th>19</th> <td>grand final</td> <td>cronulla sharks</td> <td>win</td> <td>26</td> <td>8</td> <td>20 sep</td> <td>anz stadium</td> <td>58912</td> <td>none</td> </tr> </tbody> </table>

select opp. where venue = 'anz stadium' <table_name> : table | | round | opponent | result | bro. | opp. | date | venue | crowd | position | |---:|:------------|:-------------------------|:---------|-------:|-------:|:-------|:-------------------------|--------:|:-----------| | 0 | 1 | auckland warriors | win | 14 | 2 | 1 mar | anz stadium | 42361 | 2/10 | | 1 | 2 | adelaide rams | win | 28 | 12 | 9 mar | anz stadium | 16279 | 1/10 | | 2 | 3 | perth reds | win | 26 | 16 | 16 mar | waca ground | 11109 | 2/10 | | 3 | 4 | canberra raiders | win | 24 | 8 | 24 mar | anz stadium | 26103 | 2/10 | | 4 | 5 | cronulla sharks | win | 14 | 12 | 31 mar | anz stadium | 17294 | 1/10 | | 5 | 6 | north queensland cowboys | win | 42 | 16 | 5 apr | stockland stadium | 30122 | 1/10 | | 6 | 7 | adelaide rams | win | 20 | 10 | 13 apr | adelaide oval | 17633 | 1/10 | | 7 | 8 | penrith panthers | loss | 26 | 27 | 21 apr | penrith football stadium | 12648 | 1/10 | | 8 | 9 | canterbury bulldogs | win | 34 | 16 | 28 apr | anz stadium | 17921 | 1/10 | | 9 | 10 | auckland warriors | win | 34 | 18 | 4 may | mt smart stadium | 16471 | 1/10 | | 10 | 11 | north queensland cowboys | draw | 20 | 20 | 25 may | anz stadium | 14167 | 1/10 | | 11 | 12 | hunter mariners | loss | 6 | 24 | 30 may | topper stadium | 7124 | 1/10 | | 12 | 13 | cronulla sharks | loss | 4 | 32 | 30 jun | endeavour field | 12240 | 1/10 | | 13 | 14 | perth reds | win | 50 | 14 | 6 jul | anz stadium | 11806 | 1/10 | | 14 | 15 | canberra raiders | win | 19 | 4 | 14 jul | bruce stadium | 13067 | 1/10 | | 15 | 16 | penrith panthers | win | 54 | 12 | 10 aug | anz stadium | 13921 | 1/10 | | 16 | 17 | hunter mariners | win | 34 | 16 | 18 aug | anz stadium | 13830 | 1/10 | | 17 | 18 | canterbury bulldogs | win | 32 | 24 | 25 aug | belmore oval | 9781 | 1/10 | | 18 | semi final | cronulla sharks | win | 34 | 2 | 6 sep | stockland stadium | 26256 | none | | 19 | grand final | cronulla sharks | win | 26 | 8 | 20 sep | anz stadium | 58912 | none |

| | opp. | |---:|-------:| | 0 | 2 | | 1 | 12 | | 2 | 8 | | 3 | 12 | | 4 | 16 | | 5 | 20 | | 6 | 14 | | 7 | 12 | | 8 | 16 | | 9 | 8 |

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select count ( result ) where tournament = 'world series' col : year | tournament | venue | played | won | lost | tied | n/r | result row 1 : 1989-90 | world series | australia | 8 | 6 | 2 | 0 | 0 | won row 2 : 1990 | rothmans cup | new zealand | 5 | 5 | 0 | 0 | 0 | won row 3 : 1990 | austral-asia cup | sharjah | 4 | 3 | 1 | 0 | 0 | runner-up row 4 : 1990-91 | world series | australia | 10 | 9 | 1 | 0 | 0 | won row 5 : 1991 | v west indies | west indies | 5 | 4 | 1 | 0 | 0 | won row 6 : 1991-92 | world series | australia | 10 | 7 | 2 | 0 | 1 | won row 7 : 1992 | 5th world cup | aust/nz | 8 | 4 | 4 | 0 | 0 | eliminated row 8 : 1992 | v sri lanka | sri lanka | 3 | 1 | 2 | 0 | 0 | lost row 9 : 1992-93 | world series | australia | 10 | 5 | 4 | 1 | 0 | runner-up row 10 : 1993 | v new zealand | new zealand | 5 | 3 | 2 | 0 | 0 | won row 11 : 1993 | texaco trophy | england | 3 | 3 | 0 | 0 | 0 | won row 12 : 1993-94 | world series | australia | 11 | 7 | 4 | 0 | 0 | won row 13 : 1994 | v south africa | south africa | 8 | 4 | 4 | 0 | 0 | drawn row 14 : 1994 | austral-asia cup | sharjah | 3 | 2 | 1 | 0 | 0 | semi-final row 15 : 1994 | singer world series | sri lanka | 3 | 1 | 2 | 0 | 0 | eliminated row 16 : 1994 | wills triangular series | pakistan | 6 | 5 | 1 | 0 | 0 | won row 17 : 1994-95 | world series | australia | 4 | 3 | 1 | 0 | 0 | won row 18 : 1995 | nz centenary t'ment | new zealand | 4 | 3 | 1 | 0 | 0 | won row 19 : 1995 | v west indies | west indies | 5 | 1 | 4 | 0 | 0 | lost row 20 : 1995-96 | world series | australia | 10 | 7 | 3 | 0 | 0 | won row 21 : 1996 | 6th world cup | ind/pak/sl | 7 | 5 | 2 | 0 | 0 | runner-up row 22 : 1996 | singer world series | sri lanka | 4 | 2 | 2 | 0 | 0 | runner-up row 23 : 1996 | titan cup | india | 5 | 0 | 5 | 0 | 0 | eliminated row 24 : 1996-97 | cub series | australia | 8 | 3 | 5 | 0 | 0 | eliminated row 25 : 1997 | v south africa | south africa | 7 | 4 | 3 | 0 | 0 | won row 26 : 1997 | texaco trophy | england | 3 | 0 | 3 | 0 | 0 | lost row 27 : 1997-98 | cub series | australia | 11 | 5 | 6 | 0 | 0 | won row 28 : 1998 | v new zealand | australia | 4 | 2 | 2 | 0 | 0 | drawn row 29 : 1998 | pepsi triangular series | india | 5 | 3 | 2 | 0 | 0 | won row 30 : 1998 | coca-cola cup | sharjah | 5 | 4 | 1 | 0 | 0 | runner-up row 31 : 1998 | wills cup | bangladesh | 1 | 0 | 1 | 0 | 0 | eliminated row 32 : 1998 | v pakistan | pakistan | 3 | 3 | 0 | 0 | 0 | won row 33 : 1999 | cub series | australia | 12 | 9 | 3 | 0 | 0 | won row 34 : 1999 | v west indies | west indies | 7 | 3 | 3 | 1 | 0 | drawn row 35 : 1999 | 7th world cup | uk/ire/neth | 10 | 7 | 2 | 1 | 0 | won row 36 : 1999 | aiwa cup | sri lanka | 5 | 4 | 1 | 0 | 0 | runner-up row 37 : 1999 | v zimbabwe | zimbabwe | 3 | 3 | 0 | 0 | 0 | won row 38 : totals | none | none | 225 | 140 | 81 | 3 | 1 | none

col : count ( "result" ) row 1 : 7

select count ( result ) where tournament = 'world series' <table_name> : table \begin{tabular}{llllllllll} \toprule & year & tournament & venue & played & won & lost & tied & n/r & result \\ \midrule 0 & 1989-90 & world series & australia & 8 & 6 & 2 & 0 & 0 & won \\ 1 & 1990 & rothmans cup & new zealand & 5 & 5 & 0 & 0 & 0 & won \\ 2 & 1990 & austral-asia cup & sharjah & 4 & 3 & 1 & 0 & 0 & runner-up \\ 3 & 1990-91 & world series & australia & 10 & 9 & 1 & 0 & 0 & won \\ 4 & 1991 & v west indies & west indies & 5 & 4 & 1 & 0 & 0 & won \\ 5 & 1991-92 & world series & australia & 10 & 7 & 2 & 0 & 1 & won \\ 6 & 1992 & 5th world cup & aust/nz & 8 & 4 & 4 & 0 & 0 & eliminated \\ 7 & 1992 & v sri lanka & sri lanka & 3 & 1 & 2 & 0 & 0 & lost \\ 8 & 1992-93 & world series & australia & 10 & 5 & 4 & 1 & 0 & runner-up \\ 9 & 1993 & v new zealand & new zealand & 5 & 3 & 2 & 0 & 0 & won \\ 10 & 1993 & texaco trophy & england & 3 & 3 & 0 & 0 & 0 & won \\ 11 & 1993-94 & world series & australia & 11 & 7 & 4 & 0 & 0 & won \\ 12 & 1994 & v south africa & south africa & 8 & 4 & 4 & 0 & 0 & drawn \\ 13 & 1994 & austral-asia cup & sharjah & 3 & 2 & 1 & 0 & 0 & semi-final \\ 14 & 1994 & singer world series & sri lanka & 3 & 1 & 2 & 0 & 0 & eliminated \\ 15 & 1994 & wills triangular series & pakistan & 6 & 5 & 1 & 0 & 0 & won \\ 16 & 1994-95 & world series & australia & 4 & 3 & 1 & 0 & 0 & won \\ 17 & 1995 & nz centenary t'ment & new zealand & 4 & 3 & 1 & 0 & 0 & won \\ 18 & 1995 & v west indies & west indies & 5 & 1 & 4 & 0 & 0 & lost \\ 19 & 1995-96 & world series & australia & 10 & 7 & 3 & 0 & 0 & won \\ 20 & 1996 & 6th world cup & ind/pak/sl & 7 & 5 & 2 & 0 & 0 & runner-up \\ 21 & 1996 & singer world series & sri lanka & 4 & 2 & 2 & 0 & 0 & runner-up \\ 22 & 1996 & titan cup & india & 5 & 0 & 5 & 0 & 0 & eliminated \\ 23 & 1996-97 & cub series & australia & 8 & 3 & 5 & 0 & 0 & eliminated \\ 24 & 1997 & v south africa & south africa & 7 & 4 & 3 & 0 & 0 & won \\ 25 & 1997 & texaco trophy & england & 3 & 0 & 3 & 0 & 0 & lost \\ 26 & 1997-98 & cub series & australia & 11 & 5 & 6 & 0 & 0 & won \\ 27 & 1998 & v new zealand & australia & 4 & 2 & 2 & 0 & 0 & drawn \\ 28 & 1998 & pepsi triangular series & india & 5 & 3 & 2 & 0 & 0 & won \\ 29 & 1998 & coca-cola cup & sharjah & 5 & 4 & 1 & 0 & 0 & runner-up \\ 30 & 1998 & wills cup & bangladesh & 1 & 0 & 1 & 0 & 0 & eliminated \\ 31 & 1998 & v pakistan & pakistan & 3 & 3 & 0 & 0 & 0 & won \\ 32 & 1999 & cub series & australia & 12 & 9 & 3 & 0 & 0 & won \\ 33 & 1999 & v west indies & west indies & 7 & 3 & 3 & 1 & 0 & drawn \\ 34 & 1999 & 7th world cup & uk/ire/neth & 10 & 7 & 2 & 1 & 0 & won \\ 35 & 1999 & aiwa cup & sri lanka & 5 & 4 & 1 & 0 & 0 & runner-up \\ 36 & 1999 & v zimbabwe & zimbabwe & 3 & 3 & 0 & 0 & 0 & won \\ 37 & totals & none & none & 225 & 140 & 81 & 3 & 1 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "result" ) \\ \midrule 0 & 7 \\ \bottomrule \end{tabular}

select count ( result ) where tournament = 'world series' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>tournament</th> <th>venue</th> <th>played</th> <th>won</th> <th>lost</th> <th>tied</th> <th>n/r</th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1989-90</td> <td>world series</td> <td>australia</td> <td>8</td> <td>6</td> <td>2</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>1</th> <td>1990</td> <td>rothmans cup</td> <td>new zealand</td> <td>5</td> <td>5</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>2</th> <td>1990</td> <td>austral-asia cup</td> <td>sharjah</td> <td>4</td> <td>3</td> <td>1</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>3</th> <td>1990-91</td> <td>world series</td> <td>australia</td> <td>10</td> <td>9</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>4</th> <td>1991</td> <td>v west indies</td> <td>west indies</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>5</th> <td>1991-92</td> <td>world series</td> <td>australia</td> <td>10</td> <td>7</td> <td>2</td> <td>0</td> <td>1</td> <td>won</td> </tr> <tr> <th>6</th> <td>1992</td> <td>5th world cup</td> <td>aust/nz</td> <td>8</td> <td>4</td> <td>4</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>7</th> <td>1992</td> <td>v sri lanka</td> <td>sri lanka</td> <td>3</td> <td>1</td> <td>2</td> <td>0</td> <td>0</td> <td>lost</td> </tr> <tr> <th>8</th> <td>1992-93</td> <td>world series</td> <td>australia</td> <td>10</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>9</th> <td>1993</td> <td>v new zealand</td> <td>new zealand</td> <td>5</td> <td>3</td> <td>2</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>10</th> <td>1993</td> <td>texaco trophy</td> <td>england</td> <td>3</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>11</th> <td>1993-94</td> <td>world series</td> <td>australia</td> <td>11</td> <td>7</td> <td>4</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>12</th> <td>1994</td> <td>v south africa</td> <td>south africa</td> <td>8</td> <td>4</td> <td>4</td> <td>0</td> <td>0</td> <td>drawn</td> </tr> <tr> <th>13</th> <td>1994</td> <td>austral-asia cup</td> <td>sharjah</td> <td>3</td> <td>2</td> <td>1</td> <td>0</td> <td>0</td> <td>semi-final</td> </tr> <tr> <th>14</th> <td>1994</td> <td>singer world series</td> <td>sri lanka</td> <td>3</td> <td>1</td> <td>2</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>15</th> <td>1994</td> <td>wills triangular series</td> <td>pakistan</td> <td>6</td> <td>5</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>16</th> <td>1994-95</td> <td>world series</td> <td>australia</td> <td>4</td> <td>3</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>17</th> <td>1995</td> <td>nz centenary t'ment</td> <td>new zealand</td> <td>4</td> <td>3</td> <td>1</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>18</th> <td>1995</td> <td>v west indies</td> <td>west indies</td> <td>5</td> <td>1</td> <td>4</td> <td>0</td> <td>0</td> <td>lost</td> </tr> <tr> <th>19</th> <td>1995-96</td> <td>world series</td> <td>australia</td> <td>10</td> <td>7</td> <td>3</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>20</th> <td>1996</td> <td>6th world cup</td> <td>ind/pak/sl</td> <td>7</td> <td>5</td> <td>2</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>21</th> <td>1996</td> <td>singer world series</td> <td>sri lanka</td> <td>4</td> <td>2</td> <td>2</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>22</th> <td>1996</td> <td>titan cup</td> <td>india</td> <td>5</td> <td>0</td> <td>5</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>23</th> <td>1996-97</td> <td>cub series</td> <td>australia</td> <td>8</td> <td>3</td> <td>5</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>24</th> <td>1997</td> <td>v south africa</td> <td>south africa</td> <td>7</td> <td>4</td> <td>3</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>25</th> <td>1997</td> <td>texaco trophy</td> <td>england</td> <td>3</td> <td>0</td> <td>3</td> <td>0</td> <td>0</td> <td>lost</td> </tr> <tr> <th>26</th> <td>1997-98</td> <td>cub series</td> <td>australia</td> <td>11</td> <td>5</td> <td>6</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>27</th> <td>1998</td> <td>v new zealand</td> <td>australia</td> <td>4</td> <td>2</td> <td>2</td> <td>0</td> <td>0</td> <td>drawn</td> </tr> <tr> <th>28</th> <td>1998</td> <td>pepsi triangular series</td> <td>india</td> <td>5</td> <td>3</td> <td>2</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>29</th> <td>1998</td> <td>coca-cola cup</td> <td>sharjah</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>30</th> <td>1998</td> <td>wills cup</td> <td>bangladesh</td> <td>1</td> <td>0</td> <td>1</td> <td>0</td> <td>0</td> <td>eliminated</td> </tr> <tr> <th>31</th> <td>1998</td> <td>v pakistan</td> <td>pakistan</td> <td>3</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>32</th> <td>1999</td> <td>cub series</td> <td>australia</td> <td>12</td> <td>9</td> <td>3</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>33</th> <td>1999</td> <td>v west indies</td> <td>west indies</td> <td>7</td> <td>3</td> <td>3</td> <td>1</td> <td>0</td> <td>drawn</td> </tr> <tr> <th>34</th> <td>1999</td> <td>7th world cup</td> <td>uk/ire/neth</td> <td>10</td> <td>7</td> <td>2</td> <td>1</td> <td>0</td> <td>won</td> </tr> <tr> <th>35</th> <td>1999</td> <td>aiwa cup</td> <td>sri lanka</td> <td>5</td> <td>4</td> <td>1</td> <td>0</td> <td>0</td> <td>runner-up</td> </tr> <tr> <th>36</th> <td>1999</td> <td>v zimbabwe</td> <td>zimbabwe</td> <td>3</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>won</td> </tr> <tr> <th>37</th> <td>totals</td> <td>none</td> <td>none</td> <td>225</td> <td>140</td> <td>81</td> <td>3</td> <td>1</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "result" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7</td> </tr> </tbody> </table>

select count ( result ) where tournament = 'world series' <table_name> : table | | year | tournament | venue | played | won | lost | tied | n/r | result | |---:|:--------|:------------------------|:-------------|---------:|------:|-------:|-------:|------:|:-----------| | 0 | 1989-90 | world series | australia | 8 | 6 | 2 | 0 | 0 | won | | 1 | 1990 | rothmans cup | new zealand | 5 | 5 | 0 | 0 | 0 | won | | 2 | 1990 | austral-asia cup | sharjah | 4 | 3 | 1 | 0 | 0 | runner-up | | 3 | 1990-91 | world series | australia | 10 | 9 | 1 | 0 | 0 | won | | 4 | 1991 | v west indies | west indies | 5 | 4 | 1 | 0 | 0 | won | | 5 | 1991-92 | world series | australia | 10 | 7 | 2 | 0 | 1 | won | | 6 | 1992 | 5th world cup | aust/nz | 8 | 4 | 4 | 0 | 0 | eliminated | | 7 | 1992 | v sri lanka | sri lanka | 3 | 1 | 2 | 0 | 0 | lost | | 8 | 1992-93 | world series | australia | 10 | 5 | 4 | 1 | 0 | runner-up | | 9 | 1993 | v new zealand | new zealand | 5 | 3 | 2 | 0 | 0 | won | | 10 | 1993 | texaco trophy | england | 3 | 3 | 0 | 0 | 0 | won | | 11 | 1993-94 | world series | australia | 11 | 7 | 4 | 0 | 0 | won | | 12 | 1994 | v south africa | south africa | 8 | 4 | 4 | 0 | 0 | drawn | | 13 | 1994 | austral-asia cup | sharjah | 3 | 2 | 1 | 0 | 0 | semi-final | | 14 | 1994 | singer world series | sri lanka | 3 | 1 | 2 | 0 | 0 | eliminated | | 15 | 1994 | wills triangular series | pakistan | 6 | 5 | 1 | 0 | 0 | won | | 16 | 1994-95 | world series | australia | 4 | 3 | 1 | 0 | 0 | won | | 17 | 1995 | nz centenary t'ment | new zealand | 4 | 3 | 1 | 0 | 0 | won | | 18 | 1995 | v west indies | west indies | 5 | 1 | 4 | 0 | 0 | lost | | 19 | 1995-96 | world series | australia | 10 | 7 | 3 | 0 | 0 | won | | 20 | 1996 | 6th world cup | ind/pak/sl | 7 | 5 | 2 | 0 | 0 | runner-up | | 21 | 1996 | singer world series | sri lanka | 4 | 2 | 2 | 0 | 0 | runner-up | | 22 | 1996 | titan cup | india | 5 | 0 | 5 | 0 | 0 | eliminated | | 23 | 1996-97 | cub series | australia | 8 | 3 | 5 | 0 | 0 | eliminated | | 24 | 1997 | v south africa | south africa | 7 | 4 | 3 | 0 | 0 | won | | 25 | 1997 | texaco trophy | england | 3 | 0 | 3 | 0 | 0 | lost | | 26 | 1997-98 | cub series | australia | 11 | 5 | 6 | 0 | 0 | won | | 27 | 1998 | v new zealand | australia | 4 | 2 | 2 | 0 | 0 | drawn | | 28 | 1998 | pepsi triangular series | india | 5 | 3 | 2 | 0 | 0 | won | | 29 | 1998 | coca-cola cup | sharjah | 5 | 4 | 1 | 0 | 0 | runner-up | | 30 | 1998 | wills cup | bangladesh | 1 | 0 | 1 | 0 | 0 | eliminated | | 31 | 1998 | v pakistan | pakistan | 3 | 3 | 0 | 0 | 0 | won | | 32 | 1999 | cub series | australia | 12 | 9 | 3 | 0 | 0 | won | | 33 | 1999 | v west indies | west indies | 7 | 3 | 3 | 1 | 0 | drawn | | 34 | 1999 | 7th world cup | uk/ire/neth | 10 | 7 | 2 | 1 | 0 | won | | 35 | 1999 | aiwa cup | sri lanka | 5 | 4 | 1 | 0 | 0 | runner-up | | 36 | 1999 | v zimbabwe | zimbabwe | 3 | 3 | 0 | 0 | 0 | won | | 37 | totals | none | none | 225 | 140 | 81 | 3 | 1 | none |

| | count ( "result" ) | |---:|---------------------:| | 0 | 7 |

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col : length row 1 : 2:20 row 2 : 4:00

select length where singer(s) = 'lata mangeshkar' <table_name> : table \begin{tabular}{llllll} \toprule & # & title & singer(s) & lyricist & length \\ \midrule 0 & 1 & "dil ka haal sune dilwaala" & manna dey & shailendra & 5:36 \\ 1 & 2 & "ichak dana beechak dana" & mukesh, lata mangeshkar & hasrat jaipuri & 5:08 \\ 2 & 3 & "mera juta hai japani" & mukesh & shailendra & 4:33 \\ 3 & 4 & "mudh mudh ke na dekh" & lata mangeshkar, manna dey & shailendra & 6:34 \\ 4 & 5 & "o janewale" & lata mangeshkar & hasrat jaipuri & 2:20 \\ 5 & 6 & "pyar hua iqrar hua" & lata mangeshkar, manna dey & shailendra & 4:22 \\ 6 & 7 & "ramaiya vastavaiya" & mohammed rafi, lata mangeshkar, mukesh & shailendra & 6:10 \\ 7 & 8 & "sham gayi raat aayi" & lata mangeshkar & hasrat jaipuri & 4:00 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & length \\ \midrule 0 & 2:20 \\ 1 & 4:00 \\ \bottomrule \end{tabular}

select length where singer(s) = 'lata mangeshkar' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>title</th> <th>singer(s)</th> <th>lyricist</th> <th>length</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>"dil ka haal sune dilwaala"</td> <td>manna dey</td> <td>shailendra</td> <td>5:36</td> </tr> <tr> <th>1</th> <td>2</td> <td>"ichak dana beechak dana"</td> <td>mukesh, lata mangeshkar</td> <td>hasrat jaipuri</td> <td>5:08</td> </tr> <tr> <th>2</th> <td>3</td> <td>"mera juta hai japani"</td> <td>mukesh</td> <td>shailendra</td> <td>4:33</td> </tr> <tr> <th>3</th> <td>4</td> <td>"mudh mudh ke na dekh"</td> <td>lata mangeshkar, manna dey</td> <td>shailendra</td> <td>6:34</td> </tr> <tr> <th>4</th> <td>5</td> <td>"o janewale"</td> <td>lata mangeshkar</td> <td>hasrat jaipuri</td> <td>2:20</td> </tr> <tr> <th>5</th> <td>6</td> <td>"pyar hua iqrar hua"</td> <td>lata mangeshkar, manna dey</td> <td>shailendra</td> <td>4:22</td> </tr> <tr> <th>6</th> <td>7</td> <td>"ramaiya vastavaiya"</td> <td>mohammed rafi, lata mangeshkar, mukesh</td> <td>shailendra</td> <td>6:10</td> </tr> <tr> <th>7</th> <td>8</td> <td>"sham gayi raat aayi"</td> <td>lata mangeshkar</td> <td>hasrat jaipuri</td> <td>4:00</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>length</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2:20</td> </tr> <tr> <th>1</th> <td>4:00</td> </tr> </tbody> </table>

select length where singer(s) = 'lata mangeshkar' <table_name> : table | | # | title | singer(s) | lyricist | length | |---:|----:|:----------------------------|:---------------------------------------|:---------------|:---------| | 0 | 1 | "dil ka haal sune dilwaala" | manna dey | shailendra | 5:36 | | 1 | 2 | "ichak dana beechak dana" | mukesh, lata mangeshkar | hasrat jaipuri | 5:08 | | 2 | 3 | "mera juta hai japani" | mukesh | shailendra | 4:33 | | 3 | 4 | "mudh mudh ke na dekh" | lata mangeshkar, manna dey | shailendra | 6:34 | | 4 | 5 | "o janewale" | lata mangeshkar | hasrat jaipuri | 2:20 | | 5 | 6 | "pyar hua iqrar hua" | lata mangeshkar, manna dey | shailendra | 4:22 | | 6 | 7 | "ramaiya vastavaiya" | mohammed rafi, lata mangeshkar, mukesh | shailendra | 6:10 | | 7 | 8 | "sham gayi raat aayi" | lata mangeshkar | hasrat jaipuri | 4:00 |

| | length | |---:|:---------| | 0 | 2:20 | | 1 | 4:00 |

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select count ( a.g. ) where kw < 1605 col : transmitter | kw | bbca | bbcb | d3&4 | sdn | arqa | arqb | pol. | a.g. row 1 : allenheads | 0.002 | 27 | 21 | 24 | none | none | none | v | a k row 2 : alston | 0.08 | 39 | 45 | 42 | none | none | none | v | b e k row 3 : bellingham | 0.01 | 27 | 21 | 24 | none | none | none | v | a k row 4 : blaydon burn | 0.002 | 44 | 47 | 41 | none | none | none | v | b e k row 5 : byrness | 0.01 | 27 | 21 | 24 | none | none | none | v | a k row 6 : catton beacon | 0.028 | 40 | 46 | 43 | none | none | none | v | b e k row 7 : durham | 0.003 | 41 | 47 | 44 | none | none | none | v | b e k row 8 : esh | 0.0024 | 39 | 45 | 42 | none | none | none | v | b e k row 9 : felling | 0.002 | 40 | 43 | 46 | none | none | none | v | b e k row 10 : fenham | 0.4 | 27 | 21 | 24 | 25 | 22 | 28 | v | a k row 11 : haltwhistle | 0.4 | 59 | 55 | 62- | none | none | none | v | c/d e row 12 : haydon bridge | 0.02 | 44 | 41 | 47 | none | none | none | v | b e k row 13 : hedleyhope | 0.004 | 41 | 47 | 44 | none | none | none | v | b e k row 14 : humshaugh | 0.0118 | 39 | 45 | 42 | none | none | none | v | b e k row 15 : ireshopeburn | 0.0022 | 55 | 59 | 50 | none | none | none | v | c/d e row 16 : kielder | 0.0054 | 26 | 23 | 29 | none | none | none | v | a k row 17 : morpeth | 0.0088 | 22 | 28 | 25 | none | none | none | v | a k row 18 : newton | 0.4 | 26 | 23 | 29 | none | none | none | v | a k row 19 : seaham | 0.059 | 44 | 47 | 46 | none | none | none | v | b e k row 20 : shotleyfield | 0.04 | 22 | 28 | 25 | none | none | none | v | a k row 21 : staithes | 0.002 | 52 | 51 | 48 | none | none | none | v | b c/d e row 22 : sunderland | 0.006 | 52 | 51 | 48 | none | none | none | v | b c/d e row 23 : wall | 0.0042 | 52 | 51 | 48 | none | none | none | h | b c/d e row 24 : weardale | 0.2 | 44 | 41 | 47 | none | none | none | v | b e k row 25 : whitaside | 0.0025 | 44 | 41 | 47 | none | none | none | v | b e k

col : count ( "a.g." ) row 1 : 25

select count ( a.g. ) where kw < 1605 <table_name> : table \begin{tabular}{lllllllllll} \toprule & transmitter & kw & bbca & bbcb & d3&4 & sdn & arqa & arqb & pol. & a.g. \\ \midrule 0 & allenheads & 0.002 & 27 & 21 & 24 & none & none & none & v & a k \\ 1 & alston & 0.08 & 39 & 45 & 42 & none & none & none & v & b e k \\ 2 & bellingham & 0.01 & 27 & 21 & 24 & none & none & none & v & a k \\ 3 & blaydon burn & 0.002 & 44 & 47 & 41 & none & none & none & v & b e k \\ 4 & byrness & 0.01 & 27 & 21 & 24 & none & none & none & v & a k \\ 5 & catton beacon & 0.028 & 40 & 46 & 43 & none & none & none & v & b e k \\ 6 & durham & 0.003 & 41 & 47 & 44 & none & none & none & v & b e k \\ 7 & esh & 0.0024 & 39 & 45 & 42 & none & none & none & v & b e k \\ 8 & felling & 0.002 & 40 & 43 & 46 & none & none & none & v & b e k \\ 9 & fenham & 0.4 & 27 & 21 & 24 & 25 & 22 & 28 & v & a k \\ 10 & haltwhistle & 0.4 & 59 & 55 & 62- & none & none & none & v & c/d e \\ 11 & haydon bridge & 0.02 & 44 & 41 & 47 & none & none & none & v & b e k \\ 12 & hedleyhope & 0.004 & 41 & 47 & 44 & none & none & none & v & b e k \\ 13 & humshaugh & 0.0118 & 39 & 45 & 42 & none & none & none & v & b e k \\ 14 & ireshopeburn & 0.0022 & 55 & 59 & 50 & none & none & none & v & c/d e \\ 15 & kielder & 0.0054 & 26 & 23 & 29 & none & none & none & v & a k \\ 16 & morpeth & 0.0088 & 22 & 28 & 25 & none & none & none & v & a k \\ 17 & newton & 0.4 & 26 & 23 & 29 & none & none & none & v & a k \\ 18 & seaham & 0.059 & 44 & 47 & 46 & none & none & none & v & b e k \\ 19 & shotleyfield & 0.04 & 22 & 28 & 25 & none & none & none & v & a k \\ 20 & staithes & 0.002 & 52 & 51 & 48 & none & none & none & v & b c/d e \\ 21 & sunderland & 0.006 & 52 & 51 & 48 & none & none & none & v & b c/d e \\ 22 & wall & 0.0042 & 52 & 51 & 48 & none & none & none & h & b c/d e \\ 23 & weardale & 0.2 & 44 & 41 & 47 & none & none & none & v & b e k \\ 24 & whitaside & 0.0025 & 44 & 41 & 47 & none & none & none & v & b e k \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "a.g." ) \\ \midrule 0 & 25 \\ \bottomrule \end{tabular}

select count ( a.g. ) where kw < 1605 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>transmitter</th> <th>kw</th> <th>bbca</th> <th>bbcb</th> <th>d3&4</th> <th>sdn</th> <th>arqa</th> <th>arqb</th> <th>pol.</th> <th>a.g.</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>allenheads</td> <td>0.002</td> <td>27</td> <td>21</td> <td>24</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>1</th> <td>alston</td> <td>0.08</td> <td>39</td> <td>45</td> <td>42</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>2</th> <td>bellingham</td> <td>0.01</td> <td>27</td> <td>21</td> <td>24</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>3</th> <td>blaydon burn</td> <td>0.002</td> <td>44</td> <td>47</td> <td>41</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>4</th> <td>byrness</td> <td>0.01</td> <td>27</td> <td>21</td> <td>24</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>5</th> <td>catton beacon</td> <td>0.028</td> <td>40</td> <td>46</td> <td>43</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>6</th> <td>durham</td> <td>0.003</td> <td>41</td> <td>47</td> <td>44</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>7</th> <td>esh</td> <td>0.0024</td> <td>39</td> <td>45</td> <td>42</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>8</th> <td>felling</td> <td>0.002</td> <td>40</td> <td>43</td> <td>46</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>9</th> <td>fenham</td> <td>0.4</td> <td>27</td> <td>21</td> <td>24</td> <td>25</td> <td>22</td> <td>28</td> <td>v</td> <td>a k</td> </tr> <tr> <th>10</th> <td>haltwhistle</td> <td>0.4</td> <td>59</td> <td>55</td> <td>62-</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>c/d e</td> </tr> <tr> <th>11</th> <td>haydon bridge</td> <td>0.02</td> <td>44</td> <td>41</td> <td>47</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>12</th> <td>hedleyhope</td> <td>0.004</td> <td>41</td> <td>47</td> <td>44</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>13</th> <td>humshaugh</td> <td>0.0118</td> <td>39</td> <td>45</td> <td>42</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>14</th> <td>ireshopeburn</td> <td>0.0022</td> <td>55</td> <td>59</td> <td>50</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>c/d e</td> </tr> <tr> <th>15</th> <td>kielder</td> <td>0.0054</td> <td>26</td> <td>23</td> <td>29</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>16</th> <td>morpeth</td> <td>0.0088</td> <td>22</td> <td>28</td> <td>25</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>17</th> <td>newton</td> <td>0.4</td> <td>26</td> <td>23</td> <td>29</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>18</th> <td>seaham</td> <td>0.059</td> <td>44</td> <td>47</td> <td>46</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>19</th> <td>shotleyfield</td> <td>0.04</td> <td>22</td> <td>28</td> <td>25</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>a k</td> </tr> <tr> <th>20</th> <td>staithes</td> <td>0.002</td> <td>52</td> <td>51</td> <td>48</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b c/d e</td> </tr> <tr> <th>21</th> <td>sunderland</td> <td>0.006</td> <td>52</td> <td>51</td> <td>48</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b c/d e</td> </tr> <tr> <th>22</th> <td>wall</td> <td>0.0042</td> <td>52</td> <td>51</td> <td>48</td> <td>none</td> <td>none</td> <td>none</td> <td>h</td> <td>b c/d e</td> </tr> <tr> <th>23</th> <td>weardale</td> <td>0.2</td> <td>44</td> <td>41</td> <td>47</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> <tr> <th>24</th> <td>whitaside</td> <td>0.0025</td> <td>44</td> <td>41</td> <td>47</td> <td>none</td> <td>none</td> <td>none</td> <td>v</td> <td>b e k</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "a.g." )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>25</td> </tr> </tbody> </table>

select count ( a.g. ) where kw < 1605 <table_name> : table | | transmitter | kw | bbca | bbcb | d3&4 | sdn | arqa | arqb | pol. | a.g. | |---:|:--------------|-------:|-------:|-------:|:-------|:------|:-------|:-------|:-------|:--------| | 0 | allenheads | 0.002 | 27 | 21 | 24 | none | none | none | v | a k | | 1 | alston | 0.08 | 39 | 45 | 42 | none | none | none | v | b e k | | 2 | bellingham | 0.01 | 27 | 21 | 24 | none | none | none | v | a k | | 3 | blaydon burn | 0.002 | 44 | 47 | 41 | none | none | none | v | b e k | | 4 | byrness | 0.01 | 27 | 21 | 24 | none | none | none | v | a k | | 5 | catton beacon | 0.028 | 40 | 46 | 43 | none | none | none | v | b e k | | 6 | durham | 0.003 | 41 | 47 | 44 | none | none | none | v | b e k | | 7 | esh | 0.0024 | 39 | 45 | 42 | none | none | none | v | b e k | | 8 | felling | 0.002 | 40 | 43 | 46 | none | none | none | v | b e k | | 9 | fenham | 0.4 | 27 | 21 | 24 | 25 | 22 | 28 | v | a k | | 10 | haltwhistle | 0.4 | 59 | 55 | 62- | none | none | none | v | c/d e | | 11 | haydon bridge | 0.02 | 44 | 41 | 47 | none | none | none | v | b e k | | 12 | hedleyhope | 0.004 | 41 | 47 | 44 | none | none | none | v | b e k | | 13 | humshaugh | 0.0118 | 39 | 45 | 42 | none | none | none | v | b e k | | 14 | ireshopeburn | 0.0022 | 55 | 59 | 50 | none | none | none | v | c/d e | | 15 | kielder | 0.0054 | 26 | 23 | 29 | none | none | none | v | a k | | 16 | morpeth | 0.0088 | 22 | 28 | 25 | none | none | none | v | a k | | 17 | newton | 0.4 | 26 | 23 | 29 | none | none | none | v | a k | | 18 | seaham | 0.059 | 44 | 47 | 46 | none | none | none | v | b e k | | 19 | shotleyfield | 0.04 | 22 | 28 | 25 | none | none | none | v | a k | | 20 | staithes | 0.002 | 52 | 51 | 48 | none | none | none | v | b c/d e | | 21 | sunderland | 0.006 | 52 | 51 | 48 | none | none | none | v | b c/d e | | 22 | wall | 0.0042 | 52 | 51 | 48 | none | none | none | h | b c/d e | | 23 | weardale | 0.2 | 44 | 41 | 47 | none | none | none | v | b e k | | 24 | whitaside | 0.0025 | 44 | 41 | 47 | none | none | none | v | b e k |

| | count ( "a.g." ) | |---:|-------------------:| | 0 | 25 |

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select competition where games = 19 col : season | club | competition | games | goals row 1 : 2002/03 | raec mons | jupiler league | 19 | 0 row 2 : 2003/04 | raec mons | jupiler league | 23 | 0 row 3 : 2004/05 | ksv roeselare | belgian second division | 29 | 1 row 4 : 2005/06 | ksv roeselare | jupiler league | 26 | 0 row 5 : 2006/07 | ksv roeselare | jupiler league | 29 | 1 row 6 : 2007/08 | ksv roeselare | jupiler league | 25 | 0 row 7 : 2008/09 | excelsior mouscron | jupiler league | 31 | 1 row 8 : 2009/10 | excelsior mouscron | jupiler league | 14 | 1 row 9 : 2009/10 | gyori eto fc | soproni liga | 1 | 0 row 10 : 2010/11 | kortrijk | jupiler league | 0 | 0 row 11 : none | none | total | 278 | 4

col : competition row 1 : jupiler league

select competition where games = 19 <table_name> : table \begin{tabular}{llllll} \toprule & season & club & competition & games & goals \\ \midrule 0 & 2002/03 & raec mons & jupiler league & 19 & 0 \\ 1 & 2003/04 & raec mons & jupiler league & 23 & 0 \\ 2 & 2004/05 & ksv roeselare & belgian second division & 29 & 1 \\ 3 & 2005/06 & ksv roeselare & jupiler league & 26 & 0 \\ 4 & 2006/07 & ksv roeselare & jupiler league & 29 & 1 \\ 5 & 2007/08 & ksv roeselare & jupiler league & 25 & 0 \\ 6 & 2008/09 & excelsior mouscron & jupiler league & 31 & 1 \\ 7 & 2009/10 & excelsior mouscron & jupiler league & 14 & 1 \\ 8 & 2009/10 & gyori eto fc & soproni liga & 1 & 0 \\ 9 & 2010/11 & kortrijk & jupiler league & 0 & 0 \\ 10 & none & none & total & 278 & 4 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & competition \\ \midrule 0 & jupiler league \\ \bottomrule \end{tabular}

select competition where games = 19 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>club</th> <th>competition</th> <th>games</th> <th>goals</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2002/03</td> <td>raec mons</td> <td>jupiler league</td> <td>19</td> <td>0</td> </tr> <tr> <th>1</th> <td>2003/04</td> <td>raec mons</td> <td>jupiler league</td> <td>23</td> <td>0</td> </tr> <tr> <th>2</th> <td>2004/05</td> <td>ksv roeselare</td> <td>belgian second division</td> <td>29</td> <td>1</td> </tr> <tr> <th>3</th> <td>2005/06</td> <td>ksv roeselare</td> <td>jupiler league</td> <td>26</td> <td>0</td> </tr> <tr> <th>4</th> <td>2006/07</td> <td>ksv roeselare</td> <td>jupiler league</td> <td>29</td> <td>1</td> </tr> <tr> <th>5</th> <td>2007/08</td> <td>ksv roeselare</td> <td>jupiler league</td> <td>25</td> <td>0</td> </tr> <tr> <th>6</th> <td>2008/09</td> <td>excelsior mouscron</td> <td>jupiler league</td> <td>31</td> <td>1</td> </tr> <tr> <th>7</th> <td>2009/10</td> <td>excelsior mouscron</td> <td>jupiler league</td> <td>14</td> <td>1</td> </tr> <tr> <th>8</th> <td>2009/10</td> <td>gyori eto fc</td> <td>soproni liga</td> <td>1</td> <td>0</td> </tr> <tr> <th>9</th> <td>2010/11</td> <td>kortrijk</td> <td>jupiler league</td> <td>0</td> <td>0</td> </tr> <tr> <th>10</th> <td>none</td> <td>none</td> <td>total</td> <td>278</td> <td>4</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>competition</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>jupiler league</td> </tr> </tbody> </table>

select competition where games = 19 <table_name> : table | | season | club | competition | games | goals | |---:|:---------|:-------------------|:------------------------|--------:|--------:| | 0 | 2002/03 | raec mons | jupiler league | 19 | 0 | | 1 | 2003/04 | raec mons | jupiler league | 23 | 0 | | 2 | 2004/05 | ksv roeselare | belgian second division | 29 | 1 | | 3 | 2005/06 | ksv roeselare | jupiler league | 26 | 0 | | 4 | 2006/07 | ksv roeselare | jupiler league | 29 | 1 | | 5 | 2007/08 | ksv roeselare | jupiler league | 25 | 0 | | 6 | 2008/09 | excelsior mouscron | jupiler league | 31 | 1 | | 7 | 2009/10 | excelsior mouscron | jupiler league | 14 | 1 | | 8 | 2009/10 | gyori eto fc | soproni liga | 1 | 0 | | 9 | 2010/11 | kortrijk | jupiler league | 0 | 0 | | 10 | none | none | total | 278 | 4 |

| | competition | |---:|:---------------| | 0 | jupiler league |

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col : count ( "competition" ) row 1 : 2

select count ( competition ) where year = 2002 <table_name> : table \begin{tabular}{llllll} \toprule & year & competition & venue & position & event \\ \midrule 0 & 1997 & world indoor championships & paris, france & 5th & 60 m hurdles \\ 1 & 1997 & usa outdoor championships & indianapolis, united states & 1st & 100 m hurdles \\ 2 & 1998 & grand prix final & moscow, russia & 2nd & 100 m hurdles \\ 3 & 1998 & usa indoor championships & none & 1st & 60 m hurdles \\ 4 & 1999 & world indoor championships & maebashi, japan & 6th & 60 m hurdles \\ 5 & 2000 & olympic games & sydney, australia & 3rd & 100 m hurdles \\ 6 & 2000 & grand prix final & doha, qatar & 4th & 100 m hurdles \\ 7 & 2002 & grand prix final & paris, france & 7th & 100 m hurdles \\ 8 & 2002 & usa indoor championships & none & 1st & 60 m hurdles \\ 9 & 2003 & world indoor championships & birmingham, england & 3rd & 60 m hurdles \\ 10 & 2003 & world athletics final & monaco & 6th & 100 m hurdles \\ 11 & 2004 & olympic games & athens, greece & 3rd & 100 m hurdles \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "competition" ) \\ \midrule 0 & 2 \\ \bottomrule \end{tabular}

select count ( competition ) where year = 2002 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1997</td> <td>world indoor championships</td> <td>paris, france</td> <td>5th</td> <td>60 m hurdles</td> </tr> <tr> <th>1</th> <td>1997</td> <td>usa outdoor championships</td> <td>indianapolis, united states</td> <td>1st</td> <td>100 m hurdles</td> </tr> <tr> <th>2</th> <td>1998</td> <td>grand prix final</td> <td>moscow, russia</td> <td>2nd</td> <td>100 m hurdles</td> </tr> <tr> <th>3</th> <td>1998</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>4</th> <td>1999</td> <td>world indoor championships</td> <td>maebashi, japan</td> <td>6th</td> <td>60 m hurdles</td> </tr> <tr> <th>5</th> <td>2000</td> <td>olympic games</td> <td>sydney, australia</td> <td>3rd</td> <td>100 m hurdles</td> </tr> <tr> <th>6</th> <td>2000</td> <td>grand prix final</td> <td>doha, qatar</td> <td>4th</td> <td>100 m hurdles</td> </tr> <tr> <th>7</th> <td>2002</td> <td>grand prix final</td> <td>paris, france</td> <td>7th</td> <td>100 m hurdles</td> </tr> <tr> <th>8</th> <td>2002</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>9</th> <td>2003</td> <td>world indoor championships</td> <td>birmingham, england</td> <td>3rd</td> <td>60 m hurdles</td> </tr> <tr> <th>10</th> <td>2003</td> <td>world athletics final</td> <td>monaco</td> <td>6th</td> <td>100 m hurdles</td> </tr> <tr> <th>11</th> <td>2004</td> <td>olympic games</td> <td>athens, greece</td> <td>3rd</td> <td>100 m hurdles</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "competition" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> </tbody> </table>

select count ( competition ) where year = 2002 <table_name> : table | | year | competition | venue | position | event | |---:|-------:|:---------------------------|:----------------------------|:-----------|:--------------| | 0 | 1997 | world indoor championships | paris, france | 5th | 60 m hurdles | | 1 | 1997 | usa outdoor championships | indianapolis, united states | 1st | 100 m hurdles | | 2 | 1998 | grand prix final | moscow, russia | 2nd | 100 m hurdles | | 3 | 1998 | usa indoor championships | none | 1st | 60 m hurdles | | 4 | 1999 | world indoor championships | maebashi, japan | 6th | 60 m hurdles | | 5 | 2000 | olympic games | sydney, australia | 3rd | 100 m hurdles | | 6 | 2000 | grand prix final | doha, qatar | 4th | 100 m hurdles | | 7 | 2002 | grand prix final | paris, france | 7th | 100 m hurdles | | 8 | 2002 | usa indoor championships | none | 1st | 60 m hurdles | | 9 | 2003 | world indoor championships | birmingham, england | 3rd | 60 m hurdles | | 10 | 2003 | world athletics final | monaco | 6th | 100 m hurdles | | 11 | 2004 | olympic games | athens, greece | 3rd | 100 m hurdles |

| | count ( "competition" ) | |---:|--------------------------:| | 0 | 2 |

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col : no. row 1 : 1 row 2 : 2 row 3 : 3 row 4 : 4 row 5 : 5 row 6 : 6 row 7 : 7 row 8 : 8 row 9 : 9

select no. where outcome = 'runner-up' <table_name> : table \begin{tabular}{lllllllll} \toprule & outcome & no. & date & tournament & surface & partner & opponents & score \\ \midrule 0 & winner & 1 & 2004-04-18 00:00:00 & jackson, united states & clay & alisa kleybanova & cory ann avants kristen schlukebir & 6-2, 6-3 \\ 1 & runner-up & 1 & 2004-09-26 00:00:00 & albuquerque, united states & hard & maria emilia salerni & maureen drake carly gullickson & 3-6, 6-7(6-8) \\ 2 & winner & 2 & 2005-03-27 00:00:00 & redding, united states & hard & yulia beygelzimer & leanne baker francesca lubiani & 6-4, 6-7(1-7), 6-3 \\ 3 & runner-up & 2 & 2005-05-08 00:00:00 & raleigh, united states & clay & maria fernanda alves & ashley harkleroad lindsay lee-waters & 2-6, 6-0, 3-6 \\ 4 & runner-up & 3 & 2006-03-19 00:00:00 & orange, united states & hard & lilia osterloh & kateryna bondarenko alona bondarenko & 2-6, 4-6 \\ 5 & winner & 3 & 2006-11-12 00:00:00 & pittsburgh, united states & hard (i) & alisa kleybanova & ashley harkleroad galina voskoboeva & 6-4, 5-7, 6-1 \\ 6 & runner-up & 4 & 2007-02-11 00:00:00 & midland, united states & hard (i) & maureen drake & laura granville abigail spears & 4-6, 6-3, 3-6 \\ 7 & runner-up & 5 & 2007-07-07 00:00:00 & southlake, united states & hard & valerie tetreault & surina de beer kim grant & 6-4, 4-6, 4-6 \\ 8 & winner & 4 & 2007-07-22 00:00:00 & hamilton, canada & clay & surina de beer & michaela johansson paula zabala & walkover \\ 9 & winner & 5 & 2007-08-04 00:00:00 & vancouver, canada & hard & marie-eve pelletier & soledad esperon agustina lepore & 6-4, 6-4 \\ 10 & winner & 6 & 2007-10-21 00:00:00 & lawrenceville, united states & hard & alisa kleybanova & leanne baker julie ditty & 6-2, 6-0 \\ 11 & winner & 7 & 2007-11-12 00:00:00 & pittsburgh, united states & hard (i) & alisa kleybanova & raquel kops-jones abigail spears & 6-4, 4-6, [10-6] \\ 12 & runner-up & 6 & 2008-04-27 00:00:00 & dothan, united states & clay & maria fernanda alves & tetiana luzhanska michaela pastikova & 1-6, 3-6 \\ 13 & winner & 8 & 2008-10-18 00:00:00 & toronto, canada & hard (i) & marie-eve pelletier & nikola frankova carmen klaschka & 6-4, 6-2 \\ 14 & runner-up & 7 & 2009-09-27 00:00:00 & saguenay, canada & hard (i) & rebecca marino & sofia arvidsson severine bremond beltrame & 3-6, 1-6 \\ 15 & runner-up & 8 & 2013-04-13 00:00:00 & poza rica, mexico & hard & olga savchuk & maria fernanda alvarez teran maria fernanda alves & 2-6, 3-6 \\ 16 & runner-up & 9 & 2013-05-18 00:00:00 & saint-gaudens, france & clay & kurumi nara & julia glushko paula ormaechea & 5-7, 6-7(11-13) \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & no. \\ \midrule 0 & 1 \\ 1 & 2 \\ 2 & 3 \\ 3 & 4 \\ 4 & 5 \\ 5 & 6 \\ 6 & 7 \\ 7 & 8 \\ 8 & 9 \\ \bottomrule \end{tabular}

select no. where outcome = 'runner-up' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>outcome</th> <th>no.</th> <th>date</th> <th>tournament</th> <th>surface</th> <th>partner</th> <th>opponents</th> <th>score</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>winner</td> <td>1</td> <td>2004-04-18 00:00:00</td> <td>jackson, united states</td> <td>clay</td> <td>alisa kleybanova</td> <td>cory ann avants kristen schlukebir</td> <td>6-2, 6-3</td> </tr> <tr> <th>1</th> <td>runner-up</td> <td>1</td> <td>2004-09-26 00:00:00</td> <td>albuquerque, united states</td> <td>hard</td> <td>maria emilia salerni</td> <td>maureen drake carly gullickson</td> <td>3-6, 6-7(6-8)</td> </tr> <tr> <th>2</th> <td>winner</td> <td>2</td> <td>2005-03-27 00:00:00</td> <td>redding, united states</td> <td>hard</td> <td>yulia beygelzimer</td> <td>leanne baker francesca lubiani</td> <td>6-4, 6-7(1-7), 6-3</td> </tr> <tr> <th>3</th> <td>runner-up</td> <td>2</td> <td>2005-05-08 00:00:00</td> <td>raleigh, united states</td> <td>clay</td> <td>maria fernanda alves</td> <td>ashley harkleroad lindsay lee-waters</td> <td>2-6, 6-0, 3-6</td> </tr> <tr> <th>4</th> <td>runner-up</td> <td>3</td> <td>2006-03-19 00:00:00</td> <td>orange, united states</td> <td>hard</td> <td>lilia osterloh</td> <td>kateryna bondarenko alona bondarenko</td> <td>2-6, 4-6</td> </tr> <tr> <th>5</th> <td>winner</td> <td>3</td> <td>2006-11-12 00:00:00</td> <td>pittsburgh, united states</td> <td>hard (i)</td> <td>alisa kleybanova</td> <td>ashley harkleroad galina voskoboeva</td> <td>6-4, 5-7, 6-1</td> </tr> <tr> <th>6</th> <td>runner-up</td> <td>4</td> <td>2007-02-11 00:00:00</td> <td>midland, united states</td> <td>hard (i)</td> <td>maureen drake</td> <td>laura granville abigail spears</td> <td>4-6, 6-3, 3-6</td> </tr> <tr> <th>7</th> <td>runner-up</td> <td>5</td> <td>2007-07-07 00:00:00</td> <td>southlake, united states</td> <td>hard</td> <td>valerie tetreault</td> <td>surina de beer kim grant</td> <td>6-4, 4-6, 4-6</td> </tr> <tr> <th>8</th> <td>winner</td> <td>4</td> <td>2007-07-22 00:00:00</td> <td>hamilton, canada</td> <td>clay</td> <td>surina de beer</td> <td>michaela johansson paula zabala</td> <td>walkover</td> </tr> <tr> <th>9</th> <td>winner</td> <td>5</td> <td>2007-08-04 00:00:00</td> <td>vancouver, canada</td> <td>hard</td> <td>marie-eve pelletier</td> <td>soledad esperon agustina lepore</td> <td>6-4, 6-4</td> </tr> <tr> <th>10</th> <td>winner</td> <td>6</td> <td>2007-10-21 00:00:00</td> <td>lawrenceville, united states</td> <td>hard</td> <td>alisa kleybanova</td> <td>leanne baker julie ditty</td> <td>6-2, 6-0</td> </tr> <tr> <th>11</th> <td>winner</td> <td>7</td> <td>2007-11-12 00:00:00</td> <td>pittsburgh, united states</td> <td>hard (i)</td> <td>alisa kleybanova</td> <td>raquel kops-jones abigail spears</td> <td>6-4, 4-6, [10-6]</td> </tr> <tr> <th>12</th> <td>runner-up</td> <td>6</td> <td>2008-04-27 00:00:00</td> <td>dothan, united states</td> <td>clay</td> <td>maria fernanda alves</td> <td>tetiana luzhanska michaela pastikova</td> <td>1-6, 3-6</td> </tr> <tr> <th>13</th> <td>winner</td> <td>8</td> <td>2008-10-18 00:00:00</td> <td>toronto, canada</td> <td>hard (i)</td> <td>marie-eve pelletier</td> <td>nikola frankova carmen klaschka</td> <td>6-4, 6-2</td> </tr> <tr> <th>14</th> <td>runner-up</td> <td>7</td> <td>2009-09-27 00:00:00</td> <td>saguenay, canada</td> <td>hard (i)</td> <td>rebecca marino</td> <td>sofia arvidsson severine bremond beltrame</td> <td>3-6, 1-6</td> </tr> <tr> <th>15</th> <td>runner-up</td> <td>8</td> <td>2013-04-13 00:00:00</td> <td>poza rica, mexico</td> <td>hard</td> <td>olga savchuk</td> <td>maria fernanda alvarez teran maria fernanda alves</td> <td>2-6, 3-6</td> </tr> <tr> <th>16</th> <td>runner-up</td> <td>9</td> <td>2013-05-18 00:00:00</td> <td>saint-gaudens, france</td> <td>clay</td> <td>kurumi nara</td> <td>julia glushko paula ormaechea</td> <td>5-7, 6-7(11-13)</td> </tr> </tbody> </table>

select no. where outcome = 'runner-up' <table_name> : table | | outcome | no. | date | tournament | surface | partner | opponents | score | |---:|:----------|------:|:--------------------|:-----------------------------|:----------|:---------------------|:--------------------------------------------------|:-------------------| | 0 | winner | 1 | 2004-04-18 00:00:00 | jackson, united states | clay | alisa kleybanova | cory ann avants kristen schlukebir | 6-2, 6-3 | | 1 | runner-up | 1 | 2004-09-26 00:00:00 | albuquerque, united states | hard | maria emilia salerni | maureen drake carly gullickson | 3-6, 6-7(6-8) | | 2 | winner | 2 | 2005-03-27 00:00:00 | redding, united states | hard | yulia beygelzimer | leanne baker francesca lubiani | 6-4, 6-7(1-7), 6-3 | | 3 | runner-up | 2 | 2005-05-08 00:00:00 | raleigh, united states | clay | maria fernanda alves | ashley harkleroad lindsay lee-waters | 2-6, 6-0, 3-6 | | 4 | runner-up | 3 | 2006-03-19 00:00:00 | orange, united states | hard | lilia osterloh | kateryna bondarenko alona bondarenko | 2-6, 4-6 | | 5 | winner | 3 | 2006-11-12 00:00:00 | pittsburgh, united states | hard (i) | alisa kleybanova | ashley harkleroad galina voskoboeva | 6-4, 5-7, 6-1 | | 6 | runner-up | 4 | 2007-02-11 00:00:00 | midland, united states | hard (i) | maureen drake | laura granville abigail spears | 4-6, 6-3, 3-6 | | 7 | runner-up | 5 | 2007-07-07 00:00:00 | southlake, united states | hard | valerie tetreault | surina de beer kim grant | 6-4, 4-6, 4-6 | | 8 | winner | 4 | 2007-07-22 00:00:00 | hamilton, canada | clay | surina de beer | michaela johansson paula zabala | walkover | | 9 | winner | 5 | 2007-08-04 00:00:00 | vancouver, canada | hard | marie-eve pelletier | soledad esperon agustina lepore | 6-4, 6-4 | | 10 | winner | 6 | 2007-10-21 00:00:00 | lawrenceville, united states | hard | alisa kleybanova | leanne baker julie ditty | 6-2, 6-0 | | 11 | winner | 7 | 2007-11-12 00:00:00 | pittsburgh, united states | hard (i) | alisa kleybanova | raquel kops-jones abigail spears | 6-4, 4-6, [10-6] | | 12 | runner-up | 6 | 2008-04-27 00:00:00 | dothan, united states | clay | maria fernanda alves | tetiana luzhanska michaela pastikova | 1-6, 3-6 | | 13 | winner | 8 | 2008-10-18 00:00:00 | toronto, canada | hard (i) | marie-eve pelletier | nikola frankova carmen klaschka | 6-4, 6-2 | | 14 | runner-up | 7 | 2009-09-27 00:00:00 | saguenay, canada | hard (i) | rebecca marino | sofia arvidsson severine bremond beltrame | 3-6, 1-6 | | 15 | runner-up | 8 | 2013-04-13 00:00:00 | poza rica, mexico | hard | olga savchuk | maria fernanda alvarez teran maria fernanda alves | 2-6, 3-6 | | 16 | runner-up | 9 | 2013-05-18 00:00:00 | saint-gaudens, france | clay | kurumi nara | julia glushko paula ormaechea | 5-7, 6-7(11-13) |

| | no. | |---:|------:| | 0 | 1 | | 1 | 2 | | 2 | 3 | | 3 | 4 | | 4 | 5 | | 5 | 6 | | 6 | 7 | | 7 | 8 | | 8 | 9 |

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col : count ( "*" ) row 1 : 0

select count ( * ) where year = 1985 and code = 'h' <table_name> : table \begin{tabular}{lll} \toprule & code & year \\ \midrule 0 & a & 1927 \\ 1 & b & 1928 \\ 2 & c & 1929 \\ 3 & ch & 1930 \\ 4 & d & 1931 \\ 5 & e & 1932 \\ 6 & f & 1933 \\ 7 & g & 1934 \\ 8 & h & 1935 \\ 9 & i & 1936 \\ 10 & j & 1937 \\ 11 & k & 1938 \\ 12 & l & 1939 \\ 13 & ll & 1940 \\ 14 & m & 1941 \\ 15 & n & 1942 \\ 16 & n & 1943 \\ 17 & o & 1944 \\ 18 & p & 1945 \\ 19 & q & 1946 \\ 20 & r & 1947 \\ 21 & s & 1948 \\ 22 & t & 1949 \\ 23 & u & 1950 \\ 24 & v & 1951 \\ 25 & x & 1952 \\ 26 & y & 1953 \\ 27 & z & 1954 \\ 28 & a1 & 1955 \\ 29 & b1 & 1956 \\ 30 & c1 & 1957 \\ 31 & ch1 & none \\ 32 & d1 & 1958 \\ 33 & e1 & 1959 \\ 34 & f1 & 1960 \\ 35 & g1 & 1961 \\ 36 & h1 & 1962 \\ 37 & i1 & 1963 \\ 38 & j1 & 1964 \\ 39 & k1 & 1965 \\ 40 & l1 & 1966 \\ 41 & ll1 & none \\ 42 & m1 & 1967 \\ 43 & n1 & 1968 \\ 44 & n1 & 1969 \\ 45 & o1 & 1970 \\ 46 & p1 & 1971 \\ 47 & q1 & 1972 \\ 48 & r1 & 1973 \\ 49 & s1 & 1974 \\ 50 & t1 & 1975 \\ 51 & u1 & 1976 \\ 52 & v1 & 1977 \\ 53 & x1 & 1978 \\ 54 & y1 & 1979 \\ 55 & z1 & 1980 \\ 56 & a2 & 1981 \\ 57 & b2 & 1982 \\ 58 & c2 & 1983 \\ 59 & ch2 & none \\ 60 & d2 & 1984 \\ 61 & e2 & 1985 \\ 62 & f2 & 1986 \\ 63 & g2 & 1987 \\ 64 & h2 & 1988 \\ 65 & i2 & 1989 \\ 66 & j2 & 1990 \\ 67 & k2 & 1991 \\ 68 & l2 & 1992 \\ 69 & ll2 & none \\ 70 & m2 & 1993 \\ 71 & n2 & 1994 \\ 72 & n2 & 1995 \\ 73 & o2 & 1996 \\ 74 & p2 & 1997 \\ 75 & q2 & 1998 \\ 76 & r2 & 1999 \\ 77 & s2 & 2000 \\ 78 & t2 & 2001 \\ 79 & u2 & 2002 \\ 80 & v2 & 2003 \\ 81 & x2 & 2004 \\ 82 & y2 & 2005 \\ 83 & z2 & 2006 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where year = 1985 and code = 'h' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>code</th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>a</td> <td>1927</td> </tr> <tr> <th>1</th> <td>b</td> <td>1928</td> </tr> <tr> <th>2</th> <td>c</td> <td>1929</td> </tr> <tr> <th>3</th> <td>ch</td> <td>1930</td> </tr> <tr> <th>4</th> <td>d</td> <td>1931</td> </tr> <tr> <th>5</th> <td>e</td> <td>1932</td> </tr> <tr> <th>6</th> <td>f</td> <td>1933</td> </tr> <tr> <th>7</th> <td>g</td> <td>1934</td> </tr> <tr> <th>8</th> <td>h</td> <td>1935</td> </tr> <tr> <th>9</th> <td>i</td> <td>1936</td> </tr> <tr> <th>10</th> <td>j</td> <td>1937</td> </tr> <tr> <th>11</th> <td>k</td> <td>1938</td> </tr> <tr> <th>12</th> <td>l</td> <td>1939</td> </tr> <tr> <th>13</th> <td>ll</td> <td>1940</td> </tr> <tr> <th>14</th> <td>m</td> <td>1941</td> </tr> <tr> <th>15</th> <td>n</td> <td>1942</td> </tr> <tr> <th>16</th> <td>n</td> <td>1943</td> </tr> <tr> <th>17</th> <td>o</td> <td>1944</td> </tr> <tr> <th>18</th> <td>p</td> <td>1945</td> </tr> <tr> <th>19</th> <td>q</td> <td>1946</td> </tr> <tr> <th>20</th> <td>r</td> <td>1947</td> </tr> <tr> <th>21</th> <td>s</td> <td>1948</td> </tr> <tr> <th>22</th> <td>t</td> <td>1949</td> </tr> <tr> <th>23</th> <td>u</td> <td>1950</td> </tr> <tr> <th>24</th> <td>v</td> <td>1951</td> </tr> <tr> <th>25</th> <td>x</td> <td>1952</td> </tr> <tr> <th>26</th> <td>y</td> <td>1953</td> </tr> <tr> <th>27</th> <td>z</td> <td>1954</td> </tr> <tr> <th>28</th> <td>a1</td> <td>1955</td> </tr> <tr> <th>29</th> <td>b1</td> <td>1956</td> </tr> <tr> <th>30</th> <td>c1</td> <td>1957</td> </tr> <tr> <th>31</th> <td>ch1</td> <td>none</td> </tr> <tr> <th>32</th> <td>d1</td> <td>1958</td> </tr> <tr> <th>33</th> <td>e1</td> <td>1959</td> </tr> <tr> <th>34</th> <td>f1</td> <td>1960</td> </tr> <tr> <th>35</th> <td>g1</td> <td>1961</td> </tr> <tr> <th>36</th> <td>h1</td> <td>1962</td> </tr> <tr> <th>37</th> <td>i1</td> <td>1963</td> </tr> <tr> <th>38</th> <td>j1</td> <td>1964</td> </tr> <tr> <th>39</th> <td>k1</td> <td>1965</td> </tr> <tr> <th>40</th> <td>l1</td> <td>1966</td> </tr> <tr> <th>41</th> <td>ll1</td> <td>none</td> </tr> <tr> <th>42</th> <td>m1</td> <td>1967</td> </tr> <tr> <th>43</th> <td>n1</td> <td>1968</td> </tr> <tr> <th>44</th> <td>n1</td> <td>1969</td> </tr> <tr> <th>45</th> <td>o1</td> <td>1970</td> </tr> <tr> <th>46</th> <td>p1</td> <td>1971</td> </tr> <tr> <th>47</th> <td>q1</td> <td>1972</td> </tr> <tr> <th>48</th> <td>r1</td> <td>1973</td> </tr> <tr> <th>49</th> <td>s1</td> <td>1974</td> </tr> <tr> <th>50</th> <td>t1</td> <td>1975</td> </tr> <tr> <th>51</th> <td>u1</td> <td>1976</td> </tr> <tr> <th>52</th> <td>v1</td> <td>1977</td> </tr> <tr> <th>53</th> <td>x1</td> <td>1978</td> </tr> <tr> <th>54</th> <td>y1</td> <td>1979</td> </tr> <tr> <th>55</th> <td>z1</td> <td>1980</td> </tr> <tr> <th>56</th> <td>a2</td> <td>1981</td> </tr> <tr> <th>57</th> <td>b2</td> <td>1982</td> </tr> <tr> <th>58</th> <td>c2</td> <td>1983</td> </tr> <tr> <th>59</th> <td>ch2</td> <td>none</td> </tr> <tr> <th>60</th> <td>d2</td> <td>1984</td> </tr> <tr> <th>61</th> <td>e2</td> <td>1985</td> </tr> <tr> <th>62</th> <td>f2</td> <td>1986</td> </tr> <tr> <th>63</th> <td>g2</td> <td>1987</td> </tr> <tr> <th>64</th> <td>h2</td> <td>1988</td> </tr> <tr> <th>65</th> <td>i2</td> <td>1989</td> </tr> <tr> <th>66</th> <td>j2</td> <td>1990</td> </tr> <tr> <th>67</th> <td>k2</td> <td>1991</td> </tr> <tr> <th>68</th> <td>l2</td> <td>1992</td> </tr> <tr> <th>69</th> <td>ll2</td> <td>none</td> </tr> <tr> <th>70</th> <td>m2</td> <td>1993</td> </tr> <tr> <th>71</th> <td>n2</td> <td>1994</td> </tr> <tr> <th>72</th> <td>n2</td> <td>1995</td> </tr> <tr> <th>73</th> <td>o2</td> <td>1996</td> </tr> <tr> <th>74</th> <td>p2</td> <td>1997</td> </tr> <tr> <th>75</th> <td>q2</td> <td>1998</td> </tr> <tr> <th>76</th> <td>r2</td> <td>1999</td> </tr> <tr> <th>77</th> <td>s2</td> <td>2000</td> </tr> <tr> <th>78</th> <td>t2</td> <td>2001</td> </tr> <tr> <th>79</th> <td>u2</td> <td>2002</td> </tr> <tr> <th>80</th> <td>v2</td> <td>2003</td> </tr> <tr> <th>81</th> <td>x2</td> <td>2004</td> </tr> <tr> <th>82</th> <td>y2</td> <td>2005</td> </tr> <tr> <th>83</th> <td>z2</td> <td>2006</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where year = 1985 and code = 'h' <table_name> : table | | code | year | |---:|:-------|:-------| | 0 | a | 1927 | | 1 | b | 1928 | | 2 | c | 1929 | | 3 | ch | 1930 | | 4 | d | 1931 | | 5 | e | 1932 | | 6 | f | 1933 | | 7 | g | 1934 | | 8 | h | 1935 | | 9 | i | 1936 | | 10 | j | 1937 | | 11 | k | 1938 | | 12 | l | 1939 | | 13 | ll | 1940 | | 14 | m | 1941 | | 15 | n | 1942 | | 16 | n | 1943 | | 17 | o | 1944 | | 18 | p | 1945 | | 19 | q | 1946 | | 20 | r | 1947 | | 21 | s | 1948 | | 22 | t | 1949 | | 23 | u | 1950 | | 24 | v | 1951 | | 25 | x | 1952 | | 26 | y | 1953 | | 27 | z | 1954 | | 28 | a1 | 1955 | | 29 | b1 | 1956 | | 30 | c1 | 1957 | | 31 | ch1 | none | | 32 | d1 | 1958 | | 33 | e1 | 1959 | | 34 | f1 | 1960 | | 35 | g1 | 1961 | | 36 | h1 | 1962 | | 37 | i1 | 1963 | | 38 | j1 | 1964 | | 39 | k1 | 1965 | | 40 | l1 | 1966 | | 41 | ll1 | none | | 42 | m1 | 1967 | | 43 | n1 | 1968 | | 44 | n1 | 1969 | | 45 | o1 | 1970 | | 46 | p1 | 1971 | | 47 | q1 | 1972 | | 48 | r1 | 1973 | | 49 | s1 | 1974 | | 50 | t1 | 1975 | | 51 | u1 | 1976 | | 52 | v1 | 1977 | | 53 | x1 | 1978 | | 54 | y1 | 1979 | | 55 | z1 | 1980 | | 56 | a2 | 1981 | | 57 | b2 | 1982 | | 58 | c2 | 1983 | | 59 | ch2 | none | | 60 | d2 | 1984 | | 61 | e2 | 1985 | | 62 | f2 | 1986 | | 63 | g2 | 1987 | | 64 | h2 | 1988 | | 65 | i2 | 1989 | | 66 | j2 | 1990 | | 67 | k2 | 1991 | | 68 | l2 | 1992 | | 69 | ll2 | none | | 70 | m2 | 1993 | | 71 | n2 | 1994 | | 72 | n2 | 1995 | | 73 | o2 | 1996 | | 74 | p2 | 1997 | | 75 | q2 | 1998 | | 76 | r2 | 1999 | | 77 | s2 | 2000 | | 78 | t2 | 2001 | | 79 | u2 | 2002 | | 80 | v2 | 2003 | | 81 | x2 | 2004 | | 82 | y2 | 2005 | | 83 | z2 | 2006 |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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col : notes row 1 : 54.43 m

select notes where position = '7th' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 2003 & world youth championships & sherbrooke, canada & 7th & hammer & 54.43 m \\ 1 & 2005 & alba games & la habana, cuba & 1st & hammer & 63.30 m \\ 2 & 2005 & central american and caribbean championships & nassau, bahamas & 4th & hammer & 60.49 m \\ 3 & 2005 & pan american junior championships & windsor, canada & 1st & hammer & 64.80 m \\ 4 & 2006 & nacac u23 championships & santo domingo, dominican republic & 2nd & hammer & 66.28 m \\ 5 & 2007 & pan american games & rio de janeiro, brazil & 2nd & hammer & 68.70 m \\ 6 & 2007 & world championships & osaka, japan & 9th & hammer & 70.20 m \\ 7 & 2008 & olympic games & beijing, china & 15th (q) & hammer & 68.74 m \\ 8 & 2009 & alba games & la habana, cuba & 2nd & hammer & 68.89 m \\ 9 & 2009 & central american and caribbean championships & havana, cuba & 1st & hammer & 71.32 m \\ 10 & 2009 & world championships & berlin, germany & 16th (q) & hammer & 69.97 m \\ 11 & 2011 & pan american games & guadalajara, mexico & 4th & hammer & 68.88 m \\ 12 & 2012 & olympic games & london, united kingdom & 23rd (q) & hammer & 67.93 m \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & notes \\ \midrule 0 & 54.43 m \\ \bottomrule \end{tabular}

select notes where position = '7th' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2003</td> <td>world youth championships</td> <td>sherbrooke, canada</td> <td>7th</td> <td>hammer</td> <td>54.43 m</td> </tr> <tr> <th>1</th> <td>2005</td> <td>alba games</td> <td>la habana, cuba</td> <td>1st</td> <td>hammer</td> <td>63.30 m</td> </tr> <tr> <th>2</th> <td>2005</td> <td>central american and caribbean championships</td> <td>nassau, bahamas</td> <td>4th</td> <td>hammer</td> <td>60.49 m</td> </tr> <tr> <th>3</th> <td>2005</td> <td>pan american junior championships</td> <td>windsor, canada</td> <td>1st</td> <td>hammer</td> <td>64.80 m</td> </tr> <tr> <th>4</th> <td>2006</td> <td>nacac u23 championships</td> <td>santo domingo, dominican republic</td> <td>2nd</td> <td>hammer</td> <td>66.28 m</td> </tr> <tr> <th>5</th> <td>2007</td> <td>pan american games</td> <td>rio de janeiro, brazil</td> <td>2nd</td> <td>hammer</td> <td>68.70 m</td> </tr> <tr> <th>6</th> <td>2007</td> <td>world championships</td> <td>osaka, japan</td> <td>9th</td> <td>hammer</td> <td>70.20 m</td> </tr> <tr> <th>7</th> <td>2008</td> <td>olympic games</td> <td>beijing, china</td> <td>15th (q)</td> <td>hammer</td> <td>68.74 m</td> </tr> <tr> <th>8</th> <td>2009</td> <td>alba games</td> <td>la habana, cuba</td> <td>2nd</td> <td>hammer</td> <td>68.89 m</td> </tr> <tr> <th>9</th> <td>2009</td> <td>central american and caribbean championships</td> <td>havana, cuba</td> <td>1st</td> <td>hammer</td> <td>71.32 m</td> </tr> <tr> <th>10</th> <td>2009</td> <td>world championships</td> <td>berlin, germany</td> <td>16th (q)</td> <td>hammer</td> <td>69.97 m</td> </tr> <tr> <th>11</th> <td>2011</td> <td>pan american games</td> <td>guadalajara, mexico</td> <td>4th</td> <td>hammer</td> <td>68.88 m</td> </tr> <tr> <th>12</th> <td>2012</td> <td>olympic games</td> <td>london, united kingdom</td> <td>23rd (q)</td> <td>hammer</td> <td>67.93 m</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>54.43 m</td> </tr> </tbody> </table>

select notes where position = '7th' <table_name> : table | | year | competition | venue | position | event | notes | |---:|-------:|:---------------------------------------------|:----------------------------------|:-----------|:--------|:--------| | 0 | 2003 | world youth championships | sherbrooke, canada | 7th | hammer | 54.43 m | | 1 | 2005 | alba games | la habana, cuba | 1st | hammer | 63.30 m | | 2 | 2005 | central american and caribbean championships | nassau, bahamas | 4th | hammer | 60.49 m | | 3 | 2005 | pan american junior championships | windsor, canada | 1st | hammer | 64.80 m | | 4 | 2006 | nacac u23 championships | santo domingo, dominican republic | 2nd | hammer | 66.28 m | | 5 | 2007 | pan american games | rio de janeiro, brazil | 2nd | hammer | 68.70 m | | 6 | 2007 | world championships | osaka, japan | 9th | hammer | 70.20 m | | 7 | 2008 | olympic games | beijing, china | 15th (q) | hammer | 68.74 m | | 8 | 2009 | alba games | la habana, cuba | 2nd | hammer | 68.89 m | | 9 | 2009 | central american and caribbean championships | havana, cuba | 1st | hammer | 71.32 m | | 10 | 2009 | world championships | berlin, germany | 16th (q) | hammer | 69.97 m | | 11 | 2011 | pan american games | guadalajara, mexico | 4th | hammer | 68.88 m | | 12 | 2012 | olympic games | london, united kingdom | 23rd (q) | hammer | 67.93 m |

| | notes | |---:|:--------| | 0 | 54.43 m |

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col : count ( "winner" ) row 1 : 1

select count ( winner ) where route = 'peyrehorade - bayonne' <table_name> : table \begin{tabular}{lllllll} \toprule & stage & date & route & terrain & length & winner \\ \midrule 0 & 1 & 22 june & rennes - lisieux & plain stage & 215 km (134 mi) & edward sels (bel) \\ 1 & 2 & 23 june & lisieux - amiens & plain stage & 208 km (129 mi) & andre darrigade (fra) \\ 2 & 3a & 24 june & amiens - forest & plain stage & 197 km (122 mi) & bernard vandekerkhove (bel) \\ 3 & 3b & 24 june & forest - forest & team time trial & 21 km (13 mi) & kas-kaskol \\ 4 & 4 & 25 june & forest - metz & plain stage & 292 km (181 mi) & rudi altig (ger) \\ 5 & 5 & 26 june & metz - freiburg & plain stage & 161 km (100 mi) & willy derboven (bel) \\ 6 & 6 & 27 june & freiburg - besancon & plain stage & 200 km (120 mi) & henk nijdam (ned) \\ 7 & 7 & 28 june & besancon - thonon-les-bains & plain stage & 195 km (121 mi) & jan janssen (ned) \\ 8 & 8 & 29 june & thonon-les-bains - briancon & stage with mountain(s) & 249 km (155 mi) & federico bahamontes (esp) \\ 9 & 9 & 30 june & briancon - monaco & stage with mountain(s) & 239 km (149 mi) & jacques anquetil (fra) \\ 10 & 10a & 1 july & monaco - hyeres & plain stage & 187 km (116 mi) & jan janssen (ned) \\ 11 & 10b & 1 july & hyeres - toulon & individual time trial & 21 km (13 mi) & jacques anquetil (fra) \\ 12 & 11 & 2 july & toulon - montpellier & plain stage & 250 km (160 mi) & edward sels (bel) \\ 13 & 12 & 3 july & montpellier - perpignan & plain stage & 174 km (108 mi) & jo de roo (ned) \\ 14 & 13 & 4 july & perpignan - andorra & stage with mountain(s) & 170 km (110 mi) & julio jimenez (esp) \\ 15 & 14 & 6 july & andorra - toulouse & stage with mountain(s) & 186 km (116 mi) & edward sels (bel) \\ 16 & 15 & 7 july & toulouse - luchon & stage with mountain(s) & 203 km (126 mi) & raymond poulidor (fra) \\ 17 & 16 & 8 july & luchon - pau & stage with mountain(s) & 197 km (122 mi) & federico bahamontes (esp) \\ 18 & 17 & 9 july & peyrehorade - bayonne & individual time trial & 43 km (27 mi) & jacques anquetil (fra) \\ 19 & 18 & 10 july & bayonne - bordeaux & plain stage & 187 km (116 mi) & andre darrigade (fra) \\ 20 & 19 & 11 july & bordeaux - brive & plain stage & 215 km (134 mi) & edward sels (bel) \\ 21 & 20 & 12 july & brive - puy de dome & stage with mountain(s) & 217 km (135 mi) & julio jimenez (esp) \\ 22 & 21 & 13 july & clermont-ferrand - orleans & plain stage & 311 km (193 mi) & jean stablinski (fra) \\ 23 & 22a & 14 july & orleans - versailles & plain stage & 119 km (74 mi) & benoni beheyt (bel) \\ 24 & 22b & 14 july & versailles - paris & individual time trial & 27 km (17 mi) & jacques anquetil (fra) \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "winner" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( winner ) where route = 'peyrehorade - bayonne' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>stage</th> <th>date</th> <th>route</th> <th>terrain</th> <th>length</th> <th>winner</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>22 june</td> <td>rennes - lisieux</td> <td>plain stage</td> <td>215 km (134 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>1</th> <td>2</td> <td>23 june</td> <td>lisieux - amiens</td> <td>plain stage</td> <td>208 km (129 mi)</td> <td>andre darrigade (fra)</td> </tr> <tr> <th>2</th> <td>3a</td> <td>24 june</td> <td>amiens - forest</td> <td>plain stage</td> <td>197 km (122 mi)</td> <td>bernard vandekerkhove (bel)</td> </tr> <tr> <th>3</th> <td>3b</td> <td>24 june</td> <td>forest - forest</td> <td>team time trial</td> <td>21 km (13 mi)</td> <td>kas-kaskol</td> </tr> <tr> <th>4</th> <td>4</td> <td>25 june</td> <td>forest - metz</td> <td>plain stage</td> <td>292 km (181 mi)</td> <td>rudi altig (ger)</td> </tr> <tr> <th>5</th> <td>5</td> <td>26 june</td> <td>metz - freiburg</td> <td>plain stage</td> <td>161 km (100 mi)</td> <td>willy derboven (bel)</td> </tr> <tr> <th>6</th> <td>6</td> <td>27 june</td> <td>freiburg - besancon</td> <td>plain stage</td> <td>200 km (120 mi)</td> <td>henk nijdam (ned)</td> </tr> <tr> <th>7</th> <td>7</td> <td>28 june</td> <td>besancon - thonon-les-bains</td> <td>plain stage</td> <td>195 km (121 mi)</td> <td>jan janssen (ned)</td> </tr> <tr> <th>8</th> <td>8</td> <td>29 june</td> <td>thonon-les-bains - briancon</td> <td>stage with mountain(s)</td> <td>249 km (155 mi)</td> <td>federico bahamontes (esp)</td> </tr> <tr> <th>9</th> <td>9</td> <td>30 june</td> <td>briancon - monaco</td> <td>stage with mountain(s)</td> <td>239 km (149 mi)</td> <td>jacques anquetil (fra)</td> </tr> <tr> <th>10</th> <td>10a</td> <td>1 july</td> <td>monaco - hyeres</td> <td>plain stage</td> <td>187 km (116 mi)</td> <td>jan janssen (ned)</td> </tr> <tr> <th>11</th> <td>10b</td> <td>1 july</td> <td>hyeres - toulon</td> <td>individual time trial</td> <td>21 km (13 mi)</td> <td>jacques anquetil (fra)</td> </tr> <tr> <th>12</th> <td>11</td> <td>2 july</td> <td>toulon - montpellier</td> <td>plain stage</td> <td>250 km (160 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>13</th> <td>12</td> <td>3 july</td> <td>montpellier - perpignan</td> <td>plain stage</td> <td>174 km (108 mi)</td> <td>jo de roo (ned)</td> </tr> <tr> <th>14</th> <td>13</td> <td>4 july</td> <td>perpignan - andorra</td> <td>stage with mountain(s)</td> <td>170 km (110 mi)</td> <td>julio jimenez (esp)</td> </tr> <tr> <th>15</th> <td>14</td> <td>6 july</td> <td>andorra - toulouse</td> <td>stage with mountain(s)</td> <td>186 km (116 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>16</th> <td>15</td> <td>7 july</td> <td>toulouse - luchon</td> <td>stage with mountain(s)</td> <td>203 km (126 mi)</td> <td>raymond poulidor (fra)</td> </tr> <tr> <th>17</th> <td>16</td> <td>8 july</td> <td>luchon - pau</td> <td>stage with mountain(s)</td> <td>197 km (122 mi)</td> <td>federico bahamontes (esp)</td> </tr> <tr> <th>18</th> <td>17</td> <td>9 july</td> <td>peyrehorade - bayonne</td> <td>individual time trial</td> <td>43 km (27 mi)</td> <td>jacques anquetil (fra)</td> </tr> <tr> <th>19</th> <td>18</td> <td>10 july</td> <td>bayonne - bordeaux</td> <td>plain stage</td> <td>187 km (116 mi)</td> <td>andre darrigade (fra)</td> </tr> <tr> <th>20</th> <td>19</td> <td>11 july</td> <td>bordeaux - brive</td> <td>plain stage</td> <td>215 km (134 mi)</td> <td>edward sels (bel)</td> </tr> <tr> <th>21</th> <td>20</td> <td>12 july</td> <td>brive - puy de dome</td> <td>stage with mountain(s)</td> <td>217 km (135 mi)</td> <td>julio jimenez (esp)</td> </tr> <tr> <th>22</th> <td>21</td> <td>13 july</td> <td>clermont-ferrand - orleans</td> <td>plain stage</td> <td>311 km (193 mi)</td> <td>jean stablinski (fra)</td> </tr> <tr> <th>23</th> <td>22a</td> <td>14 july</td> <td>orleans - versailles</td> <td>plain stage</td> <td>119 km (74 mi)</td> <td>benoni beheyt (bel)</td> </tr> <tr> <th>24</th> <td>22b</td> <td>14 july</td> <td>versailles - paris</td> <td>individual time trial</td> <td>27 km (17 mi)</td> <td>jacques anquetil (fra)</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "winner" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( winner ) where route = 'peyrehorade - bayonne' <table_name> : table | | stage | date | route | terrain | length | winner | |---:|:--------|:--------|:----------------------------|:-----------------------|:----------------|:----------------------------| | 0 | 1 | 22 june | rennes - lisieux | plain stage | 215 km (134 mi) | edward sels (bel) | | 1 | 2 | 23 june | lisieux - amiens | plain stage | 208 km (129 mi) | andre darrigade (fra) | | 2 | 3a | 24 june | amiens - forest | plain stage | 197 km (122 mi) | bernard vandekerkhove (bel) | | 3 | 3b | 24 june | forest - forest | team time trial | 21 km (13 mi) | kas-kaskol | | 4 | 4 | 25 june | forest - metz | plain stage | 292 km (181 mi) | rudi altig (ger) | | 5 | 5 | 26 june | metz - freiburg | plain stage | 161 km (100 mi) | willy derboven (bel) | | 6 | 6 | 27 june | freiburg - besancon | plain stage | 200 km (120 mi) | henk nijdam (ned) | | 7 | 7 | 28 june | besancon - thonon-les-bains | plain stage | 195 km (121 mi) | jan janssen (ned) | | 8 | 8 | 29 june | thonon-les-bains - briancon | stage with mountain(s) | 249 km (155 mi) | federico bahamontes (esp) | | 9 | 9 | 30 june | briancon - monaco | stage with mountain(s) | 239 km (149 mi) | jacques anquetil (fra) | | 10 | 10a | 1 july | monaco - hyeres | plain stage | 187 km (116 mi) | jan janssen (ned) | | 11 | 10b | 1 july | hyeres - toulon | individual time trial | 21 km (13 mi) | jacques anquetil (fra) | | 12 | 11 | 2 july | toulon - montpellier | plain stage | 250 km (160 mi) | edward sels (bel) | | 13 | 12 | 3 july | montpellier - perpignan | plain stage | 174 km (108 mi) | jo de roo (ned) | | 14 | 13 | 4 july | perpignan - andorra | stage with mountain(s) | 170 km (110 mi) | julio jimenez (esp) | | 15 | 14 | 6 july | andorra - toulouse | stage with mountain(s) | 186 km (116 mi) | edward sels (bel) | | 16 | 15 | 7 july | toulouse - luchon | stage with mountain(s) | 203 km (126 mi) | raymond poulidor (fra) | | 17 | 16 | 8 july | luchon - pau | stage with mountain(s) | 197 km (122 mi) | federico bahamontes (esp) | | 18 | 17 | 9 july | peyrehorade - bayonne | individual time trial | 43 km (27 mi) | jacques anquetil (fra) | | 19 | 18 | 10 july | bayonne - bordeaux | plain stage | 187 km (116 mi) | andre darrigade (fra) | | 20 | 19 | 11 july | bordeaux - brive | plain stage | 215 km (134 mi) | edward sels (bel) | | 21 | 20 | 12 july | brive - puy de dome | stage with mountain(s) | 217 km (135 mi) | julio jimenez (esp) | | 22 | 21 | 13 july | clermont-ferrand - orleans | plain stage | 311 km (193 mi) | jean stablinski (fra) | | 23 | 22a | 14 july | orleans - versailles | plain stage | 119 km (74 mi) | benoni beheyt (bel) | | 24 | 22b | 14 july | versailles - paris | individual time trial | 27 km (17 mi) | jacques anquetil (fra) |

| | count ( "winner" ) | |---:|---------------------:| | 0 | 1 |

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select count ( team ) where team = 'los angeles raiders' col : year | team | games | attempts | yards | ypc | long | tds row 1 : 1983 | los angeles rams | 16 | 390 | 1808 | 4.6 | 85 | 18 row 2 : 1984 | los angeles rams | 16 | 379 | 2105 | 5.6 | 66 | 14 row 3 : 1985 | los angeles rams | 14 | 292 | 1234 | 4.2 | 43 | 12 row 4 : 1986 | los angeles rams | 16 | 404 | 1821 | 4.5 | 42 | 11 row 5 : 1987 | los angeles rams | 3 | 60 | 277 | 4.6 | 57 | 1 row 6 : 1987 | indianapolis colts | 9 | 223 | 1011 | 4.5 | 53 | 5 row 7 : 1988 | indianapolis colts | 16 | 388 | 1659 | 4.3 | 41 | 14 row 8 : 1989 | indianapolis colts | 15 | 314 | 1311 | 4.2 | 21 | 7 row 9 : 1990 | indianapolis colts | 11 | 166 | 677 | 4.1 | 43 | 4 row 10 : 1991 | indianapolis colts | 10 | 167 | 536 | 3.2 | 28 | 2 row 11 : 1992 | los angeles raiders | 16 | 187 | 729 | 3.9 | 40 | 2 row 12 : 1993 | atlanta falcons | 4 | 26 | 91 | 3.5 | 10 | 0 row 13 : career | none | 146 | 2996 | 13259 | 4.4 | 85 | 90

col : count ( "team" ) row 1 : 1

select count ( team ) where team = 'los angeles raiders' <table_name> : table \begin{tabular}{lllllllll} \toprule & year & team & games & attempts & yards & ypc & long & tds \\ \midrule 0 & 1983 & los angeles rams & 16 & 390 & 1808 & 4.6 & 85 & 18 \\ 1 & 1984 & los angeles rams & 16 & 379 & 2105 & 5.6 & 66 & 14 \\ 2 & 1985 & los angeles rams & 14 & 292 & 1234 & 4.2 & 43 & 12 \\ 3 & 1986 & los angeles rams & 16 & 404 & 1821 & 4.5 & 42 & 11 \\ 4 & 1987 & los angeles rams & 3 & 60 & 277 & 4.6 & 57 & 1 \\ 5 & 1987 & indianapolis colts & 9 & 223 & 1011 & 4.5 & 53 & 5 \\ 6 & 1988 & indianapolis colts & 16 & 388 & 1659 & 4.3 & 41 & 14 \\ 7 & 1989 & indianapolis colts & 15 & 314 & 1311 & 4.2 & 21 & 7 \\ 8 & 1990 & indianapolis colts & 11 & 166 & 677 & 4.1 & 43 & 4 \\ 9 & 1991 & indianapolis colts & 10 & 167 & 536 & 3.2 & 28 & 2 \\ 10 & 1992 & los angeles raiders & 16 & 187 & 729 & 3.9 & 40 & 2 \\ 11 & 1993 & atlanta falcons & 4 & 26 & 91 & 3.5 & 10 & 0 \\ 12 & career & none & 146 & 2996 & 13259 & 4.4 & 85 & 90 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "team" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( team ) where team = 'los angeles raiders' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>team</th> <th>games</th> <th>attempts</th> <th>yards</th> <th>ypc</th> <th>long</th> <th>tds</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1983</td> <td>los angeles rams</td> <td>16</td> <td>390</td> <td>1808</td> <td>4.6</td> <td>85</td> <td>18</td> </tr> <tr> <th>1</th> <td>1984</td> <td>los angeles rams</td> <td>16</td> <td>379</td> <td>2105</td> <td>5.6</td> <td>66</td> <td>14</td> </tr> <tr> <th>2</th> <td>1985</td> <td>los angeles rams</td> <td>14</td> <td>292</td> <td>1234</td> <td>4.2</td> <td>43</td> <td>12</td> </tr> <tr> <th>3</th> <td>1986</td> <td>los angeles rams</td> <td>16</td> <td>404</td> <td>1821</td> <td>4.5</td> <td>42</td> <td>11</td> </tr> <tr> <th>4</th> <td>1987</td> <td>los angeles rams</td> <td>3</td> <td>60</td> <td>277</td> <td>4.6</td> <td>57</td> <td>1</td> </tr> <tr> <th>5</th> <td>1987</td> <td>indianapolis colts</td> <td>9</td> <td>223</td> <td>1011</td> <td>4.5</td> <td>53</td> <td>5</td> </tr> <tr> <th>6</th> <td>1988</td> <td>indianapolis colts</td> <td>16</td> <td>388</td> <td>1659</td> <td>4.3</td> <td>41</td> <td>14</td> </tr> <tr> <th>7</th> <td>1989</td> <td>indianapolis colts</td> <td>15</td> <td>314</td> <td>1311</td> <td>4.2</td> <td>21</td> <td>7</td> </tr> <tr> <th>8</th> <td>1990</td> <td>indianapolis colts</td> <td>11</td> <td>166</td> <td>677</td> <td>4.1</td> <td>43</td> <td>4</td> </tr> <tr> <th>9</th> <td>1991</td> <td>indianapolis colts</td> <td>10</td> <td>167</td> <td>536</td> <td>3.2</td> <td>28</td> <td>2</td> </tr> <tr> <th>10</th> <td>1992</td> <td>los angeles raiders</td> <td>16</td> <td>187</td> <td>729</td> <td>3.9</td> <td>40</td> <td>2</td> </tr> <tr> <th>11</th> <td>1993</td> <td>atlanta falcons</td> <td>4</td> <td>26</td> <td>91</td> <td>3.5</td> <td>10</td> <td>0</td> </tr> <tr> <th>12</th> <td>career</td> <td>none</td> <td>146</td> <td>2996</td> <td>13259</td> <td>4.4</td> <td>85</td> <td>90</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "team" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( team ) where team = 'los angeles raiders' <table_name> : table | | year | team | games | attempts | yards | ypc | long | tds | |---:|:-------|:--------------------|--------:|-----------:|--------:|------:|-------:|------:| | 0 | 1983 | los angeles rams | 16 | 390 | 1808 | 4.6 | 85 | 18 | | 1 | 1984 | los angeles rams | 16 | 379 | 2105 | 5.6 | 66 | 14 | | 2 | 1985 | los angeles rams | 14 | 292 | 1234 | 4.2 | 43 | 12 | | 3 | 1986 | los angeles rams | 16 | 404 | 1821 | 4.5 | 42 | 11 | | 4 | 1987 | los angeles rams | 3 | 60 | 277 | 4.6 | 57 | 1 | | 5 | 1987 | indianapolis colts | 9 | 223 | 1011 | 4.5 | 53 | 5 | | 6 | 1988 | indianapolis colts | 16 | 388 | 1659 | 4.3 | 41 | 14 | | 7 | 1989 | indianapolis colts | 15 | 314 | 1311 | 4.2 | 21 | 7 | | 8 | 1990 | indianapolis colts | 11 | 166 | 677 | 4.1 | 43 | 4 | | 9 | 1991 | indianapolis colts | 10 | 167 | 536 | 3.2 | 28 | 2 | | 10 | 1992 | los angeles raiders | 16 | 187 | 729 | 3.9 | 40 | 2 | | 11 | 1993 | atlanta falcons | 4 | 26 | 91 | 3.5 | 10 | 0 | | 12 | career | none | 146 | 2996 | 13259 | 4.4 | 85 | 90 |

| | count ( "team" ) | |---:|-------------------:| | 0 | 1 |

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col : result row 1 : w 31-10

select result where attendance = 73483 <table_name> : table \begin{tabular}{lllllll} \toprule & date & opponent# & rank# & site & result & attendance \\ \midrule 0 & september 11 & baylor & #14 & ohio stadium • columbus, oh & w 21-14 & 88622 \\ 1 & september 18 & at michigan state & #12 & spartan stadium • east lansing, mi & w 31-10 & 73483 \\ 2 & september 25 & stanford & #13 & ohio stadium • columbus, oh & l 20-23 & 89436 \\ 3 & october 2 & florida state & none & ohio stadium • columbus, oh & l 17-34 & 89491 \\ 4 & october 9 & wisconsin & none & ohio stadium • columbus, oh & l 0-6 & 88344 \\ 5 & october 16 & at #15 illinois & none & memorial stadium • champaign, il & w 26-21 & 73488 \\ 6 & october 23 & at indiana & none & memorial stadium • bloomington, in & w 49-25 & 52,04 \\ 7 & october 30 & purdue & none & ohio stadium • columbus, oh & w 38-6 & 89341 \\ 8 & november 6 & minnesota & none & ohio stadium • columbus, oh & w 35-10 & 87666 \\ 9 & november 13 & at northwestern & none & dyche stadium • evanston, il & w 40-28 & 30074 \\ 10 & november 20 & #13 michigan & none & ohio stadium • columbus, oh & w 24-14 & 90252 \\ 11 & december 17 & vs. byu & #17 & jack murphy stadium • san diego, ca (holiday bowl) & w 47-17 & 52533 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & result \\ \midrule 0 & w 31-10 \\ \bottomrule \end{tabular}

select result where attendance = 73483 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>date</th> <th>opponent#</th> <th>rank#</th> <th>site</th> <th>result</th> <th>attendance</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>september 11</td> <td>baylor</td> <td>#14</td> <td>ohio stadium • columbus, oh</td> <td>w 21-14</td> <td>88622</td> </tr> <tr> <th>1</th> <td>september 18</td> <td>at michigan state</td> <td>#12</td> <td>spartan stadium • east lansing, mi</td> <td>w 31-10</td> <td>73483</td> </tr> <tr> <th>2</th> <td>september 25</td> <td>stanford</td> <td>#13</td> <td>ohio stadium • columbus, oh</td> <td>l 20-23</td> <td>89436</td> </tr> <tr> <th>3</th> <td>october 2</td> <td>florida state</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>l 17-34</td> <td>89491</td> </tr> <tr> <th>4</th> <td>october 9</td> <td>wisconsin</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>l 0-6</td> <td>88344</td> </tr> <tr> <th>5</th> <td>october 16</td> <td>at #15 illinois</td> <td>none</td> <td>memorial stadium • champaign, il</td> <td>w 26-21</td> <td>73488</td> </tr> <tr> <th>6</th> <td>october 23</td> <td>at indiana</td> <td>none</td> <td>memorial stadium • bloomington, in</td> <td>w 49-25</td> <td>52,04</td> </tr> <tr> <th>7</th> <td>october 30</td> <td>purdue</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>w 38-6</td> <td>89341</td> </tr> <tr> <th>8</th> <td>november 6</td> <td>minnesota</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>w 35-10</td> <td>87666</td> </tr> <tr> <th>9</th> <td>november 13</td> <td>at northwestern</td> <td>none</td> <td>dyche stadium • evanston, il</td> <td>w 40-28</td> <td>30074</td> </tr> <tr> <th>10</th> <td>november 20</td> <td>#13 michigan</td> <td>none</td> <td>ohio stadium • columbus, oh</td> <td>w 24-14</td> <td>90252</td> </tr> <tr> <th>11</th> <td>december 17</td> <td>vs. byu</td> <td>#17</td> <td>jack murphy stadium • san diego, ca (holiday bowl)</td> <td>w 47-17</td> <td>52533</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>w 31-10</td> </tr> </tbody> </table>

select result where attendance = 73483 <table_name> : table | | date | opponent# | rank# | site | result | attendance | |---:|:-------------|:------------------|:--------|:---------------------------------------------------|:---------|:-------------| | 0 | september 11 | baylor | #14 | ohio stadium • columbus, oh | w 21-14 | 88622 | | 1 | september 18 | at michigan state | #12 | spartan stadium • east lansing, mi | w 31-10 | 73483 | | 2 | september 25 | stanford | #13 | ohio stadium • columbus, oh | l 20-23 | 89436 | | 3 | october 2 | florida state | none | ohio stadium • columbus, oh | l 17-34 | 89491 | | 4 | october 9 | wisconsin | none | ohio stadium • columbus, oh | l 0-6 | 88344 | | 5 | october 16 | at #15 illinois | none | memorial stadium • champaign, il | w 26-21 | 73488 | | 6 | october 23 | at indiana | none | memorial stadium • bloomington, in | w 49-25 | 52,04 | | 7 | october 30 | purdue | none | ohio stadium • columbus, oh | w 38-6 | 89341 | | 8 | november 6 | minnesota | none | ohio stadium • columbus, oh | w 35-10 | 87666 | | 9 | november 13 | at northwestern | none | dyche stadium • evanston, il | w 40-28 | 30074 | | 10 | november 20 | #13 michigan | none | ohio stadium • columbus, oh | w 24-14 | 90252 | | 11 | december 17 | vs. byu | #17 | jack murphy stadium • san diego, ca (holiday bowl) | w 47-17 | 52533 |

| | result | |---:|:---------| | 0 | w 31-10 |

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col : position row 1 : 1

select position where position = 1 <table_name> : table \begin{tabular}{lllll} \toprule & year & single & chart & position \\ \midrule 0 & 1999 & "heavy" & billboard hot 100 & 73 \\ 1 & 1999 & "heavy" & mainstream rock tracks & 1 \\ 2 & 1999 & "heavy" & modern rock tracks & 5 \\ 3 & 1999 & "run" & billboard hot 100 & 76 \\ 4 & 1999 & "run" & modern rock tracks & 36 \\ 5 & 1999 & "run" & adult top 40 & 12 \\ 6 & 1999 & "no more, no less" & mainstream rock tracks & 10 \\ 7 & 1999 & "no more, no less" & modern rock tracks & 32 \\ 8 & 1999 & "tremble for my beloved" & mainstream rock tracks & 35 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & position \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select position where position = 1 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>single</th> <th>chart</th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>"heavy"</td> <td>billboard hot 100</td> <td>73</td> </tr> <tr> <th>1</th> <td>1999</td> <td>"heavy"</td> <td>mainstream rock tracks</td> <td>1</td> </tr> <tr> <th>2</th> <td>1999</td> <td>"heavy"</td> <td>modern rock tracks</td> <td>5</td> </tr> <tr> <th>3</th> <td>1999</td> <td>"run"</td> <td>billboard hot 100</td> <td>76</td> </tr> <tr> <th>4</th> <td>1999</td> <td>"run"</td> <td>modern rock tracks</td> <td>36</td> </tr> <tr> <th>5</th> <td>1999</td> <td>"run"</td> <td>adult top 40</td> <td>12</td> </tr> <tr> <th>6</th> <td>1999</td> <td>"no more, no less"</td> <td>mainstream rock tracks</td> <td>10</td> </tr> <tr> <th>7</th> <td>1999</td> <td>"no more, no less"</td> <td>modern rock tracks</td> <td>32</td> </tr> <tr> <th>8</th> <td>1999</td> <td>"tremble for my beloved"</td> <td>mainstream rock tracks</td> <td>35</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select position where position = 1 <table_name> : table | | year | single | chart | position | |---:|-------:|:-------------------------|:-----------------------|-----------:| | 0 | 1999 | "heavy" | billboard hot 100 | 73 | | 1 | 1999 | "heavy" | mainstream rock tracks | 1 | | 2 | 1999 | "heavy" | modern rock tracks | 5 | | 3 | 1999 | "run" | billboard hot 100 | 76 | | 4 | 1999 | "run" | modern rock tracks | 36 | | 5 | 1999 | "run" | adult top 40 | 12 | | 6 | 1999 | "no more, no less" | mainstream rock tracks | 10 | | 7 | 1999 | "no more, no less" | modern rock tracks | 32 | | 8 | 1999 | "tremble for my beloved" | mainstream rock tracks | 35 |

| | position | |---:|-----------:| | 0 | 1 |

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select place where place = 3 col : place | team | titles | runners-up | winning years row 1 : 1 | maccabi tel aviv | 5 | 1 | 2007, 2010, 2011, 2012, 2013 row 2 : 2 | hapoel jerusalem | 2 | 3 | 2008, 2009 row 3 : 3 | ironi ashkelon | 1 | 0 | 2006 row 4 : 4 | maccabi rishon lezion | 0 | 1 | none row 5 : 4 | ironi nahariya | 0 | 1 | none row 6 : 4 | hapoel holon | 0 | 1 | none row 7 : 4 | maccabi ashdod | 0 | 1 | none

col : place row 1 : 3

select place where place = 3 <table_name> : table \begin{tabular}{llllll} \toprule & place & team & titles & runners-up & winning years \\ \midrule 0 & 1 & maccabi tel aviv & 5 & 1 & 2007, 2010, 2011, 2012, 2013 \\ 1 & 2 & hapoel jerusalem & 2 & 3 & 2008, 2009 \\ 2 & 3 & ironi ashkelon & 1 & 0 & 2006 \\ 3 & 4 & maccabi rishon lezion & 0 & 1 & none \\ 4 & 4 & ironi nahariya & 0 & 1 & none \\ 5 & 4 & hapoel holon & 0 & 1 & none \\ 6 & 4 & maccabi ashdod & 0 & 1 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & place \\ \midrule 0 & 3 \\ \bottomrule \end{tabular}

select place where place = 3 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> <th>team</th> <th>titles</th> <th>runners-up</th> <th>winning years</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>maccabi tel aviv</td> <td>5</td> <td>1</td> <td>2007, 2010, 2011, 2012, 2013</td> </tr> <tr> <th>1</th> <td>2</td> <td>hapoel jerusalem</td> <td>2</td> <td>3</td> <td>2008, 2009</td> </tr> <tr> <th>2</th> <td>3</td> <td>ironi ashkelon</td> <td>1</td> <td>0</td> <td>2006</td> </tr> <tr> <th>3</th> <td>4</td> <td>maccabi rishon lezion</td> <td>0</td> <td>1</td> <td>none</td> </tr> <tr> <th>4</th> <td>4</td> <td>ironi nahariya</td> <td>0</td> <td>1</td> <td>none</td> </tr> <tr> <th>5</th> <td>4</td> <td>hapoel holon</td> <td>0</td> <td>1</td> <td>none</td> </tr> <tr> <th>6</th> <td>4</td> <td>maccabi ashdod</td> <td>0</td> <td>1</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>3</td> </tr> </tbody> </table>

select place where place = 3 <table_name> : table | | place | team | titles | runners-up | winning years | |---:|--------:|:----------------------|---------:|-------------:|:-----------------------------| | 0 | 1 | maccabi tel aviv | 5 | 1 | 2007, 2010, 2011, 2012, 2013 | | 1 | 2 | hapoel jerusalem | 2 | 3 | 2008, 2009 | | 2 | 3 | ironi ashkelon | 1 | 0 | 2006 | | 3 | 4 | maccabi rishon lezion | 0 | 1 | none | | 4 | 4 | ironi nahariya | 0 | 1 | none | | 5 | 4 | hapoel holon | 0 | 1 | none | | 6 | 4 | maccabi ashdod | 0 | 1 | none |

| | place | |---:|--------:| | 0 | 3 |

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select count ( group ) where group = 'non-inscrits' col : group | members | caucusing | total row 1 : socialist group | 242 | 8 | 250 row 2 : rpr group | 136 | 6 | 140 row 3 : udf group | 107 | 6 | 113 row 4 : communist group | 34 | 2 | 36 row 5 : radical, citizen and green | 33 | 0 | 33 row 6 : non-inscrits | 5 | 0 | 5 row 7 : total | 555 | 22 | 577

col : count ( "group" ) row 1 : 1

select count ( group ) where group = 'non-inscrits' <table_name> : table \begin{tabular}{lllll} \toprule & group & members & caucusing & total \\ \midrule 0 & socialist group & 242 & 8 & 250 \\ 1 & rpr group & 136 & 6 & 140 \\ 2 & udf group & 107 & 6 & 113 \\ 3 & communist group & 34 & 2 & 36 \\ 4 & radical, citizen and green & 33 & 0 & 33 \\ 5 & non-inscrits & 5 & 0 & 5 \\ 6 & total & 555 & 22 & 577 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "group" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( group ) where group = 'non-inscrits' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>group</th> <th>members</th> <th>caucusing</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>socialist group</td> <td>242</td> <td>8</td> <td>250</td> </tr> <tr> <th>1</th> <td>rpr group</td> <td>136</td> <td>6</td> <td>140</td> </tr> <tr> <th>2</th> <td>udf group</td> <td>107</td> <td>6</td> <td>113</td> </tr> <tr> <th>3</th> <td>communist group</td> <td>34</td> <td>2</td> <td>36</td> </tr> <tr> <th>4</th> <td>radical, citizen and green</td> <td>33</td> <td>0</td> <td>33</td> </tr> <tr> <th>5</th> <td>non-inscrits</td> <td>5</td> <td>0</td> <td>5</td> </tr> <tr> <th>6</th> <td>total</td> <td>555</td> <td>22</td> <td>577</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "group" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( group ) where group = 'non-inscrits' <table_name> : table | | group | members | caucusing | total | |---:|:---------------------------|----------:|------------:|--------:| | 0 | socialist group | 242 | 8 | 250 | | 1 | rpr group | 136 | 6 | 140 | | 2 | udf group | 107 | 6 | 113 | | 3 | communist group | 34 | 2 | 36 | | 4 | radical, citizen and green | 33 | 0 | 33 | | 5 | non-inscrits | 5 | 0 | 5 | | 6 | total | 555 | 22 | 577 |

| | count ( "group" ) | |---:|--------------------:| | 0 | 1 |

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col : event row 1 : marathon row 2 : marathon row 3 : marathon

select event where competition = 'world championships' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 1994 & european championships & helsinki, finland & 48th & marathon & 2:22:49 \\ 1 & 1995 & world championships & gothenburg, sweden & 49th & marathon & 2:33:42 \\ 2 & 1996 & summer olympics & atlanta, georgia & 58th & marathon & 2:23:14 \\ 3 & 1997 & world championships & athens, greece & 48th & marathon & 2:29:10 \\ 4 & 1998 & world cross country championships & marrakech, morocco & 85th & long race & none \\ 5 & 1998 & world half marathon championships & uster, switzerland & 66th & half marathon & 1:05:00 \\ 6 & 1998 & european championships & budapest, hungary & 29th & marathon & 2:19:38 \\ 7 & 1999 & world half marathon championships & palermo, italy & 55th & half marathon & 1:05:45 \\ 8 & 1999 & frankfurt marathon & frankfurt, germany & 1st & marathon & 2:12:37 \\ 9 & 1999 & helsinki marathon & helsinki, finland & 1st & marathon & 2:19:18 \\ 10 & 2000 & summer olympics & sydney, australia & 35th & marathon & 2:19:41 \\ 11 & 2001 & frankfurt marathon & frankfurt, germany & 1st & marathon & 2:11:09 \\ 12 & 2002 & paris marathon & paris, france & 2nd & marathon & 2:08:53 \\ 13 & 2002 & european championships & munich, germany & 2nd & marathon & 2:13:18 \\ 14 & 2002 & fukuoka marathon & fukuoka, japan & 4th & marathon & 2:10:14 \\ 15 & 2003 & joongang seoul marathon & seoul, south korea & 1st & marathon & 2:09:15 \\ 16 & 2004 & summer olympics & athens, greece & 26th & marathon & 2:18:09 \\ 17 & 2004 & joongang seoul marathon & seoul, south korea & 1st & marathon & 2:09:34 \\ 18 & 2005 & joongang seoul marathon & seoul, south korea & 4th & marathon & 2:12:12 \\ 19 & 2006 & paris marathon & paris, france & 12th & marathon & 2:11:25 \\ 20 & 2007 & world championships & osaka, japan & none & marathon & dnf \\ 21 & 2007 & beppu-oita marathon & beppu-oita, japan & 8th & marathon & 2:14:49 \\ 22 & 2008 & summer olympics & beijing, china & 75th & marathon & 2:39:01 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & event \\ \midrule 0 & marathon \\ 1 & marathon \\ 2 & marathon \\ \bottomrule \end{tabular}

select event where competition = 'world championships' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1994</td> <td>european championships</td> <td>helsinki, finland</td> <td>48th</td> <td>marathon</td> <td>2:22:49</td> </tr> <tr> <th>1</th> <td>1995</td> <td>world championships</td> <td>gothenburg, sweden</td> <td>49th</td> <td>marathon</td> <td>2:33:42</td> </tr> <tr> <th>2</th> <td>1996</td> <td>summer olympics</td> <td>atlanta, georgia</td> <td>58th</td> <td>marathon</td> <td>2:23:14</td> </tr> <tr> <th>3</th> <td>1997</td> <td>world championships</td> <td>athens, greece</td> <td>48th</td> <td>marathon</td> <td>2:29:10</td> </tr> <tr> <th>4</th> <td>1998</td> <td>world cross country championships</td> <td>marrakech, morocco</td> <td>85th</td> <td>long race</td> <td>none</td> </tr> <tr> <th>5</th> <td>1998</td> <td>world half marathon championships</td> <td>uster, switzerland</td> <td>66th</td> <td>half marathon</td> <td>1:05:00</td> </tr> <tr> <th>6</th> <td>1998</td> <td>european championships</td> <td>budapest, hungary</td> <td>29th</td> <td>marathon</td> <td>2:19:38</td> </tr> <tr> <th>7</th> <td>1999</td> <td>world half marathon championships</td> <td>palermo, italy</td> <td>55th</td> <td>half marathon</td> <td>1:05:45</td> </tr> <tr> <th>8</th> <td>1999</td> <td>frankfurt marathon</td> <td>frankfurt, germany</td> <td>1st</td> <td>marathon</td> <td>2:12:37</td> </tr> <tr> <th>9</th> <td>1999</td> <td>helsinki marathon</td> <td>helsinki, finland</td> <td>1st</td> <td>marathon</td> <td>2:19:18</td> </tr> <tr> <th>10</th> <td>2000</td> <td>summer olympics</td> <td>sydney, australia</td> <td>35th</td> <td>marathon</td> <td>2:19:41</td> </tr> <tr> <th>11</th> <td>2001</td> <td>frankfurt marathon</td> <td>frankfurt, germany</td> <td>1st</td> <td>marathon</td> <td>2:11:09</td> </tr> <tr> <th>12</th> <td>2002</td> <td>paris marathon</td> <td>paris, france</td> <td>2nd</td> <td>marathon</td> <td>2:08:53</td> </tr> <tr> <th>13</th> <td>2002</td> <td>european championships</td> <td>munich, germany</td> <td>2nd</td> <td>marathon</td> <td>2:13:18</td> </tr> <tr> <th>14</th> <td>2002</td> <td>fukuoka marathon</td> <td>fukuoka, japan</td> <td>4th</td> <td>marathon</td> <td>2:10:14</td> </tr> <tr> <th>15</th> <td>2003</td> <td>joongang seoul marathon</td> <td>seoul, south korea</td> <td>1st</td> <td>marathon</td> <td>2:09:15</td> </tr> <tr> <th>16</th> <td>2004</td> <td>summer olympics</td> <td>athens, greece</td> <td>26th</td> <td>marathon</td> <td>2:18:09</td> </tr> <tr> <th>17</th> <td>2004</td> <td>joongang seoul marathon</td> <td>seoul, south korea</td> <td>1st</td> <td>marathon</td> <td>2:09:34</td> </tr> <tr> <th>18</th> <td>2005</td> <td>joongang seoul marathon</td> <td>seoul, south korea</td> <td>4th</td> <td>marathon</td> <td>2:12:12</td> </tr> <tr> <th>19</th> <td>2006</td> <td>paris marathon</td> <td>paris, france</td> <td>12th</td> <td>marathon</td> <td>2:11:25</td> </tr> <tr> <th>20</th> <td>2007</td> <td>world championships</td> <td>osaka, japan</td> <td>none</td> <td>marathon</td> <td>dnf</td> </tr> <tr> <th>21</th> <td>2007</td> <td>beppu-oita marathon</td> <td>beppu-oita, japan</td> <td>8th</td> <td>marathon</td> <td>2:14:49</td> </tr> <tr> <th>22</th> <td>2008</td> <td>summer olympics</td> <td>beijing, china</td> <td>75th</td> <td>marathon</td> <td>2:39:01</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>event</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>marathon</td> </tr> <tr> <th>1</th> <td>marathon</td> </tr> <tr> <th>2</th> <td>marathon</td> </tr> </tbody> </table>

select event where competition = 'world championships' <table_name> : table | | year | competition | venue | position | event | notes | |---:|-------:|:----------------------------------|:-------------------|:-----------|:--------------|:--------| | 0 | 1994 | european championships | helsinki, finland | 48th | marathon | 2:22:49 | | 1 | 1995 | world championships | gothenburg, sweden | 49th | marathon | 2:33:42 | | 2 | 1996 | summer olympics | atlanta, georgia | 58th | marathon | 2:23:14 | | 3 | 1997 | world championships | athens, greece | 48th | marathon | 2:29:10 | | 4 | 1998 | world cross country championships | marrakech, morocco | 85th | long race | none | | 5 | 1998 | world half marathon championships | uster, switzerland | 66th | half marathon | 1:05:00 | | 6 | 1998 | european championships | budapest, hungary | 29th | marathon | 2:19:38 | | 7 | 1999 | world half marathon championships | palermo, italy | 55th | half marathon | 1:05:45 | | 8 | 1999 | frankfurt marathon | frankfurt, germany | 1st | marathon | 2:12:37 | | 9 | 1999 | helsinki marathon | helsinki, finland | 1st | marathon | 2:19:18 | | 10 | 2000 | summer olympics | sydney, australia | 35th | marathon | 2:19:41 | | 11 | 2001 | frankfurt marathon | frankfurt, germany | 1st | marathon | 2:11:09 | | 12 | 2002 | paris marathon | paris, france | 2nd | marathon | 2:08:53 | | 13 | 2002 | european championships | munich, germany | 2nd | marathon | 2:13:18 | | 14 | 2002 | fukuoka marathon | fukuoka, japan | 4th | marathon | 2:10:14 | | 15 | 2003 | joongang seoul marathon | seoul, south korea | 1st | marathon | 2:09:15 | | 16 | 2004 | summer olympics | athens, greece | 26th | marathon | 2:18:09 | | 17 | 2004 | joongang seoul marathon | seoul, south korea | 1st | marathon | 2:09:34 | | 18 | 2005 | joongang seoul marathon | seoul, south korea | 4th | marathon | 2:12:12 | | 19 | 2006 | paris marathon | paris, france | 12th | marathon | 2:11:25 | | 20 | 2007 | world championships | osaka, japan | none | marathon | dnf | | 21 | 2007 | beppu-oita marathon | beppu-oita, japan | 8th | marathon | 2:14:49 | | 22 | 2008 | summer olympics | beijing, china | 75th | marathon | 2:39:01 |

| | event | |---:|:---------| | 0 | marathon | | 1 | marathon | | 2 | marathon |

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col : count ( "*" ) row 1 : 0

select count ( * ) where circle = 'none' and bench = 'none' <table_name> : table \begin{tabular}{lllllll} \toprule & name & type & circle & bench & formed & notes \\ \midrule 0 & uberlingen & imperial city & swab & sw & 1268 & 1803: mediatized to baden \\ 1 & ulm & 1155: free imperial city & swab & sw & 1115 & 1803: mediatized to bavaria 1809: to wurttemberg \\ 2 & umpfenbach & lordship 1805: hre princely county & none & none & none & to trauttmansdorff \\ 3 & unterwalden & imperial valley & none & none & 1415 & division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation \\ 4 & upper salm & 1163: county & none & none & 1170 & partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach \\ 5 & upper bavaria (oberbayern) & duchy & none & none & 1255 & none \\ 6 & upper schonburg & county & upp sax & none & 1569 & partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg \\ 7 & urach & county & none & none & none & 1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach \\ 8 & uri & imperial valley & none & none & 1231 & split off from habsburg 1648: left empire as member of swiss confederation \\ 9 & ursberg & 1143: hre abbey & swab & none & none & 1803; secularized \\ 10 & utrecht & bishopric & burg & ec & 1024 & 1512: burgundian circle 1528: secularized to austria 1793: council of princes \\ 11 & uznach & county & none & none & none & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where circle = 'none' and bench = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>type</th> <th>circle</th> <th>bench</th> <th>formed</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>uberlingen</td> <td>imperial city</td> <td>swab</td> <td>sw</td> <td>1268</td> <td>1803: mediatized to baden</td> </tr> <tr> <th>1</th> <td>ulm</td> <td>1155: free imperial city</td> <td>swab</td> <td>sw</td> <td>1115</td> <td>1803: mediatized to bavaria 1809: to wurttemberg</td> </tr> <tr> <th>2</th> <td>umpfenbach</td> <td>lordship 1805: hre princely county</td> <td>none</td> <td>none</td> <td>none</td> <td>to trauttmansdorff</td> </tr> <tr> <th>3</th> <td>unterwalden</td> <td>imperial valley</td> <td>none</td> <td>none</td> <td>1415</td> <td>division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation</td> </tr> <tr> <th>4</th> <td>upper salm</td> <td>1163: county</td> <td>none</td> <td>none</td> <td>1170</td> <td>partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach</td> </tr> <tr> <th>5</th> <td>upper bavaria (oberbayern)</td> <td>duchy</td> <td>none</td> <td>none</td> <td>1255</td> <td>none</td> </tr> <tr> <th>6</th> <td>upper schonburg</td> <td>county</td> <td>upp sax</td> <td>none</td> <td>1569</td> <td>partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg</td> </tr> <tr> <th>7</th> <td>urach</td> <td>county</td> <td>none</td> <td>none</td> <td>none</td> <td>1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach</td> </tr> <tr> <th>8</th> <td>uri</td> <td>imperial valley</td> <td>none</td> <td>none</td> <td>1231</td> <td>split off from habsburg 1648: left empire as member of swiss confederation</td> </tr> <tr> <th>9</th> <td>ursberg</td> <td>1143: hre abbey</td> <td>swab</td> <td>none</td> <td>none</td> <td>1803; secularized</td> </tr> <tr> <th>10</th> <td>utrecht</td> <td>bishopric</td> <td>burg</td> <td>ec</td> <td>1024</td> <td>1512: burgundian circle 1528: secularized to austria 1793: council of princes</td> </tr> <tr> <th>11</th> <td>uznach</td> <td>county</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where circle = 'none' and bench = 'none' <table_name> : table | | name | type | circle | bench | formed | notes | |---:|:---------------------------|:-----------------------------------|:---------|:--------|:---------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | uberlingen | imperial city | swab | sw | 1268 | 1803: mediatized to baden | | 1 | ulm | 1155: free imperial city | swab | sw | 1115 | 1803: mediatized to bavaria 1809: to wurttemberg | | 2 | umpfenbach | lordship 1805: hre princely county | none | none | none | to trauttmansdorff | | 3 | unterwalden | imperial valley | none | none | 1415 | division into nidwalden and obwalden 1173: to counts of habsburg 1291: nidwalden became a founding member of the swiss league 1324: immediate imperial fief (reichsunmittelbar) 1350s: division into obwalden and nidwalden 1648: left empire as member of swiss confederation | | 4 | upper salm | 1163: county | none | none | 1170 | partitioned from salm 1499: raised to wild- and rhinegraves of salm 1574: divided into salm-salm and salm-grumbach | | 5 | upper bavaria (oberbayern) | duchy | none | none | 1255 | none | | 6 | upper schonburg | county | upp sax | none | 1569 | partitioned from schonburg 1800: partitioned into schonburg-hartenstein and schonburg-waldenburg | | 7 | urach | county | none | none | none | 1060: 1st mention of urach 1080: 1st use of "count of urach" division of territory into achalm and urach 1218 egino i of urach inherited county of freiburg from zahringen 1261: counts of urach died out 1251-1265: ulrich i of wurttemberg acquired territories of counts of urach | | 8 | uri | imperial valley | none | none | 1231 | split off from habsburg 1648: left empire as member of swiss confederation | | 9 | ursberg | 1143: hre abbey | swab | none | none | 1803; secularized | | 10 | utrecht | bishopric | burg | ec | 1024 | 1512: burgundian circle 1528: secularized to austria 1793: council of princes | | 11 | uznach | county | none | none | none | none |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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select type where works number = 76024 col : number | builder | type | date | works number | notes row 1 : 51 | baldwin locomotive works | ds4-4-750 | 1949 | 74408 | acquired new 1949, retired 1970/wrecked-scrapped row 2 : 52 | baldwin locomotive works | ds4-4-750 | 1949 | 74409 | acquired new 1949, retired in 1970 and scrapped in 1990 row 3 : 53 | baldwin locomotive works | ds4-4-1000 | 1949 | 74193 | ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection row 4 : 54 | baldwin locomotive works | s-12 | 1952/1953 | 75823 | ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped row 5 : 55 | baldwin locomotive works | rs-12 | 1955 | 76024 | decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995 row 6 : 56 | baldwin locomotive works | rs-12 | 1955 | 76105 | nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56 row 7 : 57 | baldwin locomotive works | s-12 | 1953 | 75914 | nee sp 1539, acquired 1970, retired unknown, stored at willits, california row 8 : 61 | american locomotive works | rs-11 | 1979 | none | former sp. status unknown row 9 : 62 | american locomotive works | rs-11 | 1979 | none | former sp. status unknown row 10 : 63 | american locomotive works | rs-11 | 1979 | none | former sp. sold to nvrr 1987 row 11 : 64 | electro-motive diesel | gp9m | 1987 | none | former sp # 3411. operational and in regular service row 12 : 65 | electro-motive diesel | gp9m | 1987 | none | former sp # 3412. operational row 13 : 66 | electro-motive diesel | gp9m | 1956 | none | former c&o # 6145. acquired 1998. operational and in regular service row 14 : 67 | electro-motive diesel | gp9m | 6/1954 | 19554 | built as bangor and aroostook railroad # 77; acquired 1998; never delivered row 15 : m-80 | mack | railbus | 1923 | none | purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964 row 16 : m-100 | edwards rail car company | motor car | 1925 | none | acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme row 17 : m-200 | ss&iw | motor car | 1927 | none | ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway row 18 : m-300 | american car and foundry company | motor car | 1935 | none | m-300 at fort bragg ex-slgw; nee ar; operable

col : type row 1 : rs-12

select type where works number = 76024 <table_name> : table \begin{tabular}{lllllll} \toprule & number & builder & type & date & works number & notes \\ \midrule 0 & 51 & baldwin locomotive works & ds4-4-750 & 1949 & 74408 & acquired new 1949, retired 1970/wrecked-scrapped \\ 1 & 52 & baldwin locomotive works & ds4-4-750 & 1949 & 74409 & acquired new 1949, retired in 1970 and scrapped in 1990 \\ 2 & 53 & baldwin locomotive works & ds4-4-1000 & 1949 & 74193 & ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection \\ 3 & 54 & baldwin locomotive works & s-12 & 1952/1953 & 75823 & ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped \\ 4 & 55 & baldwin locomotive works & rs-12 & 1955 & 76024 & decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995 \\ 5 & 56 & baldwin locomotive works & rs-12 & 1955 & 76105 & nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56 \\ 6 & 57 & baldwin locomotive works & s-12 & 1953 & 75914 & nee sp 1539, acquired 1970, retired unknown, stored at willits, california \\ 7 & 61 & american locomotive works & rs-11 & 1979 & none & former sp. status unknown \\ 8 & 62 & american locomotive works & rs-11 & 1979 & none & former sp. status unknown \\ 9 & 63 & american locomotive works & rs-11 & 1979 & none & former sp. sold to nvrr 1987 \\ 10 & 64 & electro-motive diesel & gp9m & 1987 & none & former sp # 3411. operational and in regular service \\ 11 & 65 & electro-motive diesel & gp9m & 1987 & none & former sp # 3412. operational \\ 12 & 66 & electro-motive diesel & gp9m & 1956 & none & former c&o # 6145. acquired 1998. operational and in regular service \\ 13 & 67 & electro-motive diesel & gp9m & 6/1954 & 19554 & built as bangor and aroostook railroad # 77; acquired 1998; never delivered \\ 14 & m-80 & mack & railbus & 1923 & none & purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964 \\ 15 & m-100 & edwards rail car company & motor car & 1925 & none & acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme \\ 16 & m-200 & ss&iw & motor car & 1927 & none & ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway \\ 17 & m-300 & american car and foundry company & motor car & 1935 & none & m-300 at fort bragg ex-slgw; nee ar; operable \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & type \\ \midrule 0 & rs-12 \\ \bottomrule \end{tabular}

select type where works number = 76024 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>number</th> <th>builder</th> <th>type</th> <th>date</th> <th>works number</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>51</td> <td>baldwin locomotive works</td> <td>ds4-4-750</td> <td>1949</td> <td>74408</td> <td>acquired new 1949, retired 1970/wrecked-scrapped</td> </tr> <tr> <th>1</th> <td>52</td> <td>baldwin locomotive works</td> <td>ds4-4-750</td> <td>1949</td> <td>74409</td> <td>acquired new 1949, retired in 1970 and scrapped in 1990</td> </tr> <tr> <th>2</th> <td>53</td> <td>baldwin locomotive works</td> <td>ds4-4-1000</td> <td>1949</td> <td>74193</td> <td>ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection</td> </tr> <tr> <th>3</th> <td>54</td> <td>baldwin locomotive works</td> <td>s-12</td> <td>1952/1953</td> <td>75823</td> <td>ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped</td> </tr> <tr> <th>4</th> <td>55</td> <td>baldwin locomotive works</td> <td>rs-12</td> <td>1955</td> <td>76024</td> <td>decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995</td> </tr> <tr> <th>5</th> <td>56</td> <td>baldwin locomotive works</td> <td>rs-12</td> <td>1955</td> <td>76105</td> <td>nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56</td> </tr> <tr> <th>6</th> <td>57</td> <td>baldwin locomotive works</td> <td>s-12</td> <td>1953</td> <td>75914</td> <td>nee sp 1539, acquired 1970, retired unknown, stored at willits, california</td> </tr> <tr> <th>7</th> <td>61</td> <td>american locomotive works</td> <td>rs-11</td> <td>1979</td> <td>none</td> <td>former sp. status unknown</td> </tr> <tr> <th>8</th> <td>62</td> <td>american locomotive works</td> <td>rs-11</td> <td>1979</td> <td>none</td> <td>former sp. status unknown</td> </tr> <tr> <th>9</th> <td>63</td> <td>american locomotive works</td> <td>rs-11</td> <td>1979</td> <td>none</td> <td>former sp. sold to nvrr 1987</td> </tr> <tr> <th>10</th> <td>64</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>1987</td> <td>none</td> <td>former sp # 3411. operational and in regular service</td> </tr> <tr> <th>11</th> <td>65</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>1987</td> <td>none</td> <td>former sp # 3412. operational</td> </tr> <tr> <th>12</th> <td>66</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>1956</td> <td>none</td> <td>former c&o # 6145. acquired 1998. operational and in regular service</td> </tr> <tr> <th>13</th> <td>67</td> <td>electro-motive diesel</td> <td>gp9m</td> <td>6/1954</td> <td>19554</td> <td>built as bangor and aroostook railroad # 77; acquired 1998; never delivered</td> </tr> <tr> <th>14</th> <td>m-80</td> <td>mack</td> <td>railbus</td> <td>1923</td> <td>none</td> <td>purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964</td> </tr> <tr> <th>15</th> <td>m-100</td> <td>edwards rail car company</td> <td>motor car</td> <td>1925</td> <td>none</td> <td>acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme</td> </tr> <tr> <th>16</th> <td>m-200</td> <td>ss&iw</td> <td>motor car</td> <td>1927</td> <td>none</td> <td>ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway</td> </tr> <tr> <th>17</th> <td>m-300</td> <td>american car and foundry company</td> <td>motor car</td> <td>1935</td> <td>none</td> <td>m-300 at fort bragg ex-slgw; nee ar; operable</td> </tr> </tbody> </table>

select type where works number = 76024 <table_name> : table | | number | builder | type | date | works number | notes | |---:|:---------|:---------------------------------|:-----------|:----------|:---------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 51 | baldwin locomotive works | ds4-4-750 | 1949 | 74408 | acquired new 1949, retired 1970/wrecked-scrapped | | 1 | 52 | baldwin locomotive works | ds4-4-750 | 1949 | 74409 | acquired new 1949, retired in 1970 and scrapped in 1990 | | 2 | 53 | baldwin locomotive works | ds4-4-1000 | 1949 | 74193 | ex-pan american engineering w8380; nee army corps of engineers w8380, acquired 1956, retired in 1985, to john bradley, 1985; to roots of motive power collection | | 3 | 54 | baldwin locomotive works | s-12 | 1952/1953 | 75823 | ex-nw (3307); nee wab 307, wrecked 1968, retired 1970, scrapped | | 4 | 55 | baldwin locomotive works | rs-12 | 1955 | 76024 | decorated for the united states bicentennial nee mr 32, acquired 1968, scrapped 1995 | | 5 | 56 | baldwin locomotive works | rs-12 | 1955 | 76105 | nee mr 33, acquired 1970, retired 1985 to john bradley, 1985; to travel town museum (los angeles, ca)56 | | 6 | 57 | baldwin locomotive works | s-12 | 1953 | 75914 | nee sp 1539, acquired 1970, retired unknown, stored at willits, california | | 7 | 61 | american locomotive works | rs-11 | 1979 | none | former sp. status unknown | | 8 | 62 | american locomotive works | rs-11 | 1979 | none | former sp. status unknown | | 9 | 63 | american locomotive works | rs-11 | 1979 | none | former sp. sold to nvrr 1987 | | 10 | 64 | electro-motive diesel | gp9m | 1987 | none | former sp # 3411. operational and in regular service | | 11 | 65 | electro-motive diesel | gp9m | 1987 | none | former sp # 3412. operational | | 12 | 66 | electro-motive diesel | gp9m | 1956 | none | former c&o # 6145. acquired 1998. operational and in regular service | | 13 | 67 | electro-motive diesel | gp9m | 6/1954 | 19554 | built as bangor and aroostook railroad # 77; acquired 1998; never delivered | | 14 | m-80 | mack | railbus | 1923 | none | purchased 1925. wrecked twice: in 1957 with a delivery truck, and in 1964 with m-100. scrapped 1964 | | 15 | m-100 | edwards rail car company | motor car | 1925 | none | acquired from moorhead & north forks railroad; operable. recently repainted back to historic yellow scheme | | 16 | m-200 | ss&iw | motor car | 1927 | none | ex-trc #22; nee-lpn 20; to niles canyon railway, 1975; operable on niles canyon railway | | 17 | m-300 | american car and foundry company | motor car | 1935 | none | m-300 at fort bragg ex-slgw; nee ar; operable |

| | type | |---:|:-------| | 0 | rs-12 |

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select votes where ±% = '-1.8' col : party | candidate | votes | % | ±% row 1 : conservative | patrick mcloughlin | 24280 | 48 | 5.9 row 2 : labour | stephen clamp | 16910 | 33.4 | -0.1 row 3 : liberal democrat | jeremy beckett | 7922 | 15.7 | -1.8 row 4 : ukip | stuart bavester | 672 | 1.3 | 0.5 row 5 : monster raving loony | "the flying brick" delves | 472 | 0.9 | 0.4 row 6 : independent | robert goodall | 333 | 0.7 | 0.5 row 7 : majority | majority | 7370 | 14.6 | none row 8 : turnout | turnout | 50589 | 67.8 | -10.5 row 9 : conservative hold | conservative hold | swing | none | none

col : votes row 1 : 7922

select votes where ±% = '-1.8' <table_name> : table \begin{tabular}{llllll} \toprule & party & candidate & votes & % & ±% \\ \midrule 0 & conservative & patrick mcloughlin & 24280 & 48 & 5.9 \\ 1 & labour & stephen clamp & 16910 & 33.4 & -0.1 \\ 2 & liberal democrat & jeremy beckett & 7922 & 15.7 & -1.8 \\ 3 & ukip & stuart bavester & 672 & 1.3 & 0.5 \\ 4 & monster raving loony & "the flying brick" delves & 472 & 0.9 & 0.4 \\ 5 & independent & robert goodall & 333 & 0.7 & 0.5 \\ 6 & majority & majority & 7370 & 14.6 & none \\ 7 & turnout & turnout & 50589 & 67.8 & -10.5 \\ 8 & conservative hold & conservative hold & swing & none & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & votes \\ \midrule 0 & 7922 \\ \bottomrule \end{tabular}

select votes where ±% = '-1.8' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>party</th> <th>candidate</th> <th>votes</th> <th>%</th> <th>±%</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>conservative</td> <td>patrick mcloughlin</td> <td>24280</td> <td>48</td> <td>5.9</td> </tr> <tr> <th>1</th> <td>labour</td> <td>stephen clamp</td> <td>16910</td> <td>33.4</td> <td>-0.1</td> </tr> <tr> <th>2</th> <td>liberal democrat</td> <td>jeremy beckett</td> <td>7922</td> <td>15.7</td> <td>-1.8</td> </tr> <tr> <th>3</th> <td>ukip</td> <td>stuart bavester</td> <td>672</td> <td>1.3</td> <td>0.5</td> </tr> <tr> <th>4</th> <td>monster raving loony</td> <td>"the flying brick" delves</td> <td>472</td> <td>0.9</td> <td>0.4</td> </tr> <tr> <th>5</th> <td>independent</td> <td>robert goodall</td> <td>333</td> <td>0.7</td> <td>0.5</td> </tr> <tr> <th>6</th> <td>majority</td> <td>majority</td> <td>7370</td> <td>14.6</td> <td>none</td> </tr> <tr> <th>7</th> <td>turnout</td> <td>turnout</td> <td>50589</td> <td>67.8</td> <td>-10.5</td> </tr> <tr> <th>8</th> <td>conservative hold</td> <td>conservative hold</td> <td>swing</td> <td>none</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>votes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7922</td> </tr> </tbody> </table>

select votes where ±% = '-1.8' <table_name> : table | | party | candidate | votes | % | ±% | |---:|:---------------------|:--------------------------|:--------|:-----|:------| | 0 | conservative | patrick mcloughlin | 24280 | 48 | 5.9 | | 1 | labour | stephen clamp | 16910 | 33.4 | -0.1 | | 2 | liberal democrat | jeremy beckett | 7922 | 15.7 | -1.8 | | 3 | ukip | stuart bavester | 672 | 1.3 | 0.5 | | 4 | monster raving loony | "the flying brick" delves | 472 | 0.9 | 0.4 | | 5 | independent | robert goodall | 333 | 0.7 | 0.5 | | 6 | majority | majority | 7370 | 14.6 | none | | 7 | turnout | turnout | 50589 | 67.8 | -10.5 | | 8 | conservative hold | conservative hold | swing | none | none |

| | votes | |---:|--------:| | 0 | 7922 |

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select count ( pos ) where points > 291 col : pos | no | rider | bike | laps | time | grid | points row 1 : 1 | 93 | marc marquez | derbi | 22 | 40:46.315 | 1 | 25 row 2 : 2 | 38 | bradley smith | aprilia | 22 | 4.638 | 3 | 20 row 3 : 3 | 44 | pol espargaro | derbi | 22 | 4.996 | 2 | 16 row 4 : 4 | 11 | sandro cortese | derbi | 22 | 45.366 | 5 | 13 row 5 : 5 | 7 | efren vazquez | derbi | 22 | 45.433 | 8 | 11 row 6 : 6 | 71 | tomoyoshi koyama | aprilia | 22 | 49.685 | 6 | 10 row 7 : 7 | 35 | randy krummenacher | aprilia | 22 | 49.735 | 14 | 9 row 8 : 8 | 14 | johann zarco | aprilia | 22 | 49.743 | 10 | 8 row 9 : 9 | 94 | jonas folger | aprilia | 22 | 49.775 | 12 | 7 row 10 : 10 | 99 | danny webb | aprilia | 22 | 53.115 | 16 | 6 row 11 : 11 | 26 | adrian martin | aprilia | 22 | 58.669 | 19 | 5 row 12 : 12 | 15 | simone grotzkyj | aprilia | 22 | 58.8 | 11 | 4 row 13 : 13 | 23 | alberto moncayo | aprilia | 22 | +1:02.050 | 13 | 3 row 14 : 14 | 78 | marcel schrotter | honda | 22 | +1:15.497 | 23 | 2 row 15 : 15 | 63 | zulfahmi khairuddin | aprilia | 22 | +1:16.029 | 18 | 1 row 16 : 16 | 84 | jakub kornfeil | aprilia | 22 | +1:26.441 | 28 | none row 17 : 17 | 69 | louis rossi | aprilia | 22 | +1:33.613 | 24 | none row 18 : 18 | 87 | luca marconi | aprilia | 22 | +1:36.186 | 25 | none row 19 : 19 | 58 | joan perello | honda | 22 | +1:36.223 | 26 | none row 20 : 20 | 60 | michael van der mark | lambretta | 22 | +1:36.340 | 27 | none row 21 : 21 | 59 | johnny rosell | honda | 22 | +1:43.804 | 22 | none row 22 : 22 | 72 | marco ravaioli | lambretta | 22 | +1:55.331 | 30 | none row 23 : 23 | 56 | peter sebestyen | aprilia | 21 | +1 lap | 32 | none row 24 : ret | 40 | nicolas terol | aprilia | 21 | accident | 4 | none row 25 : ret | 39 | luis salom | aprilia | 14 | retirement | 15 | none row 26 : ret | 17 | eduard lopez | aprilia | 11 | retirement | 31 | none row 27 : ret | 55 | isaac vinales | aprilia | 10 | accident | 21 | none row 28 : ret | 50 | sturla fagerhaug | aprilia | 7 | accident | 17 | none row 29 : ret | 5 | alexis masbou | aprilia | 5 | accident | 9 | none row 30 : ret | 12 | esteve rabat | aprilia | 0 | accident | 7 | none row 31 : ret | 53 | jasper iwema | aprilia | 0 | accident | 20 | none row 32 : dns | 32 | lorenzo savadori | aprilia | none | did not start | 29 | none

col : count ( "pos" ) row 1 : 24

select count ( pos ) where points > 291 <table_name> : table \begin{tabular}{lllllllll} \toprule & pos & no & rider & bike & laps & time & grid & points \\ \midrule 0 & 1 & 93 & marc marquez & derbi & 22 & 40:46.315 & 1 & 25 \\ 1 & 2 & 38 & bradley smith & aprilia & 22 & 4.638 & 3 & 20 \\ 2 & 3 & 44 & pol espargaro & derbi & 22 & 4.996 & 2 & 16 \\ 3 & 4 & 11 & sandro cortese & derbi & 22 & 45.366 & 5 & 13 \\ 4 & 5 & 7 & efren vazquez & derbi & 22 & 45.433 & 8 & 11 \\ 5 & 6 & 71 & tomoyoshi koyama & aprilia & 22 & 49.685 & 6 & 10 \\ 6 & 7 & 35 & randy krummenacher & aprilia & 22 & 49.735 & 14 & 9 \\ 7 & 8 & 14 & johann zarco & aprilia & 22 & 49.743 & 10 & 8 \\ 8 & 9 & 94 & jonas folger & aprilia & 22 & 49.775 & 12 & 7 \\ 9 & 10 & 99 & danny webb & aprilia & 22 & 53.115 & 16 & 6 \\ 10 & 11 & 26 & adrian martin & aprilia & 22 & 58.669 & 19 & 5 \\ 11 & 12 & 15 & simone grotzkyj & aprilia & 22 & 58.8 & 11 & 4 \\ 12 & 13 & 23 & alberto moncayo & aprilia & 22 & +1:02.050 & 13 & 3 \\ 13 & 14 & 78 & marcel schrotter & honda & 22 & +1:15.497 & 23 & 2 \\ 14 & 15 & 63 & zulfahmi khairuddin & aprilia & 22 & +1:16.029 & 18 & 1 \\ 15 & 16 & 84 & jakub kornfeil & aprilia & 22 & +1:26.441 & 28 & none \\ 16 & 17 & 69 & louis rossi & aprilia & 22 & +1:33.613 & 24 & none \\ 17 & 18 & 87 & luca marconi & aprilia & 22 & +1:36.186 & 25 & none \\ 18 & 19 & 58 & joan perello & honda & 22 & +1:36.223 & 26 & none \\ 19 & 20 & 60 & michael van der mark & lambretta & 22 & +1:36.340 & 27 & none \\ 20 & 21 & 59 & johnny rosell & honda & 22 & +1:43.804 & 22 & none \\ 21 & 22 & 72 & marco ravaioli & lambretta & 22 & +1:55.331 & 30 & none \\ 22 & 23 & 56 & peter sebestyen & aprilia & 21 & +1 lap & 32 & none \\ 23 & ret & 40 & nicolas terol & aprilia & 21 & accident & 4 & none \\ 24 & ret & 39 & luis salom & aprilia & 14 & retirement & 15 & none \\ 25 & ret & 17 & eduard lopez & aprilia & 11 & retirement & 31 & none \\ 26 & ret & 55 & isaac vinales & aprilia & 10 & accident & 21 & none \\ 27 & ret & 50 & sturla fagerhaug & aprilia & 7 & accident & 17 & none \\ 28 & ret & 5 & alexis masbou & aprilia & 5 & accident & 9 & none \\ 29 & ret & 12 & esteve rabat & aprilia & 0 & accident & 7 & none \\ 30 & ret & 53 & jasper iwema & aprilia & 0 & accident & 20 & none \\ 31 & dns & 32 & lorenzo savadori & aprilia & none & did not start & 29 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "pos" ) \\ \midrule 0 & 24 \\ \bottomrule \end{tabular}

select count ( pos ) where points > 291 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pos</th> <th>no</th> <th>rider</th> <th>bike</th> <th>laps</th> <th>time</th> <th>grid</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>93</td> <td>marc marquez</td> <td>derbi</td> <td>22</td> <td>40:46.315</td> <td>1</td> <td>25</td> </tr> <tr> <th>1</th> <td>2</td> <td>38</td> <td>bradley smith</td> <td>aprilia</td> <td>22</td> <td>4.638</td> <td>3</td> <td>20</td> </tr> <tr> <th>2</th> <td>3</td> <td>44</td> <td>pol espargaro</td> <td>derbi</td> <td>22</td> <td>4.996</td> <td>2</td> <td>16</td> </tr> <tr> <th>3</th> <td>4</td> <td>11</td> <td>sandro cortese</td> <td>derbi</td> <td>22</td> <td>45.366</td> <td>5</td> <td>13</td> </tr> <tr> <th>4</th> <td>5</td> <td>7</td> <td>efren vazquez</td> <td>derbi</td> <td>22</td> <td>45.433</td> <td>8</td> <td>11</td> </tr> <tr> <th>5</th> <td>6</td> <td>71</td> <td>tomoyoshi koyama</td> <td>aprilia</td> <td>22</td> <td>49.685</td> <td>6</td> <td>10</td> </tr> <tr> <th>6</th> <td>7</td> <td>35</td> <td>randy krummenacher</td> <td>aprilia</td> <td>22</td> <td>49.735</td> <td>14</td> <td>9</td> </tr> <tr> <th>7</th> <td>8</td> <td>14</td> <td>johann zarco</td> <td>aprilia</td> <td>22</td> <td>49.743</td> <td>10</td> <td>8</td> </tr> <tr> <th>8</th> <td>9</td> <td>94</td> <td>jonas folger</td> <td>aprilia</td> <td>22</td> <td>49.775</td> <td>12</td> <td>7</td> </tr> <tr> <th>9</th> <td>10</td> <td>99</td> <td>danny webb</td> <td>aprilia</td> <td>22</td> <td>53.115</td> <td>16</td> <td>6</td> </tr> <tr> <th>10</th> <td>11</td> <td>26</td> <td>adrian martin</td> <td>aprilia</td> <td>22</td> <td>58.669</td> <td>19</td> <td>5</td> </tr> <tr> <th>11</th> <td>12</td> <td>15</td> <td>simone grotzkyj</td> <td>aprilia</td> <td>22</td> <td>58.8</td> <td>11</td> <td>4</td> </tr> <tr> <th>12</th> <td>13</td> <td>23</td> <td>alberto moncayo</td> <td>aprilia</td> <td>22</td> <td>+1:02.050</td> <td>13</td> <td>3</td> </tr> <tr> <th>13</th> <td>14</td> <td>78</td> <td>marcel schrotter</td> <td>honda</td> <td>22</td> <td>+1:15.497</td> <td>23</td> <td>2</td> </tr> <tr> <th>14</th> <td>15</td> <td>63</td> <td>zulfahmi khairuddin</td> <td>aprilia</td> <td>22</td> <td>+1:16.029</td> <td>18</td> <td>1</td> </tr> <tr> <th>15</th> <td>16</td> <td>84</td> <td>jakub kornfeil</td> <td>aprilia</td> <td>22</td> <td>+1:26.441</td> <td>28</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>69</td> <td>louis rossi</td> <td>aprilia</td> <td>22</td> <td>+1:33.613</td> <td>24</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>87</td> <td>luca marconi</td> <td>aprilia</td> <td>22</td> <td>+1:36.186</td> <td>25</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>58</td> <td>joan perello</td> <td>honda</td> <td>22</td> <td>+1:36.223</td> <td>26</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>60</td> <td>michael van der mark</td> <td>lambretta</td> <td>22</td> <td>+1:36.340</td> <td>27</td> <td>none</td> </tr> <tr> <th>20</th> <td>21</td> <td>59</td> <td>johnny rosell</td> <td>honda</td> <td>22</td> <td>+1:43.804</td> <td>22</td> <td>none</td> </tr> <tr> <th>21</th> <td>22</td> <td>72</td> <td>marco ravaioli</td> <td>lambretta</td> <td>22</td> <td>+1:55.331</td> <td>30</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>56</td> <td>peter sebestyen</td> <td>aprilia</td> <td>21</td> <td>+1 lap</td> <td>32</td> <td>none</td> </tr> <tr> <th>23</th> <td>ret</td> <td>40</td> <td>nicolas terol</td> <td>aprilia</td> <td>21</td> <td>accident</td> <td>4</td> <td>none</td> </tr> <tr> <th>24</th> <td>ret</td> <td>39</td> <td>luis salom</td> <td>aprilia</td> <td>14</td> <td>retirement</td> <td>15</td> <td>none</td> </tr> <tr> <th>25</th> <td>ret</td> <td>17</td> <td>eduard lopez</td> <td>aprilia</td> <td>11</td> <td>retirement</td> <td>31</td> <td>none</td> </tr> <tr> <th>26</th> <td>ret</td> <td>55</td> <td>isaac vinales</td> <td>aprilia</td> <td>10</td> <td>accident</td> <td>21</td> <td>none</td> </tr> <tr> <th>27</th> <td>ret</td> <td>50</td> <td>sturla fagerhaug</td> <td>aprilia</td> <td>7</td> <td>accident</td> <td>17</td> <td>none</td> </tr> <tr> <th>28</th> <td>ret</td> <td>5</td> <td>alexis masbou</td> <td>aprilia</td> <td>5</td> <td>accident</td> <td>9</td> <td>none</td> </tr> <tr> <th>29</th> <td>ret</td> <td>12</td> <td>esteve rabat</td> <td>aprilia</td> <td>0</td> <td>accident</td> <td>7</td> <td>none</td> </tr> <tr> <th>30</th> <td>ret</td> <td>53</td> <td>jasper iwema</td> <td>aprilia</td> <td>0</td> <td>accident</td> <td>20</td> <td>none</td> </tr> <tr> <th>31</th> <td>dns</td> <td>32</td> <td>lorenzo savadori</td> <td>aprilia</td> <td>none</td> <td>did not start</td> <td>29</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "pos" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>24</td> </tr> </tbody> </table>

select count ( pos ) where points > 291 <table_name> : table | | pos | no | rider | bike | laps | time | grid | points | |---:|:------|-----:|:---------------------|:----------|:-------|:--------------|-------:|:---------| | 0 | 1 | 93 | marc marquez | derbi | 22 | 40:46.315 | 1 | 25 | | 1 | 2 | 38 | bradley smith | aprilia | 22 | 4.638 | 3 | 20 | | 2 | 3 | 44 | pol espargaro | derbi | 22 | 4.996 | 2 | 16 | | 3 | 4 | 11 | sandro cortese | derbi | 22 | 45.366 | 5 | 13 | | 4 | 5 | 7 | efren vazquez | derbi | 22 | 45.433 | 8 | 11 | | 5 | 6 | 71 | tomoyoshi koyama | aprilia | 22 | 49.685 | 6 | 10 | | 6 | 7 | 35 | randy krummenacher | aprilia | 22 | 49.735 | 14 | 9 | | 7 | 8 | 14 | johann zarco | aprilia | 22 | 49.743 | 10 | 8 | | 8 | 9 | 94 | jonas folger | aprilia | 22 | 49.775 | 12 | 7 | | 9 | 10 | 99 | danny webb | aprilia | 22 | 53.115 | 16 | 6 | | 10 | 11 | 26 | adrian martin | aprilia | 22 | 58.669 | 19 | 5 | | 11 | 12 | 15 | simone grotzkyj | aprilia | 22 | 58.8 | 11 | 4 | | 12 | 13 | 23 | alberto moncayo | aprilia | 22 | +1:02.050 | 13 | 3 | | 13 | 14 | 78 | marcel schrotter | honda | 22 | +1:15.497 | 23 | 2 | | 14 | 15 | 63 | zulfahmi khairuddin | aprilia | 22 | +1:16.029 | 18 | 1 | | 15 | 16 | 84 | jakub kornfeil | aprilia | 22 | +1:26.441 | 28 | none | | 16 | 17 | 69 | louis rossi | aprilia | 22 | +1:33.613 | 24 | none | | 17 | 18 | 87 | luca marconi | aprilia | 22 | +1:36.186 | 25 | none | | 18 | 19 | 58 | joan perello | honda | 22 | +1:36.223 | 26 | none | | 19 | 20 | 60 | michael van der mark | lambretta | 22 | +1:36.340 | 27 | none | | 20 | 21 | 59 | johnny rosell | honda | 22 | +1:43.804 | 22 | none | | 21 | 22 | 72 | marco ravaioli | lambretta | 22 | +1:55.331 | 30 | none | | 22 | 23 | 56 | peter sebestyen | aprilia | 21 | +1 lap | 32 | none | | 23 | ret | 40 | nicolas terol | aprilia | 21 | accident | 4 | none | | 24 | ret | 39 | luis salom | aprilia | 14 | retirement | 15 | none | | 25 | ret | 17 | eduard lopez | aprilia | 11 | retirement | 31 | none | | 26 | ret | 55 | isaac vinales | aprilia | 10 | accident | 21 | none | | 27 | ret | 50 | sturla fagerhaug | aprilia | 7 | accident | 17 | none | | 28 | ret | 5 | alexis masbou | aprilia | 5 | accident | 9 | none | | 29 | ret | 12 | esteve rabat | aprilia | 0 | accident | 7 | none | | 30 | ret | 53 | jasper iwema | aprilia | 0 | accident | 20 | none | | 31 | dns | 32 | lorenzo savadori | aprilia | none | did not start | 29 | none |

| | count ( "pos" ) | |---:|------------------:| | 0 | 24 |

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select diver where diver = 'tine tollan (nor)' col : rank | diver | preliminary points | preliminary rank | final points row 1 : 1 | sylvie bernier (can) | 489.51 | 3 | 530.7 row 2 : 2 | kelly mccormick (usa) | 516.75 | 2 | 527.46 row 3 : 3 | christina seufert (usa) | 481.41 | 5 | 517.62 row 4 : 4 | li yihua (chn) | 517.92 | 1 | 506.52 row 5 : 5 | li qiaoxian (chn) | 466.83 | 6 | 487.68 row 6 : 6 | elsa tenorio (mex) | 460.56 | 8 | 463.56 row 7 : 7 | lesley smith (zim) | 438.72 | 10 | 451.89 row 8 : 8 | debbie fuller (can) | 437.04 | 11 | 450.99 row 9 : 9 | jennifer donnet (aus) | 432.78 | 12 | 443.13 row 10 : 10 | daphne jongejans (ned) | 487.95 | 4 | 437.4 row 11 : 11 | anita rossing (swe) | 464.58 | 7 | 424.98 row 12 : 12 | veronica ribot (arg) | 443.25 | 9 | 422.52 row 13 : 13 | ann fargher (nzl) | 421.65 | 13 | none row 14 : 14 | tine tollan (nor) | 419.55 | 14 | none row 15 : 15 | antonette wilken (zim) | 414.66 | 15 | none row 16 : 16 | guadalupe canseco (mex) | 411.96 | 16 | none row 17 : 17 | claire izacard (fra) | 403.17 | 17 | none row 18 : 18 | valerie mcfarland-beddoe (aus) | 401.13 | 18 | none row 19 : 19 | alison childs (gbr) | 400.68 | 19 | none row 20 : 20 | kerstin finke (frg) | 393.93 | 20 | none row 21 : 21 | nicole kreil (aut) | 382.68 | 21 | none row 22 : 22 | joana figueiredo (por) | 374.07 | 22 | none row 23 : 23 | angela ribeiro (bra) | 370.68 | 23 | none row 24 : 24 | rim hassan (egy) | 258.63 | 24 | none

col : diver row 1 : tine tollan (nor)

select diver where diver = 'tine tollan (nor)' <table_name> : table \begin{tabular}{llllll} \toprule & rank & diver & preliminary points & preliminary rank & final points \\ \midrule 0 & 1 & sylvie bernier (can) & 489.51 & 3 & 530.7 \\ 1 & 2 & kelly mccormick (usa) & 516.75 & 2 & 527.46 \\ 2 & 3 & christina seufert (usa) & 481.41 & 5 & 517.62 \\ 3 & 4 & li yihua (chn) & 517.92 & 1 & 506.52 \\ 4 & 5 & li qiaoxian (chn) & 466.83 & 6 & 487.68 \\ 5 & 6 & elsa tenorio (mex) & 460.56 & 8 & 463.56 \\ 6 & 7 & lesley smith (zim) & 438.72 & 10 & 451.89 \\ 7 & 8 & debbie fuller (can) & 437.04 & 11 & 450.99 \\ 8 & 9 & jennifer donnet (aus) & 432.78 & 12 & 443.13 \\ 9 & 10 & daphne jongejans (ned) & 487.95 & 4 & 437.4 \\ 10 & 11 & anita rossing (swe) & 464.58 & 7 & 424.98 \\ 11 & 12 & veronica ribot (arg) & 443.25 & 9 & 422.52 \\ 12 & 13 & ann fargher (nzl) & 421.65 & 13 & none \\ 13 & 14 & tine tollan (nor) & 419.55 & 14 & none \\ 14 & 15 & antonette wilken (zim) & 414.66 & 15 & none \\ 15 & 16 & guadalupe canseco (mex) & 411.96 & 16 & none \\ 16 & 17 & claire izacard (fra) & 403.17 & 17 & none \\ 17 & 18 & valerie mcfarland-beddoe (aus) & 401.13 & 18 & none \\ 18 & 19 & alison childs (gbr) & 400.68 & 19 & none \\ 19 & 20 & kerstin finke (frg) & 393.93 & 20 & none \\ 20 & 21 & nicole kreil (aut) & 382.68 & 21 & none \\ 21 & 22 & joana figueiredo (por) & 374.07 & 22 & none \\ 22 & 23 & angela ribeiro (bra) & 370.68 & 23 & none \\ 23 & 24 & rim hassan (egy) & 258.63 & 24 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & diver \\ \midrule 0 & tine tollan (nor) \\ \bottomrule \end{tabular}

select diver where diver = 'tine tollan (nor)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>diver</th> <th>preliminary points</th> <th>preliminary rank</th> <th>final points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>sylvie bernier (can)</td> <td>489.51</td> <td>3</td> <td>530.7</td> </tr> <tr> <th>1</th> <td>2</td> <td>kelly mccormick (usa)</td> <td>516.75</td> <td>2</td> <td>527.46</td> </tr> <tr> <th>2</th> <td>3</td> <td>christina seufert (usa)</td> <td>481.41</td> <td>5</td> <td>517.62</td> </tr> <tr> <th>3</th> <td>4</td> <td>li yihua (chn)</td> <td>517.92</td> <td>1</td> <td>506.52</td> </tr> <tr> <th>4</th> <td>5</td> <td>li qiaoxian (chn)</td> <td>466.83</td> <td>6</td> <td>487.68</td> </tr> <tr> <th>5</th> <td>6</td> <td>elsa tenorio (mex)</td> <td>460.56</td> <td>8</td> <td>463.56</td> </tr> <tr> <th>6</th> <td>7</td> <td>lesley smith (zim)</td> <td>438.72</td> <td>10</td> <td>451.89</td> </tr> <tr> <th>7</th> <td>8</td> <td>debbie fuller (can)</td> <td>437.04</td> <td>11</td> <td>450.99</td> </tr> <tr> <th>8</th> <td>9</td> <td>jennifer donnet (aus)</td> <td>432.78</td> <td>12</td> <td>443.13</td> </tr> <tr> <th>9</th> <td>10</td> <td>daphne jongejans (ned)</td> <td>487.95</td> <td>4</td> <td>437.4</td> </tr> <tr> <th>10</th> <td>11</td> <td>anita rossing (swe)</td> <td>464.58</td> <td>7</td> <td>424.98</td> </tr> <tr> <th>11</th> <td>12</td> <td>veronica ribot (arg)</td> <td>443.25</td> <td>9</td> <td>422.52</td> </tr> <tr> <th>12</th> <td>13</td> <td>ann fargher (nzl)</td> <td>421.65</td> <td>13</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>tine tollan (nor)</td> <td>419.55</td> <td>14</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>antonette wilken (zim)</td> <td>414.66</td> <td>15</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>guadalupe canseco (mex)</td> <td>411.96</td> <td>16</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>claire izacard (fra)</td> <td>403.17</td> <td>17</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>valerie mcfarland-beddoe (aus)</td> <td>401.13</td> <td>18</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>alison childs (gbr)</td> <td>400.68</td> <td>19</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>kerstin finke (frg)</td> <td>393.93</td> <td>20</td> <td>none</td> </tr> <tr> <th>20</th> <td>21</td> <td>nicole kreil (aut)</td> <td>382.68</td> <td>21</td> <td>none</td> </tr> <tr> <th>21</th> <td>22</td> <td>joana figueiredo (por)</td> <td>374.07</td> <td>22</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>angela ribeiro (bra)</td> <td>370.68</td> <td>23</td> <td>none</td> </tr> <tr> <th>23</th> <td>24</td> <td>rim hassan (egy)</td> <td>258.63</td> <td>24</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>diver</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>tine tollan (nor)</td> </tr> </tbody> </table>

select diver where diver = 'tine tollan (nor)' <table_name> : table | | rank | diver | preliminary points | preliminary rank | final points | |---:|-------:|:-------------------------------|---------------------:|-------------------:|:---------------| | 0 | 1 | sylvie bernier (can) | 489.51 | 3 | 530.7 | | 1 | 2 | kelly mccormick (usa) | 516.75 | 2 | 527.46 | | 2 | 3 | christina seufert (usa) | 481.41 | 5 | 517.62 | | 3 | 4 | li yihua (chn) | 517.92 | 1 | 506.52 | | 4 | 5 | li qiaoxian (chn) | 466.83 | 6 | 487.68 | | 5 | 6 | elsa tenorio (mex) | 460.56 | 8 | 463.56 | | 6 | 7 | lesley smith (zim) | 438.72 | 10 | 451.89 | | 7 | 8 | debbie fuller (can) | 437.04 | 11 | 450.99 | | 8 | 9 | jennifer donnet (aus) | 432.78 | 12 | 443.13 | | 9 | 10 | daphne jongejans (ned) | 487.95 | 4 | 437.4 | | 10 | 11 | anita rossing (swe) | 464.58 | 7 | 424.98 | | 11 | 12 | veronica ribot (arg) | 443.25 | 9 | 422.52 | | 12 | 13 | ann fargher (nzl) | 421.65 | 13 | none | | 13 | 14 | tine tollan (nor) | 419.55 | 14 | none | | 14 | 15 | antonette wilken (zim) | 414.66 | 15 | none | | 15 | 16 | guadalupe canseco (mex) | 411.96 | 16 | none | | 16 | 17 | claire izacard (fra) | 403.17 | 17 | none | | 17 | 18 | valerie mcfarland-beddoe (aus) | 401.13 | 18 | none | | 18 | 19 | alison childs (gbr) | 400.68 | 19 | none | | 19 | 20 | kerstin finke (frg) | 393.93 | 20 | none | | 20 | 21 | nicole kreil (aut) | 382.68 | 21 | none | | 21 | 22 | joana figueiredo (por) | 374.07 | 22 | none | | 22 | 23 | angela ribeiro (bra) | 370.68 | 23 | none | | 23 | 24 | rim hassan (egy) | 258.63 | 24 | none |

| | diver | |---:|:------------------| | 0 | tine tollan (nor) |

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col : position row 1 : 1 row 2 : 10 row 3 : 35

select position where chart = 'mainstream rock tracks' <table_name> : table \begin{tabular}{lllll} \toprule & year & single & chart & position \\ \midrule 0 & 1999 & "heavy" & billboard hot 100 & 73 \\ 1 & 1999 & "heavy" & mainstream rock tracks & 1 \\ 2 & 1999 & "heavy" & modern rock tracks & 5 \\ 3 & 1999 & "run" & billboard hot 100 & 76 \\ 4 & 1999 & "run" & modern rock tracks & 36 \\ 5 & 1999 & "run" & adult top 40 & 12 \\ 6 & 1999 & "no more, no less" & mainstream rock tracks & 10 \\ 7 & 1999 & "no more, no less" & modern rock tracks & 32 \\ 8 & 1999 & "tremble for my beloved" & mainstream rock tracks & 35 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & position \\ \midrule 0 & 1 \\ 1 & 10 \\ 2 & 35 \\ \bottomrule \end{tabular}

select position where chart = 'mainstream rock tracks' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>single</th> <th>chart</th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>"heavy"</td> <td>billboard hot 100</td> <td>73</td> </tr> <tr> <th>1</th> <td>1999</td> <td>"heavy"</td> <td>mainstream rock tracks</td> <td>1</td> </tr> <tr> <th>2</th> <td>1999</td> <td>"heavy"</td> <td>modern rock tracks</td> <td>5</td> </tr> <tr> <th>3</th> <td>1999</td> <td>"run"</td> <td>billboard hot 100</td> <td>76</td> </tr> <tr> <th>4</th> <td>1999</td> <td>"run"</td> <td>modern rock tracks</td> <td>36</td> </tr> <tr> <th>5</th> <td>1999</td> <td>"run"</td> <td>adult top 40</td> <td>12</td> </tr> <tr> <th>6</th> <td>1999</td> <td>"no more, no less"</td> <td>mainstream rock tracks</td> <td>10</td> </tr> <tr> <th>7</th> <td>1999</td> <td>"no more, no less"</td> <td>modern rock tracks</td> <td>32</td> </tr> <tr> <th>8</th> <td>1999</td> <td>"tremble for my beloved"</td> <td>mainstream rock tracks</td> <td>35</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>position</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> <tr> <th>1</th> <td>10</td> </tr> <tr> <th>2</th> <td>35</td> </tr> </tbody> </table>

select position where chart = 'mainstream rock tracks' <table_name> : table | | year | single | chart | position | |---:|-------:|:-------------------------|:-----------------------|-----------:| | 0 | 1999 | "heavy" | billboard hot 100 | 73 | | 1 | 1999 | "heavy" | mainstream rock tracks | 1 | | 2 | 1999 | "heavy" | modern rock tracks | 5 | | 3 | 1999 | "run" | billboard hot 100 | 76 | | 4 | 1999 | "run" | modern rock tracks | 36 | | 5 | 1999 | "run" | adult top 40 | 12 | | 6 | 1999 | "no more, no less" | mainstream rock tracks | 10 | | 7 | 1999 | "no more, no less" | modern rock tracks | 32 | | 8 | 1999 | "tremble for my beloved" | mainstream rock tracks | 35 |

| | position | |---:|-----------:| | 0 | 1 | | 1 | 10 | | 2 | 35 |

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select count ( nation ) where nation = 'switzerland' and gold > 1783 col : rank | nation | gold | silver | bronze | total row 1 : 1 | canada | 9 | 6 | 5 | 20 row 2 : 2 | united states | 8 | 7 | 8 | 23 row 3 : 3 | austria | 7 | 9 | 8 | 24 row 4 : 4 | japan | 4 | 2 | 1 | 7 row 5 : 5 | italy | 3 | 7 | 4 | 14 row 6 : 6 | france | 3 | 4 | 4 | 11 row 7 : 7 | australia | 3 | 4 | 0 | 7 row 8 : 8 | norway | 2 | 2 | 2 | 6 row 9 : 9 | slovenia | 2 | 1 | 2 | 5 row 10 : 10 | finland | 2 | 1 | 1 | 4 row 11 : 10 | germany | 2 | 1 | 1 | 4 row 12 : 12 | russia | 2 | 0 | 3 | 5 row 13 : 13 | switzerland | 1 | 5 | 5 | 11 row 14 : 14 | china | 1 | 1 | 1 | 3 row 15 : 15 | poland | 1 | 1 | 0 | 2 row 16 : 16 | czech republic | 1 | 0 | 1 | 2 row 17 : 17 | belgium | 1 | 0 | 0 | 1 row 18 : 18 | netherlands | 0 | 1 | 0 | 1 row 19 : 19 | spain | 0 | 0 | 3 | 3 row 20 : 20 | bulgaria | 0 | 0 | 1 | 1 row 21 : 20 | great britain | 0 | 0 | 1 | 1 row 22 : 20 | sweden | 0 | 0 | 1 | 1 row 23 : total | total | 52 | 52 | 52 | 156

col : count ( "nation" ) row 1 : 0

select count ( nation ) where nation = 'switzerland' and gold > 1783 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & canada & 9 & 6 & 5 & 20 \\ 1 & 2 & united states & 8 & 7 & 8 & 23 \\ 2 & 3 & austria & 7 & 9 & 8 & 24 \\ 3 & 4 & japan & 4 & 2 & 1 & 7 \\ 4 & 5 & italy & 3 & 7 & 4 & 14 \\ 5 & 6 & france & 3 & 4 & 4 & 11 \\ 6 & 7 & australia & 3 & 4 & 0 & 7 \\ 7 & 8 & norway & 2 & 2 & 2 & 6 \\ 8 & 9 & slovenia & 2 & 1 & 2 & 5 \\ 9 & 10 & finland & 2 & 1 & 1 & 4 \\ 10 & 10 & germany & 2 & 1 & 1 & 4 \\ 11 & 12 & russia & 2 & 0 & 3 & 5 \\ 12 & 13 & switzerland & 1 & 5 & 5 & 11 \\ 13 & 14 & china & 1 & 1 & 1 & 3 \\ 14 & 15 & poland & 1 & 1 & 0 & 2 \\ 15 & 16 & czech republic & 1 & 0 & 1 & 2 \\ 16 & 17 & belgium & 1 & 0 & 0 & 1 \\ 17 & 18 & netherlands & 0 & 1 & 0 & 1 \\ 18 & 19 & spain & 0 & 0 & 3 & 3 \\ 19 & 20 & bulgaria & 0 & 0 & 1 & 1 \\ 20 & 20 & great britain & 0 & 0 & 1 & 1 \\ 21 & 20 & sweden & 0 & 0 & 1 & 1 \\ 22 & total & total & 52 & 52 & 52 & 156 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "nation" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( nation ) where nation = 'switzerland' and gold > 1783 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>canada</td> <td>9</td> <td>6</td> <td>5</td> <td>20</td> </tr> <tr> <th>1</th> <td>2</td> <td>united states</td> <td>8</td> <td>7</td> <td>8</td> <td>23</td> </tr> <tr> <th>2</th> <td>3</td> <td>austria</td> <td>7</td> <td>9</td> <td>8</td> <td>24</td> </tr> <tr> <th>3</th> <td>4</td> <td>japan</td> <td>4</td> <td>2</td> <td>1</td> <td>7</td> </tr> <tr> <th>4</th> <td>5</td> <td>italy</td> <td>3</td> <td>7</td> <td>4</td> <td>14</td> </tr> <tr> <th>5</th> <td>6</td> <td>france</td> <td>3</td> <td>4</td> <td>4</td> <td>11</td> </tr> <tr> <th>6</th> <td>7</td> <td>australia</td> <td>3</td> <td>4</td> <td>0</td> <td>7</td> </tr> <tr> <th>7</th> <td>8</td> <td>norway</td> <td>2</td> <td>2</td> <td>2</td> <td>6</td> </tr> <tr> <th>8</th> <td>9</td> <td>slovenia</td> <td>2</td> <td>1</td> <td>2</td> <td>5</td> </tr> <tr> <th>9</th> <td>10</td> <td>finland</td> <td>2</td> <td>1</td> <td>1</td> <td>4</td> </tr> <tr> <th>10</th> <td>10</td> <td>germany</td> <td>2</td> <td>1</td> <td>1</td> <td>4</td> </tr> <tr> <th>11</th> <td>12</td> <td>russia</td> <td>2</td> <td>0</td> <td>3</td> <td>5</td> </tr> <tr> <th>12</th> <td>13</td> <td>switzerland</td> <td>1</td> <td>5</td> <td>5</td> <td>11</td> </tr> <tr> <th>13</th> <td>14</td> <td>china</td> <td>1</td> <td>1</td> <td>1</td> <td>3</td> </tr> <tr> <th>14</th> <td>15</td> <td>poland</td> <td>1</td> <td>1</td> <td>0</td> <td>2</td> </tr> <tr> <th>15</th> <td>16</td> <td>czech republic</td> <td>1</td> <td>0</td> <td>1</td> <td>2</td> </tr> <tr> <th>16</th> <td>17</td> <td>belgium</td> <td>1</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>17</th> <td>18</td> <td>netherlands</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>18</th> <td>19</td> <td>spain</td> <td>0</td> <td>0</td> <td>3</td> <td>3</td> </tr> <tr> <th>19</th> <td>20</td> <td>bulgaria</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>20</th> <td>20</td> <td>great britain</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>21</th> <td>20</td> <td>sweden</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>22</th> <td>total</td> <td>total</td> <td>52</td> <td>52</td> <td>52</td> <td>156</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "nation" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( nation ) where nation = 'switzerland' and gold > 1783 <table_name> : table | | rank | nation | gold | silver | bronze | total | |---:|:-------|:---------------|-------:|---------:|---------:|--------:| | 0 | 1 | canada | 9 | 6 | 5 | 20 | | 1 | 2 | united states | 8 | 7 | 8 | 23 | | 2 | 3 | austria | 7 | 9 | 8 | 24 | | 3 | 4 | japan | 4 | 2 | 1 | 7 | | 4 | 5 | italy | 3 | 7 | 4 | 14 | | 5 | 6 | france | 3 | 4 | 4 | 11 | | 6 | 7 | australia | 3 | 4 | 0 | 7 | | 7 | 8 | norway | 2 | 2 | 2 | 6 | | 8 | 9 | slovenia | 2 | 1 | 2 | 5 | | 9 | 10 | finland | 2 | 1 | 1 | 4 | | 10 | 10 | germany | 2 | 1 | 1 | 4 | | 11 | 12 | russia | 2 | 0 | 3 | 5 | | 12 | 13 | switzerland | 1 | 5 | 5 | 11 | | 13 | 14 | china | 1 | 1 | 1 | 3 | | 14 | 15 | poland | 1 | 1 | 0 | 2 | | 15 | 16 | czech republic | 1 | 0 | 1 | 2 | | 16 | 17 | belgium | 1 | 0 | 0 | 1 | | 17 | 18 | netherlands | 0 | 1 | 0 | 1 | | 18 | 19 | spain | 0 | 0 | 3 | 3 | | 19 | 20 | bulgaria | 0 | 0 | 1 | 1 | | 20 | 20 | great britain | 0 | 0 | 1 | 1 | | 21 | 20 | sweden | 0 | 0 | 1 | 1 | | 22 | total | total | 52 | 52 | 52 | 156 |

| | count ( "nation" ) | |---:|---------------------:| | 0 | 0 |

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select count ( * ) where country = 'italy' and points < '38.66' col : rank | athlete | country | time | behind | points row 1 : 1 | sven kramer | netherlands | 01:53.98 | 0.0 | 37.993 row 2 : 2 | sverre lunde pedersen | norway | 1:54.87 | 0.89 | 38.29 row 3 : 3 | jan blokhuijsen | netherlands | 1:54.93 | 0.95 | 38.31 row 4 : 4 | denis yuskov | russia | 1:55.13 | 1.15 | 38.376 row 5 : 5 | koen verweij | netherlands | 1:55.42 | 1.44 | 38.473 row 6 : 6 | haralds silovs | latvia | 1:55.48 | 1.5 | 38.493 row 7 : 7 | zbigniew brodka | poland | 1:55.98 | 2.0 | 38.66 row 8 : 8 | bart swings | belgium | 1:56.08 | 2.1 | 38.693 row 9 : 9 | havard bøkko | norway | 1:56.35 | 2.37 | 38.783 row 10 : 10 | jan szymanski | poland | 1:56.55 | 2.57 | 38.85 row 11 : 11 | bram smallenbroek | austria | 1:57.44 | 3.46 | 39.146 row 12 : 12 | alexis contin | france | 1:57.58 | 3.6 | 39.193 row 13 : 13 | benjamin mace | france | 1:57.80 | 3.82 | 39.266 row 14 : 14 | konrad niedzwiedzki | poland | 1:57.92 | 3.94 | 39.306 row 15 : 15 | sergey gryaztsov | russia | 1:58.73 | 4.75 | 39.576 row 16 : 16 | patrick beckert | germany | 1:59.08 | 5.1 | 39.693 row 17 : 17 | kristian reistad fredriksen | norway | 1:59.19 | 5.21 | 39.73 row 18 : 18 | luca stefani | italy | 1:59.82 | 5.84 | 39.94 row 19 : 19 | marco cignini | italy | 1:59.97 | 5.99 | 39.99 row 20 : 20 | ferre spruyt | belgium | 2:00.00 | 6.02 | 40.0 row 21 : 21 | vitaly mikhailov | belarus | 2:00.75 | 6.77 | 40.52 row 22 : 22 | milan sablik | czech republic | 2:00.95 | 6.97 | 40.316 row 23 : 23 | ted jan bloemen | netherlands | 2:01.58 | 7.6 | 40.526 row 24 : 24 | moritz geisreiter | germany | 2:01.64 | 7.66 | 40.566

col : count ( "*" ) row 1 : 0

select count ( * ) where country = 'italy' and points < '38.66' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & athlete & country & time & behind & points \\ \midrule 0 & 1 & sven kramer & netherlands & 01:53.98 & 0.0 & 37.993 \\ 1 & 2 & sverre lunde pedersen & norway & 1:54.87 & 0.89 & 38.29 \\ 2 & 3 & jan blokhuijsen & netherlands & 1:54.93 & 0.95 & 38.31 \\ 3 & 4 & denis yuskov & russia & 1:55.13 & 1.15 & 38.376 \\ 4 & 5 & koen verweij & netherlands & 1:55.42 & 1.44 & 38.473 \\ 5 & 6 & haralds silovs & latvia & 1:55.48 & 1.5 & 38.493 \\ 6 & 7 & zbigniew brodka & poland & 1:55.98 & 2.0 & 38.66 \\ 7 & 8 & bart swings & belgium & 1:56.08 & 2.1 & 38.693 \\ 8 & 9 & havard bøkko & norway & 1:56.35 & 2.37 & 38.783 \\ 9 & 10 & jan szymanski & poland & 1:56.55 & 2.57 & 38.85 \\ 10 & 11 & bram smallenbroek & austria & 1:57.44 & 3.46 & 39.146 \\ 11 & 12 & alexis contin & france & 1:57.58 & 3.6 & 39.193 \\ 12 & 13 & benjamin mace & france & 1:57.80 & 3.82 & 39.266 \\ 13 & 14 & konrad niedzwiedzki & poland & 1:57.92 & 3.94 & 39.306 \\ 14 & 15 & sergey gryaztsov & russia & 1:58.73 & 4.75 & 39.576 \\ 15 & 16 & patrick beckert & germany & 1:59.08 & 5.1 & 39.693 \\ 16 & 17 & kristian reistad fredriksen & norway & 1:59.19 & 5.21 & 39.73 \\ 17 & 18 & luca stefani & italy & 1:59.82 & 5.84 & 39.94 \\ 18 & 19 & marco cignini & italy & 1:59.97 & 5.99 & 39.99 \\ 19 & 20 & ferre spruyt & belgium & 2:00.00 & 6.02 & 40.0 \\ 20 & 21 & vitaly mikhailov & belarus & 2:00.75 & 6.77 & 40.52 \\ 21 & 22 & milan sablik & czech republic & 2:00.95 & 6.97 & 40.316 \\ 22 & 23 & ted jan bloemen & netherlands & 2:01.58 & 7.6 & 40.526 \\ 23 & 24 & moritz geisreiter & germany & 2:01.64 & 7.66 & 40.566 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where country = 'italy' and points < '38.66' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>athlete</th> <th>country</th> <th>time</th> <th>behind</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>sven kramer</td> <td>netherlands</td> <td>01:53.98</td> <td>0.0</td> <td>37.993</td> </tr> <tr> <th>1</th> <td>2</td> <td>sverre lunde pedersen</td> <td>norway</td> <td>1:54.87</td> <td>0.89</td> <td>38.29</td> </tr> <tr> <th>2</th> <td>3</td> <td>jan blokhuijsen</td> <td>netherlands</td> <td>1:54.93</td> <td>0.95</td> <td>38.31</td> </tr> <tr> <th>3</th> <td>4</td> <td>denis yuskov</td> <td>russia</td> <td>1:55.13</td> <td>1.15</td> <td>38.376</td> </tr> <tr> <th>4</th> <td>5</td> <td>koen verweij</td> <td>netherlands</td> <td>1:55.42</td> <td>1.44</td> <td>38.473</td> </tr> <tr> <th>5</th> <td>6</td> <td>haralds silovs</td> <td>latvia</td> <td>1:55.48</td> <td>1.5</td> <td>38.493</td> </tr> <tr> <th>6</th> <td>7</td> <td>zbigniew brodka</td> <td>poland</td> <td>1:55.98</td> <td>2.0</td> <td>38.66</td> </tr> <tr> <th>7</th> <td>8</td> <td>bart swings</td> <td>belgium</td> <td>1:56.08</td> <td>2.1</td> <td>38.693</td> </tr> <tr> <th>8</th> <td>9</td> <td>havard bøkko</td> <td>norway</td> <td>1:56.35</td> <td>2.37</td> <td>38.783</td> </tr> <tr> <th>9</th> <td>10</td> <td>jan szymanski</td> <td>poland</td> <td>1:56.55</td> <td>2.57</td> <td>38.85</td> </tr> <tr> <th>10</th> <td>11</td> <td>bram smallenbroek</td> <td>austria</td> <td>1:57.44</td> <td>3.46</td> <td>39.146</td> </tr> <tr> <th>11</th> <td>12</td> <td>alexis contin</td> <td>france</td> <td>1:57.58</td> <td>3.6</td> <td>39.193</td> </tr> <tr> <th>12</th> <td>13</td> <td>benjamin mace</td> <td>france</td> <td>1:57.80</td> <td>3.82</td> <td>39.266</td> </tr> <tr> <th>13</th> <td>14</td> <td>konrad niedzwiedzki</td> <td>poland</td> <td>1:57.92</td> <td>3.94</td> <td>39.306</td> </tr> <tr> <th>14</th> <td>15</td> <td>sergey gryaztsov</td> <td>russia</td> <td>1:58.73</td> <td>4.75</td> <td>39.576</td> </tr> <tr> <th>15</th> <td>16</td> <td>patrick beckert</td> <td>germany</td> <td>1:59.08</td> <td>5.1</td> <td>39.693</td> </tr> <tr> <th>16</th> <td>17</td> <td>kristian reistad fredriksen</td> <td>norway</td> <td>1:59.19</td> <td>5.21</td> <td>39.73</td> </tr> <tr> <th>17</th> <td>18</td> <td>luca stefani</td> <td>italy</td> <td>1:59.82</td> <td>5.84</td> <td>39.94</td> </tr> <tr> <th>18</th> <td>19</td> <td>marco cignini</td> <td>italy</td> <td>1:59.97</td> <td>5.99</td> <td>39.99</td> </tr> <tr> <th>19</th> <td>20</td> <td>ferre spruyt</td> <td>belgium</td> <td>2:00.00</td> <td>6.02</td> <td>40.0</td> </tr> <tr> <th>20</th> <td>21</td> <td>vitaly mikhailov</td> <td>belarus</td> <td>2:00.75</td> <td>6.77</td> <td>40.52</td> </tr> <tr> <th>21</th> <td>22</td> <td>milan sablik</td> <td>czech republic</td> <td>2:00.95</td> <td>6.97</td> <td>40.316</td> </tr> <tr> <th>22</th> <td>23</td> <td>ted jan bloemen</td> <td>netherlands</td> <td>2:01.58</td> <td>7.6</td> <td>40.526</td> </tr> <tr> <th>23</th> <td>24</td> <td>moritz geisreiter</td> <td>germany</td> <td>2:01.64</td> <td>7.66</td> <td>40.566</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where country = 'italy' and points < '38.66' <table_name> : table | | rank | athlete | country | time | behind | points | |---:|-------:|:----------------------------|:---------------|:---------|---------:|---------:| | 0 | 1 | sven kramer | netherlands | 01:53.98 | 0 | 37.993 | | 1 | 2 | sverre lunde pedersen | norway | 1:54.87 | 0.89 | 38.29 | | 2 | 3 | jan blokhuijsen | netherlands | 1:54.93 | 0.95 | 38.31 | | 3 | 4 | denis yuskov | russia | 1:55.13 | 1.15 | 38.376 | | 4 | 5 | koen verweij | netherlands | 1:55.42 | 1.44 | 38.473 | | 5 | 6 | haralds silovs | latvia | 1:55.48 | 1.5 | 38.493 | | 6 | 7 | zbigniew brodka | poland | 1:55.98 | 2 | 38.66 | | 7 | 8 | bart swings | belgium | 1:56.08 | 2.1 | 38.693 | | 8 | 9 | havard bøkko | norway | 1:56.35 | 2.37 | 38.783 | | 9 | 10 | jan szymanski | poland | 1:56.55 | 2.57 | 38.85 | | 10 | 11 | bram smallenbroek | austria | 1:57.44 | 3.46 | 39.146 | | 11 | 12 | alexis contin | france | 1:57.58 | 3.6 | 39.193 | | 12 | 13 | benjamin mace | france | 1:57.80 | 3.82 | 39.266 | | 13 | 14 | konrad niedzwiedzki | poland | 1:57.92 | 3.94 | 39.306 | | 14 | 15 | sergey gryaztsov | russia | 1:58.73 | 4.75 | 39.576 | | 15 | 16 | patrick beckert | germany | 1:59.08 | 5.1 | 39.693 | | 16 | 17 | kristian reistad fredriksen | norway | 1:59.19 | 5.21 | 39.73 | | 17 | 18 | luca stefani | italy | 1:59.82 | 5.84 | 39.94 | | 18 | 19 | marco cignini | italy | 1:59.97 | 5.99 | 39.99 | | 19 | 20 | ferre spruyt | belgium | 2:00.00 | 6.02 | 40 | | 20 | 21 | vitaly mikhailov | belarus | 2:00.75 | 6.77 | 40.52 | | 21 | 22 | milan sablik | czech republic | 2:00.95 | 6.97 | 40.316 | | 22 | 23 | ted jan bloemen | netherlands | 2:01.58 | 7.6 | 40.526 | | 23 | 24 | moritz geisreiter | germany | 2:01.64 | 7.66 | 40.566 |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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select count ( nurse : population ratio ) where mid wife: population ratio = 8 col : region | physician (gp & specialist) | physician : population ratio | health officer | ho : population ratio | all nurses | nurse : population ratio | mid-wives | mid wife: population ratio | hew | hew : population ratio row 1 : tigray | 101 | 1:44,880 | 188 | 1:24,111 | 2332 | 1:1,944 | 185 | 1:24,502 | 1433 | 1:3,163 row 2 : afar | 15 | 1:98,258 | 29 | 1:50,823 | 185 | 1:7,967 | none | none | 572 | 1:2,577 row 3 : amhara | 304 | 1:58,567 | 434 | 1:41,024 | 3790 | 1:4,698 | 212 | 1:83,983 | 7471 | 1:2,383 row 4 : oromia | 378 | 1:76,075 | 448 | 1:64,189 | 5040 | 1:5,706 | 287 | 1:100,197 | 13856 | 1:2,075 row 5 : somalia | 71 | 1:65,817 | 12 | 1:389,415 | 314 | 1:14,882 | 45 | 1:103,844 | 1427 | 1:3,275 row 6 : ben-gumuz | 12 | 1:59,309 | 42 | 1:16,945 | 452 | 1:1,575 | 37 | 1:19,235 | 499 | 1:1,426 row 7 : snnpr | 242 | 1:65,817 | 220 | 1:72,398 | 3980 | 1:4,002 | 316 | 1:50,404 | 7915 | 1:2,012 row 8 : gambella | 13 | 1:25,585 | 13 | 1:25,585 | 91 | 1:3,655 | 4 | 1:83,150 | 457 | 1:728 row 9 : harari | 29 | 1:6,655 | 31 | 1:6,226 | 276 | 1:699 | 29 | 1:6,655 | 47 | 1:4,106 row 10 : addis ababa | 934 | 1:3,056 | 170 | 1:16,791 | 3377 | 1:845 | 244 | 1:11,699 | none | none row 11 : diredawa | 53 | 1:6,796 | 19 | 1:18,957 | 272 | 1:1,324 | 20 | 1:18,009 | 142 | 1:2,537

col : count ( "nurse : population ratio" ) row 1 : 0

select count ( nurse : population ratio ) where mid wife: population ratio = 8 <table_name> : table \begin{tabular}{llllllllllll} \toprule & region & physician (gp & specialist) & physician : population ratio & health officer & ho : population ratio & all nurses & nurse : population ratio & mid-wives & mid wife: population ratio & hew & hew : population ratio \\ \midrule 0 & tigray & 101 & 1:44,880 & 188 & 1:24,111 & 2332 & 1:1,944 & 185 & 1:24,502 & 1433 & 1:3,163 \\ 1 & afar & 15 & 1:98,258 & 29 & 1:50,823 & 185 & 1:7,967 & none & none & 572 & 1:2,577 \\ 2 & amhara & 304 & 1:58,567 & 434 & 1:41,024 & 3790 & 1:4,698 & 212 & 1:83,983 & 7471 & 1:2,383 \\ 3 & oromia & 378 & 1:76,075 & 448 & 1:64,189 & 5040 & 1:5,706 & 287 & 1:100,197 & 13856 & 1:2,075 \\ 4 & somalia & 71 & 1:65,817 & 12 & 1:389,415 & 314 & 1:14,882 & 45 & 1:103,844 & 1427 & 1:3,275 \\ 5 & ben-gumuz & 12 & 1:59,309 & 42 & 1:16,945 & 452 & 1:1,575 & 37 & 1:19,235 & 499 & 1:1,426 \\ 6 & snnpr & 242 & 1:65,817 & 220 & 1:72,398 & 3980 & 1:4,002 & 316 & 1:50,404 & 7915 & 1:2,012 \\ 7 & gambella & 13 & 1:25,585 & 13 & 1:25,585 & 91 & 1:3,655 & 4 & 1:83,150 & 457 & 1:728 \\ 8 & harari & 29 & 1:6,655 & 31 & 1:6,226 & 276 & 1:699 & 29 & 1:6,655 & 47 & 1:4,106 \\ 9 & addis ababa & 934 & 1:3,056 & 170 & 1:16,791 & 3377 & 1:845 & 244 & 1:11,699 & none & none \\ 10 & diredawa & 53 & 1:6,796 & 19 & 1:18,957 & 272 & 1:1,324 & 20 & 1:18,009 & 142 & 1:2,537 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "nurse \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( nurse : population ratio ) where mid wife: population ratio = 8 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>region</th> <th>physician (gp & specialist)</th> <th>physician : population ratio</th> <th>health officer</th> <th>ho : population ratio</th> <th>all nurses</th> <th>nurse : population ratio</th> <th>mid-wives</th> <th>mid wife: population ratio</th> <th>hew</th> <th>hew : population ratio</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>tigray</td> <td>101</td> <td>1:44,880</td> <td>188</td> <td>1:24,111</td> <td>2332</td> <td>1:1,944</td> <td>185</td> <td>1:24,502</td> <td>1433</td> <td>1:3,163</td> </tr> <tr> <th>1</th> <td>afar</td> <td>15</td> <td>1:98,258</td> <td>29</td> <td>1:50,823</td> <td>185</td> <td>1:7,967</td> <td>none</td> <td>none</td> <td>572</td> <td>1:2,577</td> </tr> <tr> <th>2</th> <td>amhara</td> <td>304</td> <td>1:58,567</td> <td>434</td> <td>1:41,024</td> <td>3790</td> <td>1:4,698</td> <td>212</td> <td>1:83,983</td> <td>7471</td> <td>1:2,383</td> </tr> <tr> <th>3</th> <td>oromia</td> <td>378</td> <td>1:76,075</td> <td>448</td> <td>1:64,189</td> <td>5040</td> <td>1:5,706</td> <td>287</td> <td>1:100,197</td> <td>13856</td> <td>1:2,075</td> </tr> <tr> <th>4</th> <td>somalia</td> <td>71</td> <td>1:65,817</td> <td>12</td> <td>1:389,415</td> <td>314</td> <td>1:14,882</td> <td>45</td> <td>1:103,844</td> <td>1427</td> <td>1:3,275</td> </tr> <tr> <th>5</th> <td>ben-gumuz</td> <td>12</td> <td>1:59,309</td> <td>42</td> <td>1:16,945</td> <td>452</td> <td>1:1,575</td> <td>37</td> <td>1:19,235</td> <td>499</td> <td>1:1,426</td> </tr> <tr> <th>6</th> <td>snnpr</td> <td>242</td> <td>1:65,817</td> <td>220</td> <td>1:72,398</td> <td>3980</td> <td>1:4,002</td> <td>316</td> <td>1:50,404</td> <td>7915</td> <td>1:2,012</td> </tr> <tr> <th>7</th> <td>gambella</td> <td>13</td> <td>1:25,585</td> <td>13</td> <td>1:25,585</td> <td>91</td> <td>1:3,655</td> <td>4</td> <td>1:83,150</td> <td>457</td> <td>1:728</td> </tr> <tr> <th>8</th> <td>harari</td> <td>29</td> <td>1:6,655</td> <td>31</td> <td>1:6,226</td> <td>276</td> <td>1:699</td> <td>29</td> <td>1:6,655</td> <td>47</td> <td>1:4,106</td> </tr> <tr> <th>9</th> <td>addis ababa</td> <td>934</td> <td>1:3,056</td> <td>170</td> <td>1:16,791</td> <td>3377</td> <td>1:845</td> <td>244</td> <td>1:11,699</td> <td>none</td> <td>none</td> </tr> <tr> <th>10</th> <td>diredawa</td> <td>53</td> <td>1:6,796</td> <td>19</td> <td>1:18,957</td> <td>272</td> <td>1:1,324</td> <td>20</td> <td>1:18,009</td> <td>142</td> <td>1:2,537</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "nurse</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( nurse : population ratio ) where mid wife: population ratio = 8 <table_name> : table | | region | physician (gp & specialist) | physician : population ratio | health officer | ho : population ratio | all nurses | nurse : population ratio | mid-wives | mid wife: population ratio | hew | hew : population ratio | |---:|:------------|------------------------------:|:-------------------------------|-----------------:|:------------------------|-------------:|:---------------------------|:------------|:-----------------------------|:------|:-------------------------| | 0 | tigray | 101 | 1:44,880 | 188 | 1:24,111 | 2332 | 1:1,944 | 185 | 1:24,502 | 1433 | 1:3,163 | | 1 | afar | 15 | 1:98,258 | 29 | 1:50,823 | 185 | 1:7,967 | none | none | 572 | 1:2,577 | | 2 | amhara | 304 | 1:58,567 | 434 | 1:41,024 | 3790 | 1:4,698 | 212 | 1:83,983 | 7471 | 1:2,383 | | 3 | oromia | 378 | 1:76,075 | 448 | 1:64,189 | 5040 | 1:5,706 | 287 | 1:100,197 | 13856 | 1:2,075 | | 4 | somalia | 71 | 1:65,817 | 12 | 1:389,415 | 314 | 1:14,882 | 45 | 1:103,844 | 1427 | 1:3,275 | | 5 | ben-gumuz | 12 | 1:59,309 | 42 | 1:16,945 | 452 | 1:1,575 | 37 | 1:19,235 | 499 | 1:1,426 | | 6 | snnpr | 242 | 1:65,817 | 220 | 1:72,398 | 3980 | 1:4,002 | 316 | 1:50,404 | 7915 | 1:2,012 | | 7 | gambella | 13 | 1:25,585 | 13 | 1:25,585 | 91 | 1:3,655 | 4 | 1:83,150 | 457 | 1:728 | | 8 | harari | 29 | 1:6,655 | 31 | 1:6,226 | 276 | 1:699 | 29 | 1:6,655 | 47 | 1:4,106 | | 9 | addis ababa | 934 | 1:3,056 | 170 | 1:16,791 | 3377 | 1:845 | 244 | 1:11,699 | none | none | | 10 | diredawa | 53 | 1:6,796 | 19 | 1:18,957 | 272 | 1:1,324 | 20 | 1:18,009 | 142 | 1:2,537 |

| | count ( "nurse | |---:|-----------------:| | 0 | 0 |

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col : count ( "*" ) row 1 : 0

select count ( * ) where score = 'winner' <table_name> : table \begin{tabular}{llllllll} \toprule & outcome & no. & date & tournament & surface & opponent & score \\ \midrule 0 & runner-up & 1 & 2004-08-23 00:00:00 & la paz, bolivia & clay & jenifer widjaja & 6-3, 4-6, 0-6 \\ 1 & runner-up & 2 & 2005-06-06 00:00:00 & santa tecla, el salvador & clay & andrea benitez & 3-6, 0-6 \\ 2 & runner-up & 2 & 2005-08-22 00:00:00 & bogota, colombia & clay & carla tiene & 4-6, 0-6 \\ 3 & runner-up & 4 & 2006-05-15 00:00:00 & ciudad obregon, mexico & hard & ellah nze & 6-4, 3-6, 3-6 \\ 4 & winner & 1 & 2006-06-05 00:00:00 & xalapa, mexico & hard & maria irigoyen & 6-1, 3-6, 6-4 \\ 5 & winner & 2 & 2009-09-07 00:00:00 & mazatlan, mexico & hard & fernanda hermenegildo & 6-1, 6-2 \\ 6 & winner & 3 & 2009-11-02 00:00:00 & bogota, colombia & clay & yuliana lizarazo & 7-6(7-5), 6-4 \\ 7 & runner-up & 5 & 2009-11-16 00:00:00 & asuncion, paraguay & clay & paula ormaechea & 6-4, 4-6, 2-6 \\ 8 & winner & 4 & 2010-11-08 00:00:00 & bogota, colombia & clay & patricia ku flores & 6-1, 7-5 \\ 9 & winner & 5 & 2010-11-29 00:00:00 & santiago, chile & clay & veronica cepede royg & 6-2, 6-2 \\ 10 & winner & 6 & 2011-07-18 00:00:00 & ribeirao preto, brazil & clay & vivian segnini & 6-2, 6-2 \\ 11 & runner-up & 6 & 2011-08-08 00:00:00 & santa cruz de la sierra, bolivia & clay & maria irigoyen & 2-6, 3-6 \\ 12 & winner & 7 & 2011-08-15 00:00:00 & la paz, bolivia & clay & maria irigoyen & 6-0, 7-6(7-1) \\ 13 & runner-up & 7 & 2011-10-03 00:00:00 & yerevan, armenia & clay & julia cohen & 6-7(6-8), 2-6 \\ 14 & runner-up & 8 & 2012-03-19 00:00:00 & bangalore, india & hard & donna vekic & 2-6, 4-6 \\ 15 & runner-up & 9 & 2012-05-08 00:00:00 & brasilia, brazil & clay & gabriela paz & 3-6, 3-6 \\ 16 & winner & 8 & 2012-11-19 00:00:00 & barranquilla, colombia & clay & karolina nowak & 7-6(7-4), 6-0 \\ 17 & winner & 9 & 2013-10-21 00:00:00 & bogota, colombia & hard & anna katalina alzate esmurzaeva & 6-3, 6-3 \\ 18 & winner & 10 & 2013-11-11 00:00:00 & lima, peru & clay & patricia ku flores & 7-5, 6-7(4-7), 6-2 \\ 19 & winner & 11 & 2013-11-25 00:00:00 & bogota, colombia & clay & naomi totka & 6-1, 6-1 \\ 20 & runner-up & 10 & 2013-12-02 00:00:00 & barranquilla, colombia & clay & maria fernanda herazo & 4-6, 2-6 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where score = 'winner' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>outcome</th> <th>no.</th> <th>date</th> <th>tournament</th> <th>surface</th> <th>opponent</th> <th>score</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>runner-up</td> <td>1</td> <td>2004-08-23 00:00:00</td> <td>la paz, bolivia</td> <td>clay</td> <td>jenifer widjaja</td> <td>6-3, 4-6, 0-6</td> </tr> <tr> <th>1</th> <td>runner-up</td> <td>2</td> <td>2005-06-06 00:00:00</td> <td>santa tecla, el salvador</td> <td>clay</td> <td>andrea benitez</td> <td>3-6, 0-6</td> </tr> <tr> <th>2</th> <td>runner-up</td> <td>2</td> <td>2005-08-22 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>carla tiene</td> <td>4-6, 0-6</td> </tr> <tr> <th>3</th> <td>runner-up</td> <td>4</td> <td>2006-05-15 00:00:00</td> <td>ciudad obregon, mexico</td> <td>hard</td> <td>ellah nze</td> <td>6-4, 3-6, 3-6</td> </tr> <tr> <th>4</th> <td>winner</td> <td>1</td> <td>2006-06-05 00:00:00</td> <td>xalapa, mexico</td> <td>hard</td> <td>maria irigoyen</td> <td>6-1, 3-6, 6-4</td> </tr> <tr> <th>5</th> <td>winner</td> <td>2</td> <td>2009-09-07 00:00:00</td> <td>mazatlan, mexico</td> <td>hard</td> <td>fernanda hermenegildo</td> <td>6-1, 6-2</td> </tr> <tr> <th>6</th> <td>winner</td> <td>3</td> <td>2009-11-02 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>yuliana lizarazo</td> <td>7-6(7-5), 6-4</td> </tr> <tr> <th>7</th> <td>runner-up</td> <td>5</td> <td>2009-11-16 00:00:00</td> <td>asuncion, paraguay</td> <td>clay</td> <td>paula ormaechea</td> <td>6-4, 4-6, 2-6</td> </tr> <tr> <th>8</th> <td>winner</td> <td>4</td> <td>2010-11-08 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>patricia ku flores</td> <td>6-1, 7-5</td> </tr> <tr> <th>9</th> <td>winner</td> <td>5</td> <td>2010-11-29 00:00:00</td> <td>santiago, chile</td> <td>clay</td> <td>veronica cepede royg</td> <td>6-2, 6-2</td> </tr> <tr> <th>10</th> <td>winner</td> <td>6</td> <td>2011-07-18 00:00:00</td> <td>ribeirao preto, brazil</td> <td>clay</td> <td>vivian segnini</td> <td>6-2, 6-2</td> </tr> <tr> <th>11</th> <td>runner-up</td> <td>6</td> <td>2011-08-08 00:00:00</td> <td>santa cruz de la sierra, bolivia</td> <td>clay</td> <td>maria irigoyen</td> <td>2-6, 3-6</td> </tr> <tr> <th>12</th> <td>winner</td> <td>7</td> <td>2011-08-15 00:00:00</td> <td>la paz, bolivia</td> <td>clay</td> <td>maria irigoyen</td> <td>6-0, 7-6(7-1)</td> </tr> <tr> <th>13</th> <td>runner-up</td> <td>7</td> <td>2011-10-03 00:00:00</td> <td>yerevan, armenia</td> <td>clay</td> <td>julia cohen</td> <td>6-7(6-8), 2-6</td> </tr> <tr> <th>14</th> <td>runner-up</td> <td>8</td> <td>2012-03-19 00:00:00</td> <td>bangalore, india</td> <td>hard</td> <td>donna vekic</td> <td>2-6, 4-6</td> </tr> <tr> <th>15</th> <td>runner-up</td> <td>9</td> <td>2012-05-08 00:00:00</td> <td>brasilia, brazil</td> <td>clay</td> <td>gabriela paz</td> <td>3-6, 3-6</td> </tr> <tr> <th>16</th> <td>winner</td> <td>8</td> <td>2012-11-19 00:00:00</td> <td>barranquilla, colombia</td> <td>clay</td> <td>karolina nowak</td> <td>7-6(7-4), 6-0</td> </tr> <tr> <th>17</th> <td>winner</td> <td>9</td> <td>2013-10-21 00:00:00</td> <td>bogota, colombia</td> <td>hard</td> <td>anna katalina alzate esmurzaeva</td> <td>6-3, 6-3</td> </tr> <tr> <th>18</th> <td>winner</td> <td>10</td> <td>2013-11-11 00:00:00</td> <td>lima, peru</td> <td>clay</td> <td>patricia ku flores</td> <td>7-5, 6-7(4-7), 6-2</td> </tr> <tr> <th>19</th> <td>winner</td> <td>11</td> <td>2013-11-25 00:00:00</td> <td>bogota, colombia</td> <td>clay</td> <td>naomi totka</td> <td>6-1, 6-1</td> </tr> <tr> <th>20</th> <td>runner-up</td> <td>10</td> <td>2013-12-02 00:00:00</td> <td>barranquilla, colombia</td> <td>clay</td> <td>maria fernanda herazo</td> <td>4-6, 2-6</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where score = 'winner' <table_name> : table | | outcome | no. | date | tournament | surface | opponent | score | |---:|:----------|------:|:--------------------|:---------------------------------|:----------|:--------------------------------|:-------------------| | 0 | runner-up | 1 | 2004-08-23 00:00:00 | la paz, bolivia | clay | jenifer widjaja | 6-3, 4-6, 0-6 | | 1 | runner-up | 2 | 2005-06-06 00:00:00 | santa tecla, el salvador | clay | andrea benitez | 3-6, 0-6 | | 2 | runner-up | 2 | 2005-08-22 00:00:00 | bogota, colombia | clay | carla tiene | 4-6, 0-6 | | 3 | runner-up | 4 | 2006-05-15 00:00:00 | ciudad obregon, mexico | hard | ellah nze | 6-4, 3-6, 3-6 | | 4 | winner | 1 | 2006-06-05 00:00:00 | xalapa, mexico | hard | maria irigoyen | 6-1, 3-6, 6-4 | | 5 | winner | 2 | 2009-09-07 00:00:00 | mazatlan, mexico | hard | fernanda hermenegildo | 6-1, 6-2 | | 6 | winner | 3 | 2009-11-02 00:00:00 | bogota, colombia | clay | yuliana lizarazo | 7-6(7-5), 6-4 | | 7 | runner-up | 5 | 2009-11-16 00:00:00 | asuncion, paraguay | clay | paula ormaechea | 6-4, 4-6, 2-6 | | 8 | winner | 4 | 2010-11-08 00:00:00 | bogota, colombia | clay | patricia ku flores | 6-1, 7-5 | | 9 | winner | 5 | 2010-11-29 00:00:00 | santiago, chile | clay | veronica cepede royg | 6-2, 6-2 | | 10 | winner | 6 | 2011-07-18 00:00:00 | ribeirao preto, brazil | clay | vivian segnini | 6-2, 6-2 | | 11 | runner-up | 6 | 2011-08-08 00:00:00 | santa cruz de la sierra, bolivia | clay | maria irigoyen | 2-6, 3-6 | | 12 | winner | 7 | 2011-08-15 00:00:00 | la paz, bolivia | clay | maria irigoyen | 6-0, 7-6(7-1) | | 13 | runner-up | 7 | 2011-10-03 00:00:00 | yerevan, armenia | clay | julia cohen | 6-7(6-8), 2-6 | | 14 | runner-up | 8 | 2012-03-19 00:00:00 | bangalore, india | hard | donna vekic | 2-6, 4-6 | | 15 | runner-up | 9 | 2012-05-08 00:00:00 | brasilia, brazil | clay | gabriela paz | 3-6, 3-6 | | 16 | winner | 8 | 2012-11-19 00:00:00 | barranquilla, colombia | clay | karolina nowak | 7-6(7-4), 6-0 | | 17 | winner | 9 | 2013-10-21 00:00:00 | bogota, colombia | hard | anna katalina alzate esmurzaeva | 6-3, 6-3 | | 18 | winner | 10 | 2013-11-11 00:00:00 | lima, peru | clay | patricia ku flores | 7-5, 6-7(4-7), 6-2 | | 19 | winner | 11 | 2013-11-25 00:00:00 | bogota, colombia | clay | naomi totka | 6-1, 6-1 | | 20 | runner-up | 10 | 2013-12-02 00:00:00 | barranquilla, colombia | clay | maria fernanda herazo | 4-6, 2-6 |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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col : home town/city row 1 : san antonio

select home town/city where district = 118 <table_name> : table \begin{tabular}{lllll} \toprule & representative & party & home town/city & district \\ \midrule 0 & trey martinez fischer & d & san antonio & 116 \\ 1 & philip cortez & d & san antonio & 117 \\ 2 & joe farias & d & san antonio & 118 \\ 3 & roland gutierrez & d & san antonio & 119 \\ 4 & ruth mcclendon & d & san antonio & 120 \\ 5 & joe straus & r & san antonio & 121 \\ 6 & lyle larson & r & san antonio & 122 \\ 7 & mike villarreal & d & san antonio & 123 \\ 8 & jose menendez & d & san antonio & 124 \\ 9 & justin rodriguez & d & san antonio & 125 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & home town/city \\ \midrule 0 & san antonio \\ \bottomrule \end{tabular}

select home town/city where district = 118 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>representative</th> <th>party</th> <th>home town/city</th> <th>district</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>trey martinez fischer</td> <td>d</td> <td>san antonio</td> <td>116</td> </tr> <tr> <th>1</th> <td>philip cortez</td> <td>d</td> <td>san antonio</td> <td>117</td> </tr> <tr> <th>2</th> <td>joe farias</td> <td>d</td> <td>san antonio</td> <td>118</td> </tr> <tr> <th>3</th> <td>roland gutierrez</td> <td>d</td> <td>san antonio</td> <td>119</td> </tr> <tr> <th>4</th> <td>ruth mcclendon</td> <td>d</td> <td>san antonio</td> <td>120</td> </tr> <tr> <th>5</th> <td>joe straus</td> <td>r</td> <td>san antonio</td> <td>121</td> </tr> <tr> <th>6</th> <td>lyle larson</td> <td>r</td> <td>san antonio</td> <td>122</td> </tr> <tr> <th>7</th> <td>mike villarreal</td> <td>d</td> <td>san antonio</td> <td>123</td> </tr> <tr> <th>8</th> <td>jose menendez</td> <td>d</td> <td>san antonio</td> <td>124</td> </tr> <tr> <th>9</th> <td>justin rodriguez</td> <td>d</td> <td>san antonio</td> <td>125</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>home town/city</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>san antonio</td> </tr> </tbody> </table>

select home town/city where district = 118 <table_name> : table | | representative | party | home town/city | district | |---:|:----------------------|:--------|:-----------------|-----------:| | 0 | trey martinez fischer | d | san antonio | 116 | | 1 | philip cortez | d | san antonio | 117 | | 2 | joe farias | d | san antonio | 118 | | 3 | roland gutierrez | d | san antonio | 119 | | 4 | ruth mcclendon | d | san antonio | 120 | | 5 | joe straus | r | san antonio | 121 | | 6 | lyle larson | r | san antonio | 122 | | 7 | mike villarreal | d | san antonio | 123 | | 8 | jose menendez | d | san antonio | 124 | | 9 | justin rodriguez | d | san antonio | 125 |

| | home town/city | |---:|:-----------------| | 0 | san antonio |

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col : area (km2) row 1 : 2892 row 2 : 6973 row 3 : 5437 row 4 : 7476 row 5 : 2588 row 6 : 4033

select area (km2) where ecclesiastical province = 'santo domingo' <table_name> : table \begin{tabular}{llllllll} \toprule & ecclesiastical jurisdictions & latin name & type & rite & ecclesiastical province & established & area (km2) \\ \midrule 0 & bani & baniensis & diocese & roman & santo domingo & 8 november 1986 & 2892 \\ 1 & barahona & barahonensis & diocese & roman & santo domingo & 24 april 1976 & 6973 \\ 2 & dominican republic & reipublicae dominicanae & military ordinariate & roman & immediately subject to the holy see & 23 january 1958 & none \\ 3 & la vega & vegensis & diocese & roman & santiago de los caballeros & 25 september 1953 & 4919 \\ 4 & mao-monte cristi & maoensis-montis christi & diocese & roman & santiago de los caballeros & 16 january 1978 & 4841 \\ 5 & nuestra senora de la altagracia en higuey & higueyensis / a domina nostra vulgo de la altagracia in higuey & diocese & roman & santo domingo & 1 april 1959 & 5437 \\ 6 & puerto plata & portus argentarii & diocese & roman & santiago de los caballeros & 16 december 1996 & 2700 \\ 7 & san francisco de macoris & sancti francisci de macoris & diocese & roman & santiago de los caballeros & 16 january 1978 & 3682 \\ 8 & san juan de la maguana & sancti ioannis maguanensis & diocese & roman & santo domingo & 25 september 1953 & 7476 \\ 9 & san pedro de macoris & sancti petri de macoris & diocese & roman & santo domingo & 1 february 1997 & 2588 \\ 10 & santiago de los caballeros & sancti iacobi equitum & metropolitan archdiocese & roman & santiago de los caballeros & 25 september 1953 & 6391 \\ 11 & santo domingo & sancti dominici & metropolitan archdiocese & roman & santo domingo & 8 august 1511 & 4033 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & area (km2) \\ \midrule 0 & 2892 \\ 1 & 6973 \\ 2 & 5437 \\ 3 & 7476 \\ 4 & 2588 \\ 5 & 4033 \\ \bottomrule \end{tabular}

select area (km2) where ecclesiastical province = 'santo domingo' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>ecclesiastical jurisdictions</th> <th>latin name</th> <th>type</th> <th>rite</th> <th>ecclesiastical province</th> <th>established</th> <th>area (km2)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>bani</td> <td>baniensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>8 november 1986</td> <td>2892</td> </tr> <tr> <th>1</th> <td>barahona</td> <td>barahonensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>24 april 1976</td> <td>6973</td> </tr> <tr> <th>2</th> <td>dominican republic</td> <td>reipublicae dominicanae</td> <td>military ordinariate</td> <td>roman</td> <td>immediately subject to the holy see</td> <td>23 january 1958</td> <td>none</td> </tr> <tr> <th>3</th> <td>la vega</td> <td>vegensis</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>4919</td> </tr> <tr> <th>4</th> <td>mao-monte cristi</td> <td>maoensis-montis christi</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>4841</td> </tr> <tr> <th>5</th> <td>nuestra senora de la altagracia en higuey</td> <td>higueyensis / a domina nostra vulgo de la altagracia in higuey</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 april 1959</td> <td>5437</td> </tr> <tr> <th>6</th> <td>puerto plata</td> <td>portus argentarii</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 december 1996</td> <td>2700</td> </tr> <tr> <th>7</th> <td>san francisco de macoris</td> <td>sancti francisci de macoris</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>3682</td> </tr> <tr> <th>8</th> <td>san juan de la maguana</td> <td>sancti ioannis maguanensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>25 september 1953</td> <td>7476</td> </tr> <tr> <th>9</th> <td>san pedro de macoris</td> <td>sancti petri de macoris</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 february 1997</td> <td>2588</td> </tr> <tr> <th>10</th> <td>santiago de los caballeros</td> <td>sancti iacobi equitum</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>6391</td> </tr> <tr> <th>11</th> <td>santo domingo</td> <td>sancti dominici</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santo domingo</td> <td>8 august 1511</td> <td>4033</td> </tr> </tbody> </table>

select area (km2) where ecclesiastical province = 'santo domingo' <table_name> : table | | ecclesiastical jurisdictions | latin name | type | rite | ecclesiastical province | established | area (km2) | |---:|:------------------------------------------|:---------------------------------------------------------------|:-------------------------|:-------|:------------------------------------|:------------------|:-------------| | 0 | bani | baniensis | diocese | roman | santo domingo | 8 november 1986 | 2892 | | 1 | barahona | barahonensis | diocese | roman | santo domingo | 24 april 1976 | 6973 | | 2 | dominican republic | reipublicae dominicanae | military ordinariate | roman | immediately subject to the holy see | 23 january 1958 | none | | 3 | la vega | vegensis | diocese | roman | santiago de los caballeros | 25 september 1953 | 4919 | | 4 | mao-monte cristi | maoensis-montis christi | diocese | roman | santiago de los caballeros | 16 january 1978 | 4841 | | 5 | nuestra senora de la altagracia en higuey | higueyensis / a domina nostra vulgo de la altagracia in higuey | diocese | roman | santo domingo | 1 april 1959 | 5437 | | 6 | puerto plata | portus argentarii | diocese | roman | santiago de los caballeros | 16 december 1996 | 2700 | | 7 | san francisco de macoris | sancti francisci de macoris | diocese | roman | santiago de los caballeros | 16 january 1978 | 3682 | | 8 | san juan de la maguana | sancti ioannis maguanensis | diocese | roman | santo domingo | 25 september 1953 | 7476 | | 9 | san pedro de macoris | sancti petri de macoris | diocese | roman | santo domingo | 1 february 1997 | 2588 | | 10 | santiago de los caballeros | sancti iacobi equitum | metropolitan archdiocese | roman | santiago de los caballeros | 25 september 1953 | 6391 | | 11 | santo domingo | sancti dominici | metropolitan archdiocese | roman | santo domingo | 8 august 1511 | 4033 |

| | area (km2) | |---:|-------------:| | 0 | 2892 | | 1 | 6973 | | 2 | 5437 | | 3 | 7476 | | 4 | 2588 | | 5 | 4033 |

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col : picture row 1 : 60px

select picture where # = 4 <table_name> : table \begin{tabular}{lllllll} \toprule & # & picture & name & took office & left office & party \\ \midrule 0 & 1 & none & johan ferrier & 25 november 1975 & 13 august 1980 (resigned after a february coup d'etat) & independent \\ 1 & 2 & none & hendrick chin a sen & 15 august 1980 & 4 february 1982 & pnr \\ 2 & 3 & none & fred ramdat misier & 8 february 1982 & 25 january 1988 & independent \\ 3 & 4 & 60px & ramsewak shankar & 25 january 1988 & 24 december 1990 (deposed) & vhp \\ 4 & 5 & 60px & johan kraag & 29 december 1990 & 16 september 1991 & nps \\ 5 & 6 & none & ronald venetiaan & 16 september 1991 & 15 september 1996 & nps \\ 6 & 7 & none & jules wijdenbosch & 15 september 1996 & 12 august 2000 & ndp \\ 7 & (6) & none & ronald venetiaan & 12 august 2000 & 12 august 2010 & nps \\ 8 & 8 & none & desi bouterse & 12 august 2010 & incumbent & ndp \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & picture \\ \midrule 0 & 60px \\ \bottomrule \end{tabular}

select picture where # = 4 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>picture</th> <th>name</th> <th>took office</th> <th>left office</th> <th>party</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>none</td> <td>johan ferrier</td> <td>25 november 1975</td> <td>13 august 1980 (resigned after a february coup d'etat)</td> <td>independent</td> </tr> <tr> <th>1</th> <td>2</td> <td>none</td> <td>hendrick chin a sen</td> <td>15 august 1980</td> <td>4 february 1982</td> <td>pnr</td> </tr> <tr> <th>2</th> <td>3</td> <td>none</td> <td>fred ramdat misier</td> <td>8 february 1982</td> <td>25 january 1988</td> <td>independent</td> </tr> <tr> <th>3</th> <td>4</td> <td>60px</td> <td>ramsewak shankar</td> <td>25 january 1988</td> <td>24 december 1990 (deposed)</td> <td>vhp</td> </tr> <tr> <th>4</th> <td>5</td> <td>60px</td> <td>johan kraag</td> <td>29 december 1990</td> <td>16 september 1991</td> <td>nps</td> </tr> <tr> <th>5</th> <td>6</td> <td>none</td> <td>ronald venetiaan</td> <td>16 september 1991</td> <td>15 september 1996</td> <td>nps</td> </tr> <tr> <th>6</th> <td>7</td> <td>none</td> <td>jules wijdenbosch</td> <td>15 september 1996</td> <td>12 august 2000</td> <td>ndp</td> </tr> <tr> <th>7</th> <td>(6)</td> <td>none</td> <td>ronald venetiaan</td> <td>12 august 2000</td> <td>12 august 2010</td> <td>nps</td> </tr> <tr> <th>8</th> <td>8</td> <td>none</td> <td>desi bouterse</td> <td>12 august 2010</td> <td>incumbent</td> <td>ndp</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>picture</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>60px</td> </tr> </tbody> </table>

select picture where # = 4 <table_name> : table | | # | picture | name | took office | left office | party | |---:|:----|:----------|:--------------------|:------------------|:-------------------------------------------------------|:------------| | 0 | 1 | none | johan ferrier | 25 november 1975 | 13 august 1980 (resigned after a february coup d'etat) | independent | | 1 | 2 | none | hendrick chin a sen | 15 august 1980 | 4 february 1982 | pnr | | 2 | 3 | none | fred ramdat misier | 8 february 1982 | 25 january 1988 | independent | | 3 | 4 | 60px | ramsewak shankar | 25 january 1988 | 24 december 1990 (deposed) | vhp | | 4 | 5 | 60px | johan kraag | 29 december 1990 | 16 september 1991 | nps | | 5 | 6 | none | ronald venetiaan | 16 september 1991 | 15 september 1996 | nps | | 6 | 7 | none | jules wijdenbosch | 15 september 1996 | 12 august 2000 | ndp | | 7 | (6) | none | ronald venetiaan | 12 august 2000 | 12 august 2010 | nps | | 8 | 8 | none | desi bouterse | 12 august 2010 | incumbent | ndp |

| | picture | |---:|:----------| | 0 | 60px |

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col : joined mac row 1 : 1965 row 2 : 1977 row 3 : 2007 row 4 : 1946

select joined mac where type = 'private/non-sectarian' <table_name> : table \begin{tabular}{llllllll} \toprule & institution & location & nickname & founded & type & enrollment & joined mac \\ \midrule 0 & delaware valley college & doylestown, pennsylvania & aggies & 1917 & private/non-sectarian & 2241 & 1965 \\ 1 & desales university & center valley, pennsylvania & bulldogs & 1965 & private/catholic & 3199 & 1997 \\ 2 & eastern university & st. davids, pennsylvania & eagles & 1952 & private/baptist & 4235 & 2008 \\ 3 & fairleigh dickinson university-florham & madison, new jersey & devils & 1942 & private/non-sectarian & 3288 & 1977 \\ 4 & king's college & wilkes-barre, pennsylvania & monarchs & 1946 & private/catholic & 2725 & 1977 \\ 5 & manhattanville college & purchase, new york & valiants & 1841 & private/non-sectarian & 2695 & 2007 \\ 6 & misericordia university & dallas, pennsylvania & cougars & 1924 & private/catholic & 2830 & 2008 \\ 7 & wilkes university & wilkes-barre, pennsylvania & colonels & 1933 & private/non-sectarian & 5136 & 1946 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & joined mac \\ \midrule 0 & 1965 \\ 1 & 1977 \\ 2 & 2007 \\ 3 & 1946 \\ \bottomrule \end{tabular}

select joined mac where type = 'private/non-sectarian' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>institution</th> <th>location</th> <th>nickname</th> <th>founded</th> <th>type</th> <th>enrollment</th> <th>joined mac</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>delaware valley college</td> <td>doylestown, pennsylvania</td> <td>aggies</td> <td>1917</td> <td>private/non-sectarian</td> <td>2241</td> <td>1965</td> </tr> <tr> <th>1</th> <td>desales university</td> <td>center valley, pennsylvania</td> <td>bulldogs</td> <td>1965</td> <td>private/catholic</td> <td>3199</td> <td>1997</td> </tr> <tr> <th>2</th> <td>eastern university</td> <td>st. davids, pennsylvania</td> <td>eagles</td> <td>1952</td> <td>private/baptist</td> <td>4235</td> <td>2008</td> </tr> <tr> <th>3</th> <td>fairleigh dickinson university-florham</td> <td>madison, new jersey</td> <td>devils</td> <td>1942</td> <td>private/non-sectarian</td> <td>3288</td> <td>1977</td> </tr> <tr> <th>4</th> <td>king's college</td> <td>wilkes-barre, pennsylvania</td> <td>monarchs</td> <td>1946</td> <td>private/catholic</td> <td>2725</td> <td>1977</td> </tr> <tr> <th>5</th> <td>manhattanville college</td> <td>purchase, new york</td> <td>valiants</td> <td>1841</td> <td>private/non-sectarian</td> <td>2695</td> <td>2007</td> </tr> <tr> <th>6</th> <td>misericordia university</td> <td>dallas, pennsylvania</td> <td>cougars</td> <td>1924</td> <td>private/catholic</td> <td>2830</td> <td>2008</td> </tr> <tr> <th>7</th> <td>wilkes university</td> <td>wilkes-barre, pennsylvania</td> <td>colonels</td> <td>1933</td> <td>private/non-sectarian</td> <td>5136</td> <td>1946</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>joined mac</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1965</td> </tr> <tr> <th>1</th> <td>1977</td> </tr> <tr> <th>2</th> <td>2007</td> </tr> <tr> <th>3</th> <td>1946</td> </tr> </tbody> </table>

select joined mac where type = 'private/non-sectarian' <table_name> : table | | institution | location | nickname | founded | type | enrollment | joined mac | |---:|:---------------------------------------|:----------------------------|:-----------|----------:|:----------------------|-------------:|-------------:| | 0 | delaware valley college | doylestown, pennsylvania | aggies | 1917 | private/non-sectarian | 2241 | 1965 | | 1 | desales university | center valley, pennsylvania | bulldogs | 1965 | private/catholic | 3199 | 1997 | | 2 | eastern university | st. davids, pennsylvania | eagles | 1952 | private/baptist | 4235 | 2008 | | 3 | fairleigh dickinson university-florham | madison, new jersey | devils | 1942 | private/non-sectarian | 3288 | 1977 | | 4 | king's college | wilkes-barre, pennsylvania | monarchs | 1946 | private/catholic | 2725 | 1977 | | 5 | manhattanville college | purchase, new york | valiants | 1841 | private/non-sectarian | 2695 | 2007 | | 6 | misericordia university | dallas, pennsylvania | cougars | 1924 | private/catholic | 2830 | 2008 | | 7 | wilkes university | wilkes-barre, pennsylvania | colonels | 1933 | private/non-sectarian | 5136 | 1946 |

| | joined mac | |---:|-------------:| | 0 | 1965 | | 1 | 1977 | | 2 | 2007 | | 3 | 1946 |

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col : trainer row 1 : nick zito

select trainer where owner = 'dogwood stable' order by post asc limit 1615 <table_name> : table \begin{tabular}{llllllll} \toprule & finished & post & horse & jockey & trainer & owner & time / behind \\ \midrule 0 & 1st & 6 & silver charm & gary l. stevens & bob baffert & bob & beverly lewis & 2:02.44 \\ 1 & 2nd & 5 & captain bodgit & alex solis & gary a. capuano & team valor & none \\ 2 & 3rd & 12 & free house & david flores & j. paco gonzalez & john toffan & trudy mccaffery & none \\ 3 & 4th & 3 & pulpit & shane sellers & frank l. brothers & claiborne farm & none \\ 4 & 5th & 10 & crypto star & pat day & wayne m. catalano & evelyn & darrell yates & none \\ 5 & 6th & 9 & phantom on tour & jerry d. bailey & lynn s. whiting & w. cal partee & none \\ 6 & 7th & 5 & jack flash & craig perret & nick zito & dogwood stable & none \\ 7 & 8th & 6 & hello & mike smith & ronald mcanally & sandee & al kirkwood & none \\ 8 & 9th & 1 & concerto & carlos h. marquez, jr & john j. tammaro, iii & kinsman stable & none \\ 9 & 10th & 13 & celtic warrior & francisco torres & danny hutt & hutt, quackenbush & shaffrick & none \\ 10 & 11th & 4 & crimson classic & robby albarado & forrest kaelin & john w. clay & none \\ 11 & 12th & 15 & shammy davis & willie martinez & nick zito & fox hill farm & none \\ 12 & 13th & 11 & deeds not words & corey nakatani & d. wayne lukas & michael tabor & susan magnier & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & trainer \\ \midrule 0 & nick zito \\ \bottomrule \end{tabular}

select trainer where owner = 'dogwood stable' order by post asc limit 1615 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>finished</th> <th>post</th> <th>horse</th> <th>jockey</th> <th>trainer</th> <th>owner</th> <th>time / behind</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1st</td> <td>6</td> <td>silver charm</td> <td>gary l. stevens</td> <td>bob baffert</td> <td>bob & beverly lewis</td> <td>2:02.44</td> </tr> <tr> <th>1</th> <td>2nd</td> <td>5</td> <td>captain bodgit</td> <td>alex solis</td> <td>gary a. capuano</td> <td>team valor</td> <td>none</td> </tr> <tr> <th>2</th> <td>3rd</td> <td>12</td> <td>free house</td> <td>david flores</td> <td>j. paco gonzalez</td> <td>john toffan & trudy mccaffery</td> <td>none</td> </tr> <tr> <th>3</th> <td>4th</td> <td>3</td> <td>pulpit</td> <td>shane sellers</td> <td>frank l. brothers</td> <td>claiborne farm</td> <td>none</td> </tr> <tr> <th>4</th> <td>5th</td> <td>10</td> <td>crypto star</td> <td>pat day</td> <td>wayne m. catalano</td> <td>evelyn & darrell yates</td> <td>none</td> </tr> <tr> <th>5</th> <td>6th</td> <td>9</td> <td>phantom on tour</td> <td>jerry d. bailey</td> <td>lynn s. whiting</td> <td>w. cal partee</td> <td>none</td> </tr> <tr> <th>6</th> <td>7th</td> <td>5</td> <td>jack flash</td> <td>craig perret</td> <td>nick zito</td> <td>dogwood stable</td> <td>none</td> </tr> <tr> <th>7</th> <td>8th</td> <td>6</td> <td>hello</td> <td>mike smith</td> <td>ronald mcanally</td> <td>sandee & al kirkwood</td> <td>none</td> </tr> <tr> <th>8</th> <td>9th</td> <td>1</td> <td>concerto</td> <td>carlos h. marquez, jr</td> <td>john j. tammaro, iii</td> <td>kinsman stable</td> <td>none</td> </tr> <tr> <th>9</th> <td>10th</td> <td>13</td> <td>celtic warrior</td> <td>francisco torres</td> <td>danny hutt</td> <td>hutt, quackenbush & shaffrick</td> <td>none</td> </tr> <tr> <th>10</th> <td>11th</td> <td>4</td> <td>crimson classic</td> <td>robby albarado</td> <td>forrest kaelin</td> <td>john w. clay</td> <td>none</td> </tr> <tr> <th>11</th> <td>12th</td> <td>15</td> <td>shammy davis</td> <td>willie martinez</td> <td>nick zito</td> <td>fox hill farm</td> <td>none</td> </tr> <tr> <th>12</th> <td>13th</td> <td>11</td> <td>deeds not words</td> <td>corey nakatani</td> <td>d. wayne lukas</td> <td>michael tabor & susan magnier</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>trainer</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>nick zito</td> </tr> </tbody> </table>

select trainer where owner = 'dogwood stable' order by post asc limit 1615 <table_name> : table | | finished | post | horse | jockey | trainer | owner | time / behind | |---:|:-----------|-------:|:----------------|:----------------------|:---------------------|:------------------------------|:----------------| | 0 | 1st | 6 | silver charm | gary l. stevens | bob baffert | bob & beverly lewis | 2:02.44 | | 1 | 2nd | 5 | captain bodgit | alex solis | gary a. capuano | team valor | none | | 2 | 3rd | 12 | free house | david flores | j. paco gonzalez | john toffan & trudy mccaffery | none | | 3 | 4th | 3 | pulpit | shane sellers | frank l. brothers | claiborne farm | none | | 4 | 5th | 10 | crypto star | pat day | wayne m. catalano | evelyn & darrell yates | none | | 5 | 6th | 9 | phantom on tour | jerry d. bailey | lynn s. whiting | w. cal partee | none | | 6 | 7th | 5 | jack flash | craig perret | nick zito | dogwood stable | none | | 7 | 8th | 6 | hello | mike smith | ronald mcanally | sandee & al kirkwood | none | | 8 | 9th | 1 | concerto | carlos h. marquez, jr | john j. tammaro, iii | kinsman stable | none | | 9 | 10th | 13 | celtic warrior | francisco torres | danny hutt | hutt, quackenbush & shaffrick | none | | 10 | 11th | 4 | crimson classic | robby albarado | forrest kaelin | john w. clay | none | | 11 | 12th | 15 | shammy davis | willie martinez | nick zito | fox hill farm | none | | 12 | 13th | 11 | deeds not words | corey nakatani | d. wayne lukas | michael tabor & susan magnier | none |

| | trainer | |---:|:----------| | 0 | nick zito |

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col : count ( "distinct term start" ) row 1 : 1

select count ( distinct term start ) where term end = '1 november 1971' <table_name> : table \begin{tabular}{llll} \toprule & name & term start & term end \\ \midrule 0 & pier ruggero piccio & 1 january 1926 & 6 february 1927 \\ 1 & armando armani & 10 february 1927 & 13 october 1928 \\ 2 & giuseppe valle & 22 february 1930 & 23 november 1933 \\ 3 & antonio bosio & 23 november 1933 & 22 march 1934 \\ 4 & giuseppe valle & 22 march 1934 & 10 november 1939 \\ 5 & francesco pricolo & 10 november 1939 & 15 november 1941 \\ 6 & rino corso fougier & 15 november 1941 & 27 july 1943 \\ 7 & renato sandalli & 27 july 1943 & 18 june 1944 \\ 8 & pietro piacentini & 19 june 1944 & 13 december 1944 \\ 9 & mario ajmone cat & 13 december 1944 & 5 february 1951 \\ 10 & aldo urbani & 5 february 1951 & 10 november 1955 \\ 11 & ferdinando raffaelli & 10 november 1955 & 1 february 1958 \\ 12 & silvio napoli & 1 february 1958 & 1 september 1961 \\ 13 & aldo remondino & 1 september 1961 & 28 february 1968 \\ 14 & duilio s. fanali & 28 february 1968 & 1 november 1971 \\ 15 & vincenzo lucertini & 1 november 1971 & 27 february 1974 \\ 16 & dino ciarlo & 27 february 1974 & 20 june 1977 \\ 17 & alessandro mettimano & 20 june 1977 & 1 april 1980 \\ 18 & lamberto bartolucci & 2 april 1980 & 12 october 1983 \\ 19 & basilio cottone & 19 october 1983 & 17 september 1986 \\ 20 & franco pisano & 18 september 1986 & 15 april 1990 \\ 21 & stelio nardini & 16 april 1990 & 24 march 1993 \\ 22 & adelchi pillinini & 25 march 1993 & 3 june 1995 \\ 23 & mario arpino & 4 june 1995 & 5 february 1999 \\ 24 & andrea fornasiero & 5 february 1999 & 5 august 2001 \\ 25 & sandro ferracuti & 5 august 2001 & 4 august 2004 \\ 26 & leonardo tricarico & 5 august 2004 & 19 september 2006 \\ 27 & vincenzo camporini & 19 september 2006 & 30 january 2008 \\ 28 & daniele tei & 30 january 2008 & 25 february 2010 \\ 29 & giuseppe bernardis & 25 february 2010 & 25 february 2013 \\ 30 & pasquale preziosa & 25 february 2013 & incumbent \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "distinct term start" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( distinct term start ) where term end = '1 november 1971' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>term start</th> <th>term end</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>pier ruggero piccio</td> <td>1 january 1926</td> <td>6 february 1927</td> </tr> <tr> <th>1</th> <td>armando armani</td> <td>10 february 1927</td> <td>13 october 1928</td> </tr> <tr> <th>2</th> <td>giuseppe valle</td> <td>22 february 1930</td> <td>23 november 1933</td> </tr> <tr> <th>3</th> <td>antonio bosio</td> <td>23 november 1933</td> <td>22 march 1934</td> </tr> <tr> <th>4</th> <td>giuseppe valle</td> <td>22 march 1934</td> <td>10 november 1939</td> </tr> <tr> <th>5</th> <td>francesco pricolo</td> <td>10 november 1939</td> <td>15 november 1941</td> </tr> <tr> <th>6</th> <td>rino corso fougier</td> <td>15 november 1941</td> <td>27 july 1943</td> </tr> <tr> <th>7</th> <td>renato sandalli</td> <td>27 july 1943</td> <td>18 june 1944</td> </tr> <tr> <th>8</th> <td>pietro piacentini</td> <td>19 june 1944</td> <td>13 december 1944</td> </tr> <tr> <th>9</th> <td>mario ajmone cat</td> <td>13 december 1944</td> <td>5 february 1951</td> </tr> <tr> <th>10</th> <td>aldo urbani</td> <td>5 february 1951</td> <td>10 november 1955</td> </tr> <tr> <th>11</th> <td>ferdinando raffaelli</td> <td>10 november 1955</td> <td>1 february 1958</td> </tr> <tr> <th>12</th> <td>silvio napoli</td> <td>1 february 1958</td> <td>1 september 1961</td> </tr> <tr> <th>13</th> <td>aldo remondino</td> <td>1 september 1961</td> <td>28 february 1968</td> </tr> <tr> <th>14</th> <td>duilio s. fanali</td> <td>28 february 1968</td> <td>1 november 1971</td> </tr> <tr> <th>15</th> <td>vincenzo lucertini</td> <td>1 november 1971</td> <td>27 february 1974</td> </tr> <tr> <th>16</th> <td>dino ciarlo</td> <td>27 february 1974</td> <td>20 june 1977</td> </tr> <tr> <th>17</th> <td>alessandro mettimano</td> <td>20 june 1977</td> <td>1 april 1980</td> </tr> <tr> <th>18</th> <td>lamberto bartolucci</td> <td>2 april 1980</td> <td>12 october 1983</td> </tr> <tr> <th>19</th> <td>basilio cottone</td> <td>19 october 1983</td> <td>17 september 1986</td> </tr> <tr> <th>20</th> <td>franco pisano</td> <td>18 september 1986</td> <td>15 april 1990</td> </tr> <tr> <th>21</th> <td>stelio nardini</td> <td>16 april 1990</td> <td>24 march 1993</td> </tr> <tr> <th>22</th> <td>adelchi pillinini</td> <td>25 march 1993</td> <td>3 june 1995</td> </tr> <tr> <th>23</th> <td>mario arpino</td> <td>4 june 1995</td> <td>5 february 1999</td> </tr> <tr> <th>24</th> <td>andrea fornasiero</td> <td>5 february 1999</td> <td>5 august 2001</td> </tr> <tr> <th>25</th> <td>sandro ferracuti</td> <td>5 august 2001</td> <td>4 august 2004</td> </tr> <tr> <th>26</th> <td>leonardo tricarico</td> <td>5 august 2004</td> <td>19 september 2006</td> </tr> <tr> <th>27</th> <td>vincenzo camporini</td> <td>19 september 2006</td> <td>30 january 2008</td> </tr> <tr> <th>28</th> <td>daniele tei</td> <td>30 january 2008</td> <td>25 february 2010</td> </tr> <tr> <th>29</th> <td>giuseppe bernardis</td> <td>25 february 2010</td> <td>25 february 2013</td> </tr> <tr> <th>30</th> <td>pasquale preziosa</td> <td>25 february 2013</td> <td>incumbent</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "distinct term start" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( distinct term start ) where term end = '1 november 1971' <table_name> : table | | name | term start | term end | |---:|:---------------------|:------------------|:------------------| | 0 | pier ruggero piccio | 1 january 1926 | 6 february 1927 | | 1 | armando armani | 10 february 1927 | 13 october 1928 | | 2 | giuseppe valle | 22 february 1930 | 23 november 1933 | | 3 | antonio bosio | 23 november 1933 | 22 march 1934 | | 4 | giuseppe valle | 22 march 1934 | 10 november 1939 | | 5 | francesco pricolo | 10 november 1939 | 15 november 1941 | | 6 | rino corso fougier | 15 november 1941 | 27 july 1943 | | 7 | renato sandalli | 27 july 1943 | 18 june 1944 | | 8 | pietro piacentini | 19 june 1944 | 13 december 1944 | | 9 | mario ajmone cat | 13 december 1944 | 5 february 1951 | | 10 | aldo urbani | 5 february 1951 | 10 november 1955 | | 11 | ferdinando raffaelli | 10 november 1955 | 1 february 1958 | | 12 | silvio napoli | 1 february 1958 | 1 september 1961 | | 13 | aldo remondino | 1 september 1961 | 28 february 1968 | | 14 | duilio s. fanali | 28 february 1968 | 1 november 1971 | | 15 | vincenzo lucertini | 1 november 1971 | 27 february 1974 | | 16 | dino ciarlo | 27 february 1974 | 20 june 1977 | | 17 | alessandro mettimano | 20 june 1977 | 1 april 1980 | | 18 | lamberto bartolucci | 2 april 1980 | 12 october 1983 | | 19 | basilio cottone | 19 october 1983 | 17 september 1986 | | 20 | franco pisano | 18 september 1986 | 15 april 1990 | | 21 | stelio nardini | 16 april 1990 | 24 march 1993 | | 22 | adelchi pillinini | 25 march 1993 | 3 june 1995 | | 23 | mario arpino | 4 june 1995 | 5 february 1999 | | 24 | andrea fornasiero | 5 february 1999 | 5 august 2001 | | 25 | sandro ferracuti | 5 august 2001 | 4 august 2004 | | 26 | leonardo tricarico | 5 august 2004 | 19 september 2006 | | 27 | vincenzo camporini | 19 september 2006 | 30 january 2008 | | 28 | daniele tei | 30 january 2008 | 25 february 2010 | | 29 | giuseppe bernardis | 25 february 2010 | 25 february 2013 | | 30 | pasquale preziosa | 25 february 2013 | incumbent |

| | count ( "distinct term start" ) | |---:|----------------------------------:| | 0 | 1 |

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select nation where silver = 4 col : rank | nation | gold | silver | bronze | total row 1 : 1 | germany | 17 | 9 | 14 | 40 row 2 : 2 | russia | 12 | 16 | 8 | 36 row 3 : 3 | ukraine | 6 | 11 | 9 | 26 row 4 : 4 | norway | 6 | 2 | 7 | 15 row 5 : 5 | france | 5 | 4 | 3 | 12 row 6 : 6 | switzerland | 3 | 5 | 3 | 11 row 7 : 7 | finland | 3 | 2 | 4 | 9 row 8 : 8 | japan | 2 | 2 | 1 | 5 row 9 : 9 | netherlands | 2 | 0 | 1 | 3 row 10 : 10 | sweden | 1 | 2 | 2 | 5 row 11 : 11 | denmark | 1 | 0 | 1 | 2 row 12 : 12 | unified team | 1 | 0 | 0 | 1 row 13 : 13 | austria | 0 | 4 | 0 | 4 row 14 : 14 | slovakia | 0 | 2 | 1 | 3 row 15 : 15 | italy | 0 | 0 | 1 | 1 row 16 : 15 | poland | 0 | 0 | 1 | 1 row 17 : 15 | canada | 0 | 0 | 1 | 1 row 18 : 15 | belarus | 0 | 0 | 1 | 1 row 19 : 15 | united states | 0 | 0 | 1 | 1 row 20 : total 19 nations | total 19 nations | 59 | 59 | 59 | 177

col : nation row 1 : france row 2 : austria

select nation where silver = 4 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & germany & 17 & 9 & 14 & 40 \\ 1 & 2 & russia & 12 & 16 & 8 & 36 \\ 2 & 3 & ukraine & 6 & 11 & 9 & 26 \\ 3 & 4 & norway & 6 & 2 & 7 & 15 \\ 4 & 5 & france & 5 & 4 & 3 & 12 \\ 5 & 6 & switzerland & 3 & 5 & 3 & 11 \\ 6 & 7 & finland & 3 & 2 & 4 & 9 \\ 7 & 8 & japan & 2 & 2 & 1 & 5 \\ 8 & 9 & netherlands & 2 & 0 & 1 & 3 \\ 9 & 10 & sweden & 1 & 2 & 2 & 5 \\ 10 & 11 & denmark & 1 & 0 & 1 & 2 \\ 11 & 12 & unified team & 1 & 0 & 0 & 1 \\ 12 & 13 & austria & 0 & 4 & 0 & 4 \\ 13 & 14 & slovakia & 0 & 2 & 1 & 3 \\ 14 & 15 & italy & 0 & 0 & 1 & 1 \\ 15 & 15 & poland & 0 & 0 & 1 & 1 \\ 16 & 15 & canada & 0 & 0 & 1 & 1 \\ 17 & 15 & belarus & 0 & 0 & 1 & 1 \\ 18 & 15 & united states & 0 & 0 & 1 & 1 \\ 19 & total 19 nations & total 19 nations & 59 & 59 & 59 & 177 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & france \\ 1 & austria \\ \bottomrule \end{tabular}

select nation where silver = 4 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>germany</td> <td>17</td> <td>9</td> <td>14</td> <td>40</td> </tr> <tr> <th>1</th> <td>2</td> <td>russia</td> <td>12</td> <td>16</td> <td>8</td> <td>36</td> </tr> <tr> <th>2</th> <td>3</td> <td>ukraine</td> <td>6</td> <td>11</td> <td>9</td> <td>26</td> </tr> <tr> <th>3</th> <td>4</td> <td>norway</td> <td>6</td> <td>2</td> <td>7</td> <td>15</td> </tr> <tr> <th>4</th> <td>5</td> <td>france</td> <td>5</td> <td>4</td> <td>3</td> <td>12</td> </tr> <tr> <th>5</th> <td>6</td> <td>switzerland</td> <td>3</td> <td>5</td> <td>3</td> <td>11</td> </tr> <tr> <th>6</th> <td>7</td> <td>finland</td> <td>3</td> <td>2</td> <td>4</td> <td>9</td> </tr> <tr> <th>7</th> <td>8</td> <td>japan</td> <td>2</td> <td>2</td> <td>1</td> <td>5</td> </tr> <tr> <th>8</th> <td>9</td> <td>netherlands</td> <td>2</td> <td>0</td> <td>1</td> <td>3</td> </tr> <tr> <th>9</th> <td>10</td> <td>sweden</td> <td>1</td> <td>2</td> <td>2</td> <td>5</td> </tr> <tr> <th>10</th> <td>11</td> <td>denmark</td> <td>1</td> <td>0</td> <td>1</td> <td>2</td> </tr> <tr> <th>11</th> <td>12</td> <td>unified team</td> <td>1</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>12</th> <td>13</td> <td>austria</td> <td>0</td> <td>4</td> <td>0</td> <td>4</td> </tr> <tr> <th>13</th> <td>14</td> <td>slovakia</td> <td>0</td> <td>2</td> <td>1</td> <td>3</td> </tr> <tr> <th>14</th> <td>15</td> <td>italy</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>15</th> <td>15</td> <td>poland</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>16</th> <td>15</td> <td>canada</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>17</th> <td>15</td> <td>belarus</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>18</th> <td>15</td> <td>united states</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>19</th> <td>total 19 nations</td> <td>total 19 nations</td> <td>59</td> <td>59</td> <td>59</td> <td>177</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>france</td> </tr> <tr> <th>1</th> <td>austria</td> </tr> </tbody> </table>

select nation where silver = 4 <table_name> : table | | rank | nation | gold | silver | bronze | total | |---:|:-----------------|:-----------------|-------:|---------:|---------:|--------:| | 0 | 1 | germany | 17 | 9 | 14 | 40 | | 1 | 2 | russia | 12 | 16 | 8 | 36 | | 2 | 3 | ukraine | 6 | 11 | 9 | 26 | | 3 | 4 | norway | 6 | 2 | 7 | 15 | | 4 | 5 | france | 5 | 4 | 3 | 12 | | 5 | 6 | switzerland | 3 | 5 | 3 | 11 | | 6 | 7 | finland | 3 | 2 | 4 | 9 | | 7 | 8 | japan | 2 | 2 | 1 | 5 | | 8 | 9 | netherlands | 2 | 0 | 1 | 3 | | 9 | 10 | sweden | 1 | 2 | 2 | 5 | | 10 | 11 | denmark | 1 | 0 | 1 | 2 | | 11 | 12 | unified team | 1 | 0 | 0 | 1 | | 12 | 13 | austria | 0 | 4 | 0 | 4 | | 13 | 14 | slovakia | 0 | 2 | 1 | 3 | | 14 | 15 | italy | 0 | 0 | 1 | 1 | | 15 | 15 | poland | 0 | 0 | 1 | 1 | | 16 | 15 | canada | 0 | 0 | 1 | 1 | | 17 | 15 | belarus | 0 | 0 | 1 | 1 | | 18 | 15 | united states | 0 | 0 | 1 | 1 | | 19 | total 19 nations | total 19 nations | 59 | 59 | 59 | 177 |

| | nation | |---:|:---------| | 0 | france | | 1 | austria |

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col : count ( "*" ) row 1 : 1

select count ( * ) where left office = '26 january 1931' <table_name> : table \begin{tabular}{lllllll} \toprule & # & name (birth-death) & took office & left office & monarch & prime minister \\ \midrule 0 & 1 & the viscount gladstone (1854-1930) & 31 may 1910 & 8 september 1914 & george v & botha \\ 1 & 2 & the viscount buxton (1853-1934) & 8 september 1914 & 17 november 1920 & george v & botha \\ 2 & 3 & hrh prince arthur of connaught (1883-1938) & 17 november 1920 & 21 january 1924 & george v & smuts \\ 3 & 4 & the earl of athlone (1874-1957) & 21 january 1924 & 26 january 1931 & george v & smuts \\ 4 & 5 & the earl of clarendon (1877-1955) & 26 january 1931 & 5 april 1937 & george v & hertzog \\ 5 & 6 & sir patrick duncan (1870-1943) & 5 april 1937 & 17 july 1943 & george vi & hertzog \\ 6 & 6 & nicolaas jacobus de wet (1873-1960) (officer administering the government) & 17 july 1943 & 1 january 1946 & george vi & smuts \\ 7 & 7 & gideon brand van zyl (1873-1956) & 1 january 1946 & 1 january 1951 & george vi & smuts \\ 8 & 8 & ernest george jansen (1881-1959) & 1 january 1951 & 25 november 1959 & george vi & malan \\ 9 & 8 & lucas cornelius steyn (1903-1976) (officer administering the government) & 26 november 1959 & 11 december 1959 & elizabeth ii & verwoerd \\ 10 & 9 & charles robberts swart (1894-1982) & 11 december 1959 & 30 april 1961 & elizabeth ii & verwoerd \\ 11 & 9 & lucas cornelius steyn (1903-1976) (officer administering the government) & 30 april 1961 & 31 may 1961 & elizabeth ii & verwoerd \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where left office = '26 january 1931' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>name (birth-death)</th> <th>took office</th> <th>left office</th> <th>monarch</th> <th>prime minister</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>the viscount gladstone (1854-1930)</td> <td>31 may 1910</td> <td>8 september 1914</td> <td>george v</td> <td>botha</td> </tr> <tr> <th>1</th> <td>2</td> <td>the viscount buxton (1853-1934)</td> <td>8 september 1914</td> <td>17 november 1920</td> <td>george v</td> <td>botha</td> </tr> <tr> <th>2</th> <td>3</td> <td>hrh prince arthur of connaught (1883-1938)</td> <td>17 november 1920</td> <td>21 january 1924</td> <td>george v</td> <td>smuts</td> </tr> <tr> <th>3</th> <td>4</td> <td>the earl of athlone (1874-1957)</td> <td>21 january 1924</td> <td>26 january 1931</td> <td>george v</td> <td>smuts</td> </tr> <tr> <th>4</th> <td>5</td> <td>the earl of clarendon (1877-1955)</td> <td>26 january 1931</td> <td>5 april 1937</td> <td>george v</td> <td>hertzog</td> </tr> <tr> <th>5</th> <td>6</td> <td>sir patrick duncan (1870-1943)</td> <td>5 april 1937</td> <td>17 july 1943</td> <td>george vi</td> <td>hertzog</td> </tr> <tr> <th>6</th> <td>6</td> <td>nicolaas jacobus de wet (1873-1960) (officer administering the government)</td> <td>17 july 1943</td> <td>1 january 1946</td> <td>george vi</td> <td>smuts</td> </tr> <tr> <th>7</th> <td>7</td> <td>gideon brand van zyl (1873-1956)</td> <td>1 january 1946</td> <td>1 january 1951</td> <td>george vi</td> <td>smuts</td> </tr> <tr> <th>8</th> <td>8</td> <td>ernest george jansen (1881-1959)</td> <td>1 january 1951</td> <td>25 november 1959</td> <td>george vi</td> <td>malan</td> </tr> <tr> <th>9</th> <td>8</td> <td>lucas cornelius steyn (1903-1976) (officer administering the government)</td> <td>26 november 1959</td> <td>11 december 1959</td> <td>elizabeth ii</td> <td>verwoerd</td> </tr> <tr> <th>10</th> <td>9</td> <td>charles robberts swart (1894-1982)</td> <td>11 december 1959</td> <td>30 april 1961</td> <td>elizabeth ii</td> <td>verwoerd</td> </tr> <tr> <th>11</th> <td>9</td> <td>lucas cornelius steyn (1903-1976) (officer administering the government)</td> <td>30 april 1961</td> <td>31 may 1961</td> <td>elizabeth ii</td> <td>verwoerd</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where left office = '26 january 1931' <table_name> : table | | # | name (birth-death) | took office | left office | monarch | prime minister | |---:|----:|:---------------------------------------------------------------------------|:-----------------|:-----------------|:-------------|:-----------------| | 0 | 1 | the viscount gladstone (1854-1930) | 31 may 1910 | 8 september 1914 | george v | botha | | 1 | 2 | the viscount buxton (1853-1934) | 8 september 1914 | 17 november 1920 | george v | botha | | 2 | 3 | hrh prince arthur of connaught (1883-1938) | 17 november 1920 | 21 january 1924 | george v | smuts | | 3 | 4 | the earl of athlone (1874-1957) | 21 january 1924 | 26 january 1931 | george v | smuts | | 4 | 5 | the earl of clarendon (1877-1955) | 26 january 1931 | 5 april 1937 | george v | hertzog | | 5 | 6 | sir patrick duncan (1870-1943) | 5 april 1937 | 17 july 1943 | george vi | hertzog | | 6 | 6 | nicolaas jacobus de wet (1873-1960) (officer administering the government) | 17 july 1943 | 1 january 1946 | george vi | smuts | | 7 | 7 | gideon brand van zyl (1873-1956) | 1 january 1946 | 1 january 1951 | george vi | smuts | | 8 | 8 | ernest george jansen (1881-1959) | 1 january 1951 | 25 november 1959 | george vi | malan | | 9 | 8 | lucas cornelius steyn (1903-1976) (officer administering the government) | 26 november 1959 | 11 december 1959 | elizabeth ii | verwoerd | | 10 | 9 | charles robberts swart (1894-1982) | 11 december 1959 | 30 april 1961 | elizabeth ii | verwoerd | | 11 | 9 | lucas cornelius steyn (1903-1976) (officer administering the government) | 30 april 1961 | 31 may 1961 | elizabeth ii | verwoerd |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : old municipalities row 1 : north kynouria

select old municipalities where old municipalities = 'north kynouria' <table_name> : table \begin{tabular}{llll} \toprule & new municipality & old municipalities & seat \\ \midrule 0 & gortynia & dimitsana & dimitsana \\ 1 & gortynia & vytina & dimitsana \\ 2 & gortynia & iraia & dimitsana \\ 3 & gortynia & kleitor & dimitsana \\ 4 & gortynia & kontovazaina & dimitsana \\ 5 & gortynia & langadia & dimitsana \\ 6 & gortynia & trikolonoi & dimitsana \\ 7 & gortynia & tropaia & dimitsana \\ 8 & megalopoli & gortyna & megalopoli \\ 9 & megalopoli & falaisia & megalopoli \\ 10 & north kynouria (voreia kynouria) & north kynouria & astros \\ 11 & south kynouria (notia kynouria) & leonidio & leonidio \\ 12 & south kynouria (notia kynouria) & kosmas & leonidio \\ 13 & south kynouria (notia kynouria) & tyros & leonidio \\ 14 & tripoli & valtetsi & tripoli \\ 15 & tripoli & korythio & tripoli \\ 16 & tripoli & levidi & tripoli \\ 17 & tripoli & mantineia & tripoli \\ 18 & tripoli & skyritida & tripoli \\ 19 & tripoli & tegea & tripoli \\ 20 & tripoli & falanthos & tripoli \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & old municipalities \\ \midrule 0 & north kynouria \\ \bottomrule \end{tabular}

select old municipalities where old municipalities = 'north kynouria' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>new municipality</th> <th>old municipalities</th> <th>seat</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>gortynia</td> <td>dimitsana</td> <td>dimitsana</td> </tr> <tr> <th>1</th> <td>gortynia</td> <td>vytina</td> <td>dimitsana</td> </tr> <tr> <th>2</th> <td>gortynia</td> <td>iraia</td> <td>dimitsana</td> </tr> <tr> <th>3</th> <td>gortynia</td> <td>kleitor</td> <td>dimitsana</td> </tr> <tr> <th>4</th> <td>gortynia</td> <td>kontovazaina</td> <td>dimitsana</td> </tr> <tr> <th>5</th> <td>gortynia</td> <td>langadia</td> <td>dimitsana</td> </tr> <tr> <th>6</th> <td>gortynia</td> <td>trikolonoi</td> <td>dimitsana</td> </tr> <tr> <th>7</th> <td>gortynia</td> <td>tropaia</td> <td>dimitsana</td> </tr> <tr> <th>8</th> <td>megalopoli</td> <td>gortyna</td> <td>megalopoli</td> </tr> <tr> <th>9</th> <td>megalopoli</td> <td>falaisia</td> <td>megalopoli</td> </tr> <tr> <th>10</th> <td>north kynouria\t\t (voreia kynouria)</td> <td>north kynouria</td> <td>astros</td> </tr> <tr> <th>11</th> <td>south kynouria\t\t (notia kynouria)</td> <td>leonidio</td> <td>leonidio</td> </tr> <tr> <th>12</th> <td>south kynouria\t\t (notia kynouria)</td> <td>kosmas</td> <td>leonidio</td> </tr> <tr> <th>13</th> <td>south kynouria\t\t (notia kynouria)</td> <td>tyros</td> <td>leonidio</td> </tr> <tr> <th>14</th> <td>tripoli</td> <td>valtetsi</td> <td>tripoli</td> </tr> <tr> <th>15</th> <td>tripoli</td> <td>korythio</td> <td>tripoli</td> </tr> <tr> <th>16</th> <td>tripoli</td> <td>levidi</td> <td>tripoli</td> </tr> <tr> <th>17</th> <td>tripoli</td> <td>mantineia</td> <td>tripoli</td> </tr> <tr> <th>18</th> <td>tripoli</td> <td>skyritida</td> <td>tripoli</td> </tr> <tr> <th>19</th> <td>tripoli</td> <td>tegea</td> <td>tripoli</td> </tr> <tr> <th>20</th> <td>tripoli</td> <td>falanthos</td> <td>tripoli</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>old municipalities</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>north kynouria</td> </tr> </tbody> </table>

select old municipalities where old municipalities = 'north kynouria' <table_name> : table | | new municipality | old municipalities | seat | |---:|:-------------------|:---------------------|:-----------| | 0 | gortynia | dimitsana | dimitsana | | 1 | gortynia | vytina | dimitsana | | 2 | gortynia | iraia | dimitsana | | 3 | gortynia | kleitor | dimitsana | | 4 | gortynia | kontovazaina | dimitsana | | 5 | gortynia | langadia | dimitsana | | 6 | gortynia | trikolonoi | dimitsana | | 7 | gortynia | tropaia | dimitsana | | 8 | megalopoli | gortyna | megalopoli | | 9 | megalopoli | falaisia | megalopoli | | 10 | north kynouria (voreia kynouria) | north kynouria | astros | | 11 | south kynouria (notia kynouria) | leonidio | leonidio | | 12 | south kynouria (notia kynouria) | kosmas | leonidio | | 13 | south kynouria (notia kynouria) | tyros | leonidio | | 14 | tripoli | valtetsi | tripoli | | 15 | tripoli | korythio | tripoli | | 16 | tripoli | levidi | tripoli | | 17 | tripoli | mantineia | tripoli | | 18 | tripoli | skyritida | tripoli | | 19 | tripoli | tegea | tripoli | | 20 | tripoli | falanthos | tripoli |

| | old municipalities | |---:|:---------------------| | 0 | north kynouria |

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select count ( act ) where act = 'janelle monae' col : act | year signed | # albums released under bad boy row 1 : diddy | 1993 | 6 row 2 : the notorious b.i.g | 1993 | 5 row 3 : harve pierre | 1993 | none row 4 : the hitmen | 1993 | none row 5 : mario winans | 1995 | 1 row 6 : kalenna harper | 2004 | none row 7 : cassie | 2006 | 1 row 8 : janelle monae | 2007 | 2 row 9 : red cafe | 2009 | none row 10 : machine gun kelly | 2011 | 1 row 11 : french montana | 2012 | 1 row 12 : megan nicole | 2012 | none

col : count ( "act" ) row 1 : 1

select count ( act ) where act = 'janelle monae' <table_name> : table \begin{tabular}{llll} \toprule & act & year signed & # albums released under bad boy \\ \midrule 0 & diddy & 1993 & 6 \\ 1 & the notorious b.i.g & 1993 & 5 \\ 2 & harve pierre & 1993 & none \\ 3 & the hitmen & 1993 & none \\ 4 & mario winans & 1995 & 1 \\ 5 & kalenna harper & 2004 & none \\ 6 & cassie & 2006 & 1 \\ 7 & janelle monae & 2007 & 2 \\ 8 & red cafe & 2009 & none \\ 9 & machine gun kelly & 2011 & 1 \\ 10 & french montana & 2012 & 1 \\ 11 & megan nicole & 2012 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "act" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( act ) where act = 'janelle monae' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>act</th> <th>year signed</th> <th># albums released under bad boy</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>diddy</td> <td>1993</td> <td>6</td> </tr> <tr> <th>1</th> <td>the notorious b.i.g</td> <td>1993</td> <td>5</td> </tr> <tr> <th>2</th> <td>harve pierre</td> <td>1993</td> <td>none</td> </tr> <tr> <th>3</th> <td>the hitmen</td> <td>1993</td> <td>none</td> </tr> <tr> <th>4</th> <td>mario winans</td> <td>1995</td> <td>1</td> </tr> <tr> <th>5</th> <td>kalenna harper</td> <td>2004</td> <td>none</td> </tr> <tr> <th>6</th> <td>cassie</td> <td>2006</td> <td>1</td> </tr> <tr> <th>7</th> <td>janelle monae</td> <td>2007</td> <td>2</td> </tr> <tr> <th>8</th> <td>red cafe</td> <td>2009</td> <td>none</td> </tr> <tr> <th>9</th> <td>machine gun kelly</td> <td>2011</td> <td>1</td> </tr> <tr> <th>10</th> <td>french montana</td> <td>2012</td> <td>1</td> </tr> <tr> <th>11</th> <td>megan nicole</td> <td>2012</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "act" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( act ) where act = 'janelle monae' <table_name> : table | | act | year signed | # albums released under bad boy | |---:|:--------------------|--------------:|:----------------------------------| | 0 | diddy | 1993 | 6 | | 1 | the notorious b.i.g | 1993 | 5 | | 2 | harve pierre | 1993 | none | | 3 | the hitmen | 1993 | none | | 4 | mario winans | 1995 | 1 | | 5 | kalenna harper | 2004 | none | | 6 | cassie | 2006 | 1 | | 7 | janelle monae | 2007 | 2 | | 8 | red cafe | 2009 | none | | 9 | machine gun kelly | 2011 | 1 | | 10 | french montana | 2012 | 1 | | 11 | megan nicole | 2012 | none |

| | count ( "act" ) | |---:|------------------:| | 0 | 1 |

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select driver where no > 5 order by no asc limit 1 col : pos | no | driver | constructor | laps | time/retired | grid | points row 1 : 1 | 15 | sebastian vettel | red bull-renault | 56 | 1:57:43.485 | 1 | 10 row 2 : 2 | 14 | mark webber | red bull-renault | 56 | 10.97 | 3 | 8 row 3 : 3 | 22 | jenson button | brawn-mercedes | 56 | 44.975 | 5 | 6 row 4 : 4 | 23 | rubens barrichello | brawn-mercedes | 56 | +1:03.704 | 4 | 5 row 5 : 5 | 2 | heikki kovalainen | mclaren-mercedes | 56 | +1:05.102 | 12 | 4 row 6 : 6 | 1 | lewis hamilton | mclaren-mercedes | 56 | +1:11.866 | 9 | 3 row 7 : 7 | 10 | timo glock | toyota | 56 | +1:14.476 | 19 | 2 row 8 : 8 | 12 | sebastien buemi | toro rosso-ferrari | 56 | +1:16.439 | 10 | 1 row 9 : 9 | 7 | fernando alonso | renault | 56 | +1:24.309 | 2 | none row 10 : 10 | 4 | kimi raikkonen | ferrari | 56 | +1:31.750 | 8 | none row 11 : 11 | 11 | sebastien bourdais | toro rosso-ferrari | 56 | +1:34.156 | 15 | none row 12 : 12 | 6 | nick heidfeld | bmw sauber | 56 | +1:35.834 | 11 | none row 13 : 13 | 5 | robert kubica | bmw sauber | 56 | +1:46.853 | 17 | none row 14 : 14 | 21 | giancarlo fisichella | force india-mercedes | 55 | +1 lap | 20 | none row 15 : 15 | 16 | nico rosberg | williams-toyota | 55 | +1 lap | 7 | none row 16 : 16 | 8 | nelson piquet, jr | renault | 54 | +2 laps | 16 | none row 17 : 17 | 20 | adrian sutil | force india-mercedes | 50 | accident | 18 | none row 18 : ret | 17 | kazuki nakajima | williams-toyota | 43 | transmission | 14 | none row 19 : ret | 3 | felipe massa | ferrari | 20 | electrical | 13 | none row 20 : ret | 9 | jarno trulli | toyota | 18 | collision damage | 6 | none

col : driver row 1 : fernando alonso row 2 : nick heidfeld row 3 : nelson piquet, jr row 4 : jarno trulli

select driver where no > 5 order by no asc limit 1 <table_name> : table \begin{tabular}{lllllllll} \toprule & pos & no & driver & constructor & laps & time/retired & grid & points \\ \midrule 0 & 1 & 15 & sebastian vettel & red bull-renault & 56 & 1:57:43.485 & 1 & 10 \\ 1 & 2 & 14 & mark webber & red bull-renault & 56 & 10.97 & 3 & 8 \\ 2 & 3 & 22 & jenson button & brawn-mercedes & 56 & 44.975 & 5 & 6 \\ 3 & 4 & 23 & rubens barrichello & brawn-mercedes & 56 & +1:03.704 & 4 & 5 \\ 4 & 5 & 2 & heikki kovalainen & mclaren-mercedes & 56 & +1:05.102 & 12 & 4 \\ 5 & 6 & 1 & lewis hamilton & mclaren-mercedes & 56 & +1:11.866 & 9 & 3 \\ 6 & 7 & 10 & timo glock & toyota & 56 & +1:14.476 & 19 & 2 \\ 7 & 8 & 12 & sebastien buemi & toro rosso-ferrari & 56 & +1:16.439 & 10 & 1 \\ 8 & 9 & 7 & fernando alonso & renault & 56 & +1:24.309 & 2 & none \\ 9 & 10 & 4 & kimi raikkonen & ferrari & 56 & +1:31.750 & 8 & none \\ 10 & 11 & 11 & sebastien bourdais & toro rosso-ferrari & 56 & +1:34.156 & 15 & none \\ 11 & 12 & 6 & nick heidfeld & bmw sauber & 56 & +1:35.834 & 11 & none \\ 12 & 13 & 5 & robert kubica & bmw sauber & 56 & +1:46.853 & 17 & none \\ 13 & 14 & 21 & giancarlo fisichella & force india-mercedes & 55 & +1 lap & 20 & none \\ 14 & 15 & 16 & nico rosberg & williams-toyota & 55 & +1 lap & 7 & none \\ 15 & 16 & 8 & nelson piquet, jr & renault & 54 & +2 laps & 16 & none \\ 16 & 17 & 20 & adrian sutil & force india-mercedes & 50 & accident & 18 & none \\ 17 & ret & 17 & kazuki nakajima & williams-toyota & 43 & transmission & 14 & none \\ 18 & ret & 3 & felipe massa & ferrari & 20 & electrical & 13 & none \\ 19 & ret & 9 & jarno trulli & toyota & 18 & collision damage & 6 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & driver \\ \midrule 0 & fernando alonso \\ 1 & nick heidfeld \\ 2 & nelson piquet, jr \\ 3 & jarno trulli \\ \bottomrule \end{tabular}

select driver where no > 5 order by no asc limit 1 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pos</th> <th>no</th> <th>driver</th> <th>constructor</th> <th>laps</th> <th>time/retired</th> <th>grid</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>15</td> <td>sebastian vettel</td> <td>red bull-renault</td> <td>56</td> <td>1:57:43.485</td> <td>1</td> <td>10</td> </tr> <tr> <th>1</th> <td>2</td> <td>14</td> <td>mark webber</td> <td>red bull-renault</td> <td>56</td> <td>10.97</td> <td>3</td> <td>8</td> </tr> <tr> <th>2</th> <td>3</td> <td>22</td> <td>jenson button</td> <td>brawn-mercedes</td> <td>56</td> <td>44.975</td> <td>5</td> <td>6</td> </tr> <tr> <th>3</th> <td>4</td> <td>23</td> <td>rubens barrichello</td> <td>brawn-mercedes</td> <td>56</td> <td>+1:03.704</td> <td>4</td> <td>5</td> </tr> <tr> <th>4</th> <td>5</td> <td>2</td> <td>heikki kovalainen</td> <td>mclaren-mercedes</td> <td>56</td> <td>+1:05.102</td> <td>12</td> <td>4</td> </tr> <tr> <th>5</th> <td>6</td> <td>1</td> <td>lewis hamilton</td> <td>mclaren-mercedes</td> <td>56</td> <td>+1:11.866</td> <td>9</td> <td>3</td> </tr> <tr> <th>6</th> <td>7</td> <td>10</td> <td>timo glock</td> <td>toyota</td> <td>56</td> <td>+1:14.476</td> <td>19</td> <td>2</td> </tr> <tr> <th>7</th> <td>8</td> <td>12</td> <td>sebastien buemi</td> <td>toro rosso-ferrari</td> <td>56</td> <td>+1:16.439</td> <td>10</td> <td>1</td> </tr> <tr> <th>8</th> <td>9</td> <td>7</td> <td>fernando alonso</td> <td>renault</td> <td>56</td> <td>+1:24.309</td> <td>2</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>4</td> <td>kimi raikkonen</td> <td>ferrari</td> <td>56</td> <td>+1:31.750</td> <td>8</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>11</td> <td>sebastien bourdais</td> <td>toro rosso-ferrari</td> <td>56</td> <td>+1:34.156</td> <td>15</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>6</td> <td>nick heidfeld</td> <td>bmw sauber</td> <td>56</td> <td>+1:35.834</td> <td>11</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>5</td> <td>robert kubica</td> <td>bmw sauber</td> <td>56</td> <td>+1:46.853</td> <td>17</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>21</td> <td>giancarlo fisichella</td> <td>force india-mercedes</td> <td>55</td> <td>+1 lap</td> <td>20</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>16</td> <td>nico rosberg</td> <td>williams-toyota</td> <td>55</td> <td>+1 lap</td> <td>7</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>8</td> <td>nelson piquet, jr</td> <td>renault</td> <td>54</td> <td>+2 laps</td> <td>16</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>20</td> <td>adrian sutil</td> <td>force india-mercedes</td> <td>50</td> <td>accident</td> <td>18</td> <td>none</td> </tr> <tr> <th>17</th> <td>ret</td> <td>17</td> <td>kazuki nakajima</td> <td>williams-toyota</td> <td>43</td> <td>transmission</td> <td>14</td> <td>none</td> </tr> <tr> <th>18</th> <td>ret</td> <td>3</td> <td>felipe massa</td> <td>ferrari</td> <td>20</td> <td>electrical</td> <td>13</td> <td>none</td> </tr> <tr> <th>19</th> <td>ret</td> <td>9</td> <td>jarno trulli</td> <td>toyota</td> <td>18</td> <td>collision damage</td> <td>6</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>driver</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>fernando alonso</td> </tr> <tr> <th>1</th> <td>nick heidfeld</td> </tr> <tr> <th>2</th> <td>nelson piquet, jr</td> </tr> <tr> <th>3</th> <td>jarno trulli</td> </tr> </tbody> </table>

select driver where no > 5 order by no asc limit 1 <table_name> : table | | pos | no | driver | constructor | laps | time/retired | grid | points | |---:|:------|-----:|:---------------------|:---------------------|-------:|:-----------------|-------:|:---------| | 0 | 1 | 15 | sebastian vettel | red bull-renault | 56 | 1:57:43.485 | 1 | 10 | | 1 | 2 | 14 | mark webber | red bull-renault | 56 | 10.97 | 3 | 8 | | 2 | 3 | 22 | jenson button | brawn-mercedes | 56 | 44.975 | 5 | 6 | | 3 | 4 | 23 | rubens barrichello | brawn-mercedes | 56 | +1:03.704 | 4 | 5 | | 4 | 5 | 2 | heikki kovalainen | mclaren-mercedes | 56 | +1:05.102 | 12 | 4 | | 5 | 6 | 1 | lewis hamilton | mclaren-mercedes | 56 | +1:11.866 | 9 | 3 | | 6 | 7 | 10 | timo glock | toyota | 56 | +1:14.476 | 19 | 2 | | 7 | 8 | 12 | sebastien buemi | toro rosso-ferrari | 56 | +1:16.439 | 10 | 1 | | 8 | 9 | 7 | fernando alonso | renault | 56 | +1:24.309 | 2 | none | | 9 | 10 | 4 | kimi raikkonen | ferrari | 56 | +1:31.750 | 8 | none | | 10 | 11 | 11 | sebastien bourdais | toro rosso-ferrari | 56 | +1:34.156 | 15 | none | | 11 | 12 | 6 | nick heidfeld | bmw sauber | 56 | +1:35.834 | 11 | none | | 12 | 13 | 5 | robert kubica | bmw sauber | 56 | +1:46.853 | 17 | none | | 13 | 14 | 21 | giancarlo fisichella | force india-mercedes | 55 | +1 lap | 20 | none | | 14 | 15 | 16 | nico rosberg | williams-toyota | 55 | +1 lap | 7 | none | | 15 | 16 | 8 | nelson piquet, jr | renault | 54 | +2 laps | 16 | none | | 16 | 17 | 20 | adrian sutil | force india-mercedes | 50 | accident | 18 | none | | 17 | ret | 17 | kazuki nakajima | williams-toyota | 43 | transmission | 14 | none | | 18 | ret | 3 | felipe massa | ferrari | 20 | electrical | 13 | none | | 19 | ret | 9 | jarno trulli | toyota | 18 | collision damage | 6 | none |

| | driver | |---:|:------------------| | 0 | fernando alonso | | 1 | nick heidfeld | | 2 | nelson piquet, jr | | 3 | jarno trulli |

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select team where postseason lost = 0 col : team | year | regular season won | regular season lost | regular season win % | regular season finish | postseason won | postseason lost | postseason win % | postseason result row 1 : cle | 1991 | 32 | 53 | 0.376 | 7th in al east | none | none | none | none row 2 : cle | 1992 | 76 | 86 | 0.469 | 5th in al east | none | none | none | none row 3 : cle | 1993 | 76 | 86 | 0.469 | 6th in al east | none | none | none | none row 4 : cle | 1994 | 66 | 47 | 0.584 | 2nd in al central | none | none | none | no mlb postseason row 5 : cle | 1995 | 100 | 44 | 0.694 | 1st in al central | 9 | 6 | 0.6 | lost ws to atl row 6 : cle | 1996 | 99 | 62 | 0.615 | 1st in al central | 1 | 3 | 0.25 | lost lds to bal row 7 : cle | 1997 | 86 | 75 | 0.534 | 1st in al central | 10 | 8 | 0.556 | lost ws to fla row 8 : cle | 1998 | 89 | 73 | 0.549 | 1st in al central | 5 | 5 | 0.5 | lost lcs to nyy row 9 : cle | 1999 | 97 | 65 | 0.599 | 1st in al central | 2 | 3 | 0.4 | lost lds to bos row 10 : bal | 2000 | 74 | 88 | 0.457 | 4th in al east | none | none | none | none row 11 : bal | 2001 | 63 | 98 | 0.391 | 4th in al east | none | none | none | none row 12 : bal | 2002 | 67 | 95 | 0.414 | 4th in al east | none | none | none | none row 13 : bal | 2003 | 71 | 91 | 0.438 | 4th in al east | none | none | none | none row 14 : sea | 2005 | 69 | 93 | 0.426 | 4th in al west | none | none | none | none row 15 : sea | 2006 | 78 | 84 | 0.481 | 4th in al west | none | none | none | none row 16 : sea | 2007 | 45 | 33 | 0.571 | 2nd in al west | none | none | none | none row 17 : cle total | cle total | 721 | 591 | 0.55 | none | 27 | 25 | 0.519 | none row 18 : bal total | bal total | 275 | 372 | 0.425 | none | 0 | 0 | 0 | none row 19 : sea total | sea total | 192 | 210 | 0.478 | none | 0 | 0 | 0 | none row 20 : total | total | 1188 | 1173 | 0.503 | none | 27 | 25 | 0.519 | none

col : team row 1 : bal total row 2 : sea total

select team where postseason lost = 0 <table_name> : table \begin{tabular}{lllllllllll} \toprule & team & year & regular season won & regular season lost & regular season win % & regular season finish & postseason won & postseason lost & postseason win % & postseason result \\ \midrule 0 & cle & 1991 & 32 & 53 & 0.376 & 7th in al east & none & none & none & none \\ 1 & cle & 1992 & 76 & 86 & 0.469 & 5th in al east & none & none & none & none \\ 2 & cle & 1993 & 76 & 86 & 0.469 & 6th in al east & none & none & none & none \\ 3 & cle & 1994 & 66 & 47 & 0.584 & 2nd in al central & none & none & none & no mlb postseason \\ 4 & cle & 1995 & 100 & 44 & 0.694 & 1st in al central & 9 & 6 & 0.6 & lost ws to atl \\ 5 & cle & 1996 & 99 & 62 & 0.615 & 1st in al central & 1 & 3 & 0.25 & lost lds to bal \\ 6 & cle & 1997 & 86 & 75 & 0.534 & 1st in al central & 10 & 8 & 0.556 & lost ws to fla \\ 7 & cle & 1998 & 89 & 73 & 0.549 & 1st in al central & 5 & 5 & 0.5 & lost lcs to nyy \\ 8 & cle & 1999 & 97 & 65 & 0.599 & 1st in al central & 2 & 3 & 0.4 & lost lds to bos \\ 9 & bal & 2000 & 74 & 88 & 0.457 & 4th in al east & none & none & none & none \\ 10 & bal & 2001 & 63 & 98 & 0.391 & 4th in al east & none & none & none & none \\ 11 & bal & 2002 & 67 & 95 & 0.414 & 4th in al east & none & none & none & none \\ 12 & bal & 2003 & 71 & 91 & 0.438 & 4th in al east & none & none & none & none \\ 13 & sea & 2005 & 69 & 93 & 0.426 & 4th in al west & none & none & none & none \\ 14 & sea & 2006 & 78 & 84 & 0.481 & 4th in al west & none & none & none & none \\ 15 & sea & 2007 & 45 & 33 & 0.571 & 2nd in al west & none & none & none & none \\ 16 & cle total & cle total & 721 & 591 & 0.55 & none & 27 & 25 & 0.519 & none \\ 17 & bal total & bal total & 275 & 372 & 0.425 & none & 0 & 0 & 0 & none \\ 18 & sea total & sea total & 192 & 210 & 0.478 & none & 0 & 0 & 0 & none \\ 19 & total & total & 1188 & 1173 & 0.503 & none & 27 & 25 & 0.519 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & team \\ \midrule 0 & bal total \\ 1 & sea total \\ \bottomrule \end{tabular}

select team where postseason lost = 0 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>year</th> <th>regular season won</th> <th>regular season lost</th> <th>regular season win %</th> <th>regular season finish</th> <th>postseason won</th> <th>postseason lost</th> <th>postseason win %</th> <th>postseason result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>cle</td> <td>1991</td> <td>32</td> <td>53</td> <td>0.376</td> <td>7th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>1</th> <td>cle</td> <td>1992</td> <td>76</td> <td>86</td> <td>0.469</td> <td>5th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>2</th> <td>cle</td> <td>1993</td> <td>76</td> <td>86</td> <td>0.469</td> <td>6th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>3</th> <td>cle</td> <td>1994</td> <td>66</td> <td>47</td> <td>0.584</td> <td>2nd in al central</td> <td>none</td> <td>none</td> <td>none</td> <td>no mlb postseason</td> </tr> <tr> <th>4</th> <td>cle</td> <td>1995</td> <td>100</td> <td>44</td> <td>0.694</td> <td>1st in al central</td> <td>9</td> <td>6</td> <td>0.6</td> <td>lost ws to atl</td> </tr> <tr> <th>5</th> <td>cle</td> <td>1996</td> <td>99</td> <td>62</td> <td>0.615</td> <td>1st in al central</td> <td>1</td> <td>3</td> <td>0.25</td> <td>lost lds to bal</td> </tr> <tr> <th>6</th> <td>cle</td> <td>1997</td> <td>86</td> <td>75</td> <td>0.534</td> <td>1st in al central</td> <td>10</td> <td>8</td> <td>0.556</td> <td>lost ws to fla</td> </tr> <tr> <th>7</th> <td>cle</td> <td>1998</td> <td>89</td> <td>73</td> <td>0.549</td> <td>1st in al central</td> <td>5</td> <td>5</td> <td>0.5</td> <td>lost lcs to nyy</td> </tr> <tr> <th>8</th> <td>cle</td> <td>1999</td> <td>97</td> <td>65</td> <td>0.599</td> <td>1st in al central</td> <td>2</td> <td>3</td> <td>0.4</td> <td>lost lds to bos</td> </tr> <tr> <th>9</th> <td>bal</td> <td>2000</td> <td>74</td> <td>88</td> <td>0.457</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>10</th> <td>bal</td> <td>2001</td> <td>63</td> <td>98</td> <td>0.391</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>11</th> <td>bal</td> <td>2002</td> <td>67</td> <td>95</td> <td>0.414</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>12</th> <td>bal</td> <td>2003</td> <td>71</td> <td>91</td> <td>0.438</td> <td>4th in al east</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>13</th> <td>sea</td> <td>2005</td> <td>69</td> <td>93</td> <td>0.426</td> <td>4th in al west</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>14</th> <td>sea</td> <td>2006</td> <td>78</td> <td>84</td> <td>0.481</td> <td>4th in al west</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>15</th> <td>sea</td> <td>2007</td> <td>45</td> <td>33</td> <td>0.571</td> <td>2nd in al west</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>16</th> <td>cle total</td> <td>cle total</td> <td>721</td> <td>591</td> <td>0.55</td> <td>none</td> <td>27</td> <td>25</td> <td>0.519</td> <td>none</td> </tr> <tr> <th>17</th> <td>bal total</td> <td>bal total</td> <td>275</td> <td>372</td> <td>0.425</td> <td>none</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>18</th> <td>sea total</td> <td>sea total</td> <td>192</td> <td>210</td> <td>0.478</td> <td>none</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>19</th> <td>total</td> <td>total</td> <td>1188</td> <td>1173</td> <td>0.503</td> <td>none</td> <td>27</td> <td>25</td> <td>0.519</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>bal total</td> </tr> <tr> <th>1</th> <td>sea total</td> </tr> </tbody> </table>

select team where postseason lost = 0 <table_name> : table | | team | year | regular season won | regular season lost | regular season win % | regular season finish | postseason won | postseason lost | postseason win % | postseason result | |---:|:----------|:----------|---------------------:|----------------------:|-----------------------:|:------------------------|:-----------------|:------------------|:-------------------|:--------------------| | 0 | cle | 1991 | 32 | 53 | 0.376 | 7th in al east | none | none | none | none | | 1 | cle | 1992 | 76 | 86 | 0.469 | 5th in al east | none | none | none | none | | 2 | cle | 1993 | 76 | 86 | 0.469 | 6th in al east | none | none | none | none | | 3 | cle | 1994 | 66 | 47 | 0.584 | 2nd in al central | none | none | none | no mlb postseason | | 4 | cle | 1995 | 100 | 44 | 0.694 | 1st in al central | 9 | 6 | 0.6 | lost ws to atl | | 5 | cle | 1996 | 99 | 62 | 0.615 | 1st in al central | 1 | 3 | 0.25 | lost lds to bal | | 6 | cle | 1997 | 86 | 75 | 0.534 | 1st in al central | 10 | 8 | 0.556 | lost ws to fla | | 7 | cle | 1998 | 89 | 73 | 0.549 | 1st in al central | 5 | 5 | 0.5 | lost lcs to nyy | | 8 | cle | 1999 | 97 | 65 | 0.599 | 1st in al central | 2 | 3 | 0.4 | lost lds to bos | | 9 | bal | 2000 | 74 | 88 | 0.457 | 4th in al east | none | none | none | none | | 10 | bal | 2001 | 63 | 98 | 0.391 | 4th in al east | none | none | none | none | | 11 | bal | 2002 | 67 | 95 | 0.414 | 4th in al east | none | none | none | none | | 12 | bal | 2003 | 71 | 91 | 0.438 | 4th in al east | none | none | none | none | | 13 | sea | 2005 | 69 | 93 | 0.426 | 4th in al west | none | none | none | none | | 14 | sea | 2006 | 78 | 84 | 0.481 | 4th in al west | none | none | none | none | | 15 | sea | 2007 | 45 | 33 | 0.571 | 2nd in al west | none | none | none | none | | 16 | cle total | cle total | 721 | 591 | 0.55 | none | 27 | 25 | 0.519 | none | | 17 | bal total | bal total | 275 | 372 | 0.425 | none | 0 | 0 | 0 | none | | 18 | sea total | sea total | 192 | 210 | 0.478 | none | 0 | 0 | 0 | none | | 19 | total | total | 1188 | 1173 | 0.503 | none | 27 | 25 | 0.519 | none |

| | team | |---:|:----------| | 0 | bal total | | 1 | sea total |

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col : count ( "nation" ) row 1 : 0

select count ( nation ) where name = 1924 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & name & nation & time & speed & note \\ \midrule 0 & 1 & vilija sereikaite & lithuania & 3:33.766 & 50.522 & q \\ 1 & 2 & ellen van dijk & netherlands & 3:35.951 & 50.011 & q \\ 2 & 3 & joanna rowsell & united kingdom & 3:37.641 & 49.623 & q \\ 3 & 4 & svitlana halyuk & ukraine & 3:42.498 & 48.539 & q \\ 4 & 5 & aksana papko & belarus & 3:43.935 & 48.288 & none \\ 5 & 6 & oxana kozonchuk & russia & 3:45.132 & 47.971 & none \\ 6 & 7 & jarmila machacova & czech republic & 3:47.209 & 47.533 & none \\ 7 & 8 & stephanie pohl & germany & 3:47.483 & 47.476 & none \\ 8 & 9 & lisa brennauer & germany & 3:48.017 & 47.364 & none \\ 9 & 10 & edyta jasinska & poland & 3:48.628 & 47.238 & none \\ 10 & 11 & audrey cordon & france & 3:49.376 & 47.084 & none \\ 11 & 12 & alena amialyusik & belarus & 3:49.711 & 47.015 & none \\ 12 & 13 & hannah mayho & united kingdom & 3:50.176 & 46.92 & none \\ 13 & 14 & viktoriya kondel & russia & 3:51.349 & 46.682 & none \\ 14 & 15 & oksana lyesnik & ukraine & 3:51.543 & 46.643 & none \\ 15 & 16 & elise van hage & netherlands & 3:55.349 & 45.889 & none \\ 16 & 17 & dominika maczka & poland & 4:01.597 & 44.702 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "nation" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( nation ) where name = 1924 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>name</th> <th>nation</th> <th>time</th> <th>speed</th> <th>note</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>vilija sereikaite</td> <td>lithuania</td> <td>3:33.766</td> <td>50.522</td> <td>q</td> </tr> <tr> <th>1</th> <td>2</td> <td>ellen van dijk</td> <td>netherlands</td> <td>3:35.951</td> <td>50.011</td> <td>q</td> </tr> <tr> <th>2</th> <td>3</td> <td>joanna rowsell</td> <td>united kingdom</td> <td>3:37.641</td> <td>49.623</td> <td>q</td> </tr> <tr> <th>3</th> <td>4</td> <td>svitlana halyuk</td> <td>ukraine</td> <td>3:42.498</td> <td>48.539</td> <td>q</td> </tr> <tr> <th>4</th> <td>5</td> <td>aksana papko</td> <td>belarus</td> <td>3:43.935</td> <td>48.288</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>oxana kozonchuk</td> <td>russia</td> <td>3:45.132</td> <td>47.971</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>jarmila machacova</td> <td>czech republic</td> <td>3:47.209</td> <td>47.533</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>stephanie pohl</td> <td>germany</td> <td>3:47.483</td> <td>47.476</td> <td>none</td> </tr> <tr> <th>8</th> <td>9</td> <td>lisa brennauer</td> <td>germany</td> <td>3:48.017</td> <td>47.364</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>edyta jasinska</td> <td>poland</td> <td>3:48.628</td> <td>47.238</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>audrey cordon</td> <td>france</td> <td>3:49.376</td> <td>47.084</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>alena amialyusik</td> <td>belarus</td> <td>3:49.711</td> <td>47.015</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>hannah mayho</td> <td>united kingdom</td> <td>3:50.176</td> <td>46.92</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>viktoriya kondel</td> <td>russia</td> <td>3:51.349</td> <td>46.682</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>oksana lyesnik</td> <td>ukraine</td> <td>3:51.543</td> <td>46.643</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>elise van hage</td> <td>netherlands</td> <td>3:55.349</td> <td>45.889</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>dominika maczka</td> <td>poland</td> <td>4:01.597</td> <td>44.702</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "nation" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( nation ) where name = 1924 <table_name> : table | | rank | name | nation | time | speed | note | |---:|-------:|:------------------|:---------------|:---------|--------:|:-------| | 0 | 1 | vilija sereikaite | lithuania | 3:33.766 | 50.522 | q | | 1 | 2 | ellen van dijk | netherlands | 3:35.951 | 50.011 | q | | 2 | 3 | joanna rowsell | united kingdom | 3:37.641 | 49.623 | q | | 3 | 4 | svitlana halyuk | ukraine | 3:42.498 | 48.539 | q | | 4 | 5 | aksana papko | belarus | 3:43.935 | 48.288 | none | | 5 | 6 | oxana kozonchuk | russia | 3:45.132 | 47.971 | none | | 6 | 7 | jarmila machacova | czech republic | 3:47.209 | 47.533 | none | | 7 | 8 | stephanie pohl | germany | 3:47.483 | 47.476 | none | | 8 | 9 | lisa brennauer | germany | 3:48.017 | 47.364 | none | | 9 | 10 | edyta jasinska | poland | 3:48.628 | 47.238 | none | | 10 | 11 | audrey cordon | france | 3:49.376 | 47.084 | none | | 11 | 12 | alena amialyusik | belarus | 3:49.711 | 47.015 | none | | 12 | 13 | hannah mayho | united kingdom | 3:50.176 | 46.92 | none | | 13 | 14 | viktoriya kondel | russia | 3:51.349 | 46.682 | none | | 14 | 15 | oksana lyesnik | ukraine | 3:51.543 | 46.643 | none | | 15 | 16 | elise van hage | netherlands | 3:55.349 | 45.889 | none | | 16 | 17 | dominika maczka | poland | 4:01.597 | 44.702 | none |

| | count ( "nation" ) | |---:|---------------------:| | 0 | 0 |

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col : "% change 2011 / 12 + passengers handled" row 1 : % change 2011 / 12 + passengers handled

select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' <table_name> : table \begin{tabular}{lllll} \toprule & rank & airport & passengers handled & % change 2011 / 12 \\ \midrule 0 & 1 & netherlands - amsterdam & 105349 & none \\ 1 & 2 & united kingdom - belfast-international & 92502 & none \\ 2 & 3 & portugal - faro & 71676 & none \\ 3 & 4 & spain - barcelona & 66565 & none \\ 4 & 5 & spain - alicante & 64090 & none \\ 5 & 6 & spain - malaga & 59175 & none \\ 6 & 7 & ireland - dublin & 35524 & none \\ 7 & 8 & jersey - jersey & 35169 & 1128 \\ 8 & 9 & ireland - waterford & 31907 & 25 \\ 9 & 10 & spain - palma de mallorca & 27718 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & "% change 2011 / 12 + passengers handled" \\ \midrule 0 & % change 2011 / 12 + passengers handled \\ \bottomrule \end{tabular}

select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>airport</th> <th>passengers handled</th> <th>% change 2011 / 12</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>netherlands - amsterdam</td> <td>105349</td> <td>none</td> </tr> <tr> <th>1</th> <td>2</td> <td>united kingdom - belfast-international</td> <td>92502</td> <td>none</td> </tr> <tr> <th>2</th> <td>3</td> <td>portugal - faro</td> <td>71676</td> <td>none</td> </tr> <tr> <th>3</th> <td>4</td> <td>spain - barcelona</td> <td>66565</td> <td>none</td> </tr> <tr> <th>4</th> <td>5</td> <td>spain - alicante</td> <td>64090</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>spain - malaga</td> <td>59175</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>ireland - dublin</td> <td>35524</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>jersey - jersey</td> <td>35169</td> <td>1128</td> </tr> <tr> <th>8</th> <td>9</td> <td>ireland - waterford</td> <td>31907</td> <td>25</td> </tr> <tr> <th>9</th> <td>10</td> <td>spain - palma de mallorca</td> <td>27718</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"% change 2011 / 12 + passengers handled"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>% change 2011 / 12 + passengers handled</td> </tr> </tbody> </table>

select % change 2011 / 12 + passengers handled where airport = 'ireland - waterford' <table_name> : table | | rank | airport | passengers handled | % change 2011 / 12 | |---:|-------:|:---------------------------------------|---------------------:|:---------------------| | 0 | 1 | netherlands - amsterdam | 105349 | none | | 1 | 2 | united kingdom - belfast-international | 92502 | none | | 2 | 3 | portugal - faro | 71676 | none | | 3 | 4 | spain - barcelona | 66565 | none | | 4 | 5 | spain - alicante | 64090 | none | | 5 | 6 | spain - malaga | 59175 | none | | 6 | 7 | ireland - dublin | 35524 | none | | 7 | 8 | jersey - jersey | 35169 | 1128 | | 8 | 9 | ireland - waterford | 31907 | 25 | | 9 | 10 | spain - palma de mallorca | 27718 | none |

| | "% change 2011 / 12 + passengers handled" | |---:|:--------------------------------------------| | 0 | % change 2011 / 12 + passengers handled |

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select count ( * ) where games = '3' col : games | athletes | gold | silver | bronze | total | rank row 1 : 1988 seoul | 14 | 0 | 0 | 1 | 1 | 48 row 2 : 1992 barcelona | 5 | 0 | 0 | 0 | 0 | none row 3 : 1996 atlanta | 4 | 0 | 0 | 0 | 0 | none row 4 : 2000 sydney | 7 | 0 | 0 | 0 | 0 | none row 5 : 2004 athens | 10 | 2 | 4 | 0 | 6 | 42 row 6 : 2008 beijing | 18 | 4 | 1 | 2 | 7 | 32 row 7 : 2012 london | 31 | 3 | 0 | 3 | 6 | 37 row 8 : total | total | 9 | 5 | 6 | 20 | 54 row 9 : none | none | none | none | none | none | none

col : count ( "*" ) row 1 : 0

select count ( * ) where games = '3' <table_name> : table \begin{tabular}{llllllll} \toprule & games & athletes & gold & silver & bronze & total & rank \\ \midrule 0 & 1988 seoul & 14 & 0 & 0 & 1 & 1 & 48 \\ 1 & 1992 barcelona & 5 & 0 & 0 & 0 & 0 & none \\ 2 & 1996 atlanta & 4 & 0 & 0 & 0 & 0 & none \\ 3 & 2000 sydney & 7 & 0 & 0 & 0 & 0 & none \\ 4 & 2004 athens & 10 & 2 & 4 & 0 & 6 & 42 \\ 5 & 2008 beijing & 18 & 4 & 1 & 2 & 7 & 32 \\ 6 & 2012 london & 31 & 3 & 0 & 3 & 6 & 37 \\ 7 & total & total & 9 & 5 & 6 & 20 & 54 \\ 8 & none & none & none & none & none & none & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where games = '3' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>games</th> <th>athletes</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> <th>rank</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1988 seoul</td> <td>14</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> <td>48</td> </tr> <tr> <th>1</th> <td>1992 barcelona</td> <td>5</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>2</th> <td>1996 atlanta</td> <td>4</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>3</th> <td>2000 sydney</td> <td>7</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>none</td> </tr> <tr> <th>4</th> <td>2004 athens</td> <td>10</td> <td>2</td> <td>4</td> <td>0</td> <td>6</td> <td>42</td> </tr> <tr> <th>5</th> <td>2008 beijing</td> <td>18</td> <td>4</td> <td>1</td> <td>2</td> <td>7</td> <td>32</td> </tr> <tr> <th>6</th> <td>2012 london</td> <td>31</td> <td>3</td> <td>0</td> <td>3</td> <td>6</td> <td>37</td> </tr> <tr> <th>7</th> <td>total</td> <td>total</td> <td>9</td> <td>5</td> <td>6</td> <td>20</td> <td>54</td> </tr> <tr> <th>8</th> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where games = '3' <table_name> : table | | games | athletes | gold | silver | bronze | total | rank | |---:|:---------------|:-----------|:-------|:---------|:---------|:--------|:-------| | 0 | 1988 seoul | 14 | 0 | 0 | 1 | 1 | 48 | | 1 | 1992 barcelona | 5 | 0 | 0 | 0 | 0 | none | | 2 | 1996 atlanta | 4 | 0 | 0 | 0 | 0 | none | | 3 | 2000 sydney | 7 | 0 | 0 | 0 | 0 | none | | 4 | 2004 athens | 10 | 2 | 4 | 0 | 6 | 42 | | 5 | 2008 beijing | 18 | 4 | 1 | 2 | 7 | 32 | | 6 | 2012 london | 31 | 3 | 0 | 3 | 6 | 37 | | 7 | total | total | 9 | 5 | 6 | 20 | 54 | | 8 | none | none | none | none | none | none | none |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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select count ( player ) where player = 'bruce murray' col : # | player | goals | caps | career row 1 : 1 | landon donovan | 57 | 155 | 2000-present row 2 : 2 | clint dempsey | 36 | 103 | 2004-present row 3 : 3 | eric wynalda | 34 | 106 | 1990-2000 row 4 : 4 | brian mcbride | 30 | 95 | 1993-2006 row 5 : 5 | joe-max moore | 24 | 100 | 1992-2002 row 6 : 6 | jozy altidore | 21 | 67 | 2007-present row 7 : 6 | bruce murray | 21 | 86 | 1985-1993 row 8 : 8 | eddie johnson | 19 | 62 | 2004-present row 9 : 9 | earnie stewart | 17 | 101 | 1990-2004 row 10 : 9 | damarcus beasley | 17 | 114 | 2001-present

col : count ( "player" ) row 1 : 1

select count ( player ) where player = 'bruce murray' <table_name> : table \begin{tabular}{llllll} \toprule & # & player & goals & caps & career \\ \midrule 0 & 1 & landon donovan & 57 & 155 & 2000-present \\ 1 & 2 & clint dempsey & 36 & 103 & 2004-present \\ 2 & 3 & eric wynalda & 34 & 106 & 1990-2000 \\ 3 & 4 & brian mcbride & 30 & 95 & 1993-2006 \\ 4 & 5 & joe-max moore & 24 & 100 & 1992-2002 \\ 5 & 6 & jozy altidore & 21 & 67 & 2007-present \\ 6 & 6 & bruce murray & 21 & 86 & 1985-1993 \\ 7 & 8 & eddie johnson & 19 & 62 & 2004-present \\ 8 & 9 & earnie stewart & 17 & 101 & 1990-2004 \\ 9 & 9 & damarcus beasley & 17 & 114 & 2001-present \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "player" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( player ) where player = 'bruce murray' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>player</th> <th>goals</th> <th>caps</th> <th>career</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>landon donovan</td> <td>57</td> <td>155</td> <td>2000-present</td> </tr> <tr> <th>1</th> <td>2</td> <td>clint dempsey</td> <td>36</td> <td>103</td> <td>2004-present</td> </tr> <tr> <th>2</th> <td>3</td> <td>eric wynalda</td> <td>34</td> <td>106</td> <td>1990-2000</td> </tr> <tr> <th>3</th> <td>4</td> <td>brian mcbride</td> <td>30</td> <td>95</td> <td>1993-2006</td> </tr> <tr> <th>4</th> <td>5</td> <td>joe-max moore</td> <td>24</td> <td>100</td> <td>1992-2002</td> </tr> <tr> <th>5</th> <td>6</td> <td>jozy altidore</td> <td>21</td> <td>67</td> <td>2007-present</td> </tr> <tr> <th>6</th> <td>6</td> <td>bruce murray</td> <td>21</td> <td>86</td> <td>1985-1993</td> </tr> <tr> <th>7</th> <td>8</td> <td>eddie johnson</td> <td>19</td> <td>62</td> <td>2004-present</td> </tr> <tr> <th>8</th> <td>9</td> <td>earnie stewart</td> <td>17</td> <td>101</td> <td>1990-2004</td> </tr> <tr> <th>9</th> <td>9</td> <td>damarcus beasley</td> <td>17</td> <td>114</td> <td>2001-present</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "player" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( player ) where player = 'bruce murray' <table_name> : table | | # | player | goals | caps | career | |---:|----:|:-----------------|--------:|-------:|:-------------| | 0 | 1 | landon donovan | 57 | 155 | 2000-present | | 1 | 2 | clint dempsey | 36 | 103 | 2004-present | | 2 | 3 | eric wynalda | 34 | 106 | 1990-2000 | | 3 | 4 | brian mcbride | 30 | 95 | 1993-2006 | | 4 | 5 | joe-max moore | 24 | 100 | 1992-2002 | | 5 | 6 | jozy altidore | 21 | 67 | 2007-present | | 6 | 6 | bruce murray | 21 | 86 | 1985-1993 | | 7 | 8 | eddie johnson | 19 | 62 | 2004-present | | 8 | 9 | earnie stewart | 17 | 101 | 1990-2004 | | 9 | 9 | damarcus beasley | 17 | 114 | 2001-present |

| | count ( "player" ) | |---:|---------------------:| | 0 | 1 |

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select count ( * ) where total time < 1817 col : athlete | event | race 1 time | race 2 time | total time | total rank row 1 : johann haraldsson | giant slalom | 1:19.10 | dnf | dnf | none row 2 : kristinn magnusson | giant slalom | 1:17.50 | 1:16.29 | 2:33.79 | 42 row 3 : bjorgvin bjorgvinsson | giant slalom | 1:15.86 | dnf | dnf | none row 4 : kristinn magnusson | slalom | dnf | none | dnf | none row 5 : bjorgvin bjorgvinsson | slalom | dnf | none | dnf | none row 6 : johann haraldsson | slalom | 56.98 | 1:00.19 | 1:57.17 | 28 row 7 : kristinn bjornsson | slalom | 53.05 | 56.76 | 1:49.81 | 21

col : count ( "*" ) row 1 : 0

select count ( * ) where total time < 1817 <table_name> : table \begin{tabular}{lllllll} \toprule & athlete & event & race 1 time & race 2 time & total time & total rank \\ \midrule 0 & johann haraldsson & giant slalom & 1:19.10 & dnf & dnf & none \\ 1 & kristinn magnusson & giant slalom & 1:17.50 & 1:16.29 & 2:33.79 & 42 \\ 2 & bjorgvin bjorgvinsson & giant slalom & 1:15.86 & dnf & dnf & none \\ 3 & kristinn magnusson & slalom & dnf & none & dnf & none \\ 4 & bjorgvin bjorgvinsson & slalom & dnf & none & dnf & none \\ 5 & johann haraldsson & slalom & 56.98 & 1:00.19 & 1:57.17 & 28 \\ 6 & kristinn bjornsson & slalom & 53.05 & 56.76 & 1:49.81 & 21 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where total time < 1817 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>athlete</th> <th>event</th> <th>race 1 time</th> <th>race 2 time</th> <th>total time</th> <th>total rank</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>johann haraldsson</td> <td>giant slalom</td> <td>1:19.10</td> <td>dnf</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>1</th> <td>kristinn magnusson</td> <td>giant slalom</td> <td>1:17.50</td> <td>1:16.29</td> <td>2:33.79</td> <td>42</td> </tr> <tr> <th>2</th> <td>bjorgvin bjorgvinsson</td> <td>giant slalom</td> <td>1:15.86</td> <td>dnf</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>3</th> <td>kristinn magnusson</td> <td>slalom</td> <td>dnf</td> <td>none</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>4</th> <td>bjorgvin bjorgvinsson</td> <td>slalom</td> <td>dnf</td> <td>none</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>5</th> <td>johann haraldsson</td> <td>slalom</td> <td>56.98</td> <td>1:00.19</td> <td>1:57.17</td> <td>28</td> </tr> <tr> <th>6</th> <td>kristinn bjornsson</td> <td>slalom</td> <td>53.05</td> <td>56.76</td> <td>1:49.81</td> <td>21</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where total time < 1817 <table_name> : table | | athlete | event | race 1 time | race 2 time | total time | total rank | |---:|:----------------------|:-------------|:--------------|:--------------|:-------------|:-------------| | 0 | johann haraldsson | giant slalom | 1:19.10 | dnf | dnf | none | | 1 | kristinn magnusson | giant slalom | 1:17.50 | 1:16.29 | 2:33.79 | 42 | | 2 | bjorgvin bjorgvinsson | giant slalom | 1:15.86 | dnf | dnf | none | | 3 | kristinn magnusson | slalom | dnf | none | dnf | none | | 4 | bjorgvin bjorgvinsson | slalom | dnf | none | dnf | none | | 5 | johann haraldsson | slalom | 56.98 | 1:00.19 | 1:57.17 | 28 | | 6 | kristinn bjornsson | slalom | 53.05 | 56.76 | 1:49.81 | 21 |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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col : owner row 1 : televisa

select owner where network name = 'canal 5' <table_name> : table \begin{tabular}{llllll} \toprule & network name & flagship & programming type & owner & affiliates \\ \midrule 0 & canal de las estrellas & xew 2 & soap operas, retro movies and sports & televisa & 1 \\ 1 & canal 5 & xhgc 5 & cartoons, movies, and series & televisa & 1 \\ 2 & azteca 7 & xhimt 7 & sports, series, and movies & tv azteca & 1 \\ 3 & galavision & xeq 9 & retro programming and sports & televisa & 1 \\ 4 & once tv & xeipn 11 & educational and cultural & national polytechnic institute & 1 \\ 5 & azteca 13 & xhdf 13 & news, soap operas, and sports & tv azteca & 1 \\ 6 & independent & none & varies & independent & 2 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & owner \\ \midrule 0 & televisa \\ \bottomrule \end{tabular}

select owner where network name = 'canal 5' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>network name</th> <th>flagship</th> <th>programming type</th> <th>owner</th> <th>affiliates</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>canal de las estrellas</td> <td>xew 2</td> <td>soap operas, retro movies and sports</td> <td>televisa</td> <td>1</td> </tr> <tr> <th>1</th> <td>canal 5</td> <td>xhgc 5</td> <td>cartoons, movies, and series</td> <td>televisa</td> <td>1</td> </tr> <tr> <th>2</th> <td>azteca 7</td> <td>xhimt 7</td> <td>sports, series, and movies</td> <td>tv azteca</td> <td>1</td> </tr> <tr> <th>3</th> <td>galavision</td> <td>xeq 9</td> <td>retro programming and sports</td> <td>televisa</td> <td>1</td> </tr> <tr> <th>4</th> <td>once tv</td> <td>xeipn 11</td> <td>educational and cultural</td> <td>national polytechnic institute</td> <td>1</td> </tr> <tr> <th>5</th> <td>azteca 13</td> <td>xhdf 13</td> <td>news, soap operas, and sports</td> <td>tv azteca</td> <td>1</td> </tr> <tr> <th>6</th> <td>independent</td> <td>none</td> <td>varies</td> <td>independent</td> <td>2</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>owner</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>televisa</td> </tr> </tbody> </table>

select owner where network name = 'canal 5' <table_name> : table | | network name | flagship | programming type | owner | affiliates | |---:|:-----------------------|:-----------|:-------------------------------------|:-------------------------------|-------------:| | 0 | canal de las estrellas | xew 2 | soap operas, retro movies and sports | televisa | 1 | | 1 | canal 5 | xhgc 5 | cartoons, movies, and series | televisa | 1 | | 2 | azteca 7 | xhimt 7 | sports, series, and movies | tv azteca | 1 | | 3 | galavision | xeq 9 | retro programming and sports | televisa | 1 | | 4 | once tv | xeipn 11 | educational and cultural | national polytechnic institute | 1 | | 5 | azteca 13 | xhdf 13 | news, soap operas, and sports | tv azteca | 1 | | 6 | independent | none | varies | independent | 2 |

| | owner | |---:|:---------| | 0 | televisa |

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col : season row 1 : 2009

select season where position = '7th' <table_name> : table \begin{tabular}{lllllll} \toprule & season & level & division & section & position & movements \\ \midrule 0 & 1999 & tier 5 & division 4 & gotland & 6th & varserier (spring series) \\ 1 & none & tier 5 & division 4 & gotland & 5th & hostserier (autumn series) \\ 2 & 2000 & tier 5 & division 4 & gotland & 2nd & varserier (spring series) \\ 3 & none & tier 5 & division 4 & uppland/gotland host & 10th & hostserier (autumn series) \\ 4 & 2001 & tier 5 & division 4 & gotland & 4th & varserier (spring series) \\ 5 & none & tier 5 & division 4 & gotland & 4th & slutspel a (playoff a) \\ 6 & 2002 & tier 5 & division 4 & gotland & 3rd & promotion playoffs \\ 7 & 2003 & tier 5 & division 4 & gotland & 6th & none \\ 8 & 2004 & tier 5 & division 4 & gotland & 4th & none \\ 9 & 2005 & tier 5 & division 4 & gotland & 1st & none \\ 10 & 2006 & tier 5 & division 3 & ostra svealand & 12th & relegated \\ 11 & 2007 & tier 6 & division 4 & gotland & 2nd & none \\ 12 & 2008 & tier 6 & division 4 & gotland & 3rd & none \\ 13 & 2009 & tier 6 & division 4 & gotland & 7th & none \\ 14 & 2010 & tier 6 & division 4 & gotland & 2nd & none \\ 15 & 2011 & tier 6 & division 4 & gotland & 4th & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & season \\ \midrule 0 & 2009 \\ \bottomrule \end{tabular}

select season where position = '7th' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>level</th> <th>division</th> <th>section</th> <th>position</th> <th>movements</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>6th</td> <td>varserier (spring series)</td> </tr> <tr> <th>1</th> <td>none</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>5th</td> <td>hostserier (autumn series)</td> </tr> <tr> <th>2</th> <td>2000</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>2nd</td> <td>varserier (spring series)</td> </tr> <tr> <th>3</th> <td>none</td> <td>tier 5</td> <td>division 4</td> <td>uppland/gotland host</td> <td>10th</td> <td>hostserier (autumn series)</td> </tr> <tr> <th>4</th> <td>2001</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>varserier (spring series)</td> </tr> <tr> <th>5</th> <td>none</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>slutspel a (playoff a)</td> </tr> <tr> <th>6</th> <td>2002</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>3rd</td> <td>promotion playoffs</td> </tr> <tr> <th>7</th> <td>2003</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>6th</td> <td>none</td> </tr> <tr> <th>8</th> <td>2004</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>none</td> </tr> <tr> <th>9</th> <td>2005</td> <td>tier 5</td> <td>division 4</td> <td>gotland</td> <td>1st</td> <td>none</td> </tr> <tr> <th>10</th> <td>2006</td> <td>tier 5</td> <td>division 3</td> <td>ostra svealand</td> <td>12th</td> <td>relegated</td> </tr> <tr> <th>11</th> <td>2007</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>2nd</td> <td>none</td> </tr> <tr> <th>12</th> <td>2008</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>3rd</td> <td>none</td> </tr> <tr> <th>13</th> <td>2009</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>7th</td> <td>none</td> </tr> <tr> <th>14</th> <td>2010</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>2nd</td> <td>none</td> </tr> <tr> <th>15</th> <td>2011</td> <td>tier 6</td> <td>division 4</td> <td>gotland</td> <td>4th</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2009</td> </tr> </tbody> </table>

select season where position = '7th' <table_name> : table | | season | level | division | section | position | movements | |---:|:---------|:--------|:-----------|:---------------------|:-----------|:---------------------------| | 0 | 1999 | tier 5 | division 4 | gotland | 6th | varserier (spring series) | | 1 | none | tier 5 | division 4 | gotland | 5th | hostserier (autumn series) | | 2 | 2000 | tier 5 | division 4 | gotland | 2nd | varserier (spring series) | | 3 | none | tier 5 | division 4 | uppland/gotland host | 10th | hostserier (autumn series) | | 4 | 2001 | tier 5 | division 4 | gotland | 4th | varserier (spring series) | | 5 | none | tier 5 | division 4 | gotland | 4th | slutspel a (playoff a) | | 6 | 2002 | tier 5 | division 4 | gotland | 3rd | promotion playoffs | | 7 | 2003 | tier 5 | division 4 | gotland | 6th | none | | 8 | 2004 | tier 5 | division 4 | gotland | 4th | none | | 9 | 2005 | tier 5 | division 4 | gotland | 1st | none | | 10 | 2006 | tier 5 | division 3 | ostra svealand | 12th | relegated | | 11 | 2007 | tier 6 | division 4 | gotland | 2nd | none | | 12 | 2008 | tier 6 | division 4 | gotland | 3rd | none | | 13 | 2009 | tier 6 | division 4 | gotland | 7th | none | | 14 | 2010 | tier 6 | division 4 | gotland | 2nd | none | | 15 | 2011 | tier 6 | division 4 | gotland | 4th | none |

| | season | |---:|---------:| | 0 | 2009 |

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col : count ( "rider" ) row 1 : 11

select count ( rider ) where tyres = 'm' <table_name> : table \begin{tabular}{llllllll} \toprule & team & constructor & motorcycle & tyres & no & rider & rounds \\ \midrule 0 & camel yamaha team & yamaha & yamaha yzr-m1 & m & 5 & colin edwards & all \\ 1 & camel yamaha team & yamaha & yamaha yzr-m1 & m & 46 & valentino rossi & all \\ 2 & konica minolta honda & honda & honda rc211v & m & 6 & makoto tamada & all \\ 3 & tech 3 yamaha & yamaha & yamaha yzr-m1 & d & 7 & carlos checa & all \\ 4 & tech 3 yamaha & yamaha & yamaha yzr-m1 & d & 77 & james ellison & all \\ 5 & team roberts & team roberts & kr211v & m & 10 & kenny roberts, jr & all \\ 6 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 15 & sete gibernau & 1-7, 10-11, 13-16 \\ 7 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 65 & loris capirossi & all \\ 8 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 66 & alex hofmann & 8-9, 12 \\ 9 & ducati marlboro team & ducati & ducati desmosedici gp6 & b & 12 & troy bayliss & 17 \\ 10 & kawasaki racing team & kawasaki & kawasaki ninja zx-rr & b & 17 & randy de puniet & all \\ 11 & kawasaki racing team & kawasaki & kawasaki ninja zx-rr & b & 56 & shinya nakano & all \\ 12 & kawasaki racing team & kawasaki & kawasaki ninja zx-rr & b & 8 & naoki matsudo & 15 \\ 13 & rizla suzuki motogp & suzuki & suzuki gsv-r & b & 21 & john hopkins & all \\ 14 & rizla suzuki motogp & suzuki & suzuki gsv-r & b & 71 & chris vermeulen & all \\ 15 & rizla suzuki motogp & suzuki & suzuki gsv-r & b & 64 & kousuke akiyoshi & 15 \\ 16 & repsol honda team & honda & honda rc211v & m & 26 & dani pedrosa & all \\ 17 & repsol honda team & honda & honda rc211v & m & 69 & nicky hayden & all \\ 18 & honda lcr & honda & honda rc211v & m & 27 & casey stoner & all \\ 19 & pramac d'antin motogp & ducati & ducati desmosedici gp5 & d & 30 & jose luis cardoso & all \\ 20 & pramac d'antin motogp & ducati & ducati desmosedici gp5 & d & 66 & alex hofmann & 1-7, 10-11, 13-17 \\ 21 & pramac d'antin motogp & ducati & ducati desmosedici gp5 & d & 22 & ivan silva & 8-9, 12 \\ 22 & fortuna honda & honda & honda rc211v & m & 24 & toni elias & 1-8, 10-17 \\ 23 & fortuna honda & honda & honda rc211v & m & 33 & marco melandri & all \\ 24 & fortuna honda & honda & honda rc211v & m & 84 & michel fabrizio & 9 \\ 25 & ilmor srt & ilmor & ilmor x3 & m & 8 & garry mccoy & 16-17 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "rider" ) \\ \midrule 0 & 11 \\ \bottomrule \end{tabular}

select count ( rider ) where tyres = 'm' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>constructor</th> <th>motorcycle</th> <th>tyres</th> <th>no</th> <th>rider</th> <th>rounds</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>camel yamaha team</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>m</td> <td>5</td> <td>colin edwards</td> <td>all</td> </tr> <tr> <th>1</th> <td>camel yamaha team</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>m</td> <td>46</td> <td>valentino rossi</td> <td>all</td> </tr> <tr> <th>2</th> <td>konica minolta honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>6</td> <td>makoto tamada</td> <td>all</td> </tr> <tr> <th>3</th> <td>tech 3 yamaha</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>d</td> <td>7</td> <td>carlos checa</td> <td>all</td> </tr> <tr> <th>4</th> <td>tech 3 yamaha</td> <td>yamaha</td> <td>yamaha yzr-m1</td> <td>d</td> <td>77</td> <td>james ellison</td> <td>all</td> </tr> <tr> <th>5</th> <td>team roberts</td> <td>team roberts</td> <td>kr211v</td> <td>m</td> <td>10</td> <td>kenny roberts, jr</td> <td>all</td> </tr> <tr> <th>6</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>15</td> <td>sete gibernau</td> <td>1-7, 10-11, 13-16</td> </tr> <tr> <th>7</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>65</td> <td>loris capirossi</td> <td>all</td> </tr> <tr> <th>8</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>66</td> <td>alex hofmann</td> <td>8-9, 12</td> </tr> <tr> <th>9</th> <td>ducati marlboro team</td> <td>ducati</td> <td>ducati desmosedici gp6</td> <td>b</td> <td>12</td> <td>troy bayliss</td> <td>17</td> </tr> <tr> <th>10</th> <td>kawasaki racing team</td> <td>kawasaki</td> <td>kawasaki ninja zx-rr</td> <td>b</td> <td>17</td> <td>randy de puniet</td> <td>all</td> </tr> <tr> <th>11</th> <td>kawasaki racing team</td> <td>kawasaki</td> <td>kawasaki ninja zx-rr</td> <td>b</td> <td>56</td> <td>shinya nakano</td> <td>all</td> </tr> <tr> <th>12</th> <td>kawasaki racing team</td> <td>kawasaki</td> <td>kawasaki ninja zx-rr</td> <td>b</td> <td>8</td> <td>naoki matsudo</td> <td>15</td> </tr> <tr> <th>13</th> <td>rizla suzuki motogp</td> <td>suzuki</td> <td>suzuki gsv-r</td> <td>b</td> <td>21</td> <td>john hopkins</td> <td>all</td> </tr> <tr> <th>14</th> <td>rizla suzuki motogp</td> <td>suzuki</td> <td>suzuki gsv-r</td> <td>b</td> <td>71</td> <td>chris vermeulen</td> <td>all</td> </tr> <tr> <th>15</th> <td>rizla suzuki motogp</td> <td>suzuki</td> <td>suzuki gsv-r</td> <td>b</td> <td>64</td> <td>kousuke akiyoshi</td> <td>15</td> </tr> <tr> <th>16</th> <td>repsol honda team</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>26</td> <td>dani pedrosa</td> <td>all</td> </tr> <tr> <th>17</th> <td>repsol honda team</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>69</td> <td>nicky hayden</td> <td>all</td> </tr> <tr> <th>18</th> <td>honda lcr</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>27</td> <td>casey stoner</td> <td>all</td> </tr> <tr> <th>19</th> <td>pramac d'antin motogp</td> <td>ducati</td> <td>ducati desmosedici gp5</td> <td>d</td> <td>30</td> <td>jose luis cardoso</td> <td>all</td> </tr> <tr> <th>20</th> <td>pramac d'antin motogp</td> <td>ducati</td> <td>ducati desmosedici gp5</td> <td>d</td> <td>66</td> <td>alex hofmann</td> <td>1-7, 10-11, 13-17</td> </tr> <tr> <th>21</th> <td>pramac d'antin motogp</td> <td>ducati</td> <td>ducati desmosedici gp5</td> <td>d</td> <td>22</td> <td>ivan silva</td> <td>8-9, 12</td> </tr> <tr> <th>22</th> <td>fortuna honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>24</td> <td>toni elias</td> <td>1-8, 10-17</td> </tr> <tr> <th>23</th> <td>fortuna honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>33</td> <td>marco melandri</td> <td>all</td> </tr> <tr> <th>24</th> <td>fortuna honda</td> <td>honda</td> <td>honda rc211v</td> <td>m</td> <td>84</td> <td>michel fabrizio</td> <td>9</td> </tr> <tr> <th>25</th> <td>ilmor srt</td> <td>ilmor</td> <td>ilmor x3</td> <td>m</td> <td>8</td> <td>garry mccoy</td> <td>16-17</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "rider" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>11</td> </tr> </tbody> </table>

select count ( rider ) where tyres = 'm' <table_name> : table | | team | constructor | motorcycle | tyres | no | rider | rounds | |---:|:----------------------|:--------------|:-----------------------|:--------|-----:|:------------------|:------------------| | 0 | camel yamaha team | yamaha | yamaha yzr-m1 | m | 5 | colin edwards | all | | 1 | camel yamaha team | yamaha | yamaha yzr-m1 | m | 46 | valentino rossi | all | | 2 | konica minolta honda | honda | honda rc211v | m | 6 | makoto tamada | all | | 3 | tech 3 yamaha | yamaha | yamaha yzr-m1 | d | 7 | carlos checa | all | | 4 | tech 3 yamaha | yamaha | yamaha yzr-m1 | d | 77 | james ellison | all | | 5 | team roberts | team roberts | kr211v | m | 10 | kenny roberts, jr | all | | 6 | ducati marlboro team | ducati | ducati desmosedici gp6 | b | 15 | sete gibernau | 1-7, 10-11, 13-16 | | 7 | ducati marlboro team | ducati | ducati desmosedici gp6 | b | 65 | loris capirossi | all | | 8 | ducati marlboro team | ducati | ducati desmosedici gp6 | b | 66 | alex hofmann | 8-9, 12 | | 9 | ducati marlboro team | ducati | ducati desmosedici gp6 | b | 12 | troy bayliss | 17 | | 10 | kawasaki racing team | kawasaki | kawasaki ninja zx-rr | b | 17 | randy de puniet | all | | 11 | kawasaki racing team | kawasaki | kawasaki ninja zx-rr | b | 56 | shinya nakano | all | | 12 | kawasaki racing team | kawasaki | kawasaki ninja zx-rr | b | 8 | naoki matsudo | 15 | | 13 | rizla suzuki motogp | suzuki | suzuki gsv-r | b | 21 | john hopkins | all | | 14 | rizla suzuki motogp | suzuki | suzuki gsv-r | b | 71 | chris vermeulen | all | | 15 | rizla suzuki motogp | suzuki | suzuki gsv-r | b | 64 | kousuke akiyoshi | 15 | | 16 | repsol honda team | honda | honda rc211v | m | 26 | dani pedrosa | all | | 17 | repsol honda team | honda | honda rc211v | m | 69 | nicky hayden | all | | 18 | honda lcr | honda | honda rc211v | m | 27 | casey stoner | all | | 19 | pramac d'antin motogp | ducati | ducati desmosedici gp5 | d | 30 | jose luis cardoso | all | | 20 | pramac d'antin motogp | ducati | ducati desmosedici gp5 | d | 66 | alex hofmann | 1-7, 10-11, 13-17 | | 21 | pramac d'antin motogp | ducati | ducati desmosedici gp5 | d | 22 | ivan silva | 8-9, 12 | | 22 | fortuna honda | honda | honda rc211v | m | 24 | toni elias | 1-8, 10-17 | | 23 | fortuna honda | honda | honda rc211v | m | 33 | marco melandri | all | | 24 | fortuna honda | honda | honda rc211v | m | 84 | michel fabrizio | 9 | | 25 | ilmor srt | ilmor | ilmor x3 | m | 8 | garry mccoy | 16-17 |

| | count ( "rider" ) | |---:|--------------------:| | 0 | 11 |

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col : count ( "*" ) row 1 : 1

select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' <table_name> : table \begin{tabular}{llllllll} \toprule & date & time & opponent & site & tv & result & attendance \\ \midrule 0 & september 5 & 2:30 p.m & jackson state & davis wade stadium • starkville, ms & espnu & w 45-7 & 54232 \\ 1 & september 12 & 6:00 p.m & at auburn & jordan-hare stadium • auburn, al & secrn & l 24-49 & 85269 \\ 2 & september 19 & 6:00 p.m & at vanderbilt & vanderbilt stadium • nashville, tn & secrn & w 15-3 & 31840 \\ 3 & september 26 & 11:21 a.m & #7 lsu & davis wade stadium • starkville, ms & secn & l 26-30 & 53612 \\ 4 & october 3 & 6:30 p.m & #25 georgia tech & davis wade stadium • starkville, ms & css & l 31-42 & 50035 \\ 5 & october 10 & 11:30 a.m & houston & davis wade stadium • starkville, ms & espnu & l 24-31 & 48019 \\ 6 & october 17 & 11:30 a.m & at middle tennessee & johnny "red" floyd stadium • murfreesboro, tn & espnu & w 27-6 & 23882 \\ 7 & october 24 & 6:30 p.m & #1 florida & davis wade stadium • starkville, ms & espn & l 19-29 & 57178 \\ 8 & october 31 & 6:00 p.m & at kentucky & commonwealth stadium • lexington, ky & secrn & w 31-24 & 67953 \\ 9 & november 14 & 6:00 p.m & #2 alabama & davis wade stadium • starkville, ms (rivalry) & espn & l 3-31 & 58103 \\ 10 & november 21 & 11:21 a.m & at arkansas & war memorial stadium • little rock, ar & secn & l 21-42 & 55634 \\ 11 & november 28 & 11:21 a.m & #25 ole miss & davis wade stadium • starkville, ms (egg bowl) & secn & w 41-27 & 55365 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>date</th> <th>time</th> <th>opponent</th> <th>site</th> <th>tv</th> <th>result</th> <th>attendance</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>september 5</td> <td>2:30 p.m</td> <td>jackson state</td> <td>davis wade stadium • starkville, ms</td> <td>espnu</td> <td>w 45-7</td> <td>54232</td> </tr> <tr> <th>1</th> <td>september 12</td> <td>6:00 p.m</td> <td>at auburn</td> <td>jordan-hare stadium • auburn, al</td> <td>secrn</td> <td>l 24-49</td> <td>85269</td> </tr> <tr> <th>2</th> <td>september 19</td> <td>6:00 p.m</td> <td>at vanderbilt</td> <td>vanderbilt stadium • nashville, tn</td> <td>secrn</td> <td>w 15-3</td> <td>31840</td> </tr> <tr> <th>3</th> <td>september 26</td> <td>11:21 a.m</td> <td>#7 lsu</td> <td>davis wade stadium • starkville, ms</td> <td>secn</td> <td>l 26-30</td> <td>53612</td> </tr> <tr> <th>4</th> <td>october 3</td> <td>6:30 p.m</td> <td>#25 georgia tech</td> <td>davis wade stadium • starkville, ms</td> <td>css</td> <td>l 31-42</td> <td>50035</td> </tr> <tr> <th>5</th> <td>october 10</td> <td>11:30 a.m</td> <td>houston</td> <td>davis wade stadium • starkville, ms</td> <td>espnu</td> <td>l 24-31</td> <td>48019</td> </tr> <tr> <th>6</th> <td>october 17</td> <td>11:30 a.m</td> <td>at middle tennessee</td> <td>johnny "red" floyd stadium • murfreesboro, tn</td> <td>espnu</td> <td>w 27-6</td> <td>23882</td> </tr> <tr> <th>7</th> <td>october 24</td> <td>6:30 p.m</td> <td>#1 florida</td> <td>davis wade stadium • starkville, ms</td> <td>espn</td> <td>l 19-29</td> <td>57178</td> </tr> <tr> <th>8</th> <td>october 31</td> <td>6:00 p.m</td> <td>at kentucky</td> <td>commonwealth stadium • lexington, ky</td> <td>secrn</td> <td>w 31-24</td> <td>67953</td> </tr> <tr> <th>9</th> <td>november 14</td> <td>6:00 p.m</td> <td>#2 alabama</td> <td>davis wade stadium • starkville, ms (rivalry)</td> <td>espn</td> <td>l 3-31</td> <td>58103</td> </tr> <tr> <th>10</th> <td>november 21</td> <td>11:21 a.m</td> <td>at arkansas</td> <td>war memorial stadium • little rock, ar</td> <td>secn</td> <td>l 21-42</td> <td>55634</td> </tr> <tr> <th>11</th> <td>november 28</td> <td>11:21 a.m</td> <td>#25 ole miss</td> <td>davis wade stadium • starkville, ms (egg bowl)</td> <td>secn</td> <td>w 41-27</td> <td>55365</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where site = 'davis wade stadium • starkville, ms (rivalry)' <table_name> : table | | date | time | opponent | site | tv | result | attendance | |---:|:-------------|:----------|:--------------------|:-----------------------------------------------|:------|:---------|-------------:| | 0 | september 5 | 2:30 p.m | jackson state | davis wade stadium • starkville, ms | espnu | w 45-7 | 54232 | | 1 | september 12 | 6:00 p.m | at auburn | jordan-hare stadium • auburn, al | secrn | l 24-49 | 85269 | | 2 | september 19 | 6:00 p.m | at vanderbilt | vanderbilt stadium • nashville, tn | secrn | w 15-3 | 31840 | | 3 | september 26 | 11:21 a.m | #7 lsu | davis wade stadium • starkville, ms | secn | l 26-30 | 53612 | | 4 | october 3 | 6:30 p.m | #25 georgia tech | davis wade stadium • starkville, ms | css | l 31-42 | 50035 | | 5 | october 10 | 11:30 a.m | houston | davis wade stadium • starkville, ms | espnu | l 24-31 | 48019 | | 6 | october 17 | 11:30 a.m | at middle tennessee | johnny "red" floyd stadium • murfreesboro, tn | espnu | w 27-6 | 23882 | | 7 | october 24 | 6:30 p.m | #1 florida | davis wade stadium • starkville, ms | espn | l 19-29 | 57178 | | 8 | october 31 | 6:00 p.m | at kentucky | commonwealth stadium • lexington, ky | secrn | w 31-24 | 67953 | | 9 | november 14 | 6:00 p.m | #2 alabama | davis wade stadium • starkville, ms (rivalry) | espn | l 3-31 | 58103 | | 10 | november 21 | 11:21 a.m | at arkansas | war memorial stadium • little rock, ar | secn | l 21-42 | 55634 | | 11 | november 28 | 11:21 a.m | #25 ole miss | davis wade stadium • starkville, ms (egg bowl) | secn | w 41-27 | 55365 |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : count ( "parking" ) row 1 : 9

select count ( parking ) where parking = 'none' <table_name> : table \begin{tabular}{llllll} \toprule & stations & connections & city/ neighborhood & parking & date opened \\ \midrule 0 & north hollywood & metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757 & north hollywood & 951 spaces & october 29, 2005 \\ 1 & laurel canyon & metro local: 156, 230, 656 & valley village & none & october 29, 2005 \\ 2 & valley college & metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city & valley glen & none & october 29, 2005 \\ 3 & woodman & metro local:154, 158 & valley glen & none & october 29, 2005 \\ 4 & van nuys & metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798 & van nuys & 776 spaces & october 29, 2005 \\ 5 & sepulveda & metro local: 234 metro rapid: 734 & van nuys & 1,205 spaces & october 29, 2005 \\ 6 & woodley & metro local:164, 237 & van nuys & none & october 29, 2005 \\ 7 & balboa & metro local: 164, 236, 237 ladot commuter express: 573, 574 & lake balboa & 270 spaces & october 29, 2005 \\ 8 & reseda & metro rapid: 741 metro local: 240 & tarzana & 522 spaces & october 29, 2005 \\ 9 & tampa & metro local: 242 & tarzana & none & october 29, 2005 \\ 10 & pierce college & metro local: 164, 243 & winnetka & 373 spaces & october 29, 2005 \\ 11 & de soto & metro local: 164, 244 city of santa clarita transit: 796 & winnetka & none & october 29, 2005 \\ 12 & canoga & metro local:164, 165 city of santa clarita transit: 796 & canoga park & 612 spaces & december 27, 2006 \\ 13 & warner center & metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection & woodland hills & none & october 29, 2005 \\ 14 & sherman way & metro local: 162, 163 & canoga park & park & ride lot & june 30, 2012 \\ 15 & roscoe & metro local: 152, 353 & canoga park & none & june 30, 2012 \\ 16 & nordhoff & metro local: 166, 364 ladot dash northridge & chatsworth & none & june 30, 2012 \\ 17 & chatsworth & metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner & chatsworth & parking expanded & june 30, 2012 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "parking" ) \\ \midrule 0 & 9 \\ \bottomrule \end{tabular}

select count ( parking ) where parking = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>stations</th> <th>connections</th> <th>city/ neighborhood</th> <th>parking</th> <th>date opened</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>north hollywood</td> <td>metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757</td> <td>north hollywood</td> <td>951 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>1</th> <td>laurel canyon</td> <td>metro local: 156, 230, 656</td> <td>valley village</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>2</th> <td>valley college</td> <td>metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city</td> <td>valley glen</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>3</th> <td>woodman</td> <td>metro local:154, 158</td> <td>valley glen</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>4</th> <td>van nuys</td> <td>metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798</td> <td>van nuys</td> <td>776 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>5</th> <td>sepulveda</td> <td>metro local: 234 metro rapid: 734</td> <td>van nuys</td> <td>1,205 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>6</th> <td>woodley</td> <td>metro local:164, 237</td> <td>van nuys</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>7</th> <td>balboa</td> <td>metro local: 164, 236, 237 ladot commuter express: 573, 574</td> <td>lake balboa</td> <td>270 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>8</th> <td>reseda</td> <td>metro rapid: 741 metro local: 240</td> <td>tarzana</td> <td>522 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>9</th> <td>tampa</td> <td>metro local: 242</td> <td>tarzana</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>10</th> <td>pierce college</td> <td>metro local: 164, 243</td> <td>winnetka</td> <td>373 spaces</td> <td>october 29, 2005</td> </tr> <tr> <th>11</th> <td>de soto</td> <td>metro local: 164, 244 city of santa clarita transit: 796</td> <td>winnetka</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>12</th> <td>canoga</td> <td>metro local:164, 165 city of santa clarita transit: 796</td> <td>canoga park</td> <td>612 spaces</td> <td>december 27, 2006</td> </tr> <tr> <th>13</th> <td>warner center</td> <td>metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection</td> <td>woodland hills</td> <td>none</td> <td>october 29, 2005</td> </tr> <tr> <th>14</th> <td>sherman way</td> <td>metro local: 162, 163</td> <td>canoga park</td> <td>park & ride lot</td> <td>june 30, 2012</td> </tr> <tr> <th>15</th> <td>roscoe</td> <td>metro local: 152, 353</td> <td>canoga park</td> <td>none</td> <td>june 30, 2012</td> </tr> <tr> <th>16</th> <td>nordhoff</td> <td>metro local: 166, 364 ladot dash northridge</td> <td>chatsworth</td> <td>none</td> <td>june 30, 2012</td> </tr> <tr> <th>17</th> <td>chatsworth</td> <td>metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner</td> <td>chatsworth</td> <td>parking expanded</td> <td>june 30, 2012</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "parking" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>9</td> </tr> </tbody> </table>

select count ( parking ) where parking = 'none' <table_name> : table | | stations | connections | city/ neighborhood | parking | date opened | |---:|:----------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------|:-----------------|:------------------| | 0 | north hollywood | metro red line metro local: 152, 154, 156, 162, 183, 224, 353, 656 ladot commuter express: 549 city of santa clarita transit: 757 | north hollywood | 951 spaces | october 29, 2005 | | 1 | laurel canyon | metro local: 156, 230, 656 | valley village | none | october 29, 2005 | | 2 | valley college | metro local: 156, 167, 656 ladot commuter express: 549 ladot dash: van nuys/studio city | valley glen | none | october 29, 2005 | | 3 | woodman | metro local:154, 158 | valley glen | none | october 29, 2005 | | 4 | van nuys | metro local:154, 156, 233, 237, 656 metro rapid: 761 ladot dash: van nuys/studio city city of santa clarita transit: 793, 798 | van nuys | 776 spaces | october 29, 2005 | | 5 | sepulveda | metro local: 234 metro rapid: 734 | van nuys | 1,205 spaces | october 29, 2005 | | 6 | woodley | metro local:164, 237 | van nuys | none | october 29, 2005 | | 7 | balboa | metro local: 164, 236, 237 ladot commuter express: 573, 574 | lake balboa | 270 spaces | october 29, 2005 | | 8 | reseda | metro rapid: 741 metro local: 240 | tarzana | 522 spaces | october 29, 2005 | | 9 | tampa | metro local: 242 | tarzana | none | october 29, 2005 | | 10 | pierce college | metro local: 164, 243 | winnetka | 373 spaces | october 29, 2005 | | 11 | de soto | metro local: 164, 244 city of santa clarita transit: 796 | winnetka | none | october 29, 2005 | | 12 | canoga | metro local:164, 165 city of santa clarita transit: 796 | canoga park | 612 spaces | december 27, 2006 | | 13 | warner center | metro local: 150, 161, 164, 245, 645 metro rapid: 750 ladot commuter express: 422 city of santa clarita transit: 791, 796 ventura intercity service transit authority: conejo connection | woodland hills | none | october 29, 2005 | | 14 | sherman way | metro local: 162, 163 | canoga park | park & ride lot | june 30, 2012 | | 15 | roscoe | metro local: 152, 353 | canoga park | none | june 30, 2012 | | 16 | nordhoff | metro local: 166, 364 ladot dash northridge | chatsworth | none | june 30, 2012 | | 17 | chatsworth | metro local: 158, 166, 167, 244, 245, 364 ladot commuter express: 419 simi valley transit: c santa clarita transit: 791 metrolink ventura county line amtrak pacific surfliner | chatsworth | parking expanded | june 30, 2012 |

| | count ( "parking" ) | |---:|----------------------:| | 0 | 9 |

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select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' <table_name> : table \begin{tabular}{lllll} \toprule & award & category & recipients and nominees & result \\ \midrule 0 & 71st academy awards & best original screenplay & warren beatty and jeremy pikser & nominated \\ 1 & 56th golden globe awards & best screenplay & warren beatty and jeremy pikser & nominated \\ 2 & 56th golden globe awards & best picture & bulworth & nominated \\ 3 & 56th golden globe awards & best actor & warren beatty & nominated \\ 4 & 1998 satellite awards & best actor & warren beatty & nominated \\ 5 & 1998 writers guild of america awards & best screenplay & warren beatty and jeremy pikser & nominated \\ 6 & chicago film critics association awards 1998 & best screenplay & warren beatty and jeremy pikser & nominated \\ 7 & los angeles film critics association & best screenplay (1998) & warren beatty and jeremy pikser & won \\ 8 & 1998 golden lion awards & best film & bulworth & nominated \\ 9 & 1999 naacp image awards & outstanding actress & halle berry & nominated \\ 10 & 1999 naacp image awards & outstanding supporting actor & don cheadle & nominated \\ 11 & american film institute & 100 years...100 laughs & bulworth & nominated \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 5 \\ \bottomrule \end{tabular}

select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>award</th> <th>category</th> <th>recipients and nominees</th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>71st academy awards</td> <td>best original screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>1</th> <td>56th golden globe awards</td> <td>best screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>2</th> <td>56th golden globe awards</td> <td>best picture</td> <td>bulworth</td> <td>nominated</td> </tr> <tr> <th>3</th> <td>56th golden globe awards</td> <td>best actor</td> <td>warren beatty</td> <td>nominated</td> </tr> <tr> <th>4</th> <td>1998 satellite awards</td> <td>best actor</td> <td>warren beatty</td> <td>nominated</td> </tr> <tr> <th>5</th> <td>1998 writers guild of america awards</td> <td>best screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>6</th> <td>chicago film critics association awards 1998</td> <td>best screenplay</td> <td>warren beatty and jeremy pikser</td> <td>nominated</td> </tr> <tr> <th>7</th> <td>los angeles film critics association</td> <td>best screenplay (1998)</td> <td>warren beatty and jeremy pikser</td> <td>won</td> </tr> <tr> <th>8</th> <td>1998 golden lion awards</td> <td>best film</td> <td>bulworth</td> <td>nominated</td> </tr> <tr> <th>9</th> <td>1999 naacp image awards</td> <td>outstanding actress</td> <td>halle berry</td> <td>nominated</td> </tr> <tr> <th>10</th> <td>1999 naacp image awards</td> <td>outstanding supporting actor</td> <td>don cheadle</td> <td>nominated</td> </tr> <tr> <th>11</th> <td>american film institute</td> <td>100 years...100 laughs</td> <td>bulworth</td> <td>nominated</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>5</td> </tr> </tbody> </table>

select count ( * ) where recipients and nominees = 'warren beatty and jeremy pikser' <table_name> : table | | award | category | recipients and nominees | result | |---:|:---------------------------------------------|:-----------------------------|:--------------------------------|:----------| | 0 | 71st academy awards | best original screenplay | warren beatty and jeremy pikser | nominated | | 1 | 56th golden globe awards | best screenplay | warren beatty and jeremy pikser | nominated | | 2 | 56th golden globe awards | best picture | bulworth | nominated | | 3 | 56th golden globe awards | best actor | warren beatty | nominated | | 4 | 1998 satellite awards | best actor | warren beatty | nominated | | 5 | 1998 writers guild of america awards | best screenplay | warren beatty and jeremy pikser | nominated | | 6 | chicago film critics association awards 1998 | best screenplay | warren beatty and jeremy pikser | nominated | | 7 | los angeles film critics association | best screenplay (1998) | warren beatty and jeremy pikser | won | | 8 | 1998 golden lion awards | best film | bulworth | nominated | | 9 | 1999 naacp image awards | outstanding actress | halle berry | nominated | | 10 | 1999 naacp image awards | outstanding supporting actor | don cheadle | nominated | | 11 | american film institute | 100 years...100 laughs | bulworth | nominated |

| | count ( "*" ) | |---:|----------------:| | 0 | 5 |

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select count ( * ) where office ended = 1939 col : # | name | birth and death | office started | office ended row 1 : 1 | geir vidalin | 27 october 1761 - 20 september 1823 | 1801 | 1823 row 2 : 2 | steingrimur jonsson | none | 1824 | 1845 row 3 : 3 | helgi thordersen | 8 april 1794 - 4 december 1867 | 1846 | 1866 row 4 : 4 | 'petur petursson | 3 october 1808 - 15 may 1891 | 1866 | 1889 row 5 : 5 | hallgrimur sveinsson | 5 april 1841 - 16 december 1909 | 1889 | 1908 row 6 : 6 | þorhallur bjarnarson | 2 december 1855 - 15 december 1916 | 1908 | 1916 row 7 : 7 | jon helgason | 1866 - 1942 | 1917 | 1939 row 8 : 8 | sigurgeir sigurðsson | 3 august 1890 - 13 october 1953 | 1939 | 1953 row 9 : 9 | asmundur guðmundsson | 6 october 1888 reykholt - 29 may 1969 reykjavik | 1954 | 1989 row 10 : 10 | sigurbjorn einarsson | 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik | 1959 | 1981 row 11 : 11 | petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) | 2 june 1919 - 3 june 2010 | 1981 | 1989 row 12 : 12 | olafur skulason | 29 december 1929 - 9 june 2008 | 1989 | 1997 row 13 : 13 | karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) | 5 february 1947 reykjavik | 1998 | 2012 row 14 : 14 | agnes sigurðardottir | 19 october 1954 isafjorður | 24 june 2012 | incumbent

col : count ( "*" ) row 1 : 1

select count ( * ) where office ended = 1939 <table_name> : table \begin{tabular}{llllll} \toprule & # & name & birth and death & office started & office ended \\ \midrule 0 & 1 & geir vidalin & 27 october 1761 - 20 september 1823 & 1801 & 1823 \\ 1 & 2 & steingrimur jonsson & none & 1824 & 1845 \\ 2 & 3 & helgi thordersen & 8 april 1794 - 4 december 1867 & 1846 & 1866 \\ 3 & 4 & 'petur petursson & 3 october 1808 - 15 may 1891 & 1866 & 1889 \\ 4 & 5 & hallgrimur sveinsson & 5 april 1841 - 16 december 1909 & 1889 & 1908 \\ 5 & 6 & þorhallur bjarnarson & 2 december 1855 - 15 december 1916 & 1908 & 1916 \\ 6 & 7 & jon helgason & 1866 - 1942 & 1917 & 1939 \\ 7 & 8 & sigurgeir sigurðsson & 3 august 1890 - 13 october 1953 & 1939 & 1953 \\ 8 & 9 & asmundur guðmundsson & 6 october 1888 reykholt - 29 may 1969 reykjavik & 1954 & 1989 \\ 9 & 10 & sigurbjorn einarsson & 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik & 1959 & 1981 \\ 10 & 11 & petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) & 2 june 1919 - 3 june 2010 & 1981 & 1989 \\ 11 & 12 & olafur skulason & 29 december 1929 - 9 june 2008 & 1989 & 1997 \\ 12 & 13 & karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) & 5 february 1947 reykjavik & 1998 & 2012 \\ 13 & 14 & agnes sigurðardottir & 19 october 1954 isafjorður & 24 june 2012 & incumbent \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where office ended = 1939 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>name</th> <th>birth and death</th> <th>office started</th> <th>office ended</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>geir vidalin</td> <td>27 october 1761 - 20 september 1823</td> <td>1801</td> <td>1823</td> </tr> <tr> <th>1</th> <td>2</td> <td>steingrimur jonsson</td> <td>none</td> <td>1824</td> <td>1845</td> </tr> <tr> <th>2</th> <td>3</td> <td>helgi thordersen</td> <td>8 april 1794 - 4 december 1867</td> <td>1846</td> <td>1866</td> </tr> <tr> <th>3</th> <td>4</td> <td>'petur petursson</td> <td>3 october 1808 - 15 may 1891</td> <td>1866</td> <td>1889</td> </tr> <tr> <th>4</th> <td>5</td> <td>hallgrimur sveinsson</td> <td>5 april 1841 - 16 december 1909</td> <td>1889</td> <td>1908</td> </tr> <tr> <th>5</th> <td>6</td> <td>þorhallur bjarnarson</td> <td>2 december 1855 - 15 december 1916</td> <td>1908</td> <td>1916</td> </tr> <tr> <th>6</th> <td>7</td> <td>jon helgason</td> <td>1866 - 1942</td> <td>1917</td> <td>1939</td> </tr> <tr> <th>7</th> <td>8</td> <td>sigurgeir sigurðsson</td> <td>3 august 1890 - 13 october 1953</td> <td>1939</td> <td>1953</td> </tr> <tr> <th>8</th> <td>9</td> <td>asmundur guðmundsson</td> <td>6 october 1888 reykholt - 29 may 1969 reykjavik</td> <td>1954</td> <td>1989</td> </tr> <tr> <th>9</th> <td>10</td> <td>sigurbjorn einarsson</td> <td>30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik</td> <td>1959</td> <td>1981</td> </tr> <tr> <th>10</th> <td>11</td> <td>petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland)</td> <td>2 june 1919 - 3 june 2010</td> <td>1981</td> <td>1989</td> </tr> <tr> <th>11</th> <td>12</td> <td>olafur skulason</td> <td>29 december 1929 - 9 june 2008</td> <td>1989</td> <td>1997</td> </tr> <tr> <th>12</th> <td>13</td> <td>karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland)</td> <td>5 february 1947 reykjavik</td> <td>1998</td> <td>2012</td> </tr> <tr> <th>13</th> <td>14</td> <td>agnes sigurðardottir</td> <td>19 october 1954 isafjorður</td> <td>24 june 2012</td> <td>incumbent</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where office ended = 1939 <table_name> : table | | # | name | birth and death | office started | office ended | |---:|----:|:--------------------------------------------------------------------------|:----------------------------------------------------------------|:-----------------|:---------------| | 0 | 1 | geir vidalin | 27 october 1761 - 20 september 1823 | 1801 | 1823 | | 1 | 2 | steingrimur jonsson | none | 1824 | 1845 | | 2 | 3 | helgi thordersen | 8 april 1794 - 4 december 1867 | 1846 | 1866 | | 3 | 4 | 'petur petursson | 3 october 1808 - 15 may 1891 | 1866 | 1889 | | 4 | 5 | hallgrimur sveinsson | 5 april 1841 - 16 december 1909 | 1889 | 1908 | | 5 | 6 | þorhallur bjarnarson | 2 december 1855 - 15 december 1916 | 1908 | 1916 | | 6 | 7 | jon helgason | 1866 - 1942 | 1917 | 1939 | | 7 | 8 | sigurgeir sigurðsson | 3 august 1890 - 13 october 1953 | 1939 | 1953 | | 8 | 9 | asmundur guðmundsson | 6 october 1888 reykholt - 29 may 1969 reykjavik | 1954 | 1989 | | 9 | 10 | sigurbjorn einarsson | 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik | 1959 | 1981 | | 10 | 11 | petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) | 2 june 1919 - 3 june 2010 | 1981 | 1989 | | 11 | 12 | olafur skulason | 29 december 1929 - 9 june 2008 | 1989 | 1997 | | 12 | 13 | karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) | 5 february 1947 reykjavik | 1998 | 2012 | | 13 | 14 | agnes sigurðardottir | 19 october 1954 isafjorður | 24 june 2012 | incumbent |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : count ( "event" ) row 1 : 12

select count ( event ) where year > 15 <table_name> : table \begin{tabular}{llllll} \toprule & year & competition & venue & position & event \\ \midrule 0 & 1997 & world indoor championships & paris, france & 5th & 60 m hurdles \\ 1 & 1997 & usa outdoor championships & indianapolis, united states & 1st & 100 m hurdles \\ 2 & 1998 & grand prix final & moscow, russia & 2nd & 100 m hurdles \\ 3 & 1998 & usa indoor championships & none & 1st & 60 m hurdles \\ 4 & 1999 & world indoor championships & maebashi, japan & 6th & 60 m hurdles \\ 5 & 2000 & olympic games & sydney, australia & 3rd & 100 m hurdles \\ 6 & 2000 & grand prix final & doha, qatar & 4th & 100 m hurdles \\ 7 & 2002 & grand prix final & paris, france & 7th & 100 m hurdles \\ 8 & 2002 & usa indoor championships & none & 1st & 60 m hurdles \\ 9 & 2003 & world indoor championships & birmingham, england & 3rd & 60 m hurdles \\ 10 & 2003 & world athletics final & monaco & 6th & 100 m hurdles \\ 11 & 2004 & olympic games & athens, greece & 3rd & 100 m hurdles \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "event" ) \\ \midrule 0 & 12 \\ \bottomrule \end{tabular}

select count ( event ) where year > 15 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1997</td> <td>world indoor championships</td> <td>paris, france</td> <td>5th</td> <td>60 m hurdles</td> </tr> <tr> <th>1</th> <td>1997</td> <td>usa outdoor championships</td> <td>indianapolis, united states</td> <td>1st</td> <td>100 m hurdles</td> </tr> <tr> <th>2</th> <td>1998</td> <td>grand prix final</td> <td>moscow, russia</td> <td>2nd</td> <td>100 m hurdles</td> </tr> <tr> <th>3</th> <td>1998</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>4</th> <td>1999</td> <td>world indoor championships</td> <td>maebashi, japan</td> <td>6th</td> <td>60 m hurdles</td> </tr> <tr> <th>5</th> <td>2000</td> <td>olympic games</td> <td>sydney, australia</td> <td>3rd</td> <td>100 m hurdles</td> </tr> <tr> <th>6</th> <td>2000</td> <td>grand prix final</td> <td>doha, qatar</td> <td>4th</td> <td>100 m hurdles</td> </tr> <tr> <th>7</th> <td>2002</td> <td>grand prix final</td> <td>paris, france</td> <td>7th</td> <td>100 m hurdles</td> </tr> <tr> <th>8</th> <td>2002</td> <td>usa indoor championships</td> <td>none</td> <td>1st</td> <td>60 m hurdles</td> </tr> <tr> <th>9</th> <td>2003</td> <td>world indoor championships</td> <td>birmingham, england</td> <td>3rd</td> <td>60 m hurdles</td> </tr> <tr> <th>10</th> <td>2003</td> <td>world athletics final</td> <td>monaco</td> <td>6th</td> <td>100 m hurdles</td> </tr> <tr> <th>11</th> <td>2004</td> <td>olympic games</td> <td>athens, greece</td> <td>3rd</td> <td>100 m hurdles</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "event" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>12</td> </tr> </tbody> </table>

select count ( event ) where year > 15 <table_name> : table | | year | competition | venue | position | event | |---:|-------:|:---------------------------|:----------------------------|:-----------|:--------------| | 0 | 1997 | world indoor championships | paris, france | 5th | 60 m hurdles | | 1 | 1997 | usa outdoor championships | indianapolis, united states | 1st | 100 m hurdles | | 2 | 1998 | grand prix final | moscow, russia | 2nd | 100 m hurdles | | 3 | 1998 | usa indoor championships | none | 1st | 60 m hurdles | | 4 | 1999 | world indoor championships | maebashi, japan | 6th | 60 m hurdles | | 5 | 2000 | olympic games | sydney, australia | 3rd | 100 m hurdles | | 6 | 2000 | grand prix final | doha, qatar | 4th | 100 m hurdles | | 7 | 2002 | grand prix final | paris, france | 7th | 100 m hurdles | | 8 | 2002 | usa indoor championships | none | 1st | 60 m hurdles | | 9 | 2003 | world indoor championships | birmingham, england | 3rd | 60 m hurdles | | 10 | 2003 | world athletics final | monaco | 6th | 100 m hurdles | | 11 | 2004 | olympic games | athens, greece | 3rd | 100 m hurdles |

| | count ( "event" ) | |---:|--------------------:| | 0 | 12 |

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col : count ( "*" ) row 1 : 2

select count ( * ) where established = '16 january 1978' <table_name> : table \begin{tabular}{llllllll} \toprule & ecclesiastical jurisdictions & latin name & type & rite & ecclesiastical province & established & area (km2) \\ \midrule 0 & bani & baniensis & diocese & roman & santo domingo & 8 november 1986 & 2892 \\ 1 & barahona & barahonensis & diocese & roman & santo domingo & 24 april 1976 & 6973 \\ 2 & dominican republic & reipublicae dominicanae & military ordinariate & roman & immediately subject to the holy see & 23 january 1958 & none \\ 3 & la vega & vegensis & diocese & roman & santiago de los caballeros & 25 september 1953 & 4919 \\ 4 & mao-monte cristi & maoensis-montis christi & diocese & roman & santiago de los caballeros & 16 january 1978 & 4841 \\ 5 & nuestra senora de la altagracia en higuey & higueyensis / a domina nostra vulgo de la altagracia in higuey & diocese & roman & santo domingo & 1 april 1959 & 5437 \\ 6 & puerto plata & portus argentarii & diocese & roman & santiago de los caballeros & 16 december 1996 & 2700 \\ 7 & san francisco de macoris & sancti francisci de macoris & diocese & roman & santiago de los caballeros & 16 january 1978 & 3682 \\ 8 & san juan de la maguana & sancti ioannis maguanensis & diocese & roman & santo domingo & 25 september 1953 & 7476 \\ 9 & san pedro de macoris & sancti petri de macoris & diocese & roman & santo domingo & 1 february 1997 & 2588 \\ 10 & santiago de los caballeros & sancti iacobi equitum & metropolitan archdiocese & roman & santiago de los caballeros & 25 september 1953 & 6391 \\ 11 & santo domingo & sancti dominici & metropolitan archdiocese & roman & santo domingo & 8 august 1511 & 4033 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 2 \\ \bottomrule \end{tabular}

select count ( * ) where established = '16 january 1978' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>ecclesiastical jurisdictions</th> <th>latin name</th> <th>type</th> <th>rite</th> <th>ecclesiastical province</th> <th>established</th> <th>area (km2)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>bani</td> <td>baniensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>8 november 1986</td> <td>2892</td> </tr> <tr> <th>1</th> <td>barahona</td> <td>barahonensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>24 april 1976</td> <td>6973</td> </tr> <tr> <th>2</th> <td>dominican republic</td> <td>reipublicae dominicanae</td> <td>military ordinariate</td> <td>roman</td> <td>immediately subject to the holy see</td> <td>23 january 1958</td> <td>none</td> </tr> <tr> <th>3</th> <td>la vega</td> <td>vegensis</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>4919</td> </tr> <tr> <th>4</th> <td>mao-monte cristi</td> <td>maoensis-montis christi</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>4841</td> </tr> <tr> <th>5</th> <td>nuestra senora de la altagracia en higuey</td> <td>higueyensis / a domina nostra vulgo de la altagracia in higuey</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 april 1959</td> <td>5437</td> </tr> <tr> <th>6</th> <td>puerto plata</td> <td>portus argentarii</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 december 1996</td> <td>2700</td> </tr> <tr> <th>7</th> <td>san francisco de macoris</td> <td>sancti francisci de macoris</td> <td>diocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>16 january 1978</td> <td>3682</td> </tr> <tr> <th>8</th> <td>san juan de la maguana</td> <td>sancti ioannis maguanensis</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>25 september 1953</td> <td>7476</td> </tr> <tr> <th>9</th> <td>san pedro de macoris</td> <td>sancti petri de macoris</td> <td>diocese</td> <td>roman</td> <td>santo domingo</td> <td>1 february 1997</td> <td>2588</td> </tr> <tr> <th>10</th> <td>santiago de los caballeros</td> <td>sancti iacobi equitum</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santiago de los caballeros</td> <td>25 september 1953</td> <td>6391</td> </tr> <tr> <th>11</th> <td>santo domingo</td> <td>sancti dominici</td> <td>metropolitan archdiocese</td> <td>roman</td> <td>santo domingo</td> <td>8 august 1511</td> <td>4033</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> </tbody> </table>

select count ( * ) where established = '16 january 1978' <table_name> : table | | ecclesiastical jurisdictions | latin name | type | rite | ecclesiastical province | established | area (km2) | |---:|:------------------------------------------|:---------------------------------------------------------------|:-------------------------|:-------|:------------------------------------|:------------------|:-------------| | 0 | bani | baniensis | diocese | roman | santo domingo | 8 november 1986 | 2892 | | 1 | barahona | barahonensis | diocese | roman | santo domingo | 24 april 1976 | 6973 | | 2 | dominican republic | reipublicae dominicanae | military ordinariate | roman | immediately subject to the holy see | 23 january 1958 | none | | 3 | la vega | vegensis | diocese | roman | santiago de los caballeros | 25 september 1953 | 4919 | | 4 | mao-monte cristi | maoensis-montis christi | diocese | roman | santiago de los caballeros | 16 january 1978 | 4841 | | 5 | nuestra senora de la altagracia en higuey | higueyensis / a domina nostra vulgo de la altagracia in higuey | diocese | roman | santo domingo | 1 april 1959 | 5437 | | 6 | puerto plata | portus argentarii | diocese | roman | santiago de los caballeros | 16 december 1996 | 2700 | | 7 | san francisco de macoris | sancti francisci de macoris | diocese | roman | santiago de los caballeros | 16 january 1978 | 3682 | | 8 | san juan de la maguana | sancti ioannis maguanensis | diocese | roman | santo domingo | 25 september 1953 | 7476 | | 9 | san pedro de macoris | sancti petri de macoris | diocese | roman | santo domingo | 1 february 1997 | 2588 | | 10 | santiago de los caballeros | sancti iacobi equitum | metropolitan archdiocese | roman | santiago de los caballeros | 25 september 1953 | 6391 | | 11 | santo domingo | sancti dominici | metropolitan archdiocese | roman | santo domingo | 8 august 1511 | 4033 |

| | count ( "*" ) | |---:|----------------:| | 0 | 2 |

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col : count ( "*" ) row 1 : 1

select count ( * ) where position = '3rd' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 1979 & grandma's marathon & duluth, united states & 1st & marathon & 2:37:37 \\ 1 & 1980 & grandma's marathon & duluth, united states & 1st & marathon & 2:38:35 \\ 2 & 1981 & grandma's marathon & duluth, united states & 1st & marathon & 2:29:35 \\ 3 & 1984 & boston marathon & boston, united states & 1st & marathon & 2:29:28 \\ 4 & 1984 & olympic games & los angeles, united states & 5th & marathon & 2:28:54 \\ 5 & 1986 & osaka ladies marathon & osaka, japan & 1st & marathon & 2:30:24 \\ 6 & 1986 & commonwealth games & edinburgh, scotland & 2nd & marathon & 2:28:17 \\ 7 & 1987 & osaka ladies marathon & osaka, japan & 1st & marathon & 2:30:40 \\ 8 & 1987 & world championships & rome, italy & 21st & 10,000 m & 34:07.26 \\ 9 & 1988 & olympic games & seoul, south korea & 33rd & marathon & 2:37:52 \\ 10 & 1989 & osaka ladies marathon & osaka, japan & 1st & marathon & 2:30:21 \\ 11 & 1989 & hokkaido marathon & sapporo, japan & 1st & marathon & 2:36:39 \\ 12 & 1991 & hokkaido marathon & sapporo, japan & 1st & marathon & 2:33:20 \\ 13 & 1992 & olympic games & barcelona, spain & 3rd & marathon & 2:33:59 \\ 14 & 1996 & olympic games & atlanta, united states & 46th & marathon & 2:42:21 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where position = '3rd' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1979</td> <td>grandma's marathon</td> <td>duluth, united states</td> <td>1st</td> <td>marathon</td> <td>2:37:37</td> </tr> <tr> <th>1</th> <td>1980</td> <td>grandma's marathon</td> <td>duluth, united states</td> <td>1st</td> <td>marathon</td> <td>2:38:35</td> </tr> <tr> <th>2</th> <td>1981</td> <td>grandma's marathon</td> <td>duluth, united states</td> <td>1st</td> <td>marathon</td> <td>2:29:35</td> </tr> <tr> <th>3</th> <td>1984</td> <td>boston marathon</td> <td>boston, united states</td> <td>1st</td> <td>marathon</td> <td>2:29:28</td> </tr> <tr> <th>4</th> <td>1984</td> <td>olympic games</td> <td>los angeles, united states</td> <td>5th</td> <td>marathon</td> <td>2:28:54</td> </tr> <tr> <th>5</th> <td>1986</td> <td>osaka ladies marathon</td> <td>osaka, japan</td> <td>1st</td> <td>marathon</td> <td>2:30:24</td> </tr> <tr> <th>6</th> <td>1986</td> <td>commonwealth games</td> <td>edinburgh, scotland</td> <td>2nd</td> <td>marathon</td> <td>2:28:17</td> </tr> <tr> <th>7</th> <td>1987</td> <td>osaka ladies marathon</td> <td>osaka, japan</td> <td>1st</td> <td>marathon</td> <td>2:30:40</td> </tr> <tr> <th>8</th> <td>1987</td> <td>world championships</td> <td>rome, italy</td> <td>21st</td> <td>10,000 m</td> <td>34:07.26</td> </tr> <tr> <th>9</th> <td>1988</td> <td>olympic games</td> <td>seoul, south korea</td> <td>33rd</td> <td>marathon</td> <td>2:37:52</td> </tr> <tr> <th>10</th> <td>1989</td> <td>osaka ladies marathon</td> <td>osaka, japan</td> <td>1st</td> <td>marathon</td> <td>2:30:21</td> </tr> <tr> <th>11</th> <td>1989</td> <td>hokkaido marathon</td> <td>sapporo, japan</td> <td>1st</td> <td>marathon</td> <td>2:36:39</td> </tr> <tr> <th>12</th> <td>1991</td> <td>hokkaido marathon</td> <td>sapporo, japan</td> <td>1st</td> <td>marathon</td> <td>2:33:20</td> </tr> <tr> <th>13</th> <td>1992</td> <td>olympic games</td> <td>barcelona, spain</td> <td>3rd</td> <td>marathon</td> <td>2:33:59</td> </tr> <tr> <th>14</th> <td>1996</td> <td>olympic games</td> <td>atlanta, united states</td> <td>46th</td> <td>marathon</td> <td>2:42:21</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where position = '3rd' <table_name> : table | | year | competition | venue | position | event | notes | |---:|-------:|:----------------------|:---------------------------|:-----------|:---------|:---------| | 0 | 1979 | grandma's marathon | duluth, united states | 1st | marathon | 2:37:37 | | 1 | 1980 | grandma's marathon | duluth, united states | 1st | marathon | 2:38:35 | | 2 | 1981 | grandma's marathon | duluth, united states | 1st | marathon | 2:29:35 | | 3 | 1984 | boston marathon | boston, united states | 1st | marathon | 2:29:28 | | 4 | 1984 | olympic games | los angeles, united states | 5th | marathon | 2:28:54 | | 5 | 1986 | osaka ladies marathon | osaka, japan | 1st | marathon | 2:30:24 | | 6 | 1986 | commonwealth games | edinburgh, scotland | 2nd | marathon | 2:28:17 | | 7 | 1987 | osaka ladies marathon | osaka, japan | 1st | marathon | 2:30:40 | | 8 | 1987 | world championships | rome, italy | 21st | 10,000 m | 34:07.26 | | 9 | 1988 | olympic games | seoul, south korea | 33rd | marathon | 2:37:52 | | 10 | 1989 | osaka ladies marathon | osaka, japan | 1st | marathon | 2:30:21 | | 11 | 1989 | hokkaido marathon | sapporo, japan | 1st | marathon | 2:36:39 | | 12 | 1991 | hokkaido marathon | sapporo, japan | 1st | marathon | 2:33:20 | | 13 | 1992 | olympic games | barcelona, spain | 3rd | marathon | 2:33:59 | | 14 | 1996 | olympic games | atlanta, united states | 46th | marathon | 2:42:21 |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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select nation where nation = 'north korea (prk)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | china (chn) | 127 | 63 | 33 | 223 row 2 : 2 | japan (jpn) | 46 | 56 | 77 | 179 row 3 : 3 | south korea (kor) | 32 | 48 | 65 | 145 row 4 : 4 | chinese taipei (tpe) | 12 | 34 | 26 | 72 row 5 : 5 | macau (mac) | 11 | 16 | 17 | 44 row 6 : 6 | north korea (prk) | 6 | 10 | 20 | 36 row 7 : 7 | hong kong (hkg) | 2 | 2 | 9 | 13 row 8 : 8 | mongolia (mgl) | 1 | 1 | 6 | 8 row 9 : 9 | guam (gum) | 0 | 0 | 1 | 1 row 10 : total | total | 237 | 230 | 254 | 721

col : nation row 1 : north korea (prk)

select nation where nation = 'north korea (prk)' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & china (chn) & 127 & 63 & 33 & 223 \\ 1 & 2 & japan (jpn) & 46 & 56 & 77 & 179 \\ 2 & 3 & south korea (kor) & 32 & 48 & 65 & 145 \\ 3 & 4 & chinese taipei (tpe) & 12 & 34 & 26 & 72 \\ 4 & 5 & macau (mac) & 11 & 16 & 17 & 44 \\ 5 & 6 & north korea (prk) & 6 & 10 & 20 & 36 \\ 6 & 7 & hong kong (hkg) & 2 & 2 & 9 & 13 \\ 7 & 8 & mongolia (mgl) & 1 & 1 & 6 & 8 \\ 8 & 9 & guam (gum) & 0 & 0 & 1 & 1 \\ 9 & total & total & 237 & 230 & 254 & 721 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & north korea (prk) \\ \bottomrule \end{tabular}

select nation where nation = 'north korea (prk)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>china (chn)</td> <td>127</td> <td>63</td> <td>33</td> <td>223</td> </tr> <tr> <th>1</th> <td>2</td> <td>japan (jpn)</td> <td>46</td> <td>56</td> <td>77</td> <td>179</td> </tr> <tr> <th>2</th> <td>3</td> <td>south korea (kor)</td> <td>32</td> <td>48</td> <td>65</td> <td>145</td> </tr> <tr> <th>3</th> <td>4</td> <td>chinese taipei (tpe)</td> <td>12</td> <td>34</td> <td>26</td> <td>72</td> </tr> <tr> <th>4</th> <td>5</td> <td>macau (mac)</td> <td>11</td> <td>16</td> <td>17</td> <td>44</td> </tr> <tr> <th>5</th> <td>6</td> <td>north korea (prk)</td> <td>6</td> <td>10</td> <td>20</td> <td>36</td> </tr> <tr> <th>6</th> <td>7</td> <td>hong kong (hkg)</td> <td>2</td> <td>2</td> <td>9</td> <td>13</td> </tr> <tr> <th>7</th> <td>8</td> <td>mongolia (mgl)</td> <td>1</td> <td>1</td> <td>6</td> <td>8</td> </tr> <tr> <th>8</th> <td>9</td> <td>guam (gum)</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>9</th> <td>total</td> <td>total</td> <td>237</td> <td>230</td> <td>254</td> <td>721</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>north korea (prk)</td> </tr> </tbody> </table>

select nation where nation = 'north korea (prk)' <table_name> : table | | rank | nation | gold | silver | bronze | total | |---:|:-------|:---------------------|-------:|---------:|---------:|--------:| | 0 | 1 | china (chn) | 127 | 63 | 33 | 223 | | 1 | 2 | japan (jpn) | 46 | 56 | 77 | 179 | | 2 | 3 | south korea (kor) | 32 | 48 | 65 | 145 | | 3 | 4 | chinese taipei (tpe) | 12 | 34 | 26 | 72 | | 4 | 5 | macau (mac) | 11 | 16 | 17 | 44 | | 5 | 6 | north korea (prk) | 6 | 10 | 20 | 36 | | 6 | 7 | hong kong (hkg) | 2 | 2 | 9 | 13 | | 7 | 8 | mongolia (mgl) | 1 | 1 | 6 | 8 | | 8 | 9 | guam (gum) | 0 | 0 | 1 | 1 | | 9 | total | total | 237 | 230 | 254 | 721 |

| | nation | |---:|:------------------| | 0 | north korea (prk) |

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col : year row 1 : 2006 row 2 : 2007 row 3 : 2008 row 4 : 2009 row 5 : 2010 row 6 : 2011

select year where engine = 'honda' <table_name> : table \begin{tabular}{lllllll} \toprule & year & chassis & engine & start & finish & team \\ \midrule 0 & 2001 & dallara & oldsmobile & 11 & 1 & team penske \\ 1 & 2002 & dallara & chevrolet & 13 & 1 & team penske \\ 2 & 2003 & dallara & toyota & 1 & 2 & team penske \\ 3 & 2004 & dallara & toyota & 8 & 9 & team penske \\ 4 & 2005 & dallara & toyota & 5 & 9 & team penske \\ 5 & 2006 & dallara & honda & 2 & 25 & team penske \\ 6 & 2007 & dallara & honda & 1 & 3 & team penske \\ 7 & 2008 & dallara & honda & 4 & 4 & team penske \\ 8 & 2009 & dallara & honda & 1 & 1 & team penske \\ 9 & 2010 & dallara & honda & 1 & 9 & team penske \\ 10 & 2011 & dallara & honda & 16 & 17 & team penske \\ 11 & 2012 & dallara & chevrolet & 6 & 10 & team penske \\ 12 & 2013 & dallara & chevrolet & 8 & 6 & team penske \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 2006 \\ 1 & 2007 \\ 2 & 2008 \\ 3 & 2009 \\ 4 & 2010 \\ 5 & 2011 \\ \bottomrule \end{tabular}

select year where engine = 'honda' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>chassis</th> <th>engine</th> <th>start</th> <th>finish</th> <th>team</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2001</td> <td>dallara</td> <td>oldsmobile</td> <td>11</td> <td>1</td> <td>team penske</td> </tr> <tr> <th>1</th> <td>2002</td> <td>dallara</td> <td>chevrolet</td> <td>13</td> <td>1</td> <td>team penske</td> </tr> <tr> <th>2</th> <td>2003</td> <td>dallara</td> <td>toyota</td> <td>1</td> <td>2</td> <td>team penske</td> </tr> <tr> <th>3</th> <td>2004</td> <td>dallara</td> <td>toyota</td> <td>8</td> <td>9</td> <td>team penske</td> </tr> <tr> <th>4</th> <td>2005</td> <td>dallara</td> <td>toyota</td> <td>5</td> <td>9</td> <td>team penske</td> </tr> <tr> <th>5</th> <td>2006</td> <td>dallara</td> <td>honda</td> <td>2</td> <td>25</td> <td>team penske</td> </tr> <tr> <th>6</th> <td>2007</td> <td>dallara</td> <td>honda</td> <td>1</td> <td>3</td> <td>team penske</td> </tr> <tr> <th>7</th> <td>2008</td> <td>dallara</td> <td>honda</td> <td>4</td> <td>4</td> <td>team penske</td> </tr> <tr> <th>8</th> <td>2009</td> <td>dallara</td> <td>honda</td> <td>1</td> <td>1</td> <td>team penske</td> </tr> <tr> <th>9</th> <td>2010</td> <td>dallara</td> <td>honda</td> <td>1</td> <td>9</td> <td>team penske</td> </tr> <tr> <th>10</th> <td>2011</td> <td>dallara</td> <td>honda</td> <td>16</td> <td>17</td> <td>team penske</td> </tr> <tr> <th>11</th> <td>2012</td> <td>dallara</td> <td>chevrolet</td> <td>6</td> <td>10</td> <td>team penske</td> </tr> <tr> <th>12</th> <td>2013</td> <td>dallara</td> <td>chevrolet</td> <td>8</td> <td>6</td> <td>team penske</td> </tr> </tbody> </table>

select year where engine = 'honda' <table_name> : table | | year | chassis | engine | start | finish | team | |---:|-------:|:----------|:-----------|--------:|---------:|:------------| | 0 | 2001 | dallara | oldsmobile | 11 | 1 | team penske | | 1 | 2002 | dallara | chevrolet | 13 | 1 | team penske | | 2 | 2003 | dallara | toyota | 1 | 2 | team penske | | 3 | 2004 | dallara | toyota | 8 | 9 | team penske | | 4 | 2005 | dallara | toyota | 5 | 9 | team penske | | 5 | 2006 | dallara | honda | 2 | 25 | team penske | | 6 | 2007 | dallara | honda | 1 | 3 | team penske | | 7 | 2008 | dallara | honda | 4 | 4 | team penske | | 8 | 2009 | dallara | honda | 1 | 1 | team penske | | 9 | 2010 | dallara | honda | 1 | 9 | team penske | | 10 | 2011 | dallara | honda | 16 | 17 | team penske | | 11 | 2012 | dallara | chevrolet | 6 | 10 | team penske | | 12 | 2013 | dallara | chevrolet | 8 | 6 | team penske |

| | year | |---:|-------:| | 0 | 2006 | | 1 | 2007 | | 2 | 2008 | | 3 | 2009 | | 4 | 2010 | | 5 | 2011 |

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col : count ( "date" ) row 1 : 4

select count ( date ) where location = 'lake louise, canada' <table_name> : table \begin{tabular}{llllll} \toprule & season & date & location & discipline & place \\ \midrule 0 & 2012 & 2011-12-02 00:00:00 & lake louise, canada & downhill & 2nd \\ 1 & 2012 & 2012-01-28 00:00:00 & st. moritz, switzerland & downhill & 3rd \\ 2 & 2012 & 2012-02-04 00:00:00 & garmisch, germany & downhill & 3rd \\ 3 & 2012 & 2012-02-05 00:00:00 & garmisch, germany & super-g & 3rd \\ 4 & 2012 & 2012-02-26 00:00:00 & bansko, bulgaria & super-g & 2nd \\ 5 & 2013 & 2012-11-30 00:00:00 & lake louise, canada & downhill & 3rd \\ 6 & 2013 & 2013-03-01 00:00:00 & garmisch, germany & super-g & 1st \\ 7 & 2014 & 2013-11-29 00:00:00 & beaver creek, usa & downhill & 2nd \\ 8 & 2014 & 2013-12-01 00:00:00 & beaver creek, usa & giant slalom & 3rd \\ 9 & 2014 & 2013-12-07 00:00:00 & lake louise, canada & downhill & 2nd \\ 10 & 2014 & 2013-12-08 00:00:00 & lake louise, canada & super-g & 2nd \\ 11 & 2014 & 2013-12-14 00:00:00 & st. moritz, switzerland & super-g & 1st \\ 12 & 2014 & 2013-12-22 00:00:00 & val-d'isere, france & giant slalom & 1st \\ 13 & 2014 & 2014-01-24 00:00:00 & cortina d'ampezzo, italy & downhill & 2nd \\ 14 & 2014 & 2014-01-25 00:00:00 & cortina d'ampezzo, italy & downhill & 3rd \\ 15 & 2014 & 2014-01-26 00:00:00 & cortina d'ampezzo, italy & super-g & 2nd \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "date" ) \\ \midrule 0 & 4 \\ \bottomrule \end{tabular}

select count ( date ) where location = 'lake louise, canada' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>date</th> <th>location</th> <th>discipline</th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2012</td> <td>2011-12-02 00:00:00</td> <td>lake louise, canada</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>1</th> <td>2012</td> <td>2012-01-28 00:00:00</td> <td>st. moritz, switzerland</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>2</th> <td>2012</td> <td>2012-02-04 00:00:00</td> <td>garmisch, germany</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>3</th> <td>2012</td> <td>2012-02-05 00:00:00</td> <td>garmisch, germany</td> <td>super-g</td> <td>3rd</td> </tr> <tr> <th>4</th> <td>2012</td> <td>2012-02-26 00:00:00</td> <td>bansko, bulgaria</td> <td>super-g</td> <td>2nd</td> </tr> <tr> <th>5</th> <td>2013</td> <td>2012-11-30 00:00:00</td> <td>lake louise, canada</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>6</th> <td>2013</td> <td>2013-03-01 00:00:00</td> <td>garmisch, germany</td> <td>super-g</td> <td>1st</td> </tr> <tr> <th>7</th> <td>2014</td> <td>2013-11-29 00:00:00</td> <td>beaver creek, usa</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>8</th> <td>2014</td> <td>2013-12-01 00:00:00</td> <td>beaver creek, usa</td> <td>giant slalom</td> <td>3rd</td> </tr> <tr> <th>9</th> <td>2014</td> <td>2013-12-07 00:00:00</td> <td>lake louise, canada</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>10</th> <td>2014</td> <td>2013-12-08 00:00:00</td> <td>lake louise, canada</td> <td>super-g</td> <td>2nd</td> </tr> <tr> <th>11</th> <td>2014</td> <td>2013-12-14 00:00:00</td> <td>st. moritz, switzerland</td> <td>super-g</td> <td>1st</td> </tr> <tr> <th>12</th> <td>2014</td> <td>2013-12-22 00:00:00</td> <td>val-d'isere, france</td> <td>giant slalom</td> <td>1st</td> </tr> <tr> <th>13</th> <td>2014</td> <td>2014-01-24 00:00:00</td> <td>cortina d'ampezzo, italy</td> <td>downhill</td> <td>2nd</td> </tr> <tr> <th>14</th> <td>2014</td> <td>2014-01-25 00:00:00</td> <td>cortina d'ampezzo, italy</td> <td>downhill</td> <td>3rd</td> </tr> <tr> <th>15</th> <td>2014</td> <td>2014-01-26 00:00:00</td> <td>cortina d'ampezzo, italy</td> <td>super-g</td> <td>2nd</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "date" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>4</td> </tr> </tbody> </table>

select count ( date ) where location = 'lake louise, canada' <table_name> : table | | season | date | location | discipline | place | |---:|---------:|:--------------------|:-------------------------|:-------------|:--------| | 0 | 2012 | 2011-12-02 00:00:00 | lake louise, canada | downhill | 2nd | | 1 | 2012 | 2012-01-28 00:00:00 | st. moritz, switzerland | downhill | 3rd | | 2 | 2012 | 2012-02-04 00:00:00 | garmisch, germany | downhill | 3rd | | 3 | 2012 | 2012-02-05 00:00:00 | garmisch, germany | super-g | 3rd | | 4 | 2012 | 2012-02-26 00:00:00 | bansko, bulgaria | super-g | 2nd | | 5 | 2013 | 2012-11-30 00:00:00 | lake louise, canada | downhill | 3rd | | 6 | 2013 | 2013-03-01 00:00:00 | garmisch, germany | super-g | 1st | | 7 | 2014 | 2013-11-29 00:00:00 | beaver creek, usa | downhill | 2nd | | 8 | 2014 | 2013-12-01 00:00:00 | beaver creek, usa | giant slalom | 3rd | | 9 | 2014 | 2013-12-07 00:00:00 | lake louise, canada | downhill | 2nd | | 10 | 2014 | 2013-12-08 00:00:00 | lake louise, canada | super-g | 2nd | | 11 | 2014 | 2013-12-14 00:00:00 | st. moritz, switzerland | super-g | 1st | | 12 | 2014 | 2013-12-22 00:00:00 | val-d'isere, france | giant slalom | 1st | | 13 | 2014 | 2014-01-24 00:00:00 | cortina d'ampezzo, italy | downhill | 2nd | | 14 | 2014 | 2014-01-25 00:00:00 | cortina d'ampezzo, italy | downhill | 3rd | | 15 | 2014 | 2014-01-26 00:00:00 | cortina d'ampezzo, italy | super-g | 2nd |

| | count ( "date" ) | |---:|-------------------:| | 0 | 4 |

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select count ( * ) where latest public release date (edition) > 323 col : part | number | first public release date (first edition) | latest public release date (edition) | latest amendment | title | description row 1 : part 1 | iso/iec 15938-1 | 2002 | 2002 | 2006 | systems | the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim) row 2 : part 2 | iso/iec 15938-2 | 2002 | 2002 | none | description definition language | none row 3 : part 3 | iso/iec 15938-3 | 2002 | 2002 | 2010 | visual | none row 4 : part 4 | iso/iec 15938-4 | 2002 | 2002 | 2006 | audio | none row 5 : part 5 | iso/iec 15938-5 | 2003 | 2003 | 2008 | multimedia description schemes | none row 6 : part 6 | iso/iec 15938-6 | 2003 | 2003 | 2010 (2011) | reference software | none row 7 : part 7 | iso/iec 15938-7 | 2003 | 2003 | 2010 (2011) | conformance testing | none row 8 : part 8 | iso/iec tr 15938-8 | 2002 | 2002 | 2010 | extraction and use of mpeg-7 descriptions | none row 9 : part 9 | iso/iec 15938-9 | 2005 | 2005 | (2011) | profiles and levels | none row 10 : part 10 | iso/iec 15938-10 | 2005 | 2005 | none | schema definition | none row 11 : part 11 | iso/iec tr 15938-11 | 2005 | 2005 | none | mpeg-7 profile schemas | none row 12 : part 12 | iso/iec 15938-12 | 2008 | 2008 | (2011) | query format | none

col : count ( "*" ) row 1 : 0

select count ( * ) where latest public release date (edition) > 323 <table_name> : table \begin{tabular}{llllllll} \toprule & part & number & first public release date (first edition) & latest public release date (edition) & latest amendment & title & description \\ \midrule 0 & part 1 & iso/iec 15938-1 & 2002 & 2002 & 2006 & systems & the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim) \\ 1 & part 2 & iso/iec 15938-2 & 2002 & 2002 & none & description definition language & none \\ 2 & part 3 & iso/iec 15938-3 & 2002 & 2002 & 2010 & visual & none \\ 3 & part 4 & iso/iec 15938-4 & 2002 & 2002 & 2006 & audio & none \\ 4 & part 5 & iso/iec 15938-5 & 2003 & 2003 & 2008 & multimedia description schemes & none \\ 5 & part 6 & iso/iec 15938-6 & 2003 & 2003 & 2010 (2011) & reference software & none \\ 6 & part 7 & iso/iec 15938-7 & 2003 & 2003 & 2010 (2011) & conformance testing & none \\ 7 & part 8 & iso/iec tr 15938-8 & 2002 & 2002 & 2010 & extraction and use of mpeg-7 descriptions & none \\ 8 & part 9 & iso/iec 15938-9 & 2005 & 2005 & (2011) & profiles and levels & none \\ 9 & part 10 & iso/iec 15938-10 & 2005 & 2005 & none & schema definition & none \\ 10 & part 11 & iso/iec tr 15938-11 & 2005 & 2005 & none & mpeg-7 profile schemas & none \\ 11 & part 12 & iso/iec 15938-12 & 2008 & 2008 & (2011) & query format & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where latest public release date (edition) > 323 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>part</th> <th>number</th> <th>first public release date (first edition)</th> <th>latest public release date (edition)</th> <th>latest amendment</th> <th>title</th> <th>description</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>part 1</td> <td>iso/iec 15938-1</td> <td>2002</td> <td>2002</td> <td>2006</td> <td>systems</td> <td>the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim)</td> </tr> <tr> <th>1</th> <td>part 2</td> <td>iso/iec 15938-2</td> <td>2002</td> <td>2002</td> <td>none</td> <td>description definition language</td> <td>none</td> </tr> <tr> <th>2</th> <td>part 3</td> <td>iso/iec 15938-3</td> <td>2002</td> <td>2002</td> <td>2010</td> <td>visual</td> <td>none</td> </tr> <tr> <th>3</th> <td>part 4</td> <td>iso/iec 15938-4</td> <td>2002</td> <td>2002</td> <td>2006</td> <td>audio</td> <td>none</td> </tr> <tr> <th>4</th> <td>part 5</td> <td>iso/iec 15938-5</td> <td>2003</td> <td>2003</td> <td>2008</td> <td>multimedia description schemes</td> <td>none</td> </tr> <tr> <th>5</th> <td>part 6</td> <td>iso/iec 15938-6</td> <td>2003</td> <td>2003</td> <td>2010 (2011)</td> <td>reference software</td> <td>none</td> </tr> <tr> <th>6</th> <td>part 7</td> <td>iso/iec 15938-7</td> <td>2003</td> <td>2003</td> <td>2010 (2011)</td> <td>conformance testing</td> <td>none</td> </tr> <tr> <th>7</th> <td>part 8</td> <td>iso/iec tr 15938-8</td> <td>2002</td> <td>2002</td> <td>2010</td> <td>extraction and use of mpeg-7 descriptions</td> <td>none</td> </tr> <tr> <th>8</th> <td>part 9</td> <td>iso/iec 15938-9</td> <td>2005</td> <td>2005</td> <td>(2011)</td> <td>profiles and levels</td> <td>none</td> </tr> <tr> <th>9</th> <td>part 10</td> <td>iso/iec 15938-10</td> <td>2005</td> <td>2005</td> <td>none</td> <td>schema definition</td> <td>none</td> </tr> <tr> <th>10</th> <td>part 11</td> <td>iso/iec tr 15938-11</td> <td>2005</td> <td>2005</td> <td>none</td> <td>mpeg-7 profile schemas</td> <td>none</td> </tr> <tr> <th>11</th> <td>part 12</td> <td>iso/iec 15938-12</td> <td>2008</td> <td>2008</td> <td>(2011)</td> <td>query format</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where latest public release date (edition) > 323 <table_name> : table | | part | number | first public release date (first edition) | latest public release date (edition) | latest amendment | title | description | |---:|:--------|:--------------------|--------------------------------------------:|---------------------------------------:|:-------------------|:------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | part 1 | iso/iec 15938-1 | 2002 | 2002 | 2006 | systems | the architectural framework of mpeg-7, the carriage of mpeg-7 content - tem (textual format for mpeg-7) and the binary format for mpeg-7 descriptions (bim) | | 1 | part 2 | iso/iec 15938-2 | 2002 | 2002 | none | description definition language | none | | 2 | part 3 | iso/iec 15938-3 | 2002 | 2002 | 2010 | visual | none | | 3 | part 4 | iso/iec 15938-4 | 2002 | 2002 | 2006 | audio | none | | 4 | part 5 | iso/iec 15938-5 | 2003 | 2003 | 2008 | multimedia description schemes | none | | 5 | part 6 | iso/iec 15938-6 | 2003 | 2003 | 2010 (2011) | reference software | none | | 6 | part 7 | iso/iec 15938-7 | 2003 | 2003 | 2010 (2011) | conformance testing | none | | 7 | part 8 | iso/iec tr 15938-8 | 2002 | 2002 | 2010 | extraction and use of mpeg-7 descriptions | none | | 8 | part 9 | iso/iec 15938-9 | 2005 | 2005 | (2011) | profiles and levels | none | | 9 | part 10 | iso/iec 15938-10 | 2005 | 2005 | none | schema definition | none | | 10 | part 11 | iso/iec tr 15938-11 | 2005 | 2005 | none | mpeg-7 profile schemas | none | | 11 | part 12 | iso/iec 15938-12 | 2008 | 2008 | (2011) | query format | none |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' col : year | laureate(s) | citizenship | institution | citation row 1 : 2003 | jean-pierre serre | french | college de france | "for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory" row 2 : 2004 | michael atiyah isadore singer | british american | university of edinburgh massachusetts institute of technology | "for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics" row 3 : 2005 | peter lax | american | courant institute | "for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions" row 4 : 2006 | lennart carleson | swedish | royal institute of technology | "for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems" row 5 : 2007 | s. r. srinivasa varadhan | indian/american | courant institute | "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation" row 6 : 2008 | john g. thompson jacques tits | american belgian/french | university of florida college de france | "for their profound achievements in algebra and in particular for shaping modern group theory" row 7 : 2009 | mikhail gromov | russian/french | institut des hautes etudes scientifiques courant institute | "for his revolutionary contributions to geometry" row 8 : 2010 | john t. tate | american | university of texas at austin | "for his vast and lasting impact on the theory of numbers" row 9 : 2011 | john milnor | american | stony brook university | "for pioneering discoveries in topology, geometry, and algebra" row 10 : 2012 | endre szemeredi | hungarian/american | alfred renyi institute and rutgers university | "for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory" row 11 : 2013 | pierre deligne | belgian | institute for advanced study | "for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields" row 12 : 2014 | yakov g. sinai | russian/american | landau institute for theoretical physics and princeton university | "for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics"

col : count ( "citizenship" ) row 1 : 1

select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' <table_name> : table \begin{tabular}{llllll} \toprule & year & laureate(s) & citizenship & institution & citation \\ \midrule 0 & 2003 & jean-pierre serre & french & college de france & "for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory" \\ 1 & 2004 & michael atiyah isadore singer & british american & university of edinburgh massachusetts institute of technology & "for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics" \\ 2 & 2005 & peter lax & american & courant institute & "for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions" \\ 3 & 2006 & lennart carleson & swedish & royal institute of technology & "for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems" \\ 4 & 2007 & s. r. srinivasa varadhan & indian/american & courant institute & "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation" \\ 5 & 2008 & john g. thompson jacques tits & american belgian/french & university of florida college de france & "for their profound achievements in algebra and in particular for shaping modern group theory" \\ 6 & 2009 & mikhail gromov & russian/french & institut des hautes etudes scientifiques courant institute & "for his revolutionary contributions to geometry" \\ 7 & 2010 & john t. tate & american & university of texas at austin & "for his vast and lasting impact on the theory of numbers" \\ 8 & 2011 & john milnor & american & stony brook university & "for pioneering discoveries in topology, geometry, and algebra" \\ 9 & 2012 & endre szemeredi & hungarian/american & alfred renyi institute and rutgers university & "for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory" \\ 10 & 2013 & pierre deligne & belgian & institute for advanced study & "for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields" \\ 11 & 2014 & yakov g. sinai & russian/american & landau institute for theoretical physics and princeton university & "for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics" \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "citizenship" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>laureate(s)</th> <th>citizenship</th> <th>institution</th> <th>citation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2003</td> <td>jean-pierre serre</td> <td>french</td> <td>college de france</td> <td>"for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory"</td> </tr> <tr> <th>1</th> <td>2004</td> <td>michael atiyah isadore singer</td> <td>british american</td> <td>university of edinburgh massachusetts institute of technology</td> <td>"for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics"</td> </tr> <tr> <th>2</th> <td>2005</td> <td>peter lax</td> <td>american</td> <td>courant institute</td> <td>"for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions"</td> </tr> <tr> <th>3</th> <td>2006</td> <td>lennart carleson</td> <td>swedish</td> <td>royal institute of technology</td> <td>"for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems"</td> </tr> <tr> <th>4</th> <td>2007</td> <td>s. r. srinivasa varadhan</td> <td>indian/american</td> <td>courant institute</td> <td>"for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation"</td> </tr> <tr> <th>5</th> <td>2008</td> <td>john g. thompson jacques tits</td> <td>american belgian/french</td> <td>university of florida college de france</td> <td>"for their profound achievements in algebra and in particular for shaping modern group theory"</td> </tr> <tr> <th>6</th> <td>2009</td> <td>mikhail gromov</td> <td>russian/french</td> <td>institut des hautes etudes scientifiques courant institute</td> <td>"for his revolutionary contributions to geometry"</td> </tr> <tr> <th>7</th> <td>2010</td> <td>john t. tate</td> <td>american</td> <td>university of texas at austin</td> <td>"for his vast and lasting impact on the theory of numbers"</td> </tr> <tr> <th>8</th> <td>2011</td> <td>john milnor</td> <td>american</td> <td>stony brook university</td> <td>"for pioneering discoveries in topology, geometry, and algebra"</td> </tr> <tr> <th>9</th> <td>2012</td> <td>endre szemeredi</td> <td>hungarian/american</td> <td>alfred renyi institute and rutgers university</td> <td>"for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory"</td> </tr> <tr> <th>10</th> <td>2013</td> <td>pierre deligne</td> <td>belgian</td> <td>institute for advanced study</td> <td>"for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields"</td> </tr> <tr> <th>11</th> <td>2014</td> <td>yakov g. sinai</td> <td>russian/american</td> <td>landau institute for theoretical physics and princeton university</td> <td>"for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics"</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "citizenship" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( citizenship ) where laureate(s) = 's. r. srinivasa varadhan' <table_name> : table | | year | laureate(s) | citizenship | institution | citation | |---:|-------:|:------------------------------|:------------------------|:------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 2003 | jean-pierre serre | french | college de france | "for playing a key role in shaping the modern form of many parts of mathematics, including topology, algebraic geometry and number theory" | | 1 | 2004 | michael atiyah isadore singer | british american | university of edinburgh massachusetts institute of technology | "for their discovery and proof of the index theorem, bringing together topology, geometry and analysis, and their outstanding role in building new bridges between mathematics and theoretical physics" | | 2 | 2005 | peter lax | american | courant institute | "for his groundbreaking contributions to the theory and application of partial differential equations and to the computation of their solutions" | | 3 | 2006 | lennart carleson | swedish | royal institute of technology | "for his profound and seminal contributions to harmonic analysis and the theory of smooth dynamical systems" | | 4 | 2007 | s. r. srinivasa varadhan | indian/american | courant institute | "for his fundamental contributions to probability theory and in particular for creating a unified theory of large deviation" | | 5 | 2008 | john g. thompson jacques tits | american belgian/french | university of florida college de france | "for their profound achievements in algebra and in particular for shaping modern group theory" | | 6 | 2009 | mikhail gromov | russian/french | institut des hautes etudes scientifiques courant institute | "for his revolutionary contributions to geometry" | | 7 | 2010 | john t. tate | american | university of texas at austin | "for his vast and lasting impact on the theory of numbers" | | 8 | 2011 | john milnor | american | stony brook university | "for pioneering discoveries in topology, geometry, and algebra" | | 9 | 2012 | endre szemeredi | hungarian/american | alfred renyi institute and rutgers university | "for his fundamental contributions to discrete mathematics and theoretical computer science, and in recognition of the profound and lasting impact of these contributions on additive number theory and ergodic theory" | | 10 | 2013 | pierre deligne | belgian | institute for advanced study | "for seminal contributions to algebraic geometry and for their transformative impact on number theory, representation theory, and related fields" | | 11 | 2014 | yakov g. sinai | russian/american | landau institute for theoretical physics and princeton university | "for his fundamental contributions to dynamical systems, ergodic theory, and mathematical physics" |

| | count ( "citizenship" ) | |---:|--------------------------:| | 0 | 1 |

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select count ( place ) where tier = 4 col : season | tier | division | place row 1 : 1928-84 | 5 | regional | none row 2 : 1984/85 | 4 | 3a | 6th row 3 : 1985/86 | 4 | 3a | 9th row 4 : 1986/87 | 4 | 3a | 11th row 5 : 1987/88 | 4 | 3a | 15th row 6 : 1988/89 | 4 | 3a | 4th row 7 : 1989/90 | 4 | 3a | 9th row 8 : 1990/91 | 4 | 3a | 9th row 9 : 1991/92 | 4 | 3a | 5th row 10 : 1992/93 | 4 | 3a | 17th row 11 : 1993/94 | 4 | 3a | 7th row 12 : 1994/95 | 4 | 3a | 4th row 13 : 1995/96 | 4 | 3a | 1st row 14 : 1996/97 | 3 | 2ab | 19th row 15 : 1997/98 | 4 | 3a | 2nd

col : count ( "place" ) row 1 : 13

select count ( place ) where tier = 4 <table_name> : table \begin{tabular}{lllll} \toprule & season & tier & division & place \\ \midrule 0 & 1928-84 & 5 & regional & none \\ 1 & 1984/85 & 4 & 3a & 6th \\ 2 & 1985/86 & 4 & 3a & 9th \\ 3 & 1986/87 & 4 & 3a & 11th \\ 4 & 1987/88 & 4 & 3a & 15th \\ 5 & 1988/89 & 4 & 3a & 4th \\ 6 & 1989/90 & 4 & 3a & 9th \\ 7 & 1990/91 & 4 & 3a & 9th \\ 8 & 1991/92 & 4 & 3a & 5th \\ 9 & 1992/93 & 4 & 3a & 17th \\ 10 & 1993/94 & 4 & 3a & 7th \\ 11 & 1994/95 & 4 & 3a & 4th \\ 12 & 1995/96 & 4 & 3a & 1st \\ 13 & 1996/97 & 3 & 2ab & 19th \\ 14 & 1997/98 & 4 & 3a & 2nd \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "place" ) \\ \midrule 0 & 13 \\ \bottomrule \end{tabular}

select count ( place ) where tier = 4 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>tier</th> <th>division</th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1928-84</td> <td>5</td> <td>regional</td> <td>none</td> </tr> <tr> <th>1</th> <td>1984/85</td> <td>4</td> <td>3a</td> <td>6th</td> </tr> <tr> <th>2</th> <td>1985/86</td> <td>4</td> <td>3a</td> <td>9th</td> </tr> <tr> <th>3</th> <td>1986/87</td> <td>4</td> <td>3a</td> <td>11th</td> </tr> <tr> <th>4</th> <td>1987/88</td> <td>4</td> <td>3a</td> <td>15th</td> </tr> <tr> <th>5</th> <td>1988/89</td> <td>4</td> <td>3a</td> <td>4th</td> </tr> <tr> <th>6</th> <td>1989/90</td> <td>4</td> <td>3a</td> <td>9th</td> </tr> <tr> <th>7</th> <td>1990/91</td> <td>4</td> <td>3a</td> <td>9th</td> </tr> <tr> <th>8</th> <td>1991/92</td> <td>4</td> <td>3a</td> <td>5th</td> </tr> <tr> <th>9</th> <td>1992/93</td> <td>4</td> <td>3a</td> <td>17th</td> </tr> <tr> <th>10</th> <td>1993/94</td> <td>4</td> <td>3a</td> <td>7th</td> </tr> <tr> <th>11</th> <td>1994/95</td> <td>4</td> <td>3a</td> <td>4th</td> </tr> <tr> <th>12</th> <td>1995/96</td> <td>4</td> <td>3a</td> <td>1st</td> </tr> <tr> <th>13</th> <td>1996/97</td> <td>3</td> <td>2ab</td> <td>19th</td> </tr> <tr> <th>14</th> <td>1997/98</td> <td>4</td> <td>3a</td> <td>2nd</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "place" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>13</td> </tr> </tbody> </table>

select count ( place ) where tier = 4 <table_name> : table | | season | tier | division | place | |---:|:---------|-------:|:-----------|:--------| | 0 | 1928-84 | 5 | regional | none | | 1 | 1984/85 | 4 | 3a | 6th | | 2 | 1985/86 | 4 | 3a | 9th | | 3 | 1986/87 | 4 | 3a | 11th | | 4 | 1987/88 | 4 | 3a | 15th | | 5 | 1988/89 | 4 | 3a | 4th | | 6 | 1989/90 | 4 | 3a | 9th | | 7 | 1990/91 | 4 | 3a | 9th | | 8 | 1991/92 | 4 | 3a | 5th | | 9 | 1992/93 | 4 | 3a | 17th | | 10 | 1993/94 | 4 | 3a | 7th | | 11 | 1994/95 | 4 | 3a | 4th | | 12 | 1995/96 | 4 | 3a | 1st | | 13 | 1996/97 | 3 | 2ab | 19th | | 14 | 1997/98 | 4 | 3a | 2nd |

| | count ( "place" ) | |---:|--------------------:| | 0 | 13 |

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select co-driver where car = 'toyota corolla' col : pos. | driver | co-driver | car | time | difference | points row 1 : 1 | raffaele pinto | arnaldo bernacchini | fiat abarth 124 rallye | 6:26:15 | 0 | 20 row 2 : 2 | alcide paganelli | ninni russo | fiat abarth 124 rallye | 6:30:12 | 3.57 | none row 3 : 3 | markku alen | ilkka kivimaki | fiat abarth 124 rallye | 6:37:17 | 11.02 | none row 4 : 4 | ove andersson | arne hertz | toyota corolla | 6:40:54 | 14.39 | 10 row 5 : 5 | harry kallstrom | claes billstam | datsun 260z | 6:54:27 | 28.12 | 8 row 6 : 6 | bob neyret | yveline vanoni | alpine-renault a110 1800 | 7:04:18 | 38.03 | 6 row 7 : 7 | georg fischer | harald gottlieb | bmw 2002 | 7:05:02 | 38.47 | 4 row 8 : 8 | francisco romaozinho | jose bernardo | citroen gs | 7:17:04 | 50.49 | 3 row 9 : 9 | chris sclater | neil wilson | ford escort rs1600 | 7:26:59 | 1:00.44 | 2 row 10 : 10 | antonio borges | miguel sottomayor | fiat 124 sport spyder | 7:27:55 | 1:01.40 | none

col : co-driver row 1 : arne hertz

select co-driver where car = 'toyota corolla' <table_name> : table \begin{tabular}{llllllll} \toprule & pos. & driver & co-driver & car & time & difference & points \\ \midrule 0 & 1 & raffaele pinto & arnaldo bernacchini & fiat abarth 124 rallye & 6:26:15 & 0 & 20 \\ 1 & 2 & alcide paganelli & ninni russo & fiat abarth 124 rallye & 6:30:12 & 3.57 & none \\ 2 & 3 & markku alen & ilkka kivimaki & fiat abarth 124 rallye & 6:37:17 & 11.02 & none \\ 3 & 4 & ove andersson & arne hertz & toyota corolla & 6:40:54 & 14.39 & 10 \\ 4 & 5 & harry kallstrom & claes billstam & datsun 260z & 6:54:27 & 28.12 & 8 \\ 5 & 6 & bob neyret & yveline vanoni & alpine-renault a110 1800 & 7:04:18 & 38.03 & 6 \\ 6 & 7 & georg fischer & harald gottlieb & bmw 2002 & 7:05:02 & 38.47 & 4 \\ 7 & 8 & francisco romaozinho & jose bernardo & citroen gs & 7:17:04 & 50.49 & 3 \\ 8 & 9 & chris sclater & neil wilson & ford escort rs1600 & 7:26:59 & 1:00.44 & 2 \\ 9 & 10 & antonio borges & miguel sottomayor & fiat 124 sport spyder & 7:27:55 & 1:01.40 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & co-driver \\ \midrule 0 & arne hertz \\ \bottomrule \end{tabular}

select co-driver where car = 'toyota corolla' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pos.</th> <th>driver</th> <th>co-driver</th> <th>car</th> <th>time</th> <th>difference</th> <th>points</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>raffaele pinto</td> <td>arnaldo bernacchini</td> <td>fiat abarth 124 rallye</td> <td>6:26:15</td> <td>0</td> <td>20</td> </tr> <tr> <th>1</th> <td>2</td> <td>alcide paganelli</td> <td>ninni russo</td> <td>fiat abarth 124 rallye</td> <td>6:30:12</td> <td>3.57</td> <td>none</td> </tr> <tr> <th>2</th> <td>3</td> <td>markku alen</td> <td>ilkka kivimaki</td> <td>fiat abarth 124 rallye</td> <td>6:37:17</td> <td>11.02</td> <td>none</td> </tr> <tr> <th>3</th> <td>4</td> <td>ove andersson</td> <td>arne hertz</td> <td>toyota corolla</td> <td>6:40:54</td> <td>14.39</td> <td>10</td> </tr> <tr> <th>4</th> <td>5</td> <td>harry kallstrom</td> <td>claes billstam</td> <td>datsun 260z</td> <td>6:54:27</td> <td>28.12</td> <td>8</td> </tr> <tr> <th>5</th> <td>6</td> <td>bob neyret</td> <td>yveline vanoni</td> <td>alpine-renault a110 1800</td> <td>7:04:18</td> <td>38.03</td> <td>6</td> </tr> <tr> <th>6</th> <td>7</td> <td>georg fischer</td> <td>harald gottlieb</td> <td>bmw 2002</td> <td>7:05:02</td> <td>38.47</td> <td>4</td> </tr> <tr> <th>7</th> <td>8</td> <td>francisco romaozinho</td> <td>jose bernardo</td> <td>citroen gs</td> <td>7:17:04</td> <td>50.49</td> <td>3</td> </tr> <tr> <th>8</th> <td>9</td> <td>chris sclater</td> <td>neil wilson</td> <td>ford escort rs1600</td> <td>7:26:59</td> <td>1:00.44</td> <td>2</td> </tr> <tr> <th>9</th> <td>10</td> <td>antonio borges</td> <td>miguel sottomayor</td> <td>fiat 124 sport spyder</td> <td>7:27:55</td> <td>1:01.40</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>co-driver</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>arne hertz</td> </tr> </tbody> </table>

select co-driver where car = 'toyota corolla' <table_name> : table | | pos. | driver | co-driver | car | time | difference | points | |---:|-------:|:---------------------|:--------------------|:-------------------------|:--------|:-------------|:---------| | 0 | 1 | raffaele pinto | arnaldo bernacchini | fiat abarth 124 rallye | 6:26:15 | 0 | 20 | | 1 | 2 | alcide paganelli | ninni russo | fiat abarth 124 rallye | 6:30:12 | 3.57 | none | | 2 | 3 | markku alen | ilkka kivimaki | fiat abarth 124 rallye | 6:37:17 | 11.02 | none | | 3 | 4 | ove andersson | arne hertz | toyota corolla | 6:40:54 | 14.39 | 10 | | 4 | 5 | harry kallstrom | claes billstam | datsun 260z | 6:54:27 | 28.12 | 8 | | 5 | 6 | bob neyret | yveline vanoni | alpine-renault a110 1800 | 7:04:18 | 38.03 | 6 | | 6 | 7 | georg fischer | harald gottlieb | bmw 2002 | 7:05:02 | 38.47 | 4 | | 7 | 8 | francisco romaozinho | jose bernardo | citroen gs | 7:17:04 | 50.49 | 3 | | 8 | 9 | chris sclater | neil wilson | ford escort rs1600 | 7:26:59 | 1:00.44 | 2 | | 9 | 10 | antonio borges | miguel sottomayor | fiat 124 sport spyder | 7:27:55 | 1:01.40 | none |

| | co-driver | |---:|:------------| | 0 | arne hertz |

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col : "abs ( year - year )" row 1 : abs ( year - year )

select abs ( year - year ) where title = '24 hour party people' <table_name> : table \begin{tabular}{lllll} \toprule & year & title & role & notes \\ \midrule 0 & 1991 & let him have it & derek bentley & none \\ 1 & 1992 & death and the compass & alonso zunz & none \\ 2 & 1993 & anchoress & priest & none \\ 3 & 1994 & shallow grave & david & none \\ 4 & 1996 & jude & jude fawley & none \\ 5 & 1998 & elizabeth & duke of norfolk & none \\ 6 & 1998 & a price above rubies & sender horowitz & none \\ 7 & 1999 & heart & gary ellis & none \\ 8 & 1999 & existenz & seminar leader & none \\ 9 & 1999 & with or without you & vincent boyd & none \\ 10 & 2000 & gone in 60 seconds & raymond calitri & none \\ 11 & 2000 & the tyre & salesman & short film \\ 12 & 2001 & the others & charles stewart & none \\ 13 & 2001 & the invisible circus & wolf & none \\ 14 & 2001 & this little piggy & cabbie & short film \\ 15 & 2002 & 24 hour party people & boethius & none \\ 16 & 2002 & i am dina & leo zhukovsky & none \\ 17 & 2002 & revengers tragedy & vindici & none \\ 18 & 2002 & 28 days later & major henry west & none \\ 19 & 2007 & the dark is rising & the rider & none \\ 20 & 2008 & new orleans, mon amour & dr. henry & none \\ 21 & 2009 & g.i. joe: the rise of cobra & james mccullen / destro & none \\ 22 & 2009 & amelia & fred noonan & none \\ 23 & 2009 & the happiness salesman & salesman & short film \\ 24 & 2012 & song for marion & james harris & none \\ 25 & 2013 & thor: the dark world & malekith & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & "abs ( year - year )" \\ \midrule 0 & abs ( year - year ) \\ \bottomrule \end{tabular}

select abs ( year - year ) where title = '24 hour party people' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>title</th> <th>role</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1991</td> <td>let him have it</td> <td>derek bentley</td> <td>none</td> </tr> <tr> <th>1</th> <td>1992</td> <td>death and the compass</td> <td>alonso zunz</td> <td>none</td> </tr> <tr> <th>2</th> <td>1993</td> <td>anchoress</td> <td>priest</td> <td>none</td> </tr> <tr> <th>3</th> <td>1994</td> <td>shallow grave</td> <td>david</td> <td>none</td> </tr> <tr> <th>4</th> <td>1996</td> <td>jude</td> <td>jude fawley</td> <td>none</td> </tr> <tr> <th>5</th> <td>1998</td> <td>elizabeth</td> <td>duke of norfolk</td> <td>none</td> </tr> <tr> <th>6</th> <td>1998</td> <td>a price above rubies</td> <td>sender horowitz</td> <td>none</td> </tr> <tr> <th>7</th> <td>1999</td> <td>heart</td> <td>gary ellis</td> <td>none</td> </tr> <tr> <th>8</th> <td>1999</td> <td>existenz</td> <td>seminar leader</td> <td>none</td> </tr> <tr> <th>9</th> <td>1999</td> <td>with or without you</td> <td>vincent boyd</td> <td>none</td> </tr> <tr> <th>10</th> <td>2000</td> <td>gone in 60 seconds</td> <td>raymond calitri</td> <td>none</td> </tr> <tr> <th>11</th> <td>2000</td> <td>the tyre</td> <td>salesman</td> <td>short film</td> </tr> <tr> <th>12</th> <td>2001</td> <td>the others</td> <td>charles stewart</td> <td>none</td> </tr> <tr> <th>13</th> <td>2001</td> <td>the invisible circus</td> <td>wolf</td> <td>none</td> </tr> <tr> <th>14</th> <td>2001</td> <td>this little piggy</td> <td>cabbie</td> <td>short film</td> </tr> <tr> <th>15</th> <td>2002</td> <td>24 hour party people</td> <td>boethius</td> <td>none</td> </tr> <tr> <th>16</th> <td>2002</td> <td>i am dina</td> <td>leo zhukovsky</td> <td>none</td> </tr> <tr> <th>17</th> <td>2002</td> <td>revengers tragedy</td> <td>vindici</td> <td>none</td> </tr> <tr> <th>18</th> <td>2002</td> <td>28 days later</td> <td>major henry west</td> <td>none</td> </tr> <tr> <th>19</th> <td>2007</td> <td>the dark is rising</td> <td>the rider</td> <td>none</td> </tr> <tr> <th>20</th> <td>2008</td> <td>new orleans, mon amour</td> <td>dr. henry</td> <td>none</td> </tr> <tr> <th>21</th> <td>2009</td> <td>g.i. joe: the rise of cobra</td> <td>james mccullen / destro</td> <td>none</td> </tr> <tr> <th>22</th> <td>2009</td> <td>amelia</td> <td>fred noonan</td> <td>none</td> </tr> <tr> <th>23</th> <td>2009</td> <td>the happiness salesman</td> <td>salesman</td> <td>short film</td> </tr> <tr> <th>24</th> <td>2012</td> <td>song for marion</td> <td>james harris</td> <td>none</td> </tr> <tr> <th>25</th> <td>2013</td> <td>thor: the dark world</td> <td>malekith</td> <td>none</td> </tr> </tbody> </table>

select abs ( year - year ) where title = '24 hour party people' <table_name> : table | | year | title | role | notes | |---:|-------:|:----------------------------|:------------------------|:-----------| | 0 | 1991 | let him have it | derek bentley | none | | 1 | 1992 | death and the compass | alonso zunz | none | | 2 | 1993 | anchoress | priest | none | | 3 | 1994 | shallow grave | david | none | | 4 | 1996 | jude | jude fawley | none | | 5 | 1998 | elizabeth | duke of norfolk | none | | 6 | 1998 | a price above rubies | sender horowitz | none | | 7 | 1999 | heart | gary ellis | none | | 8 | 1999 | existenz | seminar leader | none | | 9 | 1999 | with or without you | vincent boyd | none | | 10 | 2000 | gone in 60 seconds | raymond calitri | none | | 11 | 2000 | the tyre | salesman | short film | | 12 | 2001 | the others | charles stewart | none | | 13 | 2001 | the invisible circus | wolf | none | | 14 | 2001 | this little piggy | cabbie | short film | | 15 | 2002 | 24 hour party people | boethius | none | | 16 | 2002 | i am dina | leo zhukovsky | none | | 17 | 2002 | revengers tragedy | vindici | none | | 18 | 2002 | 28 days later | major henry west | none | | 19 | 2007 | the dark is rising | the rider | none | | 20 | 2008 | new orleans, mon amour | dr. henry | none | | 21 | 2009 | g.i. joe: the rise of cobra | james mccullen / destro | none | | 22 | 2009 | amelia | fred noonan | none | | 23 | 2009 | the happiness salesman | salesman | short film | | 24 | 2012 | song for marion | james harris | none | | 25 | 2013 | thor: the dark world | malekith | none |

| | "abs ( year - year )" | |---:|:------------------------| | 0 | abs ( year - year ) |

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select place - division where place = '20th' col : season | tier | division | place row 1 : 1970-01 | 6 | regional | none row 2 : 2001/02 | 6 | 1a reg | none row 3 : 2002/03 | 5 | reg. pref | 11th row 4 : 2003/04 | 5 | reg. pref | 9th row 5 : 2004/05 | 5 | reg. pref | 1st row 6 : 2005/06 | 4 | 3a | 20th row 7 : 2006/07 | 5 | reg. pref | 3rd row 8 : 2007/08 | 5 | reg. pref | 1st row 9 : 2008/09 | 4 | 3a | 16th row 10 : 2009/10 | 4 | 3a | 17th row 11 : 2010/11 | 4 | 3a | 18th row 12 : 2011/12 | 5 | reg. pref | 2nd

col : "place - division" row 1 : place - division

select place - division where place = '20th' <table_name> : table \begin{tabular}{lllll} \toprule & season & tier & division & place \\ \midrule 0 & 1970-01 & 6 & regional & none \\ 1 & 2001/02 & 6 & 1a reg & none \\ 2 & 2002/03 & 5 & reg. pref & 11th \\ 3 & 2003/04 & 5 & reg. pref & 9th \\ 4 & 2004/05 & 5 & reg. pref & 1st \\ 5 & 2005/06 & 4 & 3a & 20th \\ 6 & 2006/07 & 5 & reg. pref & 3rd \\ 7 & 2007/08 & 5 & reg. pref & 1st \\ 8 & 2008/09 & 4 & 3a & 16th \\ 9 & 2009/10 & 4 & 3a & 17th \\ 10 & 2010/11 & 4 & 3a & 18th \\ 11 & 2011/12 & 5 & reg. pref & 2nd \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & "place - division" \\ \midrule 0 & place - division \\ \bottomrule \end{tabular}

select place - division where place = '20th' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>tier</th> <th>division</th> <th>place</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1970-01</td> <td>6</td> <td>regional</td> <td>none</td> </tr> <tr> <th>1</th> <td>2001/02</td> <td>6</td> <td>1a reg</td> <td>none</td> </tr> <tr> <th>2</th> <td>2002/03</td> <td>5</td> <td>reg. pref</td> <td>11th</td> </tr> <tr> <th>3</th> <td>2003/04</td> <td>5</td> <td>reg. pref</td> <td>9th</td> </tr> <tr> <th>4</th> <td>2004/05</td> <td>5</td> <td>reg. pref</td> <td>1st</td> </tr> <tr> <th>5</th> <td>2005/06</td> <td>4</td> <td>3a</td> <td>20th</td> </tr> <tr> <th>6</th> <td>2006/07</td> <td>5</td> <td>reg. pref</td> <td>3rd</td> </tr> <tr> <th>7</th> <td>2007/08</td> <td>5</td> <td>reg. pref</td> <td>1st</td> </tr> <tr> <th>8</th> <td>2008/09</td> <td>4</td> <td>3a</td> <td>16th</td> </tr> <tr> <th>9</th> <td>2009/10</td> <td>4</td> <td>3a</td> <td>17th</td> </tr> <tr> <th>10</th> <td>2010/11</td> <td>4</td> <td>3a</td> <td>18th</td> </tr> <tr> <th>11</th> <td>2011/12</td> <td>5</td> <td>reg. pref</td> <td>2nd</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"place - division"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>place - division</td> </tr> </tbody> </table>

select place - division where place = '20th' <table_name> : table | | season | tier | division | place | |---:|:---------|-------:|:-----------|:--------| | 0 | 1970-01 | 6 | regional | none | | 1 | 2001/02 | 6 | 1a reg | none | | 2 | 2002/03 | 5 | reg. pref | 11th | | 3 | 2003/04 | 5 | reg. pref | 9th | | 4 | 2004/05 | 5 | reg. pref | 1st | | 5 | 2005/06 | 4 | 3a | 20th | | 6 | 2006/07 | 5 | reg. pref | 3rd | | 7 | 2007/08 | 5 | reg. pref | 1st | | 8 | 2008/09 | 4 | 3a | 16th | | 9 | 2009/10 | 4 | 3a | 17th | | 10 | 2010/11 | 4 | 3a | 18th | | 11 | 2011/12 | 5 | reg. pref | 2nd |

| | "place - division" | |---:|:---------------------| | 0 | place - division |

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col : rank row 1 : 14 row 2 : 14 row 3 : 14 row 4 : 14

select rank where tally = '3-1' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & player & county & tally & total & opposition \\ \midrule 0 & 1 & eamonn flynn & dublin & 3-5 & 14 & wexford \\ 1 & 1 & charlie mccarthy & cork & 2-8 & 14 & galway \\ 2 & 3 & paddy fahy & galway & 2-7 & 13 & kildare \\ 3 & 3 & t. morrissey & wicklow & 2-7 & 13 & laois \\ 4 & 5 & charlie mccarthy & cork & 3-3 & 12 & offaly \\ 5 & 5 & michael moroney & clare & 2-6 & 12 & dublin \\ 6 & 5 & declan lovett & kerry & 1-9 & 12 & galway \\ 7 & 5 & charlie mccarthy & cork & 1-9 & 12 & tipperary \\ 8 & 9 & ger cuddy & laois & 3-2 & 11 & wicklow \\ 9 & 9 & pat enright & waterford & 2-5 & 11 & kerry \\ 10 & 9 & pat enright & waterford & 1-8 & 11 & laois \\ 11 & 9 & johnny walsh & kildare & 0-11 & 11 & waterford \\ 12 & 9 & eddie keher & kilkenny & 0-11 & 11 & wexford \\ 13 & 14 & brendan cummins & cork & 3-1 & 10 & wexford \\ 14 & 14 & p. j. molloy & galway & 3-1 & 10 & kerry \\ 15 & 14 & nick behan & kildare & 3-1 & 10 & kerry \\ 16 & 14 & seanie o'leary & cork & 3-1 & 10 & limerick \\ 17 & 14 & michael keating & tipperary & 2-4 & 10 & wexford \\ 18 & 14 & seamus richmond & antrim & 2-4 & 10 & westmeath \\ 19 & 14 & declan lovett & kerry & 2-4 & 10 & waterford \\ 20 & 14 & michael keating & tipperary & 2-4 & 10 & dublin \\ 21 & 14 & eddie keher & kilkenny & 2-4 & 10 & dublin \\ 22 & 14 & mick dwan & kildare & 2-4 & 10 & antrim \\ 23 & 14 & charlie mccarthy & cork & 1-7 & 10 & kilkenny \\ 24 & 14 & paddy fahy & galway & 0-10 & 10 & kerry \\ 25 & 14 & johnny walsh & kildare & 0-10 & 10 & westmeath \\ 26 & 27 & p flynn & wexford & 3-0 & 9 & offaly \\ 27 & 27 & n casey & clare & 3-0 & 9 & cork \\ 28 & 27 & willie moore & limerick & 3-0 & 9 & cork \\ 29 & 27 & ger cuddy & laois & 3-0 & 9 & westmeath \\ 30 & 27 & tom ryan & galway & 3-0 & 9 & laois \\ 31 & 27 & seanie o'leary & cork & 3-0 & 9 & offaly \\ 32 & 27 & p flynn & wexford & 2-3 & 9 & cork \\ 33 & 27 & eddie keher & kilkenny & 2-3 & 9 & limerick \\ 34 & 27 & johnny walsh & kildare & 1-6 & 9 & galway \\ 35 & 27 & francis loughnane & tipperary & 1-6 & 9 & cork \\ 36 & 27 & richie bennis & limerick & 1-6 & 9 & cork \\ 37 & 27 & pat enright & waterford & 0-9 & 9 & kildare \\ 38 & 27 & johnny walsh & kildare & 0-9 & 9 & kerry \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & rank \\ \midrule 0 & 14 \\ 1 & 14 \\ 2 & 14 \\ 3 & 14 \\ \bottomrule \end{tabular}

select rank where tally = '3-1' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>player</th> <th>county</th> <th>tally</th> <th>total</th> <th>opposition</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>eamonn flynn</td> <td>dublin</td> <td>3-5</td> <td>14</td> <td>wexford</td> </tr> <tr> <th>1</th> <td>1</td> <td>charlie mccarthy</td> <td>cork</td> <td>2-8</td> <td>14</td> <td>galway</td> </tr> <tr> <th>2</th> <td>3</td> <td>paddy fahy</td> <td>galway</td> <td>2-7</td> <td>13</td> <td>kildare</td> </tr> <tr> <th>3</th> <td>3</td> <td>t. morrissey</td> <td>wicklow</td> <td>2-7</td> <td>13</td> <td>laois</td> </tr> <tr> <th>4</th> <td>5</td> <td>charlie mccarthy</td> <td>cork</td> <td>3-3</td> <td>12</td> <td>offaly</td> </tr> <tr> <th>5</th> <td>5</td> <td>michael moroney</td> <td>clare</td> <td>2-6</td> <td>12</td> <td>dublin</td> </tr> <tr> <th>6</th> <td>5</td> <td>declan lovett</td> <td>kerry</td> <td>1-9</td> <td>12</td> <td>galway</td> </tr> <tr> <th>7</th> <td>5</td> <td>charlie mccarthy</td> <td>cork</td> <td>1-9</td> <td>12</td> <td>tipperary</td> </tr> <tr> <th>8</th> <td>9</td> <td>ger cuddy</td> <td>laois</td> <td>3-2</td> <td>11</td> <td>wicklow</td> </tr> <tr> <th>9</th> <td>9</td> <td>pat enright</td> <td>waterford</td> <td>2-5</td> <td>11</td> <td>kerry</td> </tr> <tr> <th>10</th> <td>9</td> <td>pat enright</td> <td>waterford</td> <td>1-8</td> <td>11</td> <td>laois</td> </tr> <tr> <th>11</th> <td>9</td> <td>johnny walsh</td> <td>kildare</td> <td>0-11</td> <td>11</td> <td>waterford</td> </tr> <tr> <th>12</th> <td>9</td> <td>eddie keher</td> <td>kilkenny</td> <td>0-11</td> <td>11</td> <td>wexford</td> </tr> <tr> <th>13</th> <td>14</td> <td>brendan cummins</td> <td>cork</td> <td>3-1</td> <td>10</td> <td>wexford</td> </tr> <tr> <th>14</th> <td>14</td> <td>p. j. molloy</td> <td>galway</td> <td>3-1</td> <td>10</td> <td>kerry</td> </tr> <tr> <th>15</th> <td>14</td> <td>nick behan</td> <td>kildare</td> <td>3-1</td> <td>10</td> <td>kerry</td> </tr> <tr> <th>16</th> <td>14</td> <td>seanie o'leary</td> <td>cork</td> <td>3-1</td> <td>10</td> <td>limerick</td> </tr> <tr> <th>17</th> <td>14</td> <td>michael keating</td> <td>tipperary</td> <td>2-4</td> <td>10</td> <td>wexford</td> </tr> <tr> <th>18</th> <td>14</td> <td>seamus richmond</td> <td>antrim</td> <td>2-4</td> <td>10</td> <td>westmeath</td> </tr> <tr> <th>19</th> <td>14</td> <td>declan lovett</td> <td>kerry</td> <td>2-4</td> <td>10</td> <td>waterford</td> </tr> <tr> <th>20</th> <td>14</td> <td>michael keating</td> <td>tipperary</td> <td>2-4</td> <td>10</td> <td>dublin</td> </tr> <tr> <th>21</th> <td>14</td> <td>eddie keher</td> <td>kilkenny</td> <td>2-4</td> <td>10</td> <td>dublin</td> </tr> <tr> <th>22</th> <td>14</td> <td>mick dwan</td> <td>kildare</td> <td>2-4</td> <td>10</td> <td>antrim</td> </tr> <tr> <th>23</th> <td>14</td> <td>charlie mccarthy</td> <td>cork</td> <td>1-7</td> <td>10</td> <td>kilkenny</td> </tr> <tr> <th>24</th> <td>14</td> <td>paddy fahy</td> <td>galway</td> <td>0-10</td> <td>10</td> <td>kerry</td> </tr> <tr> <th>25</th> <td>14</td> <td>johnny walsh</td> <td>kildare</td> <td>0-10</td> <td>10</td> <td>westmeath</td> </tr> <tr> <th>26</th> <td>27</td> <td>p flynn</td> <td>wexford</td> <td>3-0</td> <td>9</td> <td>offaly</td> </tr> <tr> <th>27</th> <td>27</td> <td>n casey</td> <td>clare</td> <td>3-0</td> <td>9</td> <td>cork</td> </tr> <tr> <th>28</th> <td>27</td> <td>willie moore</td> <td>limerick</td> <td>3-0</td> <td>9</td> <td>cork</td> </tr> <tr> <th>29</th> <td>27</td> <td>ger cuddy</td> <td>laois</td> <td>3-0</td> <td>9</td> <td>westmeath</td> </tr> <tr> <th>30</th> <td>27</td> <td>tom ryan</td> <td>galway</td> <td>3-0</td> <td>9</td> <td>laois</td> </tr> <tr> <th>31</th> <td>27</td> <td>seanie o'leary</td> <td>cork</td> <td>3-0</td> <td>9</td> <td>offaly</td> </tr> <tr> <th>32</th> <td>27</td> <td>p flynn</td> <td>wexford</td> <td>2-3</td> <td>9</td> <td>cork</td> </tr> <tr> <th>33</th> <td>27</td> <td>eddie keher</td> <td>kilkenny</td> <td>2-3</td> <td>9</td> <td>limerick</td> </tr> <tr> <th>34</th> <td>27</td> <td>johnny walsh</td> <td>kildare</td> <td>1-6</td> <td>9</td> <td>galway</td> </tr> <tr> <th>35</th> <td>27</td> <td>francis loughnane</td> <td>tipperary</td> <td>1-6</td> <td>9</td> <td>cork</td> </tr> <tr> <th>36</th> <td>27</td> <td>richie bennis</td> <td>limerick</td> <td>1-6</td> <td>9</td> <td>cork</td> </tr> <tr> <th>37</th> <td>27</td> <td>pat enright</td> <td>waterford</td> <td>0-9</td> <td>9</td> <td>kildare</td> </tr> <tr> <th>38</th> <td>27</td> <td>johnny walsh</td> <td>kildare</td> <td>0-9</td> <td>9</td> <td>kerry</td> </tr> </tbody> </table>

select rank where tally = '3-1' <table_name> : table | | rank | player | county | tally | total | opposition | |---:|-------:|:------------------|:----------|:--------|--------:|:-------------| | 0 | 1 | eamonn flynn | dublin | 3-5 | 14 | wexford | | 1 | 1 | charlie mccarthy | cork | 2-8 | 14 | galway | | 2 | 3 | paddy fahy | galway | 2-7 | 13 | kildare | | 3 | 3 | t. morrissey | wicklow | 2-7 | 13 | laois | | 4 | 5 | charlie mccarthy | cork | 3-3 | 12 | offaly | | 5 | 5 | michael moroney | clare | 2-6 | 12 | dublin | | 6 | 5 | declan lovett | kerry | 1-9 | 12 | galway | | 7 | 5 | charlie mccarthy | cork | 1-9 | 12 | tipperary | | 8 | 9 | ger cuddy | laois | 3-2 | 11 | wicklow | | 9 | 9 | pat enright | waterford | 2-5 | 11 | kerry | | 10 | 9 | pat enright | waterford | 1-8 | 11 | laois | | 11 | 9 | johnny walsh | kildare | 0-11 | 11 | waterford | | 12 | 9 | eddie keher | kilkenny | 0-11 | 11 | wexford | | 13 | 14 | brendan cummins | cork | 3-1 | 10 | wexford | | 14 | 14 | p. j. molloy | galway | 3-1 | 10 | kerry | | 15 | 14 | nick behan | kildare | 3-1 | 10 | kerry | | 16 | 14 | seanie o'leary | cork | 3-1 | 10 | limerick | | 17 | 14 | michael keating | tipperary | 2-4 | 10 | wexford | | 18 | 14 | seamus richmond | antrim | 2-4 | 10 | westmeath | | 19 | 14 | declan lovett | kerry | 2-4 | 10 | waterford | | 20 | 14 | michael keating | tipperary | 2-4 | 10 | dublin | | 21 | 14 | eddie keher | kilkenny | 2-4 | 10 | dublin | | 22 | 14 | mick dwan | kildare | 2-4 | 10 | antrim | | 23 | 14 | charlie mccarthy | cork | 1-7 | 10 | kilkenny | | 24 | 14 | paddy fahy | galway | 0-10 | 10 | kerry | | 25 | 14 | johnny walsh | kildare | 0-10 | 10 | westmeath | | 26 | 27 | p flynn | wexford | 3-0 | 9 | offaly | | 27 | 27 | n casey | clare | 3-0 | 9 | cork | | 28 | 27 | willie moore | limerick | 3-0 | 9 | cork | | 29 | 27 | ger cuddy | laois | 3-0 | 9 | westmeath | | 30 | 27 | tom ryan | galway | 3-0 | 9 | laois | | 31 | 27 | seanie o'leary | cork | 3-0 | 9 | offaly | | 32 | 27 | p flynn | wexford | 2-3 | 9 | cork | | 33 | 27 | eddie keher | kilkenny | 2-3 | 9 | limerick | | 34 | 27 | johnny walsh | kildare | 1-6 | 9 | galway | | 35 | 27 | francis loughnane | tipperary | 1-6 | 9 | cork | | 36 | 27 | richie bennis | limerick | 1-6 | 9 | cork | | 37 | 27 | pat enright | waterford | 0-9 | 9 | kildare | | 38 | 27 | johnny walsh | kildare | 0-9 | 9 | kerry |

| | rank | |---:|-------:| | 0 | 14 | | 1 | 14 | | 2 | 14 | | 3 | 14 |

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col : length row 1 : 7:24

select length where version = 'axwell remix' <table_name> : table \begin{tabular}{lllllll} \toprule & version & length & album & remixed by & year & comment \\ \midrule 0 & single version / radio edit & 3:39 & go - the very best of moby & mhc aka philip larsen and chis smith & 2006 & remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one \\ 1 & extended remix & 6:48 & none & mhc aka philip larsen and chis smith & 2006 & similar to the previous but longer \\ 2 & axwell remix & 7:24 & none & axwell & 2006 & used in a scene in the 2008 movie 21 \\ 3 & enzo mori & stephan clark remix & 7:10 & none & enzo mori and stephan clark & 2006 & none \\ 4 & mhc club remix & 7:31 & none & mhc aka philip larsen and chis smith & 2006 & none \\ 5 & zloot remix & 4:36 & none & toni toolz & 2006 & none \\ 6 & music video & 3:58 & none & none & 2006 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & length \\ \midrule 0 & 7:24 \\ \bottomrule \end{tabular}

select length where version = 'axwell remix' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>version</th> <th>length</th> <th>album</th> <th>remixed by</th> <th>year</th> <th>comment</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>single version / radio edit</td> <td>3:39</td> <td>go - the very best of moby</td> <td>mhc aka philip larsen and chis smith</td> <td>2006</td> <td>remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one</td> </tr> <tr> <th>1</th> <td>extended remix</td> <td>6:48</td> <td>none</td> <td>mhc aka philip larsen and chis smith</td> <td>2006</td> <td>similar to the previous but longer</td> </tr> <tr> <th>2</th> <td>axwell remix</td> <td>7:24</td> <td>none</td> <td>axwell</td> <td>2006</td> <td>used in a scene in the 2008 movie 21</td> </tr> <tr> <th>3</th> <td>enzo mori & stephan clark remix</td> <td>7:10</td> <td>none</td> <td>enzo mori and stephan clark</td> <td>2006</td> <td>none</td> </tr> <tr> <th>4</th> <td>mhc club remix</td> <td>7:31</td> <td>none</td> <td>mhc aka philip larsen and chis smith</td> <td>2006</td> <td>none</td> </tr> <tr> <th>5</th> <td>zloot remix</td> <td>4:36</td> <td>none</td> <td>toni toolz</td> <td>2006</td> <td>none</td> </tr> <tr> <th>6</th> <td>music video</td> <td>3:58</td> <td>none</td> <td>none</td> <td>2006</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>length</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7:24</td> </tr> </tbody> </table>

select length where version = 'axwell remix' <table_name> : table | | version | length | album | remixed by | year | comment | |---:|:--------------------------------|:---------|:---------------------------|:-------------------------------------|-------:|:-------------------------------------------------------------------------------------------------------------------------------------------| | 0 | single version / radio edit | 3:39 | go - the very best of moby | mhc aka philip larsen and chis smith | 2006 | remixed version with dance sonorities, with english and french lyrics which alternate. this version is more rhythmic than the original one | | 1 | extended remix | 6:48 | none | mhc aka philip larsen and chis smith | 2006 | similar to the previous but longer | | 2 | axwell remix | 7:24 | none | axwell | 2006 | used in a scene in the 2008 movie 21 | | 3 | enzo mori & stephan clark remix | 7:10 | none | enzo mori and stephan clark | 2006 | none | | 4 | mhc club remix | 7:31 | none | mhc aka philip larsen and chis smith | 2006 | none | | 5 | zloot remix | 4:36 | none | toni toolz | 2006 | none | | 6 | music video | 3:58 | none | none | 2006 | none |

| | length | |---:|:---------| | 0 | 7:24 |

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select month where month = 'precipitation inches (mm)' col : month | jan | feb | mar | apr | may | jun | jul | aug | sep | oct | nov | dec | year row 1 : record high °f (°c) | 76 (24) | 86 (30) | 96 (36) | 96 (36) | 95 (35) | 104 (40) | 111 (44) | 109 (43) | 105 (41) | 96 (36) | 90 (32) | 78 (26) | 111 (44) row 2 : average high °f (°c) | 46.2 (7.9) | 50.4 (10.2) | 59.1 (15.1) | 68.7 (20.4) | 75.5 (24.2) | 83.5 (28.6) | 88.7 (31.5) | 89.4 (31.9) | 80.8 (27.1) | 70.3 (21.3) | 59.2 (15.1) | 48.0 (8.9) | 68.3 (20.2) row 3 : average low °f (°c) | 26.1 (-3.3) | 29.0 (-1.7) | 37.8 (3.2) | 46.9 (8.3) | 55.7 (13.2) | 64.1 (17.8) | 68.7 (20.4) | 67.7 (19.8) | 58.9 (14.9) | 47.6 (8.7) | 39.2 (4) | 28.1 (-2.2) | 47.5 (8.6) row 4 : record low °f (°c) | -23 (-31) | -24 (-31) | -11 (-24) | 18 (-8) | 28 (-2) | 41 (5) | 48 (9) | 44 (7) | 29 (-2) | 17 (-8) | 5 (-15) | -12 (-24) | -24 (-31) row 5 : precipitation inches (mm) | 1.99 (50.5) | 2.43 (61.7) | 3.54 (89.9) | 4.05 (102.9) | 4.99 (126.7) | 4.59 (116.6) | 3.18 (80.8) | 2.75 (69.9) | 4.43 (112.5) | 3.83 (97.3) | 4.19 (106.4) | 2.73 (69.3) | 42.7 (1,084.6) row 6 : snowfall inches (cm) | 1.6 (4.1) | 2.0 (5.1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | .7 (1.8) | 4.4 (11.2) row 7 : avg. precipitation days (≥ 0.01 in) | 5.4 | 6.6 | 8.2 | 9.0 | 11.2 | 8.9 | 7.0 | 6.4 | 7.6 | 7.9 | 7.0 | 6.3 | 91.4 row 8 : avg. snowy days (≥ 0.1 in) | .7 | .9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .5 | 2.3

col : month row 1 : precipitation inches (mm)

select month where month = 'precipitation inches (mm)' <table_name> : table \begin{tabular}{lllllllllllllll} \toprule & month & jan & feb & mar & apr & may & jun & jul & aug & sep & oct & nov & dec & year \\ \midrule 0 & record high °f (°c) & 76 (24) & 86 (30) & 96 (36) & 96 (36) & 95 (35) & 104 (40) & 111 (44) & 109 (43) & 105 (41) & 96 (36) & 90 (32) & 78 (26) & 111 (44) \\ 1 & average high °f (°c) & 46.2 (7.9) & 50.4 (10.2) & 59.1 (15.1) & 68.7 (20.4) & 75.5 (24.2) & 83.5 (28.6) & 88.7 (31.5) & 89.4 (31.9) & 80.8 (27.1) & 70.3 (21.3) & 59.2 (15.1) & 48.0 (8.9) & 68.3 (20.2) \\ 2 & average low °f (°c) & 26.1 (-3.3) & 29.0 (-1.7) & 37.8 (3.2) & 46.9 (8.3) & 55.7 (13.2) & 64.1 (17.8) & 68.7 (20.4) & 67.7 (19.8) & 58.9 (14.9) & 47.6 (8.7) & 39.2 (4) & 28.1 (-2.2) & 47.5 (8.6) \\ 3 & record low °f (°c) & -23 (-31) & -24 (-31) & -11 (-24) & 18 (-8) & 28 (-2) & 41 (5) & 48 (9) & 44 (7) & 29 (-2) & 17 (-8) & 5 (-15) & -12 (-24) & -24 (-31) \\ 4 & precipitation inches (mm) & 1.99 (50.5) & 2.43 (61.7) & 3.54 (89.9) & 4.05 (102.9) & 4.99 (126.7) & 4.59 (116.6) & 3.18 (80.8) & 2.75 (69.9) & 4.43 (112.5) & 3.83 (97.3) & 4.19 (106.4) & 2.73 (69.3) & 42.7 (1,084.6) \\ 5 & snowfall inches (cm) & 1.6 (4.1) & 2.0 (5.1) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & 0 (0) & .7 (1.8) & 4.4 (11.2) \\ 6 & avg. precipitation days (≥ 0.01 in) & 5.4 & 6.6 & 8.2 & 9.0 & 11.2 & 8.9 & 7.0 & 6.4 & 7.6 & 7.9 & 7.0 & 6.3 & 91.4 \\ 7 & avg. snowy days (≥ 0.1 in) & .7 & .9 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & .5 & 2.3 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & month \\ \midrule 0 & precipitation inches (mm) \\ \bottomrule \end{tabular}

select month where month = 'precipitation inches (mm)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>month</th> <th>jan</th> <th>feb</th> <th>mar</th> <th>apr</th> <th>may</th> <th>jun</th> <th>jul</th> <th>aug</th> <th>sep</th> <th>oct</th> <th>nov</th> <th>dec</th> <th>year</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>record high °f (°c)</td> <td>76 (24)</td> <td>86 (30)</td> <td>96 (36)</td> <td>96 (36)</td> <td>95 (35)</td> <td>104 (40)</td> <td>111 (44)</td> <td>109 (43)</td> <td>105 (41)</td> <td>96 (36)</td> <td>90 (32)</td> <td>78 (26)</td> <td>111 (44)</td> </tr> <tr> <th>1</th> <td>average high °f (°c)</td> <td>46.2 (7.9)</td> <td>50.4 (10.2)</td> <td>59.1 (15.1)</td> <td>68.7 (20.4)</td> <td>75.5 (24.2)</td> <td>83.5 (28.6)</td> <td>88.7 (31.5)</td> <td>89.4 (31.9)</td> <td>80.8 (27.1)</td> <td>70.3 (21.3)</td> <td>59.2 (15.1)</td> <td>48.0 (8.9)</td> <td>68.3 (20.2)</td> </tr> <tr> <th>2</th> <td>average low °f (°c)</td> <td>26.1 (-3.3)</td> <td>29.0 (-1.7)</td> <td>37.8 (3.2)</td> <td>46.9 (8.3)</td> <td>55.7 (13.2)</td> <td>64.1 (17.8)</td> <td>68.7 (20.4)</td> <td>67.7 (19.8)</td> <td>58.9 (14.9)</td> <td>47.6 (8.7)</td> <td>39.2 (4)</td> <td>28.1 (-2.2)</td> <td>47.5 (8.6)</td> </tr> <tr> <th>3</th> <td>record low °f (°c)</td> <td>-23 (-31)</td> <td>-24 (-31)</td> <td>-11 (-24)</td> <td>18 (-8)</td> <td>28 (-2)</td> <td>41 (5)</td> <td>48 (9)</td> <td>44 (7)</td> <td>29 (-2)</td> <td>17 (-8)</td> <td>5 (-15)</td> <td>-12 (-24)</td> <td>-24 (-31)</td> </tr> <tr> <th>4</th> <td>precipitation inches (mm)</td> <td>1.99 (50.5)</td> <td>2.43 (61.7)</td> <td>3.54 (89.9)</td> <td>4.05 (102.9)</td> <td>4.99 (126.7)</td> <td>4.59 (116.6)</td> <td>3.18 (80.8)</td> <td>2.75 (69.9)</td> <td>4.43 (112.5)</td> <td>3.83 (97.3)</td> <td>4.19 (106.4)</td> <td>2.73 (69.3)</td> <td>42.7 (1,084.6)</td> </tr> <tr> <th>5</th> <td>snowfall inches (cm)</td> <td>1.6 (4.1)</td> <td>2.0 (5.1)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>0 (0)</td> <td>.7 (1.8)</td> <td>4.4 (11.2)</td> </tr> <tr> <th>6</th> <td>avg. precipitation days (≥ 0.01 in)</td> <td>5.4</td> <td>6.6</td> <td>8.2</td> <td>9.0</td> <td>11.2</td> <td>8.9</td> <td>7.0</td> <td>6.4</td> <td>7.6</td> <td>7.9</td> <td>7.0</td> <td>6.3</td> <td>91.4</td> </tr> <tr> <th>7</th> <td>avg. snowy days (≥ 0.1 in)</td> <td>.7</td> <td>.9</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>0</td> <td>.5</td> <td>2.3</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>month</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>precipitation inches (mm)</td> </tr> </tbody> </table>

select month where month = 'precipitation inches (mm)' <table_name> : table | | month | jan | feb | mar | apr | may | jun | jul | aug | sep | oct | nov | dec | year | |---:|:------------------------------------|:------------|:------------|:------------|:-------------|:-------------|:-------------|:------------|:------------|:-------------|:------------|:-------------|:------------|:---------------| | 0 | record high °f (°c) | 76 (24) | 86 (30) | 96 (36) | 96 (36) | 95 (35) | 104 (40) | 111 (44) | 109 (43) | 105 (41) | 96 (36) | 90 (32) | 78 (26) | 111 (44) | | 1 | average high °f (°c) | 46.2 (7.9) | 50.4 (10.2) | 59.1 (15.1) | 68.7 (20.4) | 75.5 (24.2) | 83.5 (28.6) | 88.7 (31.5) | 89.4 (31.9) | 80.8 (27.1) | 70.3 (21.3) | 59.2 (15.1) | 48.0 (8.9) | 68.3 (20.2) | | 2 | average low °f (°c) | 26.1 (-3.3) | 29.0 (-1.7) | 37.8 (3.2) | 46.9 (8.3) | 55.7 (13.2) | 64.1 (17.8) | 68.7 (20.4) | 67.7 (19.8) | 58.9 (14.9) | 47.6 (8.7) | 39.2 (4) | 28.1 (-2.2) | 47.5 (8.6) | | 3 | record low °f (°c) | -23 (-31) | -24 (-31) | -11 (-24) | 18 (-8) | 28 (-2) | 41 (5) | 48 (9) | 44 (7) | 29 (-2) | 17 (-8) | 5 (-15) | -12 (-24) | -24 (-31) | | 4 | precipitation inches (mm) | 1.99 (50.5) | 2.43 (61.7) | 3.54 (89.9) | 4.05 (102.9) | 4.99 (126.7) | 4.59 (116.6) | 3.18 (80.8) | 2.75 (69.9) | 4.43 (112.5) | 3.83 (97.3) | 4.19 (106.4) | 2.73 (69.3) | 42.7 (1,084.6) | | 5 | snowfall inches (cm) | 1.6 (4.1) | 2.0 (5.1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | .7 (1.8) | 4.4 (11.2) | | 6 | avg. precipitation days (≥ 0.01 in) | 5.4 | 6.6 | 8.2 | 9.0 | 11.2 | 8.9 | 7.0 | 6.4 | 7.6 | 7.9 | 7.0 | 6.3 | 91.4 | | 7 | avg. snowy days (≥ 0.1 in) | .7 | .9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .5 | 2.3 |

| | month | |---:|:--------------------------| | 0 | precipitation inches (mm) |

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select gold where rank = 5 col : rank | nation | gold | silver | bronze | total row 1 : 1 | cuba | 4 | 3 | 2 | 9 row 2 : 2 | canada | 4 | 2 | 1 | 7 row 3 : 3 | united states | 2 | 0 | 2 | 4 row 4 : 4 | mexico | 1 | 1 | 0 | 2 row 5 : 5 | ecuador | 1 | 0 | 0 | 1 row 6 : 6 | argentina | 0 | 4 | 3 | 7 row 7 : 7 | brazil | 0 | 2 | 2 | 4 row 8 : 8 | chile | 0 | 0 | 1 | 1 row 9 : 8 | venezuela | 0 | 0 | 1 | 1 row 10 : total | total | 12 | 12 | 12 | 36

col : gold row 1 : 1

select gold where rank = 5 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & cuba & 4 & 3 & 2 & 9 \\ 1 & 2 & canada & 4 & 2 & 1 & 7 \\ 2 & 3 & united states & 2 & 0 & 2 & 4 \\ 3 & 4 & mexico & 1 & 1 & 0 & 2 \\ 4 & 5 & ecuador & 1 & 0 & 0 & 1 \\ 5 & 6 & argentina & 0 & 4 & 3 & 7 \\ 6 & 7 & brazil & 0 & 2 & 2 & 4 \\ 7 & 8 & chile & 0 & 0 & 1 & 1 \\ 8 & 8 & venezuela & 0 & 0 & 1 & 1 \\ 9 & total & total & 12 & 12 & 12 & 36 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & gold \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select gold where rank = 5 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>cuba</td> <td>4</td> <td>3</td> <td>2</td> <td>9</td> </tr> <tr> <th>1</th> <td>2</td> <td>canada</td> <td>4</td> <td>2</td> <td>1</td> <td>7</td> </tr> <tr> <th>2</th> <td>3</td> <td>united states</td> <td>2</td> <td>0</td> <td>2</td> <td>4</td> </tr> <tr> <th>3</th> <td>4</td> <td>mexico</td> <td>1</td> <td>1</td> <td>0</td> <td>2</td> </tr> <tr> <th>4</th> <td>5</td> <td>ecuador</td> <td>1</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>5</th> <td>6</td> <td>argentina</td> <td>0</td> <td>4</td> <td>3</td> <td>7</td> </tr> <tr> <th>6</th> <td>7</td> <td>brazil</td> <td>0</td> <td>2</td> <td>2</td> <td>4</td> </tr> <tr> <th>7</th> <td>8</td> <td>chile</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>8</th> <td>8</td> <td>venezuela</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> <tr> <th>9</th> <td>total</td> <td>total</td> <td>12</td> <td>12</td> <td>12</td> <td>36</td> </tr> </tbody> </table>

select gold where rank = 5 <table_name> : table | | rank | nation | gold | silver | bronze | total | |---:|:-------|:--------------|-------:|---------:|---------:|--------:| | 0 | 1 | cuba | 4 | 3 | 2 | 9 | | 1 | 2 | canada | 4 | 2 | 1 | 7 | | 2 | 3 | united states | 2 | 0 | 2 | 4 | | 3 | 4 | mexico | 1 | 1 | 0 | 2 | | 4 | 5 | ecuador | 1 | 0 | 0 | 1 | | 5 | 6 | argentina | 0 | 4 | 3 | 7 | | 6 | 7 | brazil | 0 | 2 | 2 | 4 | | 7 | 8 | chile | 0 | 0 | 1 | 1 | | 8 | 8 | venezuela | 0 | 0 | 1 | 1 | | 9 | total | total | 12 | 12 | 12 | 36 |

| | gold | |---:|-------:| | 0 | 1 |

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select runners-up + runners-up where team = 'swindon town' col : team | winners | runners-up | years won | years runner-up row 1 : liverpool | 8 | 3 | 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 | 1978, 1987, 2005 row 2 : aston villa | 5 | 3 | 1961, 1975, 1977, 1994, 1996 | 1963, 1971, 2010 row 3 : manchester united | 4 | 4 | 1992, 2006, 2009, 2010 | 1983, 1991, 1994, 2003 row 4 : tottenham hotspur | 4 | 3 | 1971, 1973, 1999, 2008 | 1982, 2002, 2009 row 5 : chelsea | 4 | 2 | 1965, 1998, 2005, 2007 | 1972, 2008 row 6 : nottingham forest | 4 | 2 | 1978, 1979, 1989, 1990 | 1980, 1992 row 7 : leicester city | 3 | 2 | 1964, 1997, 2000 | 1965, 1999 row 8 : manchester city | 3 | 1 | 1970, 1976, 2014 | 1974 row 9 : arsenal | 2 | 5 | 1987, 1993 | 1968, 1969, 1988, 2007, 2011 row 10 : norwich city | 2 | 2 | 1962, 1985 | 1973, 1975 row 11 : birmingham city | 2 | 1 | 1963, 2011 | 2001 row 12 : wolverhampton wanderers | 2 | 0 | 1974, 1980 | none row 13 : west bromwich albion | 1 | 2 | 1966 | 1967, 1970 row 14 : middlesbrough | 1 | 2 | 2004 | 1997, 1998 row 15 : queens park rangers | 1 | 1 | 1967 | 1986 row 16 : leeds united | 1 | 1 | 1968 | 1996 row 17 : stoke city | 1 | 1 | 1972 | 1964 row 18 : luton town | 1 | 1 | 1988 | 1989 row 19 : sheffield wednesday | 1 | 1 | 1991 | 1993 row 20 : swindon town | 1 | 0 | 1969 | none row 21 : oxford united | 1 | 0 | 1986 | none row 22 : blackburn rovers | 1 | 0 | 2002 | none row 23 : swansea city | 1 | 0 | 2013 | none row 24 : west ham united | 0 | 2 | none | 1966, 1981 row 25 : everton | 0 | 2 | none | 1977, 1984 row 26 : bolton wanderers | 0 | 2 | none | 1995, 2004 row 27 : sunderland | 0 | 2 | none | 1985, 2014 row 28 : rotherham united | 0 | 1 | none | 1961 row 29 : rochdale | 0 | 1 | none | 1962 row 30 : newcastle united | 0 | 1 | none | 1976 row 31 : southampton | 0 | 1 | none | 1979 row 32 : oldham athletic | 0 | 1 | none | 1990 row 33 : tranmere rovers | 0 | 1 | none | 2000 row 34 : wigan athletic | 0 | 1 | none | 2006 row 35 : cardiff city | 0 | 1 | none | 2012 row 36 : bradford city | 0 | 1 | none | 2013

col : "runners-up + runners-up" row 1 : runners-up + runners-up

select runners-up + runners-up where team = 'swindon town' <table_name> : table \begin{tabular}{llllll} \toprule & team & winners & runners-up & years won & years runner-up \\ \midrule 0 & liverpool & 8 & 3 & 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 & 1978, 1987, 2005 \\ 1 & aston villa & 5 & 3 & 1961, 1975, 1977, 1994, 1996 & 1963, 1971, 2010 \\ 2 & manchester united & 4 & 4 & 1992, 2006, 2009, 2010 & 1983, 1991, 1994, 2003 \\ 3 & tottenham hotspur & 4 & 3 & 1971, 1973, 1999, 2008 & 1982, 2002, 2009 \\ 4 & chelsea & 4 & 2 & 1965, 1998, 2005, 2007 & 1972, 2008 \\ 5 & nottingham forest & 4 & 2 & 1978, 1979, 1989, 1990 & 1980, 1992 \\ 6 & leicester city & 3 & 2 & 1964, 1997, 2000 & 1965, 1999 \\ 7 & manchester city & 3 & 1 & 1970, 1976, 2014 & 1974 \\ 8 & arsenal & 2 & 5 & 1987, 1993 & 1968, 1969, 1988, 2007, 2011 \\ 9 & norwich city & 2 & 2 & 1962, 1985 & 1973, 1975 \\ 10 & birmingham city & 2 & 1 & 1963, 2011 & 2001 \\ 11 & wolverhampton wanderers & 2 & 0 & 1974, 1980 & none \\ 12 & west bromwich albion & 1 & 2 & 1966 & 1967, 1970 \\ 13 & middlesbrough & 1 & 2 & 2004 & 1997, 1998 \\ 14 & queens park rangers & 1 & 1 & 1967 & 1986 \\ 15 & leeds united & 1 & 1 & 1968 & 1996 \\ 16 & stoke city & 1 & 1 & 1972 & 1964 \\ 17 & luton town & 1 & 1 & 1988 & 1989 \\ 18 & sheffield wednesday & 1 & 1 & 1991 & 1993 \\ 19 & swindon town & 1 & 0 & 1969 & none \\ 20 & oxford united & 1 & 0 & 1986 & none \\ 21 & blackburn rovers & 1 & 0 & 2002 & none \\ 22 & swansea city & 1 & 0 & 2013 & none \\ 23 & west ham united & 0 & 2 & none & 1966, 1981 \\ 24 & everton & 0 & 2 & none & 1977, 1984 \\ 25 & bolton wanderers & 0 & 2 & none & 1995, 2004 \\ 26 & sunderland & 0 & 2 & none & 1985, 2014 \\ 27 & rotherham united & 0 & 1 & none & 1961 \\ 28 & rochdale & 0 & 1 & none & 1962 \\ 29 & newcastle united & 0 & 1 & none & 1976 \\ 30 & southampton & 0 & 1 & none & 1979 \\ 31 & oldham athletic & 0 & 1 & none & 1990 \\ 32 & tranmere rovers & 0 & 1 & none & 2000 \\ 33 & wigan athletic & 0 & 1 & none & 2006 \\ 34 & cardiff city & 0 & 1 & none & 2012 \\ 35 & bradford city & 0 & 1 & none & 2013 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & "runners-up + runners-up" \\ \midrule 0 & runners-up + runners-up \\ \bottomrule \end{tabular}

select runners-up + runners-up where team = 'swindon town' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>winners</th> <th>runners-up</th> <th>years won</th> <th>years runner-up</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>liverpool</td> <td>8</td> <td>3</td> <td>1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012</td> <td>1978, 1987, 2005</td> </tr> <tr> <th>1</th> <td>aston villa</td> <td>5</td> <td>3</td> <td>1961, 1975, 1977, 1994, 1996</td> <td>1963, 1971, 2010</td> </tr> <tr> <th>2</th> <td>manchester united</td> <td>4</td> <td>4</td> <td>1992, 2006, 2009, 2010</td> <td>1983, 1991, 1994, 2003</td> </tr> <tr> <th>3</th> <td>tottenham hotspur</td> <td>4</td> <td>3</td> <td>1971, 1973, 1999, 2008</td> <td>1982, 2002, 2009</td> </tr> <tr> <th>4</th> <td>chelsea</td> <td>4</td> <td>2</td> <td>1965, 1998, 2005, 2007</td> <td>1972, 2008</td> </tr> <tr> <th>5</th> <td>nottingham forest</td> <td>4</td> <td>2</td> <td>1978, 1979, 1989, 1990</td> <td>1980, 1992</td> </tr> <tr> <th>6</th> <td>leicester city</td> <td>3</td> <td>2</td> <td>1964, 1997, 2000</td> <td>1965, 1999</td> </tr> <tr> <th>7</th> <td>manchester city</td> <td>3</td> <td>1</td> <td>1970, 1976, 2014</td> <td>1974</td> </tr> <tr> <th>8</th> <td>arsenal</td> <td>2</td> <td>5</td> <td>1987, 1993</td> <td>1968, 1969, 1988, 2007, 2011</td> </tr> <tr> <th>9</th> <td>norwich city</td> <td>2</td> <td>2</td> <td>1962, 1985</td> <td>1973, 1975</td> </tr> <tr> <th>10</th> <td>birmingham city</td> <td>2</td> <td>1</td> <td>1963, 2011</td> <td>2001</td> </tr> <tr> <th>11</th> <td>wolverhampton wanderers</td> <td>2</td> <td>0</td> <td>1974, 1980</td> <td>none</td> </tr> <tr> <th>12</th> <td>west bromwich albion</td> <td>1</td> <td>2</td> <td>1966</td> <td>1967, 1970</td> </tr> <tr> <th>13</th> <td>middlesbrough</td> <td>1</td> <td>2</td> <td>2004</td> <td>1997, 1998</td> </tr> <tr> <th>14</th> <td>queens park rangers</td> <td>1</td> <td>1</td> <td>1967</td> <td>1986</td> </tr> <tr> <th>15</th> <td>leeds united</td> <td>1</td> <td>1</td> <td>1968</td> <td>1996</td> </tr> <tr> <th>16</th> <td>stoke city</td> <td>1</td> <td>1</td> <td>1972</td> <td>1964</td> </tr> <tr> <th>17</th> <td>luton town</td> <td>1</td> <td>1</td> <td>1988</td> <td>1989</td> </tr> <tr> <th>18</th> <td>sheffield wednesday</td> <td>1</td> <td>1</td> <td>1991</td> <td>1993</td> </tr> <tr> <th>19</th> <td>swindon town</td> <td>1</td> <td>0</td> <td>1969</td> <td>none</td> </tr> <tr> <th>20</th> <td>oxford united</td> <td>1</td> <td>0</td> <td>1986</td> <td>none</td> </tr> <tr> <th>21</th> <td>blackburn rovers</td> <td>1</td> <td>0</td> <td>2002</td> <td>none</td> </tr> <tr> <th>22</th> <td>swansea city</td> <td>1</td> <td>0</td> <td>2013</td> <td>none</td> </tr> <tr> <th>23</th> <td>west ham united</td> <td>0</td> <td>2</td> <td>none</td> <td>1966, 1981</td> </tr> <tr> <th>24</th> <td>everton</td> <td>0</td> <td>2</td> <td>none</td> <td>1977, 1984</td> </tr> <tr> <th>25</th> <td>bolton wanderers</td> <td>0</td> <td>2</td> <td>none</td> <td>1995, 2004</td> </tr> <tr> <th>26</th> <td>sunderland</td> <td>0</td> <td>2</td> <td>none</td> <td>1985, 2014</td> </tr> <tr> <th>27</th> <td>rotherham united</td> <td>0</td> <td>1</td> <td>none</td> <td>1961</td> </tr> <tr> <th>28</th> <td>rochdale</td> <td>0</td> <td>1</td> <td>none</td> <td>1962</td> </tr> <tr> <th>29</th> <td>newcastle united</td> <td>0</td> <td>1</td> <td>none</td> <td>1976</td> </tr> <tr> <th>30</th> <td>southampton</td> <td>0</td> <td>1</td> <td>none</td> <td>1979</td> </tr> <tr> <th>31</th> <td>oldham athletic</td> <td>0</td> <td>1</td> <td>none</td> <td>1990</td> </tr> <tr> <th>32</th> <td>tranmere rovers</td> <td>0</td> <td>1</td> <td>none</td> <td>2000</td> </tr> <tr> <th>33</th> <td>wigan athletic</td> <td>0</td> <td>1</td> <td>none</td> <td>2006</td> </tr> <tr> <th>34</th> <td>cardiff city</td> <td>0</td> <td>1</td> <td>none</td> <td>2012</td> </tr> <tr> <th>35</th> <td>bradford city</td> <td>0</td> <td>1</td> <td>none</td> <td>2013</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"runners-up + runners-up"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>runners-up + runners-up</td> </tr> </tbody> </table>

select runners-up + runners-up where team = 'swindon town' <table_name> : table | | team | winners | runners-up | years won | years runner-up | |---:|:------------------------|----------:|-------------:|:-----------------------------------------------|:-----------------------------| | 0 | liverpool | 8 | 3 | 1981, 1982, 1983, 1984, 1995, 2001, 2003, 2012 | 1978, 1987, 2005 | | 1 | aston villa | 5 | 3 | 1961, 1975, 1977, 1994, 1996 | 1963, 1971, 2010 | | 2 | manchester united | 4 | 4 | 1992, 2006, 2009, 2010 | 1983, 1991, 1994, 2003 | | 3 | tottenham hotspur | 4 | 3 | 1971, 1973, 1999, 2008 | 1982, 2002, 2009 | | 4 | chelsea | 4 | 2 | 1965, 1998, 2005, 2007 | 1972, 2008 | | 5 | nottingham forest | 4 | 2 | 1978, 1979, 1989, 1990 | 1980, 1992 | | 6 | leicester city | 3 | 2 | 1964, 1997, 2000 | 1965, 1999 | | 7 | manchester city | 3 | 1 | 1970, 1976, 2014 | 1974 | | 8 | arsenal | 2 | 5 | 1987, 1993 | 1968, 1969, 1988, 2007, 2011 | | 9 | norwich city | 2 | 2 | 1962, 1985 | 1973, 1975 | | 10 | birmingham city | 2 | 1 | 1963, 2011 | 2001 | | 11 | wolverhampton wanderers | 2 | 0 | 1974, 1980 | none | | 12 | west bromwich albion | 1 | 2 | 1966 | 1967, 1970 | | 13 | middlesbrough | 1 | 2 | 2004 | 1997, 1998 | | 14 | queens park rangers | 1 | 1 | 1967 | 1986 | | 15 | leeds united | 1 | 1 | 1968 | 1996 | | 16 | stoke city | 1 | 1 | 1972 | 1964 | | 17 | luton town | 1 | 1 | 1988 | 1989 | | 18 | sheffield wednesday | 1 | 1 | 1991 | 1993 | | 19 | swindon town | 1 | 0 | 1969 | none | | 20 | oxford united | 1 | 0 | 1986 | none | | 21 | blackburn rovers | 1 | 0 | 2002 | none | | 22 | swansea city | 1 | 0 | 2013 | none | | 23 | west ham united | 0 | 2 | none | 1966, 1981 | | 24 | everton | 0 | 2 | none | 1977, 1984 | | 25 | bolton wanderers | 0 | 2 | none | 1995, 2004 | | 26 | sunderland | 0 | 2 | none | 1985, 2014 | | 27 | rotherham united | 0 | 1 | none | 1961 | | 28 | rochdale | 0 | 1 | none | 1962 | | 29 | newcastle united | 0 | 1 | none | 1976 | | 30 | southampton | 0 | 1 | none | 1979 | | 31 | oldham athletic | 0 | 1 | none | 1990 | | 32 | tranmere rovers | 0 | 1 | none | 2000 | | 33 | wigan athletic | 0 | 1 | none | 2006 | | 34 | cardiff city | 0 | 1 | none | 2012 | | 35 | bradford city | 0 | 1 | none | 2013 |

| | "runners-up + runners-up" | |---:|:----------------------------| | 0 | runners-up + runners-up |

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col : year row 1 : 2006

select year where role = 'scott' <table_name> : table \begin{tabular}{lllll} \toprule & year & title & role & notes \\ \midrule 0 & 1999 & bob rizzo's simply funk with suzanne & himself & as matthew j. morrison \\ 1 & 2003 & marci x & boyz r us & as matthew j. morrison \\ 2 & 2005 & once upon a mattress & sir harry & none \\ 3 & 2006 & blinders & scott & none \\ 4 & 2007 & music and lyrics & ray & none \\ 5 & 2007 & dan in real life & policeman & none \\ 6 & 2007 & i think i love my wife & salesman #2 & none \\ 7 & 2011 & the muppets & mahna mahna host & none \\ 8 & 2012 & what to expect when you're expecting & evan & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 2006 \\ \bottomrule \end{tabular}

select year where role = 'scott' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>title</th> <th>role</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>bob rizzo's simply funk with suzanne</td> <td>himself</td> <td>as matthew j. morrison</td> </tr> <tr> <th>1</th> <td>2003</td> <td>marci x</td> <td>boyz r us</td> <td>as matthew j. morrison</td> </tr> <tr> <th>2</th> <td>2005</td> <td>once upon a mattress</td> <td>sir harry</td> <td>none</td> </tr> <tr> <th>3</th> <td>2006</td> <td>blinders</td> <td>scott</td> <td>none</td> </tr> <tr> <th>4</th> <td>2007</td> <td>music and lyrics</td> <td>ray</td> <td>none</td> </tr> <tr> <th>5</th> <td>2007</td> <td>dan in real life</td> <td>policeman</td> <td>none</td> </tr> <tr> <th>6</th> <td>2007</td> <td>i think i love my wife</td> <td>salesman #2</td> <td>none</td> </tr> <tr> <th>7</th> <td>2011</td> <td>the muppets</td> <td>mahna mahna host</td> <td>none</td> </tr> <tr> <th>8</th> <td>2012</td> <td>what to expect when you're expecting</td> <td>evan</td> <td>none</td> </tr> </tbody> </table>

select year where role = 'scott' <table_name> : table | | year | title | role | notes | |---:|-------:|:-------------------------------------|:-----------------|:-----------------------| | 0 | 1999 | bob rizzo's simply funk with suzanne | himself | as matthew j. morrison | | 1 | 2003 | marci x | boyz r us | as matthew j. morrison | | 2 | 2005 | once upon a mattress | sir harry | none | | 3 | 2006 | blinders | scott | none | | 4 | 2007 | music and lyrics | ray | none | | 5 | 2007 | dan in real life | policeman | none | | 6 | 2007 | i think i love my wife | salesman #2 | none | | 7 | 2011 | the muppets | mahna mahna host | none | | 8 | 2012 | what to expect when you're expecting | evan | none |

| | year | |---:|-------:| | 0 | 2006 |

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select count ( result ) where date = 'none' col : week | date | tv time | opponent | result | attendance | bye row 1 : 1 | september 6, 1998 | fox 1:05 pm mt | at dallas cowboys | l 38-10 | 63602 | 0 row 2 : 2 | september 13, 1998 | fox 1:15 pm mt | at seattle seahawks | l 33-14 | 57678 | 0 row 3 : 3 | september 20, 1998 | espn 5:15 pm mt | philadelphia eagles | w 17-3 | 39782 | 0 row 4 : 4 | september 27, 1998 | fox 10:00 am mt | at st. louis rams | w 20-17 | 55832 | 0 row 5 : 5 | october 4, 1998 | cbs 1:05 pm mt | oakland raiders | l 23-20 | 53,24 | 0 row 6 : 6 | october 11, 1998 | fox 1:05 pm mt | chicago bears | w 20-7 | 50495 | 0 row 7 : 7 | october 18, 1998 | fox 10:00 am mt | at new york giants | l 34-7 | 70456 | 0 row 8 : 8 | none | none | none | none | none | 1 row 9 : 9 | november 1, 1998 | fox 11:00 am mt | at detroit lions | w 17-15 | 66087 | 0 row 10 : 10 | november 8, 1998 | fox 2:15 pm mt | washington redskins | w 29-27 | 45,95 | 0 row 11 : 11 | november 15, 1998 | fox 2:15 pm mt | dallas cowboys | l 35-28 | 71,67 | 0 row 12 : 12 | november 22, 1998 | fox 11:00 am mt | at washington redskins | w 45-42 | 63435 | 0 row 13 : 13 | november 29, 1998 | fox 11:00 am mt | at kansas city chiefs | l 34-24 | 69613 | 0 row 14 : 14 | december 6, 1998 | fox 2:15 pm mt | new york giants | l 23-19 | 46128 | 0 row 15 : 15 | december 13, 1998 | fox 11:00 am mt | at philadelphia eagles | w 20-17 | 62176 | 0 row 16 : 16 | december 20, 1998 | fox 2:05 pm mt | new orleans saints | w 19-17 | 51617 | 0 row 17 : 17 | december 27, 1998 | cbs 2:05 pm mt | san diego chargers | w 16-13 | 71,67 | 0

col : count ( "result" ) row 1 : 1

select count ( result ) where date = 'none' <table_name> : table \begin{tabular}{llllllll} \toprule & week & date & tv time & opponent & result & attendance & bye \\ \midrule 0 & 1 & september 6, 1998 & fox 1:05 pm mt & at dallas cowboys & l 38-10 & 63602 & 0 \\ 1 & 2 & september 13, 1998 & fox 1:15 pm mt & at seattle seahawks & l 33-14 & 57678 & 0 \\ 2 & 3 & september 20, 1998 & espn 5:15 pm mt & philadelphia eagles & w 17-3 & 39782 & 0 \\ 3 & 4 & september 27, 1998 & fox 10:00 am mt & at st. louis rams & w 20-17 & 55832 & 0 \\ 4 & 5 & october 4, 1998 & cbs 1:05 pm mt & oakland raiders & l 23-20 & 53,24 & 0 \\ 5 & 6 & october 11, 1998 & fox 1:05 pm mt & chicago bears & w 20-7 & 50495 & 0 \\ 6 & 7 & october 18, 1998 & fox 10:00 am mt & at new york giants & l 34-7 & 70456 & 0 \\ 7 & 8 & none & none & none & none & none & 1 \\ 8 & 9 & november 1, 1998 & fox 11:00 am mt & at detroit lions & w 17-15 & 66087 & 0 \\ 9 & 10 & november 8, 1998 & fox 2:15 pm mt & washington redskins & w 29-27 & 45,95 & 0 \\ 10 & 11 & november 15, 1998 & fox 2:15 pm mt & dallas cowboys & l 35-28 & 71,67 & 0 \\ 11 & 12 & november 22, 1998 & fox 11:00 am mt & at washington redskins & w 45-42 & 63435 & 0 \\ 12 & 13 & november 29, 1998 & fox 11:00 am mt & at kansas city chiefs & l 34-24 & 69613 & 0 \\ 13 & 14 & december 6, 1998 & fox 2:15 pm mt & new york giants & l 23-19 & 46128 & 0 \\ 14 & 15 & december 13, 1998 & fox 11:00 am mt & at philadelphia eagles & w 20-17 & 62176 & 0 \\ 15 & 16 & december 20, 1998 & fox 2:05 pm mt & new orleans saints & w 19-17 & 51617 & 0 \\ 16 & 17 & december 27, 1998 & cbs 2:05 pm mt & san diego chargers & w 16-13 & 71,67 & 0 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "result" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( result ) where date = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>week</th> <th>date</th> <th>tv time</th> <th>opponent</th> <th>result</th> <th>attendance</th> <th>bye</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>september 6, 1998</td> <td>fox 1:05 pm mt</td> <td>at dallas cowboys</td> <td>l 38-10</td> <td>63602</td> <td>0</td> </tr> <tr> <th>1</th> <td>2</td> <td>september 13, 1998</td> <td>fox 1:15 pm mt</td> <td>at seattle seahawks</td> <td>l 33-14</td> <td>57678</td> <td>0</td> </tr> <tr> <th>2</th> <td>3</td> <td>september 20, 1998</td> <td>espn 5:15 pm mt</td> <td>philadelphia eagles</td> <td>w 17-3</td> <td>39782</td> <td>0</td> </tr> <tr> <th>3</th> <td>4</td> <td>september 27, 1998</td> <td>fox 10:00 am mt</td> <td>at st. louis rams</td> <td>w 20-17</td> <td>55832</td> <td>0</td> </tr> <tr> <th>4</th> <td>5</td> <td>october 4, 1998</td> <td>cbs 1:05 pm mt</td> <td>oakland raiders</td> <td>l 23-20</td> <td>53,24</td> <td>0</td> </tr> <tr> <th>5</th> <td>6</td> <td>october 11, 1998</td> <td>fox 1:05 pm mt</td> <td>chicago bears</td> <td>w 20-7</td> <td>50495</td> <td>0</td> </tr> <tr> <th>6</th> <td>7</td> <td>october 18, 1998</td> <td>fox 10:00 am mt</td> <td>at new york giants</td> <td>l 34-7</td> <td>70456</td> <td>0</td> </tr> <tr> <th>7</th> <td>8</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>none</td> <td>1</td> </tr> <tr> <th>8</th> <td>9</td> <td>november 1, 1998</td> <td>fox 11:00 am mt</td> <td>at detroit lions</td> <td>w 17-15</td> <td>66087</td> <td>0</td> </tr> <tr> <th>9</th> <td>10</td> <td>november 8, 1998</td> <td>fox 2:15 pm mt</td> <td>washington redskins</td> <td>w 29-27</td> <td>45,95</td> <td>0</td> </tr> <tr> <th>10</th> <td>11</td> <td>november 15, 1998</td> <td>fox 2:15 pm mt</td> <td>dallas cowboys</td> <td>l 35-28</td> <td>71,67</td> <td>0</td> </tr> <tr> <th>11</th> <td>12</td> <td>november 22, 1998</td> <td>fox 11:00 am mt</td> <td>at washington redskins</td> <td>w 45-42</td> <td>63435</td> <td>0</td> </tr> <tr> <th>12</th> <td>13</td> <td>november 29, 1998</td> <td>fox 11:00 am mt</td> <td>at kansas city chiefs</td> <td>l 34-24</td> <td>69613</td> <td>0</td> </tr> <tr> <th>13</th> <td>14</td> <td>december 6, 1998</td> <td>fox 2:15 pm mt</td> <td>new york giants</td> <td>l 23-19</td> <td>46128</td> <td>0</td> </tr> <tr> <th>14</th> <td>15</td> <td>december 13, 1998</td> <td>fox 11:00 am mt</td> <td>at philadelphia eagles</td> <td>w 20-17</td> <td>62176</td> <td>0</td> </tr> <tr> <th>15</th> <td>16</td> <td>december 20, 1998</td> <td>fox 2:05 pm mt</td> <td>new orleans saints</td> <td>w 19-17</td> <td>51617</td> <td>0</td> </tr> <tr> <th>16</th> <td>17</td> <td>december 27, 1998</td> <td>cbs 2:05 pm mt</td> <td>san diego chargers</td> <td>w 16-13</td> <td>71,67</td> <td>0</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "result" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( result ) where date = 'none' <table_name> : table | | week | date | tv time | opponent | result | attendance | bye | |---:|-------:|:-------------------|:----------------|:-----------------------|:---------|:-------------|------:| | 0 | 1 | september 6, 1998 | fox 1:05 pm mt | at dallas cowboys | l 38-10 | 63602 | 0 | | 1 | 2 | september 13, 1998 | fox 1:15 pm mt | at seattle seahawks | l 33-14 | 57678 | 0 | | 2 | 3 | september 20, 1998 | espn 5:15 pm mt | philadelphia eagles | w 17-3 | 39782 | 0 | | 3 | 4 | september 27, 1998 | fox 10:00 am mt | at st. louis rams | w 20-17 | 55832 | 0 | | 4 | 5 | october 4, 1998 | cbs 1:05 pm mt | oakland raiders | l 23-20 | 53,24 | 0 | | 5 | 6 | october 11, 1998 | fox 1:05 pm mt | chicago bears | w 20-7 | 50495 | 0 | | 6 | 7 | october 18, 1998 | fox 10:00 am mt | at new york giants | l 34-7 | 70456 | 0 | | 7 | 8 | none | none | none | none | none | 1 | | 8 | 9 | november 1, 1998 | fox 11:00 am mt | at detroit lions | w 17-15 | 66087 | 0 | | 9 | 10 | november 8, 1998 | fox 2:15 pm mt | washington redskins | w 29-27 | 45,95 | 0 | | 10 | 11 | november 15, 1998 | fox 2:15 pm mt | dallas cowboys | l 35-28 | 71,67 | 0 | | 11 | 12 | november 22, 1998 | fox 11:00 am mt | at washington redskins | w 45-42 | 63435 | 0 | | 12 | 13 | november 29, 1998 | fox 11:00 am mt | at kansas city chiefs | l 34-24 | 69613 | 0 | | 13 | 14 | december 6, 1998 | fox 2:15 pm mt | new york giants | l 23-19 | 46128 | 0 | | 14 | 15 | december 13, 1998 | fox 11:00 am mt | at philadelphia eagles | w 20-17 | 62176 | 0 | | 15 | 16 | december 20, 1998 | fox 2:05 pm mt | new orleans saints | w 19-17 | 51617 | 0 | | 16 | 17 | december 27, 1998 | cbs 2:05 pm mt | san diego chargers | w 16-13 | 71,67 | 0 |

| | count ( "result" ) | |---:|---------------------:| | 0 | 1 |

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col : year row 1 : 2008

select year where award = 'capital awards' <table_name> : table \begin{tabular}{llllll} \toprule & year & award & nominated work & category & result \\ \midrule 0 & 2007 & cosmopolitan ultimate woman of the year & leona lewis & newcomer of the year & won \\ 1 & 2007 & the record of the year & "bleeding love" & the record of the year & won \\ 2 & 2008 & capital awards & leona lewis & favourite uk female artist & won \\ 3 & 2008 & britain's best & leona lewis & music award & won \\ 4 & 2008 & newnownext awards & leona lewis & the kylie award: next international crossover & won \\ 5 & 2008 & glamour woman of the year awards & leona lewis & uk solo artist & won \\ 6 & 2008 & nickelodeon uk kids choice awards & "bleeding love" & favourite song & won \\ 7 & 2008 & uk music video awards & "bleeding love" & people's choice award & won \\ 8 & 2008 & bambi award & leona lewis & shooting star & won \\ 9 & 2008 & new music weekly awards & leona lewis & top 40 new artist of the year & won \\ 10 & 2008 & billboard 2008 year end award & leona lewis & best new artist & won \\ 11 & 2008 & vh1 video of the year & "bleeding love" & best video & won \\ 12 & 2008 & nme best album & "spirit" & best album & nominated \\ 13 & 2008 & peta & leona lewis & person of the year & won \\ 14 & 2009 & naacp image awards & leona lewis & outstanding new artist & nominated \\ 15 & 2009 & swiss music awards & leona lewis & best international newcomer & won \\ 16 & 2009 & japan gold disc awards & leona lewis & new artist of the year & won \\ 17 & 2009 & hito pop music awards & "bleeding love" & best western song & won \\ 18 & 2009 & peta - sexiest vegetarian alive awards & leona lewis & sexiest vegetarian celebrity 2009 & won \\ 19 & 2009 & apra awards & "bleeding love" & most played foreign work & won \\ 20 & 2009 & beffta awards & leona lewis & best female act & won \\ 21 & 2009 & cosmopolitan awards & leona lewis & ultimate music star & won \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 2008 \\ \bottomrule \end{tabular}

select year where award = 'capital awards' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>award</th> <th>nominated work</th> <th>category</th> <th>result</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2007</td> <td>cosmopolitan ultimate woman of the year</td> <td>leona lewis</td> <td>newcomer of the year</td> <td>won</td> </tr> <tr> <th>1</th> <td>2007</td> <td>the record of the year</td> <td>"bleeding love"</td> <td>the record of the year</td> <td>won</td> </tr> <tr> <th>2</th> <td>2008</td> <td>capital awards</td> <td>leona lewis</td> <td>favourite uk female artist</td> <td>won</td> </tr> <tr> <th>3</th> <td>2008</td> <td>britain's best</td> <td>leona lewis</td> <td>music award</td> <td>won</td> </tr> <tr> <th>4</th> <td>2008</td> <td>newnownext awards</td> <td>leona lewis</td> <td>the kylie award: next international crossover</td> <td>won</td> </tr> <tr> <th>5</th> <td>2008</td> <td>glamour woman of the year awards</td> <td>leona lewis</td> <td>uk solo artist</td> <td>won</td> </tr> <tr> <th>6</th> <td>2008</td> <td>nickelodeon uk kids choice awards</td> <td>"bleeding love"</td> <td>favourite song</td> <td>won</td> </tr> <tr> <th>7</th> <td>2008</td> <td>uk music video awards</td> <td>"bleeding love"</td> <td>people's choice award</td> <td>won</td> </tr> <tr> <th>8</th> <td>2008</td> <td>bambi award</td> <td>leona lewis</td> <td>shooting star</td> <td>won</td> </tr> <tr> <th>9</th> <td>2008</td> <td>new music weekly awards</td> <td>leona lewis</td> <td>top 40 new artist of the year</td> <td>won</td> </tr> <tr> <th>10</th> <td>2008</td> <td>billboard 2008 year end award</td> <td>leona lewis</td> <td>best new artist</td> <td>won</td> </tr> <tr> <th>11</th> <td>2008</td> <td>vh1 video of the year</td> <td>"bleeding love"</td> <td>best video</td> <td>won</td> </tr> <tr> <th>12</th> <td>2008</td> <td>nme best album</td> <td>"spirit"</td> <td>best album</td> <td>nominated</td> </tr> <tr> <th>13</th> <td>2008</td> <td>peta</td> <td>leona lewis</td> <td>person of the year</td> <td>won</td> </tr> <tr> <th>14</th> <td>2009</td> <td>naacp image awards</td> <td>leona lewis</td> <td>outstanding new artist</td> <td>nominated</td> </tr> <tr> <th>15</th> <td>2009</td> <td>swiss music awards</td> <td>leona lewis</td> <td>best international newcomer</td> <td>won</td> </tr> <tr> <th>16</th> <td>2009</td> <td>japan gold disc awards</td> <td>leona lewis</td> <td>new artist of the year</td> <td>won</td> </tr> <tr> <th>17</th> <td>2009</td> <td>hito pop music awards</td> <td>"bleeding love"</td> <td>best western song</td> <td>won</td> </tr> <tr> <th>18</th> <td>2009</td> <td>peta - sexiest vegetarian alive awards</td> <td>leona lewis</td> <td>sexiest vegetarian celebrity 2009</td> <td>won</td> </tr> <tr> <th>19</th> <td>2009</td> <td>apra awards</td> <td>"bleeding love"</td> <td>most played foreign work</td> <td>won</td> </tr> <tr> <th>20</th> <td>2009</td> <td>beffta awards</td> <td>leona lewis</td> <td>best female act</td> <td>won</td> </tr> <tr> <th>21</th> <td>2009</td> <td>cosmopolitan awards</td> <td>leona lewis</td> <td>ultimate music star</td> <td>won</td> </tr> </tbody> </table>

select year where award = 'capital awards' <table_name> : table | | year | award | nominated work | category | result | |---:|-------:|:----------------------------------------|:-----------------|:----------------------------------------------|:----------| | 0 | 2007 | cosmopolitan ultimate woman of the year | leona lewis | newcomer of the year | won | | 1 | 2007 | the record of the year | "bleeding love" | the record of the year | won | | 2 | 2008 | capital awards | leona lewis | favourite uk female artist | won | | 3 | 2008 | britain's best | leona lewis | music award | won | | 4 | 2008 | newnownext awards | leona lewis | the kylie award: next international crossover | won | | 5 | 2008 | glamour woman of the year awards | leona lewis | uk solo artist | won | | 6 | 2008 | nickelodeon uk kids choice awards | "bleeding love" | favourite song | won | | 7 | 2008 | uk music video awards | "bleeding love" | people's choice award | won | | 8 | 2008 | bambi award | leona lewis | shooting star | won | | 9 | 2008 | new music weekly awards | leona lewis | top 40 new artist of the year | won | | 10 | 2008 | billboard 2008 year end award | leona lewis | best new artist | won | | 11 | 2008 | vh1 video of the year | "bleeding love" | best video | won | | 12 | 2008 | nme best album | "spirit" | best album | nominated | | 13 | 2008 | peta | leona lewis | person of the year | won | | 14 | 2009 | naacp image awards | leona lewis | outstanding new artist | nominated | | 15 | 2009 | swiss music awards | leona lewis | best international newcomer | won | | 16 | 2009 | japan gold disc awards | leona lewis | new artist of the year | won | | 17 | 2009 | hito pop music awards | "bleeding love" | best western song | won | | 18 | 2009 | peta - sexiest vegetarian alive awards | leona lewis | sexiest vegetarian celebrity 2009 | won | | 19 | 2009 | apra awards | "bleeding love" | most played foreign work | won | | 20 | 2009 | beffta awards | leona lewis | best female act | won | | 21 | 2009 | cosmopolitan awards | leona lewis | ultimate music star | won |

| | year | |---:|-------:| | 0 | 2008 |

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select count ( * ) where player = 336 col : place | player | country | score | to par | money ($) row 1 : 1 | ralph guldahl | united states | 72-68-70-69=279 | -9 | 1,500 row 2 : 2 | sam snead | united states | 70-70-72-68=280 | -8 | 800 row 3 : t3 | billy burke | united states | 69-72-71-70=282 | -6 | 550 row 4 : t3 | lawson little | united states | 72-72-68-70=282 | -6 | 550 row 5 : 5 | gene sarazen | united states | 73-66-72-72=283 | -5 | 400 row 6 : 6 | craig wood | united states | 72-73-71-68=284 | -4 | 300 row 7 : 7 | byron nelson | united states | 71-69-72-75=287 | -1 | 250 row 8 : 8 | henry picard | united states | 71-71-76-71=289 | 1 | 175 row 9 : 9 | ben hogan | united states | 75-71-72-72=290 | 2 | 125 row 10 : t10 | ed dudley | united states | 75-75-69-72=291 | 3 | 100 row 11 : t10 | toney penna | united states | 72-75-72-72=291 | 3 | 100

col : count ( "*" ) row 1 : 0

select count ( * ) where player = 336 <table_name> : table \begin{tabular}{lllllll} \toprule & place & player & country & score & to par & money ($) \\ \midrule 0 & 1 & ralph guldahl & united states & 72-68-70-69=279 & -9 & 1,500 \\ 1 & 2 & sam snead & united states & 70-70-72-68=280 & -8 & 800 \\ 2 & t3 & billy burke & united states & 69-72-71-70=282 & -6 & 550 \\ 3 & t3 & lawson little & united states & 72-72-68-70=282 & -6 & 550 \\ 4 & 5 & gene sarazen & united states & 73-66-72-72=283 & -5 & 400 \\ 5 & 6 & craig wood & united states & 72-73-71-68=284 & -4 & 300 \\ 6 & 7 & byron nelson & united states & 71-69-72-75=287 & -1 & 250 \\ 7 & 8 & henry picard & united states & 71-71-76-71=289 & 1 & 175 \\ 8 & 9 & ben hogan & united states & 75-71-72-72=290 & 2 & 125 \\ 9 & t10 & ed dudley & united states & 75-75-69-72=291 & 3 & 100 \\ 10 & t10 & toney penna & united states & 72-75-72-72=291 & 3 & 100 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select count ( * ) where player = 336 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> <th>player</th> <th>country</th> <th>score</th> <th>to par</th> <th>money ($)</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>ralph guldahl</td> <td>united states</td> <td>72-68-70-69=279</td> <td>-9</td> <td>1,500</td> </tr> <tr> <th>1</th> <td>2</td> <td>sam snead</td> <td>united states</td> <td>70-70-72-68=280</td> <td>-8</td> <td>800</td> </tr> <tr> <th>2</th> <td>t3</td> <td>billy burke</td> <td>united states</td> <td>69-72-71-70=282</td> <td>-6</td> <td>550</td> </tr> <tr> <th>3</th> <td>t3</td> <td>lawson little</td> <td>united states</td> <td>72-72-68-70=282</td> <td>-6</td> <td>550</td> </tr> <tr> <th>4</th> <td>5</td> <td>gene sarazen</td> <td>united states</td> <td>73-66-72-72=283</td> <td>-5</td> <td>400</td> </tr> <tr> <th>5</th> <td>6</td> <td>craig wood</td> <td>united states</td> <td>72-73-71-68=284</td> <td>-4</td> <td>300</td> </tr> <tr> <th>6</th> <td>7</td> <td>byron nelson</td> <td>united states</td> <td>71-69-72-75=287</td> <td>-1</td> <td>250</td> </tr> <tr> <th>7</th> <td>8</td> <td>henry picard</td> <td>united states</td> <td>71-71-76-71=289</td> <td>1</td> <td>175</td> </tr> <tr> <th>8</th> <td>9</td> <td>ben hogan</td> <td>united states</td> <td>75-71-72-72=290</td> <td>2</td> <td>125</td> </tr> <tr> <th>9</th> <td>t10</td> <td>ed dudley</td> <td>united states</td> <td>75-75-69-72=291</td> <td>3</td> <td>100</td> </tr> <tr> <th>10</th> <td>t10</td> <td>toney penna</td> <td>united states</td> <td>72-75-72-72=291</td> <td>3</td> <td>100</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select count ( * ) where player = 336 <table_name> : table | | place | player | country | score | to par | money ($) | |---:|:--------|:--------------|:--------------|:----------------|---------:|:------------| | 0 | 1 | ralph guldahl | united states | 72-68-70-69=279 | -9 | 1,500 | | 1 | 2 | sam snead | united states | 70-70-72-68=280 | -8 | 800 | | 2 | t3 | billy burke | united states | 69-72-71-70=282 | -6 | 550 | | 3 | t3 | lawson little | united states | 72-72-68-70=282 | -6 | 550 | | 4 | 5 | gene sarazen | united states | 73-66-72-72=283 | -5 | 400 | | 5 | 6 | craig wood | united states | 72-73-71-68=284 | -4 | 300 | | 6 | 7 | byron nelson | united states | 71-69-72-75=287 | -1 | 250 | | 7 | 8 | henry picard | united states | 71-71-76-71=289 | 1 | 175 | | 8 | 9 | ben hogan | united states | 75-71-72-72=290 | 2 | 125 | | 9 | t10 | ed dudley | united states | 75-75-69-72=291 | 3 | 100 | | 10 | t10 | toney penna | united states | 72-75-72-72=291 | 3 | 100 |

| | count ( "*" ) | |---:|----------------:| | 0 | 0 |

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col : venue row 1 : city stadium, lida

select venue where capacity = 4000 <table_name> : table \begin{tabular}{llllll} \toprule & team & location & venue & capacity & position in 1993-94 \\ \midrule 0 & dinamo minsk & minsk & dinamo, minsk & 41040 & 1 \\ 1 & dinamo-93 & minsk & dinamo, minsk & 41040 & 2 \\ 2 & dvina & vitebsk & central, vitebsk & 8300 & 3 \\ 3 & dnepr & mogilev & spartak, mogilev & 11200 & 4 \\ 4 & bobruisk & bobruisk & spartak, bobruisk & 3550 & 5 \\ 5 & torpedo minsk & minsk & torpedo, minsk & 5200 & 6 \\ 6 & shinnik & bobruisk & spartak, bobruisk & 3550 & 7 \\ 7 & dinamo brest & brest & dinamo, brest & 10080 & 8 \\ 8 & molodechno & molodechno & city stadium, molodechno & 5500 & 9 \\ 9 & lokomotiv & vitebsk & central, vitebsk & 8300 & 10 \\ 10 & neman & grodno & neman & 6300 & 11 \\ 11 & vedrich & rechytsa & central, rechytsa & 3550 & 12 \\ 12 & shakhtyor & soligorsk & stroitel & 5000 & 13 \\ 13 & torpedo mogilev & mogilev & torpedo, mogilev & 3500 & 14 \\ 14 & gomselmash & gomel & central, gomel & 11800 & 15 \\ 15 & obuvshchik & lida & city stadium, lida & 4000 & first league, 1 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & venue \\ \midrule 0 & city stadium, lida \\ \bottomrule \end{tabular}

select venue where capacity = 4000 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>team</th> <th>location</th> <th>venue</th> <th>capacity</th> <th>position in 1993-94</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>dinamo minsk</td> <td>minsk</td> <td>dinamo, minsk</td> <td>41040</td> <td>1</td> </tr> <tr> <th>1</th> <td>dinamo-93</td> <td>minsk</td> <td>dinamo, minsk</td> <td>41040</td> <td>2</td> </tr> <tr> <th>2</th> <td>dvina</td> <td>vitebsk</td> <td>central, vitebsk</td> <td>8300</td> <td>3</td> </tr> <tr> <th>3</th> <td>dnepr</td> <td>mogilev</td> <td>spartak, mogilev</td> <td>11200</td> <td>4</td> </tr> <tr> <th>4</th> <td>bobruisk</td> <td>bobruisk</td> <td>spartak, bobruisk</td> <td>3550</td> <td>5</td> </tr> <tr> <th>5</th> <td>torpedo minsk</td> <td>minsk</td> <td>torpedo, minsk</td> <td>5200</td> <td>6</td> </tr> <tr> <th>6</th> <td>shinnik</td> <td>bobruisk</td> <td>spartak, bobruisk</td> <td>3550</td> <td>7</td> </tr> <tr> <th>7</th> <td>dinamo brest</td> <td>brest</td> <td>dinamo, brest</td> <td>10080</td> <td>8</td> </tr> <tr> <th>8</th> <td>molodechno</td> <td>molodechno</td> <td>city stadium, molodechno</td> <td>5500</td> <td>9</td> </tr> <tr> <th>9</th> <td>lokomotiv</td> <td>vitebsk</td> <td>central, vitebsk</td> <td>8300</td> <td>10</td> </tr> <tr> <th>10</th> <td>neman</td> <td>grodno</td> <td>neman</td> <td>6300</td> <td>11</td> </tr> <tr> <th>11</th> <td>vedrich</td> <td>rechytsa</td> <td>central, rechytsa</td> <td>3550</td> <td>12</td> </tr> <tr> <th>12</th> <td>shakhtyor</td> <td>soligorsk</td> <td>stroitel</td> <td>5000</td> <td>13</td> </tr> <tr> <th>13</th> <td>torpedo mogilev</td> <td>mogilev</td> <td>torpedo, mogilev</td> <td>3500</td> <td>14</td> </tr> <tr> <th>14</th> <td>gomselmash</td> <td>gomel</td> <td>central, gomel</td> <td>11800</td> <td>15</td> </tr> <tr> <th>15</th> <td>obuvshchik</td> <td>lida</td> <td>city stadium, lida</td> <td>4000</td> <td>first league, 1</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>venue</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>city stadium, lida</td> </tr> </tbody> </table>

select venue where capacity = 4000 <table_name> : table | | team | location | venue | capacity | position in 1993-94 | |---:|:----------------|:-----------|:-------------------------|-----------:|:----------------------| | 0 | dinamo minsk | minsk | dinamo, minsk | 41040 | 1 | | 1 | dinamo-93 | minsk | dinamo, minsk | 41040 | 2 | | 2 | dvina | vitebsk | central, vitebsk | 8300 | 3 | | 3 | dnepr | mogilev | spartak, mogilev | 11200 | 4 | | 4 | bobruisk | bobruisk | spartak, bobruisk | 3550 | 5 | | 5 | torpedo minsk | minsk | torpedo, minsk | 5200 | 6 | | 6 | shinnik | bobruisk | spartak, bobruisk | 3550 | 7 | | 7 | dinamo brest | brest | dinamo, brest | 10080 | 8 | | 8 | molodechno | molodechno | city stadium, molodechno | 5500 | 9 | | 9 | lokomotiv | vitebsk | central, vitebsk | 8300 | 10 | | 10 | neman | grodno | neman | 6300 | 11 | | 11 | vedrich | rechytsa | central, rechytsa | 3550 | 12 | | 12 | shakhtyor | soligorsk | stroitel | 5000 | 13 | | 13 | torpedo mogilev | mogilev | torpedo, mogilev | 3500 | 14 | | 14 | gomselmash | gomel | central, gomel | 11800 | 15 | | 15 | obuvshchik | lida | city stadium, lida | 4000 | first league, 1 |

| | venue | |---:|:-------------------| | 0 | city stadium, lida |

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select min ( attendance ) where venue = 'lambeau field' col : week | date | opponent | result | venue | attendance row 1 : 1 | 1978-09-03 00:00:00 | at detroit lions | w 13-7 | pontiac silverdome | 51187 row 2 : 2 | 1978-09-10 00:00:00 | new orleans saints | w 28-17 | milwaukee county stadium | 54336 row 3 : 3 | 1978-09-17 00:00:00 | oakland raiders | l 28-3 | lambeau field | 55903 row 4 : 4 | 1978-09-24 00:00:00 | at san diego chargers | w 24-3 | san diego stadium | 42755 row 5 : 5 | 1978-10-01 00:00:00 | detroit lions | w 35-14 | milwaukee county stadium | 54601 row 6 : 6 | 1978-10-08 00:00:00 | chicago bears | w 24-14 | lambeau field | 56267 row 7 : 7 | 1978-10-15 00:00:00 | seattle seahawks | w 45-28 | milwaukee county stadium | 52712 row 8 : 8 | 1978-10-22 00:00:00 | at minnesota vikings | l 21-7 | metropolitan stadium | 47411 row 9 : 9 | 1978-10-29 00:00:00 | tampa bay buccaneers | w 9-7 | lambeau field | 55108 row 10 : 10 | 1978-11-05 00:00:00 | at philadelphia eagles | l 10-3 | veterans stadium | 64214 row 11 : 11 | 1978-11-12 00:00:00 | dallas cowboys | l 42-14 | milwaukee county stadium | 55256 row 12 : 12 | 1978-11-19 00:00:00 | at denver broncos | l 16-3 | mile high stadium | 74965 row 13 : 13 | 1978-11-26 00:00:00 | minnesota vikings | t 10-10 (ot) | lambeau field | 51737 row 14 : 14 | 1978-12-03 00:00:00 | at tampa bay buccaneers | w 17-7 | tampa stadium | 67754 row 15 : 15 | 1978-12-10 00:00:00 | at chicago bears | l 14-0 | soldier field | 34306 row 16 : 16 | 1978-12-17 00:00:00 | at los angeles rams | l 31-14 | los angeles memorial coliseum | 42500

col : min ( "attendance" ) row 1 : 51737

select min ( attendance ) where venue = 'lambeau field' <table_name> : table \begin{tabular}{lllllll} \toprule & week & date & opponent & result & venue & attendance \\ \midrule 0 & 1 & 1978-09-03 00:00:00 & at detroit lions & w 13-7 & pontiac silverdome & 51187 \\ 1 & 2 & 1978-09-10 00:00:00 & new orleans saints & w 28-17 & milwaukee county stadium & 54336 \\ 2 & 3 & 1978-09-17 00:00:00 & oakland raiders & l 28-3 & lambeau field & 55903 \\ 3 & 4 & 1978-09-24 00:00:00 & at san diego chargers & w 24-3 & san diego stadium & 42755 \\ 4 & 5 & 1978-10-01 00:00:00 & detroit lions & w 35-14 & milwaukee county stadium & 54601 \\ 5 & 6 & 1978-10-08 00:00:00 & chicago bears & w 24-14 & lambeau field & 56267 \\ 6 & 7 & 1978-10-15 00:00:00 & seattle seahawks & w 45-28 & milwaukee county stadium & 52712 \\ 7 & 8 & 1978-10-22 00:00:00 & at minnesota vikings & l 21-7 & metropolitan stadium & 47411 \\ 8 & 9 & 1978-10-29 00:00:00 & tampa bay buccaneers & w 9-7 & lambeau field & 55108 \\ 9 & 10 & 1978-11-05 00:00:00 & at philadelphia eagles & l 10-3 & veterans stadium & 64214 \\ 10 & 11 & 1978-11-12 00:00:00 & dallas cowboys & l 42-14 & milwaukee county stadium & 55256 \\ 11 & 12 & 1978-11-19 00:00:00 & at denver broncos & l 16-3 & mile high stadium & 74965 \\ 12 & 13 & 1978-11-26 00:00:00 & minnesota vikings & t 10-10 (ot) & lambeau field & 51737 \\ 13 & 14 & 1978-12-03 00:00:00 & at tampa bay buccaneers & w 17-7 & tampa stadium & 67754 \\ 14 & 15 & 1978-12-10 00:00:00 & at chicago bears & l 14-0 & soldier field & 34306 \\ 15 & 16 & 1978-12-17 00:00:00 & at los angeles rams & l 31-14 & los angeles memorial coliseum & 42500 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & min ( "attendance" ) \\ \midrule 0 & 51737 \\ \bottomrule \end{tabular}

select min ( attendance ) where venue = 'lambeau field' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>week</th> <th>date</th> <th>opponent</th> <th>result</th> <th>venue</th> <th>attendance</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>1978-09-03 00:00:00</td> <td>at detroit lions</td> <td>w 13-7</td> <td>pontiac silverdome</td> <td>51187</td> </tr> <tr> <th>1</th> <td>2</td> <td>1978-09-10 00:00:00</td> <td>new orleans saints</td> <td>w 28-17</td> <td>milwaukee county stadium</td> <td>54336</td> </tr> <tr> <th>2</th> <td>3</td> <td>1978-09-17 00:00:00</td> <td>oakland raiders</td> <td>l 28-3</td> <td>lambeau field</td> <td>55903</td> </tr> <tr> <th>3</th> <td>4</td> <td>1978-09-24 00:00:00</td> <td>at san diego chargers</td> <td>w 24-3</td> <td>san diego stadium</td> <td>42755</td> </tr> <tr> <th>4</th> <td>5</td> <td>1978-10-01 00:00:00</td> <td>detroit lions</td> <td>w 35-14</td> <td>milwaukee county stadium</td> <td>54601</td> </tr> <tr> <th>5</th> <td>6</td> <td>1978-10-08 00:00:00</td> <td>chicago bears</td> <td>w 24-14</td> <td>lambeau field</td> <td>56267</td> </tr> <tr> <th>6</th> <td>7</td> <td>1978-10-15 00:00:00</td> <td>seattle seahawks</td> <td>w 45-28</td> <td>milwaukee county stadium</td> <td>52712</td> </tr> <tr> <th>7</th> <td>8</td> <td>1978-10-22 00:00:00</td> <td>at minnesota vikings</td> <td>l 21-7</td> <td>metropolitan stadium</td> <td>47411</td> </tr> <tr> <th>8</th> <td>9</td> <td>1978-10-29 00:00:00</td> <td>tampa bay buccaneers</td> <td>w 9-7</td> <td>lambeau field</td> <td>55108</td> </tr> <tr> <th>9</th> <td>10</td> <td>1978-11-05 00:00:00</td> <td>at philadelphia eagles</td> <td>l 10-3</td> <td>veterans stadium</td> <td>64214</td> </tr> <tr> <th>10</th> <td>11</td> <td>1978-11-12 00:00:00</td> <td>dallas cowboys</td> <td>l 42-14</td> <td>milwaukee county stadium</td> <td>55256</td> </tr> <tr> <th>11</th> <td>12</td> <td>1978-11-19 00:00:00</td> <td>at denver broncos</td> <td>l 16-3</td> <td>mile high stadium</td> <td>74965</td> </tr> <tr> <th>12</th> <td>13</td> <td>1978-11-26 00:00:00</td> <td>minnesota vikings</td> <td>t 10-10 (ot)</td> <td>lambeau field</td> <td>51737</td> </tr> <tr> <th>13</th> <td>14</td> <td>1978-12-03 00:00:00</td> <td>at tampa bay buccaneers</td> <td>w 17-7</td> <td>tampa stadium</td> <td>67754</td> </tr> <tr> <th>14</th> <td>15</td> <td>1978-12-10 00:00:00</td> <td>at chicago bears</td> <td>l 14-0</td> <td>soldier field</td> <td>34306</td> </tr> <tr> <th>15</th> <td>16</td> <td>1978-12-17 00:00:00</td> <td>at los angeles rams</td> <td>l 31-14</td> <td>los angeles memorial coliseum</td> <td>42500</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>min ( "attendance" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>51737</td> </tr> </tbody> </table>

select min ( attendance ) where venue = 'lambeau field' <table_name> : table | | week | date | opponent | result | venue | attendance | |---:|-------:|:--------------------|:------------------------|:-------------|:------------------------------|-------------:| | 0 | 1 | 1978-09-03 00:00:00 | at detroit lions | w 13-7 | pontiac silverdome | 51187 | | 1 | 2 | 1978-09-10 00:00:00 | new orleans saints | w 28-17 | milwaukee county stadium | 54336 | | 2 | 3 | 1978-09-17 00:00:00 | oakland raiders | l 28-3 | lambeau field | 55903 | | 3 | 4 | 1978-09-24 00:00:00 | at san diego chargers | w 24-3 | san diego stadium | 42755 | | 4 | 5 | 1978-10-01 00:00:00 | detroit lions | w 35-14 | milwaukee county stadium | 54601 | | 5 | 6 | 1978-10-08 00:00:00 | chicago bears | w 24-14 | lambeau field | 56267 | | 6 | 7 | 1978-10-15 00:00:00 | seattle seahawks | w 45-28 | milwaukee county stadium | 52712 | | 7 | 8 | 1978-10-22 00:00:00 | at minnesota vikings | l 21-7 | metropolitan stadium | 47411 | | 8 | 9 | 1978-10-29 00:00:00 | tampa bay buccaneers | w 9-7 | lambeau field | 55108 | | 9 | 10 | 1978-11-05 00:00:00 | at philadelphia eagles | l 10-3 | veterans stadium | 64214 | | 10 | 11 | 1978-11-12 00:00:00 | dallas cowboys | l 42-14 | milwaukee county stadium | 55256 | | 11 | 12 | 1978-11-19 00:00:00 | at denver broncos | l 16-3 | mile high stadium | 74965 | | 12 | 13 | 1978-11-26 00:00:00 | minnesota vikings | t 10-10 (ot) | lambeau field | 51737 | | 13 | 14 | 1978-12-03 00:00:00 | at tampa bay buccaneers | w 17-7 | tampa stadium | 67754 | | 14 | 15 | 1978-12-10 00:00:00 | at chicago bears | l 14-0 | soldier field | 34306 | | 15 | 16 | 1978-12-17 00:00:00 | at los angeles rams | l 31-14 | los angeles memorial coliseum | 42500 |

| | min ( "attendance" ) | |---:|-----------------------:| | 0 | 51737 |

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col : "abs ( distance (km) - distance (km) )" row 1 : abs ( distance (km) - distance (km) ) row 2 : abs ( distance (km) - distance (km) ) row 3 : abs ( distance (km) - distance (km) )

select abs ( distance (km) - distance (km) ) where location = 'soja' <table_name> : table \begin{tabular}{llllll} \toprule & name & japanese & distance (km) & connections & location \\ \midrule 0 & okayama & 岡山 & 0.0 & sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line & kita-ku, okayama \\ 1 & bizen-mikado & 備前三門 & 1.9 & none & kita-ku, okayama \\ 2 & daianji & 大安寺 & 3.3 & none & kita-ku, okayama \\ 3 & bizen-ichinomiya & 備前一宮 & 6.5 & none & kita-ku, okayama \\ 4 & kibitsu & 吉備津 & 8.4 & none & kita-ku, okayama \\ 5 & bitchu-takamatsu & 備中高松 & 11.0 & none & kita-ku, okayama \\ 6 & ashimori & 足守 & 13.4 & none & kita-ku, okayama \\ 7 & hattori & 服部 & 16.2 & none & soja \\ 8 & higashi-soja & 東総社 & 18.8 & none & soja \\ 9 & soja & 総社 & 20.4 & hakubi line ibara railway ibara line & soja \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & "abs ( distance (km) - distance (km) )" \\ \midrule 0 & abs ( distance (km) - distance (km) ) \\ 1 & abs ( distance (km) - distance (km) ) \\ 2 & abs ( distance (km) - distance (km) ) \\ \bottomrule \end{tabular}

select abs ( distance (km) - distance (km) ) where location = 'soja' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>japanese</th> <th>distance (km)</th> <th>connections</th> <th>location</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>okayama</td> <td>岡山</td> <td>0.0</td> <td>sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line</td> <td>kita-ku, okayama</td> </tr> <tr> <th>1</th> <td>bizen-mikado</td> <td>備前三門</td> <td>1.9</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>2</th> <td>daianji</td> <td>大安寺</td> <td>3.3</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>3</th> <td>bizen-ichinomiya</td> <td>備前一宮</td> <td>6.5</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>4</th> <td>kibitsu</td> <td>吉備津</td> <td>8.4</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>5</th> <td>bitchu-takamatsu</td> <td>備中高松</td> <td>11.0</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>6</th> <td>ashimori</td> <td>足守</td> <td>13.4</td> <td>none</td> <td>kita-ku, okayama</td> </tr> <tr> <th>7</th> <td>hattori</td> <td>服部</td> <td>16.2</td> <td>none</td> <td>soja</td> </tr> <tr> <th>8</th> <td>higashi-soja</td> <td>東総社</td> <td>18.8</td> <td>none</td> <td>soja</td> </tr> <tr> <th>9</th> <td>soja</td> <td>総社</td> <td>20.4</td> <td>hakubi line ibara railway ibara line</td> <td>soja</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>"abs ( distance (km) - distance (km) )"</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>abs ( distance (km) - distance (km) )</td> </tr> <tr> <th>1</th> <td>abs ( distance (km) - distance (km) )</td> </tr> <tr> <th>2</th> <td>abs ( distance (km) - distance (km) )</td> </tr> </tbody> </table>

select abs ( distance (km) - distance (km) ) where location = 'soja' <table_name> : table | | name | japanese | distance (km) | connections | location | |---:|:-----------------|:-----------|----------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------| | 0 | okayama | 岡山 | 0 | sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line | kita-ku, okayama | | 1 | bizen-mikado | 備前三門 | 1.9 | none | kita-ku, okayama | | 2 | daianji | 大安寺 | 3.3 | none | kita-ku, okayama | | 3 | bizen-ichinomiya | 備前一宮 | 6.5 | none | kita-ku, okayama | | 4 | kibitsu | 吉備津 | 8.4 | none | kita-ku, okayama | | 5 | bitchu-takamatsu | 備中高松 | 11 | none | kita-ku, okayama | | 6 | ashimori | 足守 | 13.4 | none | kita-ku, okayama | | 7 | hattori | 服部 | 16.2 | none | soja | | 8 | higashi-soja | 東総社 | 18.8 | none | soja | | 9 | soja | 総社 | 20.4 | hakubi line ibara railway ibara line | soja |

| | "abs ( distance (km) - distance (km) )" | |---:|:------------------------------------------| | 0 | abs ( distance (km) - distance (km) ) | | 1 | abs ( distance (km) - distance (km) ) | | 2 | abs ( distance (km) - distance (km) ) |

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col : count ( "*" ) row 1 : 1

select count ( * ) where player = 'dustin johnson' <table_name> : table \begin{tabular}{llllll} \toprule & place & player & country & score & to par \\ \midrule 0 & 1 & dustin johnson & united states & 71-70-66=207 & -6 \\ 1 & 2 & graeme mcdowell & northern ireland & 71-68-71=210 & -3 \\ 2 & 3 & tiger woods & united states & 74-72-66=212 & -1 \\ 3 & t4 & ernie els & south africa & 73-68-72=213 & e \\ 4 & t4 & gregory havret & france & 73-71-69=213 & e \\ 5 & 6 & phil mickelson & united states & 75-66-73=214 & 1 \\ 6 & t7 & alex cejka & germany & 70-72-74=216 & 3 \\ 7 & t7 & tim clark & south africa & 72-72-72=216 & 3 \\ 8 & t7 & ryo ishikawa & japan & 70-71-75=216 & 3 \\ 9 & t10 & martin kaymer & germany & 74-71-72=217 & 4 \\ 10 & t10 & davis love iii & united states & 75-74-68=217 & 4 \\ 11 & t10 & sean o'hair & united states & 76-71-70=217 & 4 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where player = 'dustin johnson' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>place</th> <th>player</th> <th>country</th> <th>score</th> <th>to par</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>dustin johnson</td> <td>united states</td> <td>71-70-66=207</td> <td>-6</td> </tr> <tr> <th>1</th> <td>2</td> <td>graeme mcdowell</td> <td>northern ireland</td> <td>71-68-71=210</td> <td>-3</td> </tr> <tr> <th>2</th> <td>3</td> <td>tiger woods</td> <td>united states</td> <td>74-72-66=212</td> <td>-1</td> </tr> <tr> <th>3</th> <td>t4</td> <td>ernie els</td> <td>south africa</td> <td>73-68-72=213</td> <td>e</td> </tr> <tr> <th>4</th> <td>t4</td> <td>gregory havret</td> <td>france</td> <td>73-71-69=213</td> <td>e</td> </tr> <tr> <th>5</th> <td>6</td> <td>phil mickelson</td> <td>united states</td> <td>75-66-73=214</td> <td>1</td> </tr> <tr> <th>6</th> <td>t7</td> <td>alex cejka</td> <td>germany</td> <td>70-72-74=216</td> <td>3</td> </tr> <tr> <th>7</th> <td>t7</td> <td>tim clark</td> <td>south africa</td> <td>72-72-72=216</td> <td>3</td> </tr> <tr> <th>8</th> <td>t7</td> <td>ryo ishikawa</td> <td>japan</td> <td>70-71-75=216</td> <td>3</td> </tr> <tr> <th>9</th> <td>t10</td> <td>martin kaymer</td> <td>germany</td> <td>74-71-72=217</td> <td>4</td> </tr> <tr> <th>10</th> <td>t10</td> <td>davis love iii</td> <td>united states</td> <td>75-74-68=217</td> <td>4</td> </tr> <tr> <th>11</th> <td>t10</td> <td>sean o'hair</td> <td>united states</td> <td>76-71-70=217</td> <td>4</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where player = 'dustin johnson' <table_name> : table | | place | player | country | score | to par | |---:|:--------|:----------------|:-----------------|:-------------|:---------| | 0 | 1 | dustin johnson | united states | 71-70-66=207 | -6 | | 1 | 2 | graeme mcdowell | northern ireland | 71-68-71=210 | -3 | | 2 | 3 | tiger woods | united states | 74-72-66=212 | -1 | | 3 | t4 | ernie els | south africa | 73-68-72=213 | e | | 4 | t4 | gregory havret | france | 73-71-69=213 | e | | 5 | 6 | phil mickelson | united states | 75-66-73=214 | 1 | | 6 | t7 | alex cejka | germany | 70-72-74=216 | 3 | | 7 | t7 | tim clark | south africa | 72-72-72=216 | 3 | | 8 | t7 | ryo ishikawa | japan | 70-71-75=216 | 3 | | 9 | t10 | martin kaymer | germany | 74-71-72=217 | 4 | | 10 | t10 | davis love iii | united states | 75-74-68=217 | 4 | | 11 | t10 | sean o'hair | united states | 76-71-70=217 | 4 |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : count ( "*" ) row 1 : 30

select count ( * ) where division one > 881 <table_name> : table \begin{tabular}{lllll} \toprule & season & division one & division two & division three \\ \midrule 0 & 1983-84 & whitehawk & portfield & east preston \\ 1 & 1984-85 & steyning town & shoreham & oakwood \\ 2 & 1985-86 & steyning town & wick & seaford town \\ 3 & 1986-87 & arundel & pagham & langney sports \\ 4 & 1987-88 & pagham & langney sports & midway \\ 5 & 1988-89 & pagham & seaford town & saltdean united \\ 6 & 1989-90 & wick & bexhill town & worthing united \\ 7 & 1990-91 & littlehampton town & newhaven & ifield \\ 8 & 1991-92 & peacehaven & telscombe & portfield & hassocks \\ 9 & 1992-93 & peacehaven & telscombe & crowborough athletic & withdean \\ 10 & 1993-94 & wick & shoreham & bosham \\ 11 & 1994-95 & peacehaven & telscombe & mile oak & midhurst & easebourne \\ 12 & 1995-96 & peacehaven & telscombe & saltdean united & ifield \\ 13 & 1996-97 & burgess hill town & littlehampton town & sidlesham \\ 14 & 1997-98 & burgess hill town & east preston & lingfield \\ 15 & 1998-99 & burgess hill town & sidley united & oving social club \\ 16 & 1999-2000 & langney sports & sidlesham & bosham \\ 17 & 2000-01 & sidley united & southwick & rye united \\ 18 & 2001-02 & burgess hill town & rye & iden united & pease pottage village \\ 19 & 2002-03 & burgess hill town & rye & iden united & midhurst & easebourne \\ 20 & 2003-04 & chichester city united & littlehampton town & crowborough athletic \\ 21 & 2004-05 & horsham y m c a & crowborough athletic & storrington \\ 22 & 2005-06 & horsham y m c a & oakwood & peacehaven & telscombe \\ 23 & 2006-07 & eastbourne town & pagham & rustington \\ 24 & 2007-08 & crowborough athletic & east grinstead town & loxwood \\ 25 & 2008-09 & eastbourne united association & peacehaven & telscombe & clymping \\ 26 & 2009-10 & whitehawk & rye united & bosham \\ 27 & 2010-11 & crawley down & a.f.c. uckfield & dorking wanderers \\ 28 & 2011-12 & three bridges & east preston & newhaven \\ 29 & 2012-13 & peacehaven & telscombe & littlehampton town & sidlesham \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 30 \\ \bottomrule \end{tabular}

select count ( * ) where division one > 881 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>division one</th> <th>division two</th> <th>division three</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1983-84</td> <td>whitehawk</td> <td>portfield</td> <td>east preston</td> </tr> <tr> <th>1</th> <td>1984-85</td> <td>steyning town</td> <td>shoreham</td> <td>oakwood</td> </tr> <tr> <th>2</th> <td>1985-86</td> <td>steyning town</td> <td>wick</td> <td>seaford town</td> </tr> <tr> <th>3</th> <td>1986-87</td> <td>arundel</td> <td>pagham</td> <td>langney sports</td> </tr> <tr> <th>4</th> <td>1987-88</td> <td>pagham</td> <td>langney sports</td> <td>midway</td> </tr> <tr> <th>5</th> <td>1988-89</td> <td>pagham</td> <td>seaford town</td> <td>saltdean united</td> </tr> <tr> <th>6</th> <td>1989-90</td> <td>wick</td> <td>bexhill town</td> <td>worthing united</td> </tr> <tr> <th>7</th> <td>1990-91</td> <td>littlehampton town</td> <td>newhaven</td> <td>ifield</td> </tr> <tr> <th>8</th> <td>1991-92</td> <td>peacehaven & telscombe</td> <td>portfield</td> <td>hassocks</td> </tr> <tr> <th>9</th> <td>1992-93</td> <td>peacehaven & telscombe</td> <td>crowborough athletic</td> <td>withdean</td> </tr> <tr> <th>10</th> <td>1993-94</td> <td>wick</td> <td>shoreham</td> <td>bosham</td> </tr> <tr> <th>11</th> <td>1994-95</td> <td>peacehaven & telscombe</td> <td>mile oak</td> <td>midhurst & easebourne</td> </tr> <tr> <th>12</th> <td>1995-96</td> <td>peacehaven & telscombe</td> <td>saltdean united</td> <td>ifield</td> </tr> <tr> <th>13</th> <td>1996-97</td> <td>burgess hill town</td> <td>littlehampton town</td> <td>sidlesham</td> </tr> <tr> <th>14</th> <td>1997-98</td> <td>burgess hill town</td> <td>east preston</td> <td>lingfield</td> </tr> <tr> <th>15</th> <td>1998-99</td> <td>burgess hill town</td> <td>sidley united</td> <td>oving social club</td> </tr> <tr> <th>16</th> <td>1999-2000</td> <td>langney sports</td> <td>sidlesham</td> <td>bosham</td> </tr> <tr> <th>17</th> <td>2000-01</td> <td>sidley united</td> <td>southwick</td> <td>rye united</td> </tr> <tr> <th>18</th> <td>2001-02</td> <td>burgess hill town</td> <td>rye & iden united</td> <td>pease pottage village</td> </tr> <tr> <th>19</th> <td>2002-03</td> <td>burgess hill town</td> <td>rye & iden united</td> <td>midhurst & easebourne</td> </tr> <tr> <th>20</th> <td>2003-04</td> <td>chichester city united</td> <td>littlehampton town</td> <td>crowborough athletic</td> </tr> <tr> <th>21</th> <td>2004-05</td> <td>horsham y m c a</td> <td>crowborough athletic</td> <td>storrington</td> </tr> <tr> <th>22</th> <td>2005-06</td> <td>horsham y m c a</td> <td>oakwood</td> <td>peacehaven & telscombe</td> </tr> <tr> <th>23</th> <td>2006-07</td> <td>eastbourne town</td> <td>pagham</td> <td>rustington</td> </tr> <tr> <th>24</th> <td>2007-08</td> <td>crowborough athletic</td> <td>east grinstead town</td> <td>loxwood</td> </tr> <tr> <th>25</th> <td>2008-09</td> <td>eastbourne united association</td> <td>peacehaven & telscombe</td> <td>clymping</td> </tr> <tr> <th>26</th> <td>2009-10</td> <td>whitehawk</td> <td>rye united</td> <td>bosham</td> </tr> <tr> <th>27</th> <td>2010-11</td> <td>crawley down</td> <td>a.f.c. uckfield</td> <td>dorking wanderers</td> </tr> <tr> <th>28</th> <td>2011-12</td> <td>three bridges</td> <td>east preston</td> <td>newhaven</td> </tr> <tr> <th>29</th> <td>2012-13</td> <td>peacehaven & telscombe</td> <td>littlehampton town</td> <td>sidlesham</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>30</td> </tr> </tbody> </table>

select count ( * ) where division one > 881 <table_name> : table | | season | division one | division two | division three | |---:|:----------|:------------------------------|:-----------------------|:-----------------------| | 0 | 1983-84 | whitehawk | portfield | east preston | | 1 | 1984-85 | steyning town | shoreham | oakwood | | 2 | 1985-86 | steyning town | wick | seaford town | | 3 | 1986-87 | arundel | pagham | langney sports | | 4 | 1987-88 | pagham | langney sports | midway | | 5 | 1988-89 | pagham | seaford town | saltdean united | | 6 | 1989-90 | wick | bexhill town | worthing united | | 7 | 1990-91 | littlehampton town | newhaven | ifield | | 8 | 1991-92 | peacehaven & telscombe | portfield | hassocks | | 9 | 1992-93 | peacehaven & telscombe | crowborough athletic | withdean | | 10 | 1993-94 | wick | shoreham | bosham | | 11 | 1994-95 | peacehaven & telscombe | mile oak | midhurst & easebourne | | 12 | 1995-96 | peacehaven & telscombe | saltdean united | ifield | | 13 | 1996-97 | burgess hill town | littlehampton town | sidlesham | | 14 | 1997-98 | burgess hill town | east preston | lingfield | | 15 | 1998-99 | burgess hill town | sidley united | oving social club | | 16 | 1999-2000 | langney sports | sidlesham | bosham | | 17 | 2000-01 | sidley united | southwick | rye united | | 18 | 2001-02 | burgess hill town | rye & iden united | pease pottage village | | 19 | 2002-03 | burgess hill town | rye & iden united | midhurst & easebourne | | 20 | 2003-04 | chichester city united | littlehampton town | crowborough athletic | | 21 | 2004-05 | horsham y m c a | crowborough athletic | storrington | | 22 | 2005-06 | horsham y m c a | oakwood | peacehaven & telscombe | | 23 | 2006-07 | eastbourne town | pagham | rustington | | 24 | 2007-08 | crowborough athletic | east grinstead town | loxwood | | 25 | 2008-09 | eastbourne united association | peacehaven & telscombe | clymping | | 26 | 2009-10 | whitehawk | rye united | bosham | | 27 | 2010-11 | crawley down | a.f.c. uckfield | dorking wanderers | | 28 | 2011-12 | three bridges | east preston | newhaven | | 29 | 2012-13 | peacehaven & telscombe | littlehampton town | sidlesham |

| | count ( "*" ) | |---:|----------------:| | 0 | 30 |

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col : count ( "*" ) row 1 : 1

select count ( * ) where host city = 'salt lake city, utah' <table_name> : table \begin{tabular}{lllllll} \toprule & games & host city & dates & nations & participants & events \\ \midrule 0 & 1904 summer olympics & st. louis, missouri & 1 july - 23 november & 12 & 651 & 91 \\ 1 & 1932 winter olympics & lake placid, new york & 7 - 15 february & 17 & 252 & 14 \\ 2 & 1932 summer olympics & los angeles, california & 30 july - 14 august & 37 & 1332 & 117 \\ 3 & 1960 winter olympics & squaw valley, california & 2 - 20 february & 30 & 665 & 27 \\ 4 & 1980 winter olympics & lake placid, new york & 13 - 24 february & 37 & 1072 & 38 \\ 5 & 1984 summer olympics & los angeles, california & 20 july - 18 august & 140 & 6829 & 221 \\ 6 & 1996 summer olympics & atlanta, georgia & 18 july - 4 august & 197 & 1318 & 271 \\ 7 & 2002 winter olympics & salt lake city, utah & 8 - 24 february & 77 & 2399 & 78 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where host city = 'salt lake city, utah' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>games</th> <th>host city</th> <th>dates</th> <th>nations</th> <th>participants</th> <th>events</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1904 summer olympics</td> <td>st. louis, missouri</td> <td>1 july - 23 november</td> <td>12</td> <td>651</td> <td>91</td> </tr> <tr> <th>1</th> <td>1932 winter olympics</td> <td>lake placid, new york</td> <td>7 - 15 february</td> <td>17</td> <td>252</td> <td>14</td> </tr> <tr> <th>2</th> <td>1932 summer olympics</td> <td>los angeles, california</td> <td>30 july - 14 august</td> <td>37</td> <td>1332</td> <td>117</td> </tr> <tr> <th>3</th> <td>1960 winter olympics</td> <td>squaw valley, california</td> <td>2 - 20 february</td> <td>30</td> <td>665</td> <td>27</td> </tr> <tr> <th>4</th> <td>1980 winter olympics</td> <td>lake placid, new york</td> <td>13 - 24 february</td> <td>37</td> <td>1072</td> <td>38</td> </tr> <tr> <th>5</th> <td>1984 summer olympics</td> <td>los angeles, california</td> <td>20 july - 18 august</td> <td>140</td> <td>6829</td> <td>221</td> </tr> <tr> <th>6</th> <td>1996 summer olympics</td> <td>atlanta, georgia</td> <td>18 july - 4 august</td> <td>197</td> <td>1318</td> <td>271</td> </tr> <tr> <th>7</th> <td>2002 winter olympics</td> <td>salt lake city, utah</td> <td>8 - 24 february</td> <td>77</td> <td>2399</td> <td>78</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where host city = 'salt lake city, utah' <table_name> : table | | games | host city | dates | nations | participants | events | |---:|:---------------------|:-------------------------|:---------------------|----------:|---------------:|---------:| | 0 | 1904 summer olympics | st. louis, missouri | 1 july - 23 november | 12 | 651 | 91 | | 1 | 1932 winter olympics | lake placid, new york | 7 - 15 february | 17 | 252 | 14 | | 2 | 1932 summer olympics | los angeles, california | 30 july - 14 august | 37 | 1332 | 117 | | 3 | 1960 winter olympics | squaw valley, california | 2 - 20 february | 30 | 665 | 27 | | 4 | 1980 winter olympics | lake placid, new york | 13 - 24 february | 37 | 1072 | 38 | | 5 | 1984 summer olympics | los angeles, california | 20 july - 18 august | 140 | 6829 | 221 | | 6 | 1996 summer olympics | atlanta, georgia | 18 july - 4 august | 197 | 1318 | 271 | | 7 | 2002 winter olympics | salt lake city, utah | 8 - 24 february | 77 | 2399 | 78 |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : time row 1 : 1:28.18

select time where athlete = 'sylvia filipsson' <table_name> : table \begin{tabular}{llllll} \toprule & rank & athlete & country & time & notes \\ \midrule 0 & none & nataliya petrusyova & soviet union & 1:24.10 & or \\ 1 & none & leah poulos & united states & 1:25.41 & none \\ 2 & none & sylvia albrecht & east germany & 1:26.46 & none \\ 3 & 4 & karin enke & east germany & 1:26.66 & none \\ 4 & 5 & beth heiden & united states & 1:27.01 & none \\ 5 & 6 & annie borckink & netherlands & 1:27.24 & none \\ 6 & 7 & sylvia burka & canada & 1:27.50 & none \\ 7 & 8 & ann-sofie jarnstrom & sweden & 1:28.10 & none \\ 8 & 9 & sylvia filipsson & sweden & 1:28.18 & none \\ 9 & 10 & annette carlen-karlsson & sweden & 1:28.25 & none \\ 10 & 11 & valentina lalenkova & soviet union & 1:28.27 & none \\ 11 & 12 & bjørg eva jensen & norway & 1:28.55 & none \\ 12 & 13 & sijtje van der lende & netherlands & 1:28.72 & none \\ 13 & 14 & sarah docter & united states & 1:28.80 & none \\ 14 & 14 & haitske valentijn-pijlman & netherlands & 1:28.80 & none \\ 15 & 16 & erwina rys-ferens & poland & 1:28.82 & none \\ 16 & 17 & miyoshi kato & japan & 1:28.97 & none \\ 17 & 18 & christa rothenburger & east germany & 1:29.69 & none \\ 18 & 19 & brenda webster & canada & 1:29.84 & none \\ 19 & 20 & irina kuleshova-kovrova & soviet union & 1:29.94 & none \\ 20 & 21 & monika pflug & west germany & 1:30.13 & none \\ 21 & 22 & makiko nagaya & japan & 1:30.27 & none \\ 22 & 23 & sigrid smuda & west germany & 1:30.29 & none \\ 23 & 24 & kathy vogt & canada & 1:30.33 & none \\ 24 & 25 & yuko yaegashi-ota & japan & 1:30.72 & none \\ 25 & 26 & lee nam-sun & south korea & 1:31.30 & none \\ 26 & 27 & cao guifeng & china & 1:31.74 & none \\ 27 & 28 & anneli repola & finland & 1:31.76 & none \\ 28 & 29 & silvia brunner & switzerland & 1:31.79 & none \\ 29 & 30 & lee seong-ae & south korea & 1:32.04 & none \\ 30 & 31 & zhang li & china & 1:32.20 & none \\ 31 & 32 & shen zhenshu & china & 1:32.49 & none \\ 32 & 33 & brigitte flierl & west germany & 1:33.61 & none \\ 33 & 34 & kim yeong-hui & south korea & 1:34.17 & none \\ 34 & 35 & kim ferran & great britain & 1:34.19 & none \\ 35 & 36 & marzia peretti & italy & 1:35.66 & none \\ 36 & 37 & mandy horsepool & great britain & 1:36.31 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & time \\ \midrule 0 & 1:28.18 \\ \bottomrule \end{tabular}

select time where athlete = 'sylvia filipsson' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>athlete</th> <th>country</th> <th>time</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>none</td> <td>nataliya petrusyova</td> <td>soviet union</td> <td>1:24.10</td> <td>or</td> </tr> <tr> <th>1</th> <td>none</td> <td>leah poulos</td> <td>united states</td> <td>1:25.41</td> <td>none</td> </tr> <tr> <th>2</th> <td>none</td> <td>sylvia albrecht</td> <td>east germany</td> <td>1:26.46</td> <td>none</td> </tr> <tr> <th>3</th> <td>4</td> <td>karin enke</td> <td>east germany</td> <td>1:26.66</td> <td>none</td> </tr> <tr> <th>4</th> <td>5</td> <td>beth heiden</td> <td>united states</td> <td>1:27.01</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>annie borckink</td> <td>netherlands</td> <td>1:27.24</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>sylvia burka</td> <td>canada</td> <td>1:27.50</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>ann-sofie jarnstrom</td> <td>sweden</td> <td>1:28.10</td> <td>none</td> </tr> <tr> <th>8</th> <td>9</td> <td>sylvia filipsson</td> <td>sweden</td> <td>1:28.18</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>annette carlen-karlsson</td> <td>sweden</td> <td>1:28.25</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>valentina lalenkova</td> <td>soviet union</td> <td>1:28.27</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>bjørg eva jensen</td> <td>norway</td> <td>1:28.55</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>sijtje van der lende</td> <td>netherlands</td> <td>1:28.72</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>sarah docter</td> <td>united states</td> <td>1:28.80</td> <td>none</td> </tr> <tr> <th>14</th> <td>14</td> <td>haitske valentijn-pijlman</td> <td>netherlands</td> <td>1:28.80</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>erwina rys-ferens</td> <td>poland</td> <td>1:28.82</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>miyoshi kato</td> <td>japan</td> <td>1:28.97</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>christa rothenburger</td> <td>east germany</td> <td>1:29.69</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>brenda webster</td> <td>canada</td> <td>1:29.84</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>irina kuleshova-kovrova</td> <td>soviet union</td> <td>1:29.94</td> <td>none</td> </tr> <tr> <th>20</th> <td>21</td> <td>monika pflug</td> <td>west germany</td> <td>1:30.13</td> <td>none</td> </tr> <tr> <th>21</th> <td>22</td> <td>makiko nagaya</td> <td>japan</td> <td>1:30.27</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>sigrid smuda</td> <td>west germany</td> <td>1:30.29</td> <td>none</td> </tr> <tr> <th>23</th> <td>24</td> <td>kathy vogt</td> <td>canada</td> <td>1:30.33</td> <td>none</td> </tr> <tr> <th>24</th> <td>25</td> <td>yuko yaegashi-ota</td> <td>japan</td> <td>1:30.72</td> <td>none</td> </tr> <tr> <th>25</th> <td>26</td> <td>lee nam-sun</td> <td>south korea</td> <td>1:31.30</td> <td>none</td> </tr> <tr> <th>26</th> <td>27</td> <td>cao guifeng</td> <td>china</td> <td>1:31.74</td> <td>none</td> </tr> <tr> <th>27</th> <td>28</td> <td>anneli repola</td> <td>finland</td> <td>1:31.76</td> <td>none</td> </tr> <tr> <th>28</th> <td>29</td> <td>silvia brunner</td> <td>switzerland</td> <td>1:31.79</td> <td>none</td> </tr> <tr> <th>29</th> <td>30</td> <td>lee seong-ae</td> <td>south korea</td> <td>1:32.04</td> <td>none</td> </tr> <tr> <th>30</th> <td>31</td> <td>zhang li</td> <td>china</td> <td>1:32.20</td> <td>none</td> </tr> <tr> <th>31</th> <td>32</td> <td>shen zhenshu</td> <td>china</td> <td>1:32.49</td> <td>none</td> </tr> <tr> <th>32</th> <td>33</td> <td>brigitte flierl</td> <td>west germany</td> <td>1:33.61</td> <td>none</td> </tr> <tr> <th>33</th> <td>34</td> <td>kim yeong-hui</td> <td>south korea</td> <td>1:34.17</td> <td>none</td> </tr> <tr> <th>34</th> <td>35</td> <td>kim ferran</td> <td>great britain</td> <td>1:34.19</td> <td>none</td> </tr> <tr> <th>35</th> <td>36</td> <td>marzia peretti</td> <td>italy</td> <td>1:35.66</td> <td>none</td> </tr> <tr> <th>36</th> <td>37</td> <td>mandy horsepool</td> <td>great britain</td> <td>1:36.31</td> <td>none</td> </tr> </tbody> </table>

select time where athlete = 'sylvia filipsson' <table_name> : table | | rank | athlete | country | time | notes | |---:|:-------|:--------------------------|:--------------|:--------|:--------| | 0 | none | nataliya petrusyova | soviet union | 1:24.10 | or | | 1 | none | leah poulos | united states | 1:25.41 | none | | 2 | none | sylvia albrecht | east germany | 1:26.46 | none | | 3 | 4 | karin enke | east germany | 1:26.66 | none | | 4 | 5 | beth heiden | united states | 1:27.01 | none | | 5 | 6 | annie borckink | netherlands | 1:27.24 | none | | 6 | 7 | sylvia burka | canada | 1:27.50 | none | | 7 | 8 | ann-sofie jarnstrom | sweden | 1:28.10 | none | | 8 | 9 | sylvia filipsson | sweden | 1:28.18 | none | | 9 | 10 | annette carlen-karlsson | sweden | 1:28.25 | none | | 10 | 11 | valentina lalenkova | soviet union | 1:28.27 | none | | 11 | 12 | bjørg eva jensen | norway | 1:28.55 | none | | 12 | 13 | sijtje van der lende | netherlands | 1:28.72 | none | | 13 | 14 | sarah docter | united states | 1:28.80 | none | | 14 | 14 | haitske valentijn-pijlman | netherlands | 1:28.80 | none | | 15 | 16 | erwina rys-ferens | poland | 1:28.82 | none | | 16 | 17 | miyoshi kato | japan | 1:28.97 | none | | 17 | 18 | christa rothenburger | east germany | 1:29.69 | none | | 18 | 19 | brenda webster | canada | 1:29.84 | none | | 19 | 20 | irina kuleshova-kovrova | soviet union | 1:29.94 | none | | 20 | 21 | monika pflug | west germany | 1:30.13 | none | | 21 | 22 | makiko nagaya | japan | 1:30.27 | none | | 22 | 23 | sigrid smuda | west germany | 1:30.29 | none | | 23 | 24 | kathy vogt | canada | 1:30.33 | none | | 24 | 25 | yuko yaegashi-ota | japan | 1:30.72 | none | | 25 | 26 | lee nam-sun | south korea | 1:31.30 | none | | 26 | 27 | cao guifeng | china | 1:31.74 | none | | 27 | 28 | anneli repola | finland | 1:31.76 | none | | 28 | 29 | silvia brunner | switzerland | 1:31.79 | none | | 29 | 30 | lee seong-ae | south korea | 1:32.04 | none | | 30 | 31 | zhang li | china | 1:32.20 | none | | 31 | 32 | shen zhenshu | china | 1:32.49 | none | | 32 | 33 | brigitte flierl | west germany | 1:33.61 | none | | 33 | 34 | kim yeong-hui | south korea | 1:34.17 | none | | 34 | 35 | kim ferran | great britain | 1:34.19 | none | | 35 | 36 | marzia peretti | italy | 1:35.66 | none | | 36 | 37 | mandy horsepool | great britain | 1:36.31 | none |

| | time | |---:|:--------| | 0 | 1:28.18 |

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col : count ( "country" ) row 1 : 10

select count ( country ) where country = 'sweden' <table_name> : table \begin{tabular}{lllllll} \toprule & season & team & country & competition & matches & goals \\ \midrule 0 & 1999 & djurgardens if & sweden & allsvenskan & 15 & 1 \\ 1 & 2000 & djurgardens if & sweden & superettan & 15 & 3 \\ 2 & 2001 & djurgardens if & sweden & allsvenskan & 22 & 7 \\ 3 & 2002-2003 & grazer ak & austria & bundesliga & 24 & 6 \\ 4 & 2003 & denizlispor & turkey & super lig & 3 & 0 \\ 5 & 2003 & landskrona bois & sweden & allsvenskan & 11 & 3 \\ 6 & 2004 & landskrona bois & sweden & allsvenskan & 22 & 4 \\ 7 & 2005 & djurgardens if & sweden & allsvenskan & 24 & 12 \\ 8 & 2006 & djurgardens if & sweden & allsvenskan & 17 & 6 \\ 9 & 2007 & djurgardens if & sweden & allsvenskan & 23 & 4 \\ 10 & 2008 & djurgardens if & sweden & allsvenskan & 29 & 6 \\ 11 & 2008-09 & esbjerg fb & denmark & superliga & 6 & 0 \\ 12 & 2010 & aab & denmark & superliga & 3 & 1 \\ 13 & 2011 & assyriska ff & sweden & superettan & 19 & 5 \\ 14 & total & total & total & total & 233 & 58 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "country" ) \\ \midrule 0 & 10 \\ \bottomrule \end{tabular}

select count ( country ) where country = 'sweden' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>team</th> <th>country</th> <th>competition</th> <th>matches</th> <th>goals</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1999</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>15</td> <td>1</td> </tr> <tr> <th>1</th> <td>2000</td> <td>djurgardens if</td> <td>sweden</td> <td>superettan</td> <td>15</td> <td>3</td> </tr> <tr> <th>2</th> <td>2001</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>22</td> <td>7</td> </tr> <tr> <th>3</th> <td>2002-2003</td> <td>grazer ak</td> <td>austria</td> <td>bundesliga</td> <td>24</td> <td>6</td> </tr> <tr> <th>4</th> <td>2003</td> <td>denizlispor</td> <td>turkey</td> <td>super lig</td> <td>3</td> <td>0</td> </tr> <tr> <th>5</th> <td>2003</td> <td>landskrona bois</td> <td>sweden</td> <td>allsvenskan</td> <td>11</td> <td>3</td> </tr> <tr> <th>6</th> <td>2004</td> <td>landskrona bois</td> <td>sweden</td> <td>allsvenskan</td> <td>22</td> <td>4</td> </tr> <tr> <th>7</th> <td>2005</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>24</td> <td>12</td> </tr> <tr> <th>8</th> <td>2006</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>17</td> <td>6</td> </tr> <tr> <th>9</th> <td>2007</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>23</td> <td>4</td> </tr> <tr> <th>10</th> <td>2008</td> <td>djurgardens if</td> <td>sweden</td> <td>allsvenskan</td> <td>29</td> <td>6</td> </tr> <tr> <th>11</th> <td>2008-09</td> <td>esbjerg fb</td> <td>denmark</td> <td>superliga</td> <td>6</td> <td>0</td> </tr> <tr> <th>12</th> <td>2010</td> <td>aab</td> <td>denmark</td> <td>superliga</td> <td>3</td> <td>1</td> </tr> <tr> <th>13</th> <td>2011</td> <td>assyriska ff</td> <td>sweden</td> <td>superettan</td> <td>19</td> <td>5</td> </tr> <tr> <th>14</th> <td>total</td> <td>total</td> <td>total</td> <td>total</td> <td>233</td> <td>58</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "country" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>10</td> </tr> </tbody> </table>

select count ( country ) where country = 'sweden' <table_name> : table | | season | team | country | competition | matches | goals | |---:|:----------|:----------------|:----------|:--------------|----------:|--------:| | 0 | 1999 | djurgardens if | sweden | allsvenskan | 15 | 1 | | 1 | 2000 | djurgardens if | sweden | superettan | 15 | 3 | | 2 | 2001 | djurgardens if | sweden | allsvenskan | 22 | 7 | | 3 | 2002-2003 | grazer ak | austria | bundesliga | 24 | 6 | | 4 | 2003 | denizlispor | turkey | super lig | 3 | 0 | | 5 | 2003 | landskrona bois | sweden | allsvenskan | 11 | 3 | | 6 | 2004 | landskrona bois | sweden | allsvenskan | 22 | 4 | | 7 | 2005 | djurgardens if | sweden | allsvenskan | 24 | 12 | | 8 | 2006 | djurgardens if | sweden | allsvenskan | 17 | 6 | | 9 | 2007 | djurgardens if | sweden | allsvenskan | 23 | 4 | | 10 | 2008 | djurgardens if | sweden | allsvenskan | 29 | 6 | | 11 | 2008-09 | esbjerg fb | denmark | superliga | 6 | 0 | | 12 | 2010 | aab | denmark | superliga | 3 | 1 | | 13 | 2011 | assyriska ff | sweden | superettan | 19 | 5 | | 14 | total | total | total | total | 233 | 58 |

| | count ( "country" ) | |---:|----------------------:| | 0 | 10 |

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select count ( * ) where percentage = '1.9%' col : governorate | percentage | seats won | total seats row 1 : al-anbar | none | 0 | 29 row 2 : babil | 8.2% | 5 | 30 row 3 : baghdad | 5.4% | 3 | 57 row 4 : basra | 11.6% | 5 | 35 row 5 : dhi qar | 11.1% | 5 | 31 row 6 : diyala | none | 0 | 29 row 7 : karbala | 6.4% | 4 | 27 row 8 : maysan | 15.2% | 7 | 27 row 9 : al-muthanna | 9.3% | 5 | 26 row 10 : najaf | 14.8% | 7 | 28 row 11 : ninawa | 1.9% | 0 | 37 row 12 : al-qadisiyyah | 11.7% | 4 | 28 row 13 : salah ad-din | 2.9% | 1 | 28 row 14 : wassit | 10.0% | 6 | 28 row 15 : total | 6.6% | 52 | 440

col : count ( "*" ) row 1 : 1

select count ( * ) where percentage = '1.9%' <table_name> : table \begin{tabular}{lllll} \toprule & governorate & percentage & seats won & total seats \\ \midrule 0 & al-anbar & none & 0 & 29 \\ 1 & babil & 8.2% & 5 & 30 \\ 2 & baghdad & 5.4% & 3 & 57 \\ 3 & basra & 11.6% & 5 & 35 \\ 4 & dhi qar & 11.1% & 5 & 31 \\ 5 & diyala & none & 0 & 29 \\ 6 & karbala & 6.4% & 4 & 27 \\ 7 & maysan & 15.2% & 7 & 27 \\ 8 & al-muthanna & 9.3% & 5 & 26 \\ 9 & najaf & 14.8% & 7 & 28 \\ 10 & ninawa & 1.9% & 0 & 37 \\ 11 & al-qadisiyyah & 11.7% & 4 & 28 \\ 12 & salah ad-din & 2.9% & 1 & 28 \\ 13 & wassit & 10.0% & 6 & 28 \\ 14 & total & 6.6% & 52 & 440 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where percentage = '1.9%' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>governorate</th> <th>percentage</th> <th>seats won</th> <th>total seats</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>al-anbar</td> <td>none</td> <td>0</td> <td>29</td> </tr> <tr> <th>1</th> <td>babil</td> <td>8.2%</td> <td>5</td> <td>30</td> </tr> <tr> <th>2</th> <td>baghdad</td> <td>5.4%</td> <td>3</td> <td>57</td> </tr> <tr> <th>3</th> <td>basra</td> <td>11.6%</td> <td>5</td> <td>35</td> </tr> <tr> <th>4</th> <td>dhi qar</td> <td>11.1%</td> <td>5</td> <td>31</td> </tr> <tr> <th>5</th> <td>diyala</td> <td>none</td> <td>0</td> <td>29</td> </tr> <tr> <th>6</th> <td>karbala</td> <td>6.4%</td> <td>4</td> <td>27</td> </tr> <tr> <th>7</th> <td>maysan</td> <td>15.2%</td> <td>7</td> <td>27</td> </tr> <tr> <th>8</th> <td>al-muthanna</td> <td>9.3%</td> <td>5</td> <td>26</td> </tr> <tr> <th>9</th> <td>najaf</td> <td>14.8%</td> <td>7</td> <td>28</td> </tr> <tr> <th>10</th> <td>ninawa</td> <td>1.9%</td> <td>0</td> <td>37</td> </tr> <tr> <th>11</th> <td>al-qadisiyyah</td> <td>11.7%</td> <td>4</td> <td>28</td> </tr> <tr> <th>12</th> <td>salah ad-din</td> <td>2.9%</td> <td>1</td> <td>28</td> </tr> <tr> <th>13</th> <td>wassit</td> <td>10.0%</td> <td>6</td> <td>28</td> </tr> <tr> <th>14</th> <td>total</td> <td>6.6%</td> <td>52</td> <td>440</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where percentage = '1.9%' <table_name> : table | | governorate | percentage | seats won | total seats | |---:|:--------------|:-------------|------------:|--------------:| | 0 | al-anbar | none | 0 | 29 | | 1 | babil | 8.2% | 5 | 30 | | 2 | baghdad | 5.4% | 3 | 57 | | 3 | basra | 11.6% | 5 | 35 | | 4 | dhi qar | 11.1% | 5 | 31 | | 5 | diyala | none | 0 | 29 | | 6 | karbala | 6.4% | 4 | 27 | | 7 | maysan | 15.2% | 7 | 27 | | 8 | al-muthanna | 9.3% | 5 | 26 | | 9 | najaf | 14.8% | 7 | 28 | | 10 | ninawa | 1.9% | 0 | 37 | | 11 | al-qadisiyyah | 11.7% | 4 | 28 | | 12 | salah ad-din | 2.9% | 1 | 28 | | 13 | wassit | 10.0% | 6 | 28 | | 14 | total | 6.6% | 52 | 440 |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : nation row 1 : germany

select nation where nation = 'germany' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & heat & nation & competitors & time & notes \\ \midrule 0 & 1 & 2 & united states & kelly willie, derrick brew, andrew rock, darold williamson & 2:59.30 & q \\ 1 & 2 & 2 & nigeria & james godday, musa audu, saul weigopwa, enefiok udo-obong & 3:01.60 & q, sb \\ 2 & 3 & 2 & bahamas & andrae williams, dennis darling, nathaniel mckinney, christopher brown & 3:01.74 & q, sb \\ 3 & 4 & 1 & great britain & timothy benjamin, sean baldock, malachi davis, matthew elias & 3:02.40 & q, sb \\ 4 & 5 & 1 & japan & yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato & 3:02.71 & q \\ 5 & 6 & 1 & germany & ingo schultz, kamghe gaba, ruwen faller, bastian swillims & 3:02.77 & q \\ 6 & 7 & 1 & australia & john steffensen, clinton hill, patrick dwyer, mark ormrod & 3:03.06 & q \\ 7 & 8 & 1 & botswana & oganeditse moseki, johnson kubisa, california molefe, kagiso kilego & 3:03.32 & q, sb \\ 8 & 9 & 2 & russia & aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko & 3:03.35 & none \\ 9 & 10 & 2 & poland & piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo & 3:03.69 & none \\ 10 & 11 & 2 & ukraine & volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup & 3:04.01 & none \\ 11 & 12 & 1 & greece & stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis & 3:04.27 & sb \\ 12 & 13 & 1 & france & ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone & 3:04.39 & none \\ 13 & 14 & 2 & spain & eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina & 3:05.03 & sb \\ 14 & none & 2 & south africa & marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe & dnf & none \\ 15 & none & 1 & jamaica & michael campbell, michael blackwood, jermaine gonzales, davian clarke & dsq & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & germany \\ \bottomrule \end{tabular}

select nation where nation = 'germany' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>heat</th> <th>nation</th> <th>competitors</th> <th>time</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>2</td> <td>united states</td> <td>kelly willie, derrick brew, andrew rock, darold williamson</td> <td>2:59.30</td> <td>q</td> </tr> <tr> <th>1</th> <td>2</td> <td>2</td> <td>nigeria</td> <td>james godday, musa audu, saul weigopwa, enefiok udo-obong</td> <td>3:01.60</td> <td>q, sb</td> </tr> <tr> <th>2</th> <td>3</td> <td>2</td> <td>bahamas</td> <td>andrae williams, dennis darling, nathaniel mckinney, christopher brown</td> <td>3:01.74</td> <td>q, sb</td> </tr> <tr> <th>3</th> <td>4</td> <td>1</td> <td>great britain</td> <td>timothy benjamin, sean baldock, malachi davis, matthew elias</td> <td>3:02.40</td> <td>q, sb</td> </tr> <tr> <th>4</th> <td>5</td> <td>1</td> <td>japan</td> <td>yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato</td> <td>3:02.71</td> <td>q</td> </tr> <tr> <th>5</th> <td>6</td> <td>1</td> <td>germany</td> <td>ingo schultz, kamghe gaba, ruwen faller, bastian swillims</td> <td>3:02.77</td> <td>q</td> </tr> <tr> <th>6</th> <td>7</td> <td>1</td> <td>australia</td> <td>john steffensen, clinton hill, patrick dwyer, mark ormrod</td> <td>3:03.06</td> <td>q</td> </tr> <tr> <th>7</th> <td>8</td> <td>1</td> <td>botswana</td> <td>oganeditse moseki, johnson kubisa, california molefe, kagiso kilego</td> <td>3:03.32</td> <td>q, sb</td> </tr> <tr> <th>8</th> <td>9</td> <td>2</td> <td>russia</td> <td>aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko</td> <td>3:03.35</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>2</td> <td>poland</td> <td>piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo</td> <td>3:03.69</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>2</td> <td>ukraine</td> <td>volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup</td> <td>3:04.01</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>1</td> <td>greece</td> <td>stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis</td> <td>3:04.27</td> <td>sb</td> </tr> <tr> <th>12</th> <td>13</td> <td>1</td> <td>france</td> <td>ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone</td> <td>3:04.39</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>2</td> <td>spain</td> <td>eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina</td> <td>3:05.03</td> <td>sb</td> </tr> <tr> <th>14</th> <td>none</td> <td>2</td> <td>south africa</td> <td>marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe</td> <td>dnf</td> <td>none</td> </tr> <tr> <th>15</th> <td>none</td> <td>1</td> <td>jamaica</td> <td>michael campbell, michael blackwood, jermaine gonzales, davian clarke</td> <td>dsq</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>germany</td> </tr> </tbody> </table>

select nation where nation = 'germany' <table_name> : table | | rank | heat | nation | competitors | time | notes | |---:|:-------|-------:|:--------------|:------------------------------------------------------------------------------|:--------|:--------| | 0 | 1 | 2 | united states | kelly willie, derrick brew, andrew rock, darold williamson | 2:59.30 | q | | 1 | 2 | 2 | nigeria | james godday, musa audu, saul weigopwa, enefiok udo-obong | 3:01.60 | q, sb | | 2 | 3 | 2 | bahamas | andrae williams, dennis darling, nathaniel mckinney, christopher brown | 3:01.74 | q, sb | | 3 | 4 | 1 | great britain | timothy benjamin, sean baldock, malachi davis, matthew elias | 3:02.40 | q, sb | | 4 | 5 | 1 | japan | yuki yamaguchi, jun osakada, tomohiro ito, mitsuhiro sato | 3:02.71 | q | | 5 | 6 | 1 | germany | ingo schultz, kamghe gaba, ruwen faller, bastian swillims | 3:02.77 | q | | 6 | 7 | 1 | australia | john steffensen, clinton hill, patrick dwyer, mark ormrod | 3:03.06 | q | | 7 | 8 | 1 | botswana | oganeditse moseki, johnson kubisa, california molefe, kagiso kilego | 3:03.32 | q, sb | | 8 | 9 | 2 | russia | aleksandr larin, andrey rudnitskiy, oleg mishukov, ruslan mashchenko | 3:03.35 | none | | 9 | 10 | 2 | poland | piotr rysiukiewicz, piotr klimczak, marcin marciniszyn, marek plawgo | 3:03.69 | none | | 10 | 11 | 2 | ukraine | volodymyr demchenko, yevgeniy zyukov, myhaylo knysh, andriy tverdostup | 3:04.01 | none | | 11 | 12 | 1 | greece | stilianos dimotsios, anastasios gousis, panagiotis sarris, periklis iakovakis | 3:04.27 | sb | | 12 | 13 | 1 | france | ahmed douhou, ibrahima wade, abderrahim el haouzy, leslie djhone | 3:04.39 | none | | 13 | 14 | 2 | spain | eduardo ivan rodriguez, david canal, luis flores, antonio manuel reina | 3:05.03 | sb | | 14 | none | 2 | south africa | marcus la grange, hendrick mokganyetsi, ockert cilliers, arnaud malherbe | dnf | none | | 15 | none | 1 | jamaica | michael campbell, michael blackwood, jermaine gonzales, davian clarke | dsq | none |

| | nation | |---:|:---------| | 0 | germany |

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select round where method = 'unanimous decision' col : record | date | result | opponent | location | method | round row 1 : 13-0 | 2013-07-12 00:00:00 | win | igor pylypenko | porsche arena, stuttgart, germany | unanimous decision | 6 row 2 : 12-0 | 2013-10-27 00:00:00 | win | alphonce mchumiatumbo | sarajevo, bosnia and herzegovina | decision | 8 row 3 : 11-0 | 2013-06-07 00:00:00 | win | alexander vasiliev | westfalenhalle, dortmund, germany | tko | 2 row 4 : 10-0 | 2013-02-02 00:00:00 | win | niko falin | iss dome, dusseldorf, germany | unanimous decision | 6 row 5 : 9-0 | 2012-02-12 00:00:00 | win | ladislav kovarik | esprit arena, dusseldorf, germany | unanimous decision | 6 row 6 : 8-0 | 2012-06-08 00:00:00 | win | ivica perkovic | sarajevo, bosnia and herzegovina | unanimous decision | 12 row 7 : 7-0 | 2012-04-13 00:00:00 | win | aliaksandr makaranka | lanxess arena, cologne, germany | ko | 1 row 8 : 6-0 | 2011-12-17 00:00:00 | win | ferenc zsalek | sarajevo, bosnia and herzegovina | ko | 3 row 9 : 5-0 | 2011-12-02 00:00:00 | win | liridon memishi | sap arena, mannheim, germany | unanimous decision | 6 row 10 : 4-0 | 2011-06-25 00:00:00 | win | werner kreiskott | lanxess arena, cologne, germany | unanimous decision | 6 row 11 : 3-0 | 2011-02-19 00:00:00 | win | ergin solmaz | porsche arena, stuttgart, germany | unanimous decision | 4 row 12 : 2-0 | 2004-09-03 00:00:00 | win | tomasz zeprzalka | gorazde, bosnia and herzegovina | tko | 2 row 13 : 1-0 | 2004-02-07 00:00:00 | win | ergin solmaz | sarajevo, bosnia and herzegovina | unanimous decision | 4

col : round row 1 : 6 row 2 : 6 row 3 : 6 row 4 : 12 row 5 : 6 row 6 : 6 row 7 : 4 row 8 : 4

select round where method = 'unanimous decision' <table_name> : table \begin{tabular}{llllllll} \toprule & record & date & result & opponent & location & method & round \\ \midrule 0 & 13-0 & 2013-07-12 00:00:00 & win & igor pylypenko & porsche arena, stuttgart, germany & unanimous decision & 6 \\ 1 & 12-0 & 2013-10-27 00:00:00 & win & alphonce mchumiatumbo & sarajevo, bosnia and herzegovina & decision & 8 \\ 2 & 11-0 & 2013-06-07 00:00:00 & win & alexander vasiliev & westfalenhalle, dortmund, germany & tko & 2 \\ 3 & 10-0 & 2013-02-02 00:00:00 & win & niko falin & iss dome, dusseldorf, germany & unanimous decision & 6 \\ 4 & 9-0 & 2012-02-12 00:00:00 & win & ladislav kovarik & esprit arena, dusseldorf, germany & unanimous decision & 6 \\ 5 & 8-0 & 2012-06-08 00:00:00 & win & ivica perkovic & sarajevo, bosnia and herzegovina & unanimous decision & 12 \\ 6 & 7-0 & 2012-04-13 00:00:00 & win & aliaksandr makaranka & lanxess arena, cologne, germany & ko & 1 \\ 7 & 6-0 & 2011-12-17 00:00:00 & win & ferenc zsalek & sarajevo, bosnia and herzegovina & ko & 3 \\ 8 & 5-0 & 2011-12-02 00:00:00 & win & liridon memishi & sap arena, mannheim, germany & unanimous decision & 6 \\ 9 & 4-0 & 2011-06-25 00:00:00 & win & werner kreiskott & lanxess arena, cologne, germany & unanimous decision & 6 \\ 10 & 3-0 & 2011-02-19 00:00:00 & win & ergin solmaz & porsche arena, stuttgart, germany & unanimous decision & 4 \\ 11 & 2-0 & 2004-09-03 00:00:00 & win & tomasz zeprzalka & gorazde, bosnia and herzegovina & tko & 2 \\ 12 & 1-0 & 2004-02-07 00:00:00 & win & ergin solmaz & sarajevo, bosnia and herzegovina & unanimous decision & 4 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & round \\ \midrule 0 & 6 \\ 1 & 6 \\ 2 & 6 \\ 3 & 12 \\ 4 & 6 \\ 5 & 6 \\ 6 & 4 \\ 7 & 4 \\ \bottomrule \end{tabular}

select round where method = 'unanimous decision' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>record</th> <th>date</th> <th>result</th> <th>opponent</th> <th>location</th> <th>method</th> <th>round</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>13-0</td> <td>2013-07-12 00:00:00</td> <td>win</td> <td>igor pylypenko</td> <td>porsche arena, stuttgart, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>1</th> <td>12-0</td> <td>2013-10-27 00:00:00</td> <td>win</td> <td>alphonce mchumiatumbo</td> <td>sarajevo, bosnia and herzegovina</td> <td>decision</td> <td>8</td> </tr> <tr> <th>2</th> <td>11-0</td> <td>2013-06-07 00:00:00</td> <td>win</td> <td>alexander vasiliev</td> <td>westfalenhalle, dortmund, germany</td> <td>tko</td> <td>2</td> </tr> <tr> <th>3</th> <td>10-0</td> <td>2013-02-02 00:00:00</td> <td>win</td> <td>niko falin</td> <td>iss dome, dusseldorf, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>4</th> <td>9-0</td> <td>2012-02-12 00:00:00</td> <td>win</td> <td>ladislav kovarik</td> <td>esprit arena, dusseldorf, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>5</th> <td>8-0</td> <td>2012-06-08 00:00:00</td> <td>win</td> <td>ivica perkovic</td> <td>sarajevo, bosnia and herzegovina</td> <td>unanimous decision</td> <td>12</td> </tr> <tr> <th>6</th> <td>7-0</td> <td>2012-04-13 00:00:00</td> <td>win</td> <td>aliaksandr makaranka</td> <td>lanxess arena, cologne, germany</td> <td>ko</td> <td>1</td> </tr> <tr> <th>7</th> <td>6-0</td> <td>2011-12-17 00:00:00</td> <td>win</td> <td>ferenc zsalek</td> <td>sarajevo, bosnia and herzegovina</td> <td>ko</td> <td>3</td> </tr> <tr> <th>8</th> <td>5-0</td> <td>2011-12-02 00:00:00</td> <td>win</td> <td>liridon memishi</td> <td>sap arena, mannheim, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>9</th> <td>4-0</td> <td>2011-06-25 00:00:00</td> <td>win</td> <td>werner kreiskott</td> <td>lanxess arena, cologne, germany</td> <td>unanimous decision</td> <td>6</td> </tr> <tr> <th>10</th> <td>3-0</td> <td>2011-02-19 00:00:00</td> <td>win</td> <td>ergin solmaz</td> <td>porsche arena, stuttgart, germany</td> <td>unanimous decision</td> <td>4</td> </tr> <tr> <th>11</th> <td>2-0</td> <td>2004-09-03 00:00:00</td> <td>win</td> <td>tomasz zeprzalka</td> <td>gorazde, bosnia and herzegovina</td> <td>tko</td> <td>2</td> </tr> <tr> <th>12</th> <td>1-0</td> <td>2004-02-07 00:00:00</td> <td>win</td> <td>ergin solmaz</td> <td>sarajevo, bosnia and herzegovina</td> <td>unanimous decision</td> <td>4</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>round</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>6</td> </tr> <tr> <th>1</th> <td>6</td> </tr> <tr> <th>2</th> <td>6</td> </tr> <tr> <th>3</th> <td>12</td> </tr> <tr> <th>4</th> <td>6</td> </tr> <tr> <th>5</th> <td>6</td> </tr> <tr> <th>6</th> <td>4</td> </tr> <tr> <th>7</th> <td>4</td> </tr> </tbody> </table>

select round where method = 'unanimous decision' <table_name> : table | | record | date | result | opponent | location | method | round | |---:|:---------|:--------------------|:---------|:----------------------|:----------------------------------|:-------------------|--------:| | 0 | 13-0 | 2013-07-12 00:00:00 | win | igor pylypenko | porsche arena, stuttgart, germany | unanimous decision | 6 | | 1 | 12-0 | 2013-10-27 00:00:00 | win | alphonce mchumiatumbo | sarajevo, bosnia and herzegovina | decision | 8 | | 2 | 11-0 | 2013-06-07 00:00:00 | win | alexander vasiliev | westfalenhalle, dortmund, germany | tko | 2 | | 3 | 10-0 | 2013-02-02 00:00:00 | win | niko falin | iss dome, dusseldorf, germany | unanimous decision | 6 | | 4 | 9-0 | 2012-02-12 00:00:00 | win | ladislav kovarik | esprit arena, dusseldorf, germany | unanimous decision | 6 | | 5 | 8-0 | 2012-06-08 00:00:00 | win | ivica perkovic | sarajevo, bosnia and herzegovina | unanimous decision | 12 | | 6 | 7-0 | 2012-04-13 00:00:00 | win | aliaksandr makaranka | lanxess arena, cologne, germany | ko | 1 | | 7 | 6-0 | 2011-12-17 00:00:00 | win | ferenc zsalek | sarajevo, bosnia and herzegovina | ko | 3 | | 8 | 5-0 | 2011-12-02 00:00:00 | win | liridon memishi | sap arena, mannheim, germany | unanimous decision | 6 | | 9 | 4-0 | 2011-06-25 00:00:00 | win | werner kreiskott | lanxess arena, cologne, germany | unanimous decision | 6 | | 10 | 3-0 | 2011-02-19 00:00:00 | win | ergin solmaz | porsche arena, stuttgart, germany | unanimous decision | 4 | | 11 | 2-0 | 2004-09-03 00:00:00 | win | tomasz zeprzalka | gorazde, bosnia and herzegovina | tko | 2 | | 12 | 1-0 | 2004-02-07 00:00:00 | win | ergin solmaz | sarajevo, bosnia and herzegovina | unanimous decision | 4 |

| | round | |---:|--------:| | 0 | 6 | | 1 | 6 | | 2 | 6 | | 3 | 12 | | 4 | 6 | | 5 | 6 | | 6 | 4 | | 7 | 4 |

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col : count ( "japanese title" ) row 1 : 2

select count ( japanese title ) where year > 2010 <table_name> : table \begin{tabular}{llllll} \toprule & year & japanese title & english title & role & network \\ \midrule 0 & 1997 & あくり & agri & none & nhk \\ 1 & 1998 & ラフアントヒース & love & peace & yohei horiguchi & ntv \\ 2 & 2001 & ネハーラント & neverland & osamu seto & tbs \\ 3 & 2002 & hito ni yasashiku (人にやさしく / 3ヒース ) & be nice to people & yusuke & fuji tv \\ 4 & 2002 & engimono (演技者) & acting by & hachida & fuji tv \\ 5 & 2004 & kino wa tomo kyo no teki & none & none & none \\ 6 & 2005 & dekabeya (六本木おかしな捜査班) & funny roppongi squad & yukio ochi & tv asahi \\ 7 & 2005 & asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ) & to asuka and to the unseen child & sawamura kazuya & fuji tv \\ 8 & 2005 & nemureru mori no shitai (眠れる森の死体) & sleeping corpse & eiji/yamazaki & fuji tv \\ 9 & 2006 & アキハハラ@deep & akihabara@deep & box & tbs \\ 10 & 2007 & hana yori dango returns & boys over flowers 2 & junpei oribe & tbs \\ 11 & 2007 & hanazakari no kimitachi e & ikemen paradise & shuichi nakatsu & fuji tv \\ 12 & 2008 & hachimitsu to clover (ハチミツとクローハー) & honey & clover & yuta takemoto & fuji tv \\ 13 & 2008 & hanazakari no kimitachi e & ikemen paradise & shuichi nakatsu & fuji tv \\ 14 & 2008 & mao & devil & naoto serizawa & tbs \\ 15 & 2009 & inochi naki mono no koe (ウォイス) & voice & ryosuke ishimatsu & fuji tv \\ 16 & 2009 & majo saiban (魔女裁判) & the witch trial & toru yoshioka & fuji tv \\ 17 & 2009 & yonimo \"kim\" yo na monogatari & the law of recycling suicides & r 8427 & none \\ 18 & 2010 & unobore deka (うぬほれ刑事) & conceited detective & sadame honjo & tbs \\ 19 & 2010 & kyuukei no kouya & spherical wilderness & shoichi soeda & fuji tv \\ 20 & 2012 & osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~) & late blooming sunflower -my life renewed- & jotaro kodaira & fuji tv \\ 21 & 2014 & gunshi kanbei & none & dom justo takayama & nhk \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "japanese title" ) \\ \midrule 0 & 2 \\ \bottomrule \end{tabular}

select count ( japanese title ) where year > 2010 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>japanese title</th> <th>english title</th> <th>role</th> <th>network</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1997</td> <td>あくり</td> <td>agri</td> <td>none</td> <td>nhk</td> </tr> <tr> <th>1</th> <td>1998</td> <td>ラフアントヒース</td> <td>love & peace</td> <td>yohei horiguchi</td> <td>ntv</td> </tr> <tr> <th>2</th> <td>2001</td> <td>ネハーラント</td> <td>neverland</td> <td>osamu seto</td> <td>tbs</td> </tr> <tr> <th>3</th> <td>2002</td> <td>hito ni yasashiku (人にやさしく / 3ヒース )</td> <td>be nice to people</td> <td>yusuke</td> <td>fuji tv</td> </tr> <tr> <th>4</th> <td>2002</td> <td>engimono (演技者)</td> <td>acting by</td> <td>hachida</td> <td>fuji tv</td> </tr> <tr> <th>5</th> <td>2004</td> <td>kino wa tomo kyo no teki</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>6</th> <td>2005</td> <td>dekabeya (六本木おかしな捜査班)</td> <td>funny roppongi squad</td> <td>yukio ochi</td> <td>tv asahi</td> </tr> <tr> <th>7</th> <td>2005</td> <td>asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ)</td> <td>to asuka and to the unseen child</td> <td>sawamura kazuya</td> <td>fuji tv</td> </tr> <tr> <th>8</th> <td>2005</td> <td>nemureru mori no shitai (眠れる森の死体)</td> <td>sleeping corpse</td> <td>eiji/yamazaki</td> <td>fuji tv</td> </tr> <tr> <th>9</th> <td>2006</td> <td>アキハハラ@deep</td> <td>akihabara@deep</td> <td>box</td> <td>tbs</td> </tr> <tr> <th>10</th> <td>2007</td> <td>hana yori dango returns</td> <td>boys over flowers 2</td> <td>junpei oribe</td> <td>tbs</td> </tr> <tr> <th>11</th> <td>2007</td> <td>hanazakari no kimitachi e</td> <td>ikemen paradise</td> <td>shuichi nakatsu</td> <td>fuji tv</td> </tr> <tr> <th>12</th> <td>2008</td> <td>hachimitsu to clover (ハチミツとクローハー)</td> <td>honey & clover</td> <td>yuta takemoto</td> <td>fuji tv</td> </tr> <tr> <th>13</th> <td>2008</td> <td>hanazakari no kimitachi e</td> <td>ikemen paradise</td> <td>shuichi nakatsu</td> <td>fuji tv</td> </tr> <tr> <th>14</th> <td>2008</td> <td>mao</td> <td>devil</td> <td>naoto serizawa</td> <td>tbs</td> </tr> <tr> <th>15</th> <td>2009</td> <td>inochi naki mono no koe (ウォイス)</td> <td>voice</td> <td>ryosuke ishimatsu</td> <td>fuji tv</td> </tr> <tr> <th>16</th> <td>2009</td> <td>majo saiban (魔女裁判)</td> <td>the witch trial</td> <td>toru yoshioka</td> <td>fuji tv</td> </tr> <tr> <th>17</th> <td>2009</td> <td>yonimo \"kim\" yo na monogatari</td> <td>the law of recycling suicides</td> <td>r 8427</td> <td>none</td> </tr> <tr> <th>18</th> <td>2010</td> <td>unobore deka (うぬほれ刑事)</td> <td>conceited detective</td> <td>sadame honjo</td> <td>tbs</td> </tr> <tr> <th>19</th> <td>2010</td> <td>kyuukei no kouya</td> <td>spherical wilderness</td> <td>shoichi soeda</td> <td>fuji tv</td> </tr> <tr> <th>20</th> <td>2012</td> <td>osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~)</td> <td>late blooming sunflower -my life renewed-</td> <td>jotaro kodaira</td> <td>fuji tv</td> </tr> <tr> <th>21</th> <td>2014</td> <td>gunshi kanbei</td> <td>none</td> <td>dom justo takayama</td> <td>nhk</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "japanese title" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2</td> </tr> </tbody> </table>

select count ( japanese title ) where year > 2010 <table_name> : table | | year | japanese title | english title | role | network | |---:|-------:|:--------------------------------------------------------------------------------------------|:------------------------------------------|:-------------------|:----------| | 0 | 1997 | あくり | agri | none | nhk | | 1 | 1998 | ラフアントヒース | love & peace | yohei horiguchi | ntv | | 2 | 2001 | ネハーラント | neverland | osamu seto | tbs | | 3 | 2002 | hito ni yasashiku (人にやさしく / 3ヒース ) | be nice to people | yusuke | fuji tv | | 4 | 2002 | engimono (演技者) | acting by | hachida | fuji tv | | 5 | 2004 | kino wa tomo kyo no teki | none | none | none | | 6 | 2005 | dekabeya (六本木おかしな捜査班) | funny roppongi squad | yukio ochi | tv asahi | | 7 | 2005 | asuka e, soshite mada minu ko e (飛鳥へ、そしてまた見ぬ子へ) | to asuka and to the unseen child | sawamura kazuya | fuji tv | | 8 | 2005 | nemureru mori no shitai (眠れる森の死体) | sleeping corpse | eiji/yamazaki | fuji tv | | 9 | 2006 | アキハハラ@deep | akihabara@deep | box | tbs | | 10 | 2007 | hana yori dango returns | boys over flowers 2 | junpei oribe | tbs | | 11 | 2007 | hanazakari no kimitachi e | ikemen paradise | shuichi nakatsu | fuji tv | | 12 | 2008 | hachimitsu to clover (ハチミツとクローハー) | honey & clover | yuta takemoto | fuji tv | | 13 | 2008 | hanazakari no kimitachi e | ikemen paradise | shuichi nakatsu | fuji tv | | 14 | 2008 | mao | devil | naoto serizawa | tbs | | 15 | 2009 | inochi naki mono no koe (ウォイス) | voice | ryosuke ishimatsu | fuji tv | | 16 | 2009 | majo saiban (魔女裁判) | the witch trial | toru yoshioka | fuji tv | | 17 | 2009 | yonimo \"kim\" yo na monogatari | the law of recycling suicides | r 8427 | none | | 18 | 2010 | unobore deka (うぬほれ刑事) | conceited detective | sadame honjo | tbs | | 19 | 2010 | kyuukei no kouya | spherical wilderness | shoichi soeda | fuji tv | | 20 | 2012 | osozaki no himawari ~boku no jinsei, renewal~ (遅咲きのヒマワリ ~ホクの人生、リニューアル~) | late blooming sunflower -my life renewed- | jotaro kodaira | fuji tv | | 21 | 2014 | gunshi kanbei | none | dom justo takayama | nhk |

| | count ( "japanese title" ) | |---:|-----------------------------:| | 0 | 2 |

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col : year row 1 : 1973 row 2 : 1973

select year where label = 'emi' <table_name> : table \begin{tabular}{llllll} \toprule & year & title & label & uk singles chart & u.s. billboard hot 100 chart \\ \midrule 0 & 1969 & "melting pot" & philips & 3 & none \\ 1 & 1970 & "good morning freedom" & philips & 10 & none \\ 2 & 1970 & "our world" & philips & 17 & 64 \\ 3 & 1971 & "the banner man" & regal zonophone & 3 & none \\ 4 & 1972 & "stay with me" & regal zonophone & 11 & none \\ 5 & 1973 & "by the devil (i was tempted)" & emi & 26 & none \\ 6 & 1973 & "randy" & emi & 9 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & year \\ \midrule 0 & 1973 \\ 1 & 1973 \\ \bottomrule \end{tabular}

select year where label = 'emi' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>title</th> <th>label</th> <th>uk singles chart</th> <th>u.s. billboard hot 100 chart</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1969</td> <td>"melting pot"</td> <td>philips</td> <td>3</td> <td>none</td> </tr> <tr> <th>1</th> <td>1970</td> <td>"good morning freedom"</td> <td>philips</td> <td>10</td> <td>none</td> </tr> <tr> <th>2</th> <td>1970</td> <td>"our world"</td> <td>philips</td> <td>17</td> <td>64</td> </tr> <tr> <th>3</th> <td>1971</td> <td>"the banner man"</td> <td>regal zonophone</td> <td>3</td> <td>none</td> </tr> <tr> <th>4</th> <td>1972</td> <td>"stay with me"</td> <td>regal zonophone</td> <td>11</td> <td>none</td> </tr> <tr> <th>5</th> <td>1973</td> <td>"by the devil (i was tempted)"</td> <td>emi</td> <td>26</td> <td>none</td> </tr> <tr> <th>6</th> <td>1973</td> <td>"randy"</td> <td>emi</td> <td>9</td> <td>none</td> </tr> </tbody> </table>

select year where label = 'emi' <table_name> : table | | year | title | label | uk singles chart | u.s. billboard hot 100 chart | |---:|-------:|:-------------------------------|:----------------|-------------------:|:-------------------------------| | 0 | 1969 | "melting pot" | philips | 3 | none | | 1 | 1970 | "good morning freedom" | philips | 10 | none | | 2 | 1970 | "our world" | philips | 17 | 64 | | 3 | 1971 | "the banner man" | regal zonophone | 3 | none | | 4 | 1972 | "stay with me" | regal zonophone | 11 | none | | 5 | 1973 | "by the devil (i was tempted)" | emi | 26 | none | | 6 | 1973 | "randy" | emi | 9 | none |

| | year | |---:|-------:| | 0 | 1973 | | 1 | 1973 |

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col : sum ( "competition" ) row 1 : 0

select sum ( competition ) where venue = 'osaka, japan' <table_name> : table \begin{tabular}{lllllll} \toprule & year & competition & venue & position & event & notes \\ \midrule 0 & 1998 & turin marathon & turin, italy & 3rd & marathon & 2:12:59 \\ 1 & 2003 & lisbon marathon & lisbon, portugal & 1st & marathon & 2:15:31 \\ 2 & 2004 & vienna marathon & vienna, austria & 3rd & marathon & 2:11:24 \\ 3 & 2004 & berlin marathon & berlin, germany & 5th & marathon & 2:09:08 \\ 4 & 2005 & world championships & helsinki, finland & 18th & marathon & 2:16:33 \\ 5 & 2006 & paris marathon & paris, france & 4th & marathon & 2:08:55 \\ 6 & 2006 & lisbon marathon & lisbon, portugal & 1st & marathon & 2:21:08 \\ 7 & 2007 & world championships & osaka, japan & none & marathon & dns \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & sum ( "competition" ) \\ \midrule 0 & 0 \\ \bottomrule \end{tabular}

select sum ( competition ) where venue = 'osaka, japan' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>year</th> <th>competition</th> <th>venue</th> <th>position</th> <th>event</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1998</td> <td>turin marathon</td> <td>turin, italy</td> <td>3rd</td> <td>marathon</td> <td>2:12:59</td> </tr> <tr> <th>1</th> <td>2003</td> <td>lisbon marathon</td> <td>lisbon, portugal</td> <td>1st</td> <td>marathon</td> <td>2:15:31</td> </tr> <tr> <th>2</th> <td>2004</td> <td>vienna marathon</td> <td>vienna, austria</td> <td>3rd</td> <td>marathon</td> <td>2:11:24</td> </tr> <tr> <th>3</th> <td>2004</td> <td>berlin marathon</td> <td>berlin, germany</td> <td>5th</td> <td>marathon</td> <td>2:09:08</td> </tr> <tr> <th>4</th> <td>2005</td> <td>world championships</td> <td>helsinki, finland</td> <td>18th</td> <td>marathon</td> <td>2:16:33</td> </tr> <tr> <th>5</th> <td>2006</td> <td>paris marathon</td> <td>paris, france</td> <td>4th</td> <td>marathon</td> <td>2:08:55</td> </tr> <tr> <th>6</th> <td>2006</td> <td>lisbon marathon</td> <td>lisbon, portugal</td> <td>1st</td> <td>marathon</td> <td>2:21:08</td> </tr> <tr> <th>7</th> <td>2007</td> <td>world championships</td> <td>osaka, japan</td> <td>none</td> <td>marathon</td> <td>dns</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>sum ( "competition" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0</td> </tr> </tbody> </table>

select sum ( competition ) where venue = 'osaka, japan' <table_name> : table | | year | competition | venue | position | event | notes | |---:|-------:|:--------------------|:------------------|:-----------|:---------|:--------| | 0 | 1998 | turin marathon | turin, italy | 3rd | marathon | 2:12:59 | | 1 | 2003 | lisbon marathon | lisbon, portugal | 1st | marathon | 2:15:31 | | 2 | 2004 | vienna marathon | vienna, austria | 3rd | marathon | 2:11:24 | | 3 | 2004 | berlin marathon | berlin, germany | 5th | marathon | 2:09:08 | | 4 | 2005 | world championships | helsinki, finland | 18th | marathon | 2:16:33 | | 5 | 2006 | paris marathon | paris, france | 4th | marathon | 2:08:55 | | 6 | 2006 | lisbon marathon | lisbon, portugal | 1st | marathon | 2:21:08 | | 7 | 2007 | world championships | osaka, japan | none | marathon | dns |

| | sum ( "competition" ) | |---:|------------------------:| | 0 | 0 |

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select package where flash size = '4k' col : chip | flash size | eeprom | sram | frequency [mhz] | package row 1 : at90s1200 | 1k | 64 | 0 | 12 | pdip-20 row 2 : at90s2313 | 2k | 128 | 128 | 10 | pdip-20 row 3 : at90s/ls2323 | 2k | 128 | 128 | 10 | pdip-8 row 4 : at90s/ls2343 | 2k | 128 | 128 | 10 | pdip-8 row 5 : at90s4414 | 4k | 256 | 256 | 8 | pdip-40 row 6 : at90s/ls4434 | 4k | 256 | 256 | 8 | pdip-40 row 7 : at90s8515 | 8k | 512 | 512 | 8 | pdip-40 row 8 : at90s/ls8535 | 8k | 512 | 512 | 8 | pdip-40

col : package row 1 : pdip-40 row 2 : pdip-40

select package where flash size = '4k' <table_name> : table \begin{tabular}{lllllll} \toprule & chip & flash size & eeprom & sram & frequency [mhz] & package \\ \midrule 0 & at90s1200 & 1k & 64 & 0 & 12 & pdip-20 \\ 1 & at90s2313 & 2k & 128 & 128 & 10 & pdip-20 \\ 2 & at90s/ls2323 & 2k & 128 & 128 & 10 & pdip-8 \\ 3 & at90s/ls2343 & 2k & 128 & 128 & 10 & pdip-8 \\ 4 & at90s4414 & 4k & 256 & 256 & 8 & pdip-40 \\ 5 & at90s/ls4434 & 4k & 256 & 256 & 8 & pdip-40 \\ 6 & at90s8515 & 8k & 512 & 512 & 8 & pdip-40 \\ 7 & at90s/ls8535 & 8k & 512 & 512 & 8 & pdip-40 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & package \\ \midrule 0 & pdip-40 \\ 1 & pdip-40 \\ \bottomrule \end{tabular}

select package where flash size = '4k' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>chip</th> <th>flash size</th> <th>eeprom</th> <th>sram</th> <th>frequency [mhz]</th> <th>package</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>at90s1200</td> <td>1k</td> <td>64</td> <td>0</td> <td>12</td> <td>pdip-20</td> </tr> <tr> <th>1</th> <td>at90s2313</td> <td>2k</td> <td>128</td> <td>128</td> <td>10</td> <td>pdip-20</td> </tr> <tr> <th>2</th> <td>at90s/ls2323</td> <td>2k</td> <td>128</td> <td>128</td> <td>10</td> <td>pdip-8</td> </tr> <tr> <th>3</th> <td>at90s/ls2343</td> <td>2k</td> <td>128</td> <td>128</td> <td>10</td> <td>pdip-8</td> </tr> <tr> <th>4</th> <td>at90s4414</td> <td>4k</td> <td>256</td> <td>256</td> <td>8</td> <td>pdip-40</td> </tr> <tr> <th>5</th> <td>at90s/ls4434</td> <td>4k</td> <td>256</td> <td>256</td> <td>8</td> <td>pdip-40</td> </tr> <tr> <th>6</th> <td>at90s8515</td> <td>8k</td> <td>512</td> <td>512</td> <td>8</td> <td>pdip-40</td> </tr> <tr> <th>7</th> <td>at90s/ls8535</td> <td>8k</td> <td>512</td> <td>512</td> <td>8</td> <td>pdip-40</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>package</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>pdip-40</td> </tr> <tr> <th>1</th> <td>pdip-40</td> </tr> </tbody> </table>

select package where flash size = '4k' <table_name> : table | | chip | flash size | eeprom | sram | frequency [mhz] | package | |---:|:-------------|:-------------|---------:|-------:|------------------:|:----------| | 0 | at90s1200 | 1k | 64 | 0 | 12 | pdip-20 | | 1 | at90s2313 | 2k | 128 | 128 | 10 | pdip-20 | | 2 | at90s/ls2323 | 2k | 128 | 128 | 10 | pdip-8 | | 3 | at90s/ls2343 | 2k | 128 | 128 | 10 | pdip-8 | | 4 | at90s4414 | 4k | 256 | 256 | 8 | pdip-40 | | 5 | at90s/ls4434 | 4k | 256 | 256 | 8 | pdip-40 | | 6 | at90s8515 | 8k | 512 | 512 | 8 | pdip-40 | | 7 | at90s/ls8535 | 8k | 512 | 512 | 8 | pdip-40 |

| | package | |---:|:----------| | 0 | pdip-40 | | 1 | pdip-40 |

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col : count ( "*" ) row 1 : 7

select count ( * ) where partner = 'jim mcmanus' <table_name> : table \begin{tabular}{lllllllll} \toprule & outcome & no. & date & tournament & surface & partner & opponents in the final & score in the final \\ \midrule 0 & runner-up & 1 & 1969 & los angeles, u.s & hard & jim mcmanus & pancho gonzales ron holmberg & 3-6, 4-6 \\ 1 & runner-up & 2 & 1970 & merion, u.s & hard & jim mcmanus & william bowrey ray ruffels & 6-3, 2-6, 5-7 \\ 2 & winner & 1 & 1971 & columbus, u.s & hard & jim mcmanus & jimmy connors roscoe tanner & 4-6, 7-5, 6-2 \\ 3 & winner & 2 & 1971 & merion, u.s & hard & clark graebner & robert mckinley dick stockton & 7-6, 6-3 \\ 4 & winner & 3 & 1971 & sacramento, u.s & hard & jim mcmanus & bob maud frew mcmillan & 7-6, 6-3 \\ 5 & winner & 4 & 1972 & los angeles, u.s & outdoor & jim mcmanus & ilie nastase ion tiriac & 6-2, 5-7, 6-4 \\ 6 & winner & 5 & 1972 & london/queen's club, england & grass & jim mcmanus & jurgen fassbender karl meiler & 4-6, 6-3, 7-5 \\ 7 & runner-up & 3 & 1972 & tanglewood, u.s & other & jim mcmanus & bob hewitt andrew pattison & 4-6, 4-6 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 7 \\ \bottomrule \end{tabular}

select count ( * ) where partner = 'jim mcmanus' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>outcome</th> <th>no.</th> <th>date</th> <th>tournament</th> <th>surface</th> <th>partner</th> <th>opponents in the final</th> <th>score in the final</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>runner-up</td> <td>1</td> <td>1969</td> <td>los angeles, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>pancho gonzales ron holmberg</td> <td>3-6, 4-6</td> </tr> <tr> <th>1</th> <td>runner-up</td> <td>2</td> <td>1970</td> <td>merion, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>william bowrey ray ruffels</td> <td>6-3, 2-6, 5-7</td> </tr> <tr> <th>2</th> <td>winner</td> <td>1</td> <td>1971</td> <td>columbus, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>jimmy connors roscoe tanner</td> <td>4-6, 7-5, 6-2</td> </tr> <tr> <th>3</th> <td>winner</td> <td>2</td> <td>1971</td> <td>merion, u.s</td> <td>hard</td> <td>clark graebner</td> <td>robert mckinley dick stockton</td> <td>7-6, 6-3</td> </tr> <tr> <th>4</th> <td>winner</td> <td>3</td> <td>1971</td> <td>sacramento, u.s</td> <td>hard</td> <td>jim mcmanus</td> <td>bob maud frew mcmillan</td> <td>7-6, 6-3</td> </tr> <tr> <th>5</th> <td>winner</td> <td>4</td> <td>1972</td> <td>los angeles, u.s</td> <td>outdoor</td> <td>jim mcmanus</td> <td>ilie nastase ion tiriac</td> <td>6-2, 5-7, 6-4</td> </tr> <tr> <th>6</th> <td>winner</td> <td>5</td> <td>1972</td> <td>london/queen's club, england</td> <td>grass</td> <td>jim mcmanus</td> <td>jurgen fassbender karl meiler</td> <td>4-6, 6-3, 7-5</td> </tr> <tr> <th>7</th> <td>runner-up</td> <td>3</td> <td>1972</td> <td>tanglewood, u.s</td> <td>other</td> <td>jim mcmanus</td> <td>bob hewitt andrew pattison</td> <td>4-6, 4-6</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>7</td> </tr> </tbody> </table>

select count ( * ) where partner = 'jim mcmanus' <table_name> : table | | outcome | no. | date | tournament | surface | partner | opponents in the final | score in the final | |---:|:----------|------:|-------:|:-----------------------------|:----------|:---------------|:------------------------------|:---------------------| | 0 | runner-up | 1 | 1969 | los angeles, u.s | hard | jim mcmanus | pancho gonzales ron holmberg | 3-6, 4-6 | | 1 | runner-up | 2 | 1970 | merion, u.s | hard | jim mcmanus | william bowrey ray ruffels | 6-3, 2-6, 5-7 | | 2 | winner | 1 | 1971 | columbus, u.s | hard | jim mcmanus | jimmy connors roscoe tanner | 4-6, 7-5, 6-2 | | 3 | winner | 2 | 1971 | merion, u.s | hard | clark graebner | robert mckinley dick stockton | 7-6, 6-3 | | 4 | winner | 3 | 1971 | sacramento, u.s | hard | jim mcmanus | bob maud frew mcmillan | 7-6, 6-3 | | 5 | winner | 4 | 1972 | los angeles, u.s | outdoor | jim mcmanus | ilie nastase ion tiriac | 6-2, 5-7, 6-4 | | 6 | winner | 5 | 1972 | london/queen's club, england | grass | jim mcmanus | jurgen fassbender karl meiler | 4-6, 6-3, 7-5 | | 7 | runner-up | 3 | 1972 | tanglewood, u.s | other | jim mcmanus | bob hewitt andrew pattison | 4-6, 4-6 |

| | count ( "*" ) | |---:|----------------:| | 0 | 7 |

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select # where # = 14 col : # | name | birth and death | office started | office ended row 1 : 1 | geir vidalin | 27 october 1761 - 20 september 1823 | 1801 | 1823 row 2 : 2 | steingrimur jonsson | none | 1824 | 1845 row 3 : 3 | helgi thordersen | 8 april 1794 - 4 december 1867 | 1846 | 1866 row 4 : 4 | 'petur petursson | 3 october 1808 - 15 may 1891 | 1866 | 1889 row 5 : 5 | hallgrimur sveinsson | 5 april 1841 - 16 december 1909 | 1889 | 1908 row 6 : 6 | þorhallur bjarnarson | 2 december 1855 - 15 december 1916 | 1908 | 1916 row 7 : 7 | jon helgason | 1866 - 1942 | 1917 | 1939 row 8 : 8 | sigurgeir sigurðsson | 3 august 1890 - 13 october 1953 | 1939 | 1953 row 9 : 9 | asmundur guðmundsson | 6 october 1888 reykholt - 29 may 1969 reykjavik | 1954 | 1989 row 10 : 10 | sigurbjorn einarsson | 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik | 1959 | 1981 row 11 : 11 | petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) | 2 june 1919 - 3 june 2010 | 1981 | 1989 row 12 : 12 | olafur skulason | 29 december 1929 - 9 june 2008 | 1989 | 1997 row 13 : 13 | karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) | 5 february 1947 reykjavik | 1998 | 2012 row 14 : 14 | agnes sigurðardottir | 19 october 1954 isafjorður | 24 june 2012 | incumbent

col : # row 1 : 14

select # where # = 14 <table_name> : table \begin{tabular}{llllll} \toprule & # & name & birth and death & office started & office ended \\ \midrule 0 & 1 & geir vidalin & 27 october 1761 - 20 september 1823 & 1801 & 1823 \\ 1 & 2 & steingrimur jonsson & none & 1824 & 1845 \\ 2 & 3 & helgi thordersen & 8 april 1794 - 4 december 1867 & 1846 & 1866 \\ 3 & 4 & 'petur petursson & 3 october 1808 - 15 may 1891 & 1866 & 1889 \\ 4 & 5 & hallgrimur sveinsson & 5 april 1841 - 16 december 1909 & 1889 & 1908 \\ 5 & 6 & þorhallur bjarnarson & 2 december 1855 - 15 december 1916 & 1908 & 1916 \\ 6 & 7 & jon helgason & 1866 - 1942 & 1917 & 1939 \\ 7 & 8 & sigurgeir sigurðsson & 3 august 1890 - 13 october 1953 & 1939 & 1953 \\ 8 & 9 & asmundur guðmundsson & 6 october 1888 reykholt - 29 may 1969 reykjavik & 1954 & 1989 \\ 9 & 10 & sigurbjorn einarsson & 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik & 1959 & 1981 \\ 10 & 11 & petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) & 2 june 1919 - 3 june 2010 & 1981 & 1989 \\ 11 & 12 & olafur skulason & 29 december 1929 - 9 june 2008 & 1989 & 1997 \\ 12 & 13 & karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) & 5 february 1947 reykjavik & 1998 & 2012 \\ 13 & 14 & agnes sigurðardottir & 19 october 1954 isafjorður & 24 june 2012 & incumbent \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & # \\ \midrule 0 & 14 \\ \bottomrule \end{tabular}

select # where # = 14 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>#</th> <th>name</th> <th>birth and death</th> <th>office started</th> <th>office ended</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>geir vidalin</td> <td>27 october 1761 - 20 september 1823</td> <td>1801</td> <td>1823</td> </tr> <tr> <th>1</th> <td>2</td> <td>steingrimur jonsson</td> <td>none</td> <td>1824</td> <td>1845</td> </tr> <tr> <th>2</th> <td>3</td> <td>helgi thordersen</td> <td>8 april 1794 - 4 december 1867</td> <td>1846</td> <td>1866</td> </tr> <tr> <th>3</th> <td>4</td> <td>'petur petursson</td> <td>3 october 1808 - 15 may 1891</td> <td>1866</td> <td>1889</td> </tr> <tr> <th>4</th> <td>5</td> <td>hallgrimur sveinsson</td> <td>5 april 1841 - 16 december 1909</td> <td>1889</td> <td>1908</td> </tr> <tr> <th>5</th> <td>6</td> <td>þorhallur bjarnarson</td> <td>2 december 1855 - 15 december 1916</td> <td>1908</td> <td>1916</td> </tr> <tr> <th>6</th> <td>7</td> <td>jon helgason</td> <td>1866 - 1942</td> <td>1917</td> <td>1939</td> </tr> <tr> <th>7</th> <td>8</td> <td>sigurgeir sigurðsson</td> <td>3 august 1890 - 13 october 1953</td> <td>1939</td> <td>1953</td> </tr> <tr> <th>8</th> <td>9</td> <td>asmundur guðmundsson</td> <td>6 october 1888 reykholt - 29 may 1969 reykjavik</td> <td>1954</td> <td>1989</td> </tr> <tr> <th>9</th> <td>10</td> <td>sigurbjorn einarsson</td> <td>30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik</td> <td>1959</td> <td>1981</td> </tr> <tr> <th>10</th> <td>11</td> <td>petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland)</td> <td>2 june 1919 - 3 june 2010</td> <td>1981</td> <td>1989</td> </tr> <tr> <th>11</th> <td>12</td> <td>olafur skulason</td> <td>29 december 1929 - 9 june 2008</td> <td>1989</td> <td>1997</td> </tr> <tr> <th>12</th> <td>13</td> <td>karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland)</td> <td>5 february 1947 reykjavik</td> <td>1998</td> <td>2012</td> </tr> <tr> <th>13</th> <td>14</td> <td>agnes sigurðardottir</td> <td>19 october 1954 isafjorður</td> <td>24 june 2012</td> <td>incumbent</td> </tr> </tbody> </table>

select # where # = 14 <table_name> : table | | # | name | birth and death | office started | office ended | |---:|----:|:--------------------------------------------------------------------------|:----------------------------------------------------------------|:-----------------|:---------------| | 0 | 1 | geir vidalin | 27 october 1761 - 20 september 1823 | 1801 | 1823 | | 1 | 2 | steingrimur jonsson | none | 1824 | 1845 | | 2 | 3 | helgi thordersen | 8 april 1794 - 4 december 1867 | 1846 | 1866 | | 3 | 4 | 'petur petursson | 3 october 1808 - 15 may 1891 | 1866 | 1889 | | 4 | 5 | hallgrimur sveinsson | 5 april 1841 - 16 december 1909 | 1889 | 1908 | | 5 | 6 | þorhallur bjarnarson | 2 december 1855 - 15 december 1916 | 1908 | 1916 | | 6 | 7 | jon helgason | 1866 - 1942 | 1917 | 1939 | | 7 | 8 | sigurgeir sigurðsson | 3 august 1890 - 13 october 1953 | 1939 | 1953 | | 8 | 9 | asmundur guðmundsson | 6 october 1888 reykholt - 29 may 1969 reykjavik | 1954 | 1989 | | 9 | 10 | sigurbjorn einarsson | 30 june 1911 vestur-skaftafellssysla - 28 august 2008 reykjavik | 1959 | 1981 | | 10 | 11 | petur sigurgeirsson (son of sigurgeir sigurðsson, 8th bishop of iceland) | 2 june 1919 - 3 june 2010 | 1981 | 1989 | | 11 | 12 | olafur skulason | 29 december 1929 - 9 june 2008 | 1989 | 1997 | | 12 | 13 | karl sigurbjornsson (son of sigurbjorn einarsson, 10th bishop of iceland) | 5 february 1947 reykjavik | 1998 | 2012 | | 13 | 14 | agnes sigurðardottir | 19 october 1954 isafjorður | 24 june 2012 | incumbent |

| | # | |---:|----:| | 0 | 14 |

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select name where street address = 'central avenue southeast and main street southeast' col : name | street address | years as tallest | height ft (m) | floors row 1 : globe building | 4th street south | 1882-1886 | 157 (48) | 8 row 2 : lumber exchange building | 10 5th street south | 1886-1887 | 165 (50) | 12 row 3 : industrial exposition building | central avenue southeast and main street southeast | 1887-1890 | 240 (73) | 8 row 4 : metropolitan building | 308 2nd avenue south | 1890-1895 | 258 (79) | 12 row 5 : minneapolis city hall | 350 5th street south | 1895-1929 | 341 (104) | 14 row 6 : foshay tower | 821 marquette avenue | 1929-1973 | 448 (137) | 32 row 7 : ids tower | 80 8th street south | 1973-present | 792 (241) | 55

col : name row 1 : industrial exposition building

select name where street address = 'central avenue southeast and main street southeast' <table_name> : table \begin{tabular}{llllll} \toprule & name & street address & years as tallest & height ft (m) & floors \\ \midrule 0 & globe building & 4th street south & 1882-1886 & 157 (48) & 8 \\ 1 & lumber exchange building & 10 5th street south & 1886-1887 & 165 (50) & 12 \\ 2 & industrial exposition building & central avenue southeast and main street southeast & 1887-1890 & 240 (73) & 8 \\ 3 & metropolitan building & 308 2nd avenue south & 1890-1895 & 258 (79) & 12 \\ 4 & minneapolis city hall & 350 5th street south & 1895-1929 & 341 (104) & 14 \\ 5 & foshay tower & 821 marquette avenue & 1929-1973 & 448 (137) & 32 \\ 6 & ids tower & 80 8th street south & 1973-present & 792 (241) & 55 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & name \\ \midrule 0 & industrial exposition building \\ \bottomrule \end{tabular}

select name where street address = 'central avenue southeast and main street southeast' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> <th>street address</th> <th>years as tallest</th> <th>height ft (m)</th> <th>floors</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>globe building</td> <td>4th street south</td> <td>1882-1886</td> <td>157 (48)</td> <td>8</td> </tr> <tr> <th>1</th> <td>lumber exchange building</td> <td>10 5th street south</td> <td>1886-1887</td> <td>165 (50)</td> <td>12</td> </tr> <tr> <th>2</th> <td>industrial exposition building</td> <td>central avenue southeast and main street southeast</td> <td>1887-1890</td> <td>240 (73)</td> <td>8</td> </tr> <tr> <th>3</th> <td>metropolitan building</td> <td>308 2nd avenue south</td> <td>1890-1895</td> <td>258 (79)</td> <td>12</td> </tr> <tr> <th>4</th> <td>minneapolis city hall</td> <td>350 5th street south</td> <td>1895-1929</td> <td>341 (104)</td> <td>14</td> </tr> <tr> <th>5</th> <td>foshay tower</td> <td>821 marquette avenue</td> <td>1929-1973</td> <td>448 (137)</td> <td>32</td> </tr> <tr> <th>6</th> <td>ids tower</td> <td>80 8th street south</td> <td>1973-present</td> <td>792 (241)</td> <td>55</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>name</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>industrial exposition building</td> </tr> </tbody> </table>

select name where street address = 'central avenue southeast and main street southeast' <table_name> : table | | name | street address | years as tallest | height ft (m) | floors | |---:|:-------------------------------|:---------------------------------------------------|:-------------------|:----------------|---------:| | 0 | globe building | 4th street south | 1882-1886 | 157 (48) | 8 | | 1 | lumber exchange building | 10 5th street south | 1886-1887 | 165 (50) | 12 | | 2 | industrial exposition building | central avenue southeast and main street southeast | 1887-1890 | 240 (73) | 8 | | 3 | metropolitan building | 308 2nd avenue south | 1890-1895 | 258 (79) | 12 | | 4 | minneapolis city hall | 350 5th street south | 1895-1929 | 341 (104) | 14 | | 5 | foshay tower | 821 marquette avenue | 1929-1973 | 448 (137) | 32 | | 6 | ids tower | 80 8th street south | 1973-present | 792 (241) | 55 |

| | name | |---:|:-------------------------------| | 0 | industrial exposition building |

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select count ( 2.27 ) where rank < 3 col : rank | athlete | nationality | 2.15 | 2.2 | 2.24 | 2.27 | result | notes row 1 : 1 | yaroslav rybakov | russia | o | o | o | o | 2.27 | q row 2 : 1 | andriy sokolovskyy | ukraine | o | o | o | o | 2.27 | q row 3 : 1 | stefan holm | sweden | o | o | o | o | 2.27 | q row 4 : 1 | andrey tereshin | russia | o | o | o | o | 2.27 | q row 5 : 1 | victor moya | cuba | o | o | o | o | 2.27 | q, pb row 6 : 1 | linus thornblad | sweden | o | o | o | o | 2.27 | q row 7 : 7 | giulio ciotti | italy | o | o | o | xxx | 2.24 | q row 8 : 8 | robert wolski | poland | xo | o | o | xxx | 2.24 | q row 9 : 9 | ramsay carelse | south africa | xo | xo | o | xxx | 2.24 | none row 10 : 10 | tora harris | united states | o | o | xo | xxx | 2.24 | none row 11 : 10 | nicola ciotti | italy | o | o | xo | xxx | 2.24 | none row 12 : 10 | wojciech theiner | poland | o | o | xo | xxx | 2.24 | none row 13 : 13 | tomas janku | czech republic | o | o | xxo | xxx | 2.24 | none row 14 : 13 | mustapha raifak | france | o | o | xxo | xxx | 2.24 | none row 15 : 15 | svatoslav ton | czech republic | o | xo | xxx | none | 2.2 | none row 16 : 16 | adam shunk | united states | o | xxx | none | 2.15 | none | none row 17 : 16 | roman fricke | germany | o | xxx | none | 2.15 | none | none

col : count ( "2.27" ) row 1 : 14

select count ( 2.27 ) where rank < 3 <table_name> : table \begin{tabular}{llllllllll} \toprule & rank & athlete & nationality & 2.15 & 2.2 & 2.24 & 2.27 & result & notes \\ \midrule 0 & 1 & yaroslav rybakov & russia & o & o & o & o & 2.27 & q \\ 1 & 1 & andriy sokolovskyy & ukraine & o & o & o & o & 2.27 & q \\ 2 & 1 & stefan holm & sweden & o & o & o & o & 2.27 & q \\ 3 & 1 & andrey tereshin & russia & o & o & o & o & 2.27 & q \\ 4 & 1 & victor moya & cuba & o & o & o & o & 2.27 & q, pb \\ 5 & 1 & linus thornblad & sweden & o & o & o & o & 2.27 & q \\ 6 & 7 & giulio ciotti & italy & o & o & o & xxx & 2.24 & q \\ 7 & 8 & robert wolski & poland & xo & o & o & xxx & 2.24 & q \\ 8 & 9 & ramsay carelse & south africa & xo & xo & o & xxx & 2.24 & none \\ 9 & 10 & tora harris & united states & o & o & xo & xxx & 2.24 & none \\ 10 & 10 & nicola ciotti & italy & o & o & xo & xxx & 2.24 & none \\ 11 & 10 & wojciech theiner & poland & o & o & xo & xxx & 2.24 & none \\ 12 & 13 & tomas janku & czech republic & o & o & xxo & xxx & 2.24 & none \\ 13 & 13 & mustapha raifak & france & o & o & xxo & xxx & 2.24 & none \\ 14 & 15 & svatoslav ton & czech republic & o & xo & xxx & none & 2.2 & none \\ 15 & 16 & adam shunk & united states & o & xxx & none & 2.15 & none & none \\ 16 & 16 & roman fricke & germany & o & xxx & none & 2.15 & none & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "2.27" ) \\ \midrule 0 & 14 \\ \bottomrule \end{tabular}

select count ( 2.27 ) where rank < 3 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>athlete</th> <th>nationality</th> <th>2.15</th> <th>2.2</th> <th>2.24</th> <th>2.27</th> <th>result</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>yaroslav rybakov</td> <td>russia</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>1</th> <td>1</td> <td>andriy sokolovskyy</td> <td>ukraine</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>2</th> <td>1</td> <td>stefan holm</td> <td>sweden</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>3</th> <td>1</td> <td>andrey tereshin</td> <td>russia</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>4</th> <td>1</td> <td>victor moya</td> <td>cuba</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q, pb</td> </tr> <tr> <th>5</th> <td>1</td> <td>linus thornblad</td> <td>sweden</td> <td>o</td> <td>o</td> <td>o</td> <td>o</td> <td>2.27</td> <td>q</td> </tr> <tr> <th>6</th> <td>7</td> <td>giulio ciotti</td> <td>italy</td> <td>o</td> <td>o</td> <td>o</td> <td>xxx</td> <td>2.24</td> <td>q</td> </tr> <tr> <th>7</th> <td>8</td> <td>robert wolski</td> <td>poland</td> <td>xo</td> <td>o</td> <td>o</td> <td>xxx</td> <td>2.24</td> <td>q</td> </tr> <tr> <th>8</th> <td>9</td> <td>ramsay carelse</td> <td>south africa</td> <td>xo</td> <td>xo</td> <td>o</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>tora harris</td> <td>united states</td> <td>o</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>10</th> <td>10</td> <td>nicola ciotti</td> <td>italy</td> <td>o</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>11</th> <td>10</td> <td>wojciech theiner</td> <td>poland</td> <td>o</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>tomas janku</td> <td>czech republic</td> <td>o</td> <td>o</td> <td>xxo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>13</th> <td>13</td> <td>mustapha raifak</td> <td>france</td> <td>o</td> <td>o</td> <td>xxo</td> <td>xxx</td> <td>2.24</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>svatoslav ton</td> <td>czech republic</td> <td>o</td> <td>xo</td> <td>xxx</td> <td>none</td> <td>2.2</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>adam shunk</td> <td>united states</td> <td>o</td> <td>xxx</td> <td>none</td> <td>2.15</td> <td>none</td> <td>none</td> </tr> <tr> <th>16</th> <td>16</td> <td>roman fricke</td> <td>germany</td> <td>o</td> <td>xxx</td> <td>none</td> <td>2.15</td> <td>none</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "2.27" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>14</td> </tr> </tbody> </table>

select count ( 2.27 ) where rank < 3 <table_name> : table | | rank | athlete | nationality | 2.15 | 2.2 | 2.24 | 2.27 | result | notes | |---:|-------:|:-------------------|:---------------|:-------|:------|:-------|:-------|:---------|:--------| | 0 | 1 | yaroslav rybakov | russia | o | o | o | o | 2.27 | q | | 1 | 1 | andriy sokolovskyy | ukraine | o | o | o | o | 2.27 | q | | 2 | 1 | stefan holm | sweden | o | o | o | o | 2.27 | q | | 3 | 1 | andrey tereshin | russia | o | o | o | o | 2.27 | q | | 4 | 1 | victor moya | cuba | o | o | o | o | 2.27 | q, pb | | 5 | 1 | linus thornblad | sweden | o | o | o | o | 2.27 | q | | 6 | 7 | giulio ciotti | italy | o | o | o | xxx | 2.24 | q | | 7 | 8 | robert wolski | poland | xo | o | o | xxx | 2.24 | q | | 8 | 9 | ramsay carelse | south africa | xo | xo | o | xxx | 2.24 | none | | 9 | 10 | tora harris | united states | o | o | xo | xxx | 2.24 | none | | 10 | 10 | nicola ciotti | italy | o | o | xo | xxx | 2.24 | none | | 11 | 10 | wojciech theiner | poland | o | o | xo | xxx | 2.24 | none | | 12 | 13 | tomas janku | czech republic | o | o | xxo | xxx | 2.24 | none | | 13 | 13 | mustapha raifak | france | o | o | xxo | xxx | 2.24 | none | | 14 | 15 | svatoslav ton | czech republic | o | xo | xxx | none | 2.2 | none | | 15 | 16 | adam shunk | united states | o | xxx | none | 2.15 | none | none | | 16 | 16 | roman fricke | germany | o | xxx | none | 2.15 | none | none |

| | count ( "2.27" ) | |---:|-------------------:| | 0 | 14 |

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select count ( name ) where name = 'zoltan kiss' col : position | nation | number | name | soproni liga | uefa cup | hungarian cup | league cup | total row 1 : 1 | | 14 | gergely rudolf | 16 | 3 | 0 | 0 | 19 row 2 : 2 | | 41 | lorant olah | 12 | 1 | 0 | 0 | 13 row 3 : 3 | | 99 | omagbemi dudu | 4 | 1 | 5 | 0 | 10 row 4 : 4 | | 55 | peter szakaly | 9 | 0 | 0 | 0 | 9 row 5 : 5 | | 77 | peter czvitkovics | 7 | 0 | 0 | 0 | 7 row 6 : 6 | | 4 | leandro de almeida | 5 | 0 | 1 | 0 | 6 row 7 : 7 | | 17 | norbert meszaros | 3 | 0 | 0 | 0 | 3 row 8 : 8 | | 8 | zsombor kerekes | 1 | 0 | 2 | 0 | 3 row 9 : 9 | | 10 | igor bogdanovic | 0 | 0 | 3 | 0 | 3 row 10 : 10 | | 2 | istvan szucs | 2 | 0 | 0 | 0 | 2 row 11 : 11 | | 30 | zoltan kiss | 2 | 0 | 0 | 0 | 2 row 12 : 12 | | 23 | peter szilagyi | 2 | 0 | 0 | 0 | 2 row 13 : 13 | | 7 | tibor dombi | 2 | 0 | 0 | 0 | 2 row 14 : 14 | | 13 | peter biro | 1 | 0 | 0 | 0 | 1 row 15 : 15 | | 27 | gabor demjen | 1 | 0 | 0 | 0 | 1 row 16 : 16 | | 19 | vinicius galvao leal | 1 | 0 | 0 | 0 | 1 row 17 : 17 | | 1 | vukasin poleksic | 1 | 0 | 0 | 0 | 1 row 18 : 18 | | 83 | zoltan varga | 0 | 0 | 1 | 0 | 1 row 19 : 19 | | 16 | adam komlosi | 0 | 0 | 1 | 0 | 1 row 20 : none | | none | own goals | 1 | 0 | 0 | 0 | 1 row 21 : none | | none | totals | 70 | 5 | 13 | 0 | 88

col : count ( "name" ) row 1 : 1

select count ( name ) where name = 'zoltan kiss' <table_name> : table \begin{tabular}{llllllllll} \toprule & position & nation & number & name & soproni liga & uefa cup & hungarian cup & league cup & total \\ \midrule 0 & 1 & & 14 & gergely rudolf & 16 & 3 & 0 & 0 & 19 \\ 1 & 2 & & 41 & lorant olah & 12 & 1 & 0 & 0 & 13 \\ 2 & 3 & & 99 & omagbemi dudu & 4 & 1 & 5 & 0 & 10 \\ 3 & 4 & & 55 & peter szakaly & 9 & 0 & 0 & 0 & 9 \\ 4 & 5 & & 77 & peter czvitkovics & 7 & 0 & 0 & 0 & 7 \\ 5 & 6 & & 4 & leandro de almeida & 5 & 0 & 1 & 0 & 6 \\ 6 & 7 & & 17 & norbert meszaros & 3 & 0 & 0 & 0 & 3 \\ 7 & 8 & & 8 & zsombor kerekes & 1 & 0 & 2 & 0 & 3 \\ 8 & 9 & & 10 & igor bogdanovic & 0 & 0 & 3 & 0 & 3 \\ 9 & 10 & & 2 & istvan szucs & 2 & 0 & 0 & 0 & 2 \\ 10 & 11 & & 30 & zoltan kiss & 2 & 0 & 0 & 0 & 2 \\ 11 & 12 & & 23 & peter szilagyi & 2 & 0 & 0 & 0 & 2 \\ 12 & 13 & & 7 & tibor dombi & 2 & 0 & 0 & 0 & 2 \\ 13 & 14 & & 13 & peter biro & 1 & 0 & 0 & 0 & 1 \\ 14 & 15 & & 27 & gabor demjen & 1 & 0 & 0 & 0 & 1 \\ 15 & 16 & & 19 & vinicius galvao leal & 1 & 0 & 0 & 0 & 1 \\ 16 & 17 & & 1 & vukasin poleksic & 1 & 0 & 0 & 0 & 1 \\ 17 & 18 & & 83 & zoltan varga & 0 & 0 & 1 & 0 & 1 \\ 18 & 19 & & 16 & adam komlosi & 0 & 0 & 1 & 0 & 1 \\ 19 & none & & none & own goals & 1 & 0 & 0 & 0 & 1 \\ 20 & none & & none & totals & 70 & 5 & 13 & 0 & 88 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "name" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( name ) where name = 'zoltan kiss' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>position</th> <th>nation</th> <th>number</th> <th>name</th> <th>soproni liga</th> <th>uefa cup</th> <th>hungarian cup</th> <th>league cup</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td></td> <td>14</td> <td>gergely rudolf</td> <td>16</td> <td>3</td> <td>0</td> <td>0</td> <td>19</td> </tr> <tr> <th>1</th> <td>2</td> <td></td> <td>41</td> <td>lorant olah</td> <td>12</td> <td>1</td> <td>0</td> <td>0</td> <td>13</td> </tr> <tr> <th>2</th> <td>3</td> <td></td> <td>99</td> <td>omagbemi dudu</td> <td>4</td> <td>1</td> <td>5</td> <td>0</td> <td>10</td> </tr> <tr> <th>3</th> <td>4</td> <td></td> <td>55</td> <td>peter szakaly</td> <td>9</td> <td>0</td> <td>0</td> <td>0</td> <td>9</td> </tr> <tr> <th>4</th> <td>5</td> <td></td> <td>77</td> <td>peter czvitkovics</td> <td>7</td> <td>0</td> <td>0</td> <td>0</td> <td>7</td> </tr> <tr> <th>5</th> <td>6</td> <td></td> <td>4</td> <td>leandro de almeida</td> <td>5</td> <td>0</td> <td>1</td> <td>0</td> <td>6</td> </tr> <tr> <th>6</th> <td>7</td> <td></td> <td>17</td> <td>norbert meszaros</td> <td>3</td> <td>0</td> <td>0</td> <td>0</td> <td>3</td> </tr> <tr> <th>7</th> <td>8</td> <td></td> <td>8</td> <td>zsombor kerekes</td> <td>1</td> <td>0</td> <td>2</td> <td>0</td> <td>3</td> </tr> <tr> <th>8</th> <td>9</td> <td></td> <td>10</td> <td>igor bogdanovic</td> <td>0</td> <td>0</td> <td>3</td> <td>0</td> <td>3</td> </tr> <tr> <th>9</th> <td>10</td> <td></td> <td>2</td> <td>istvan szucs</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>10</th> <td>11</td> <td></td> <td>30</td> <td>zoltan kiss</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>11</th> <td>12</td> <td></td> <td>23</td> <td>peter szilagyi</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>12</th> <td>13</td> <td></td> <td>7</td> <td>tibor dombi</td> <td>2</td> <td>0</td> <td>0</td> <td>0</td> <td>2</td> </tr> <tr> <th>13</th> <td>14</td> <td></td> <td>13</td> <td>peter biro</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>14</th> <td>15</td> <td></td> <td>27</td> <td>gabor demjen</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>15</th> <td>16</td> <td></td> <td>19</td> <td>vinicius galvao leal</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>16</th> <td>17</td> <td></td> <td>1</td> <td>vukasin poleksic</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>17</th> <td>18</td> <td></td> <td>83</td> <td>zoltan varga</td> <td>0</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>18</th> <td>19</td> <td></td> <td>16</td> <td>adam komlosi</td> <td>0</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>19</th> <td>none</td> <td></td> <td>none</td> <td>own goals</td> <td>1</td> <td>0</td> <td>0</td> <td>0</td> <td>1</td> </tr> <tr> <th>20</th> <td>none</td> <td></td> <td>none</td> <td>totals</td> <td>70</td> <td>5</td> <td>13</td> <td>0</td> <td>88</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "name" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( name ) where name = 'zoltan kiss' <table_name> : table | | position | nation | number | name | soproni liga | uefa cup | hungarian cup | league cup | total | |---:|:-----------|:---------|:---------|:---------------------|---------------:|-----------:|----------------:|-------------:|--------:| | 0 | 1 | | 14 | gergely rudolf | 16 | 3 | 0 | 0 | 19 | | 1 | 2 | | 41 | lorant olah | 12 | 1 | 0 | 0 | 13 | | 2 | 3 | | 99 | omagbemi dudu | 4 | 1 | 5 | 0 | 10 | | 3 | 4 | | 55 | peter szakaly | 9 | 0 | 0 | 0 | 9 | | 4 | 5 | | 77 | peter czvitkovics | 7 | 0 | 0 | 0 | 7 | | 5 | 6 | | 4 | leandro de almeida | 5 | 0 | 1 | 0 | 6 | | 6 | 7 | | 17 | norbert meszaros | 3 | 0 | 0 | 0 | 3 | | 7 | 8 | | 8 | zsombor kerekes | 1 | 0 | 2 | 0 | 3 | | 8 | 9 | | 10 | igor bogdanovic | 0 | 0 | 3 | 0 | 3 | | 9 | 10 | | 2 | istvan szucs | 2 | 0 | 0 | 0 | 2 | | 10 | 11 | | 30 | zoltan kiss | 2 | 0 | 0 | 0 | 2 | | 11 | 12 | | 23 | peter szilagyi | 2 | 0 | 0 | 0 | 2 | | 12 | 13 | | 7 | tibor dombi | 2 | 0 | 0 | 0 | 2 | | 13 | 14 | | 13 | peter biro | 1 | 0 | 0 | 0 | 1 | | 14 | 15 | | 27 | gabor demjen | 1 | 0 | 0 | 0 | 1 | | 15 | 16 | | 19 | vinicius galvao leal | 1 | 0 | 0 | 0 | 1 | | 16 | 17 | | 1 | vukasin poleksic | 1 | 0 | 0 | 0 | 1 | | 17 | 18 | | 83 | zoltan varga | 0 | 0 | 1 | 0 | 1 | | 18 | 19 | | 16 | adam komlosi | 0 | 0 | 1 | 0 | 1 | | 19 | none | | none | own goals | 1 | 0 | 0 | 0 | 1 | | 20 | none | | none | totals | 70 | 5 | 13 | 0 | 88 |

| | count ( "name" ) | |---:|-------------------:| | 0 | 1 |

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select nation where nation = 'greece' order by silver desc limit 1 col : rank | nation | gold | silver | bronze | total row 1 : 1 | netherlands | 20 | 9 | 0 | 29 row 2 : 2 | italy | 10 | 15 | 3 | 28 row 3 : 3 | belgium | 1 | 2 | 6 | 9 row 4 : 4 | spain | 1 | 1 | 13 | 15 row 5 : 5 | great britain | 0 | 2 | 0 | 2 row 6 : 6 | germany | 0 | 1 | 7 | 8 row 7 : 7 | greece | 0 | 1 | 0 | 1 row 8 : 7 | russia | 0 | 1 | 0 | 1 row 9 : 9 | sweden | 0 | 0 | 2 | 2 row 10 : 10 | france | 0 | 0 | 1 | 1

col : nation row 1 : greece

select nation where nation = 'greece' order by silver desc limit 1 <table_name> : table \begin{tabular}{lllllll} \toprule & rank & nation & gold & silver & bronze & total \\ \midrule 0 & 1 & netherlands & 20 & 9 & 0 & 29 \\ 1 & 2 & italy & 10 & 15 & 3 & 28 \\ 2 & 3 & belgium & 1 & 2 & 6 & 9 \\ 3 & 4 & spain & 1 & 1 & 13 & 15 \\ 4 & 5 & great britain & 0 & 2 & 0 & 2 \\ 5 & 6 & germany & 0 & 1 & 7 & 8 \\ 6 & 7 & greece & 0 & 1 & 0 & 1 \\ 7 & 7 & russia & 0 & 1 & 0 & 1 \\ 8 & 9 & sweden & 0 & 0 & 2 & 2 \\ 9 & 10 & france & 0 & 0 & 1 & 1 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & nation \\ \midrule 0 & greece \\ \bottomrule \end{tabular}

select nation where nation = 'greece' order by silver desc limit 1 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>nation</th> <th>gold</th> <th>silver</th> <th>bronze</th> <th>total</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>netherlands</td> <td>20</td> <td>9</td> <td>0</td> <td>29</td> </tr> <tr> <th>1</th> <td>2</td> <td>italy</td> <td>10</td> <td>15</td> <td>3</td> <td>28</td> </tr> <tr> <th>2</th> <td>3</td> <td>belgium</td> <td>1</td> <td>2</td> <td>6</td> <td>9</td> </tr> <tr> <th>3</th> <td>4</td> <td>spain</td> <td>1</td> <td>1</td> <td>13</td> <td>15</td> </tr> <tr> <th>4</th> <td>5</td> <td>great britain</td> <td>0</td> <td>2</td> <td>0</td> <td>2</td> </tr> <tr> <th>5</th> <td>6</td> <td>germany</td> <td>0</td> <td>1</td> <td>7</td> <td>8</td> </tr> <tr> <th>6</th> <td>7</td> <td>greece</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>7</th> <td>7</td> <td>russia</td> <td>0</td> <td>1</td> <td>0</td> <td>1</td> </tr> <tr> <th>8</th> <td>9</td> <td>sweden</td> <td>0</td> <td>0</td> <td>2</td> <td>2</td> </tr> <tr> <th>9</th> <td>10</td> <td>france</td> <td>0</td> <td>0</td> <td>1</td> <td>1</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>nation</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>greece</td> </tr> </tbody> </table>

select nation where nation = 'greece' order by silver desc limit 1 <table_name> : table | | rank | nation | gold | silver | bronze | total | |---:|-------:|:--------------|-------:|---------:|---------:|--------:| | 0 | 1 | netherlands | 20 | 9 | 0 | 29 | | 1 | 2 | italy | 10 | 15 | 3 | 28 | | 2 | 3 | belgium | 1 | 2 | 6 | 9 | | 3 | 4 | spain | 1 | 1 | 13 | 15 | | 4 | 5 | great britain | 0 | 2 | 0 | 2 | | 5 | 6 | germany | 0 | 1 | 7 | 8 | | 6 | 7 | greece | 0 | 1 | 0 | 1 | | 7 | 7 | russia | 0 | 1 | 0 | 1 | | 8 | 9 | sweden | 0 | 0 | 2 | 2 | | 9 | 10 | france | 0 | 0 | 1 | 1 |

| | nation | |---:|:---------| | 0 | greece |

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col : count ( "distinct player" ) row 1 : 1

select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' <table_name> : table \begin{tabular}{lllllll} \toprule & pick # & player & position & nationality & nhl team & college/junior/club team \\ \midrule 0 & 148 & paul krake & goalie & canada & quebec nordiques & university of alaska anchorage (ncaa) \\ 1 & 149 & phil huber & center & canada & new york islanders & kamloops blazers (whl) \\ 2 & 150 & derek langille & defense & canada & toronto maple leafs & north bay centennials (ohl) \\ 3 & 151 & jim solly & left wing & canada & winnipeg jets & bowling green state university (ncaa) \\ 4 & 152 & sergei starikov & defense & soviet union & new jersey devils & cska moscow (ussr) \\ 5 & 153 & milan tichy & defense & czechoslovakia & chicago blackhawks & prince albert raiders (whl) \\ 6 & 154 & jon pratt & left wing & united states & minnesota north stars & pingree high school (ushs-ma) \\ 7 & 155 & rob sangster & left wing & canada & vancouver canucks & kitchener rangers (ohl) \\ 8 & 156 & kevin plager & right wing & united states & st. louis blues & parkway north high school (ushs-mo) \\ 9 & 157 & raymond saumier & right wing & canada & hartford whalers & trois rivieres draveurs (qmjhl) \\ 10 & 158 & andy suhy & defense & united states & detroit red wings & western michigan university (ncaa) \\ 11 & 159 & sverre sears & defense & united states & philadelphia flyers & princeton university (ncaa) \\ 12 & 160 & greg spenrath & defense & canada & new york rangers & tri-city americans (whl) \\ 13 & 161 & derek plante & center & united states & buffalo sabres & cloquet high school (ushs-mn) \\ 14 & 162 & darcy martini & defense & canada & edmonton oilers & michigan technological university (ncaa) \\ 15 & 163 & david shute & left wing & united states & pittsburgh penguins & victoria cougars (whl) \\ 16 & 164 & rick allain & defense & canada & boston bruins & kitchener rangers (ohl) \\ 17 & 165 & sean whyte & right wing & canada & los angeles kings & guelph platers (ohl) \\ 18 & 166 & dean holoien & right wing & canada & washington capitals & saskatoon blades (whl) \\ 19 & 167 & patrick lebeau & left wing & canada & montreal canadiens & st-jean lynx (qmjhl) \\ 20 & 168 & kevin wortman & defense & united states & calgary flames & american international college (ncaa) \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "distinct player" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pick #</th> <th>player</th> <th>position</th> <th>nationality</th> <th>nhl team</th> <th>college/junior/club team</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>148</td> <td>paul krake</td> <td>goalie</td> <td>canada</td> <td>quebec nordiques</td> <td>university of alaska anchorage (ncaa)</td> </tr> <tr> <th>1</th> <td>149</td> <td>phil huber</td> <td>center</td> <td>canada</td> <td>new york islanders</td> <td>kamloops blazers (whl)</td> </tr> <tr> <th>2</th> <td>150</td> <td>derek langille</td> <td>defense</td> <td>canada</td> <td>toronto maple leafs</td> <td>north bay centennials (ohl)</td> </tr> <tr> <th>3</th> <td>151</td> <td>jim solly</td> <td>left wing</td> <td>canada</td> <td>winnipeg jets</td> <td>bowling green state university (ncaa)</td> </tr> <tr> <th>4</th> <td>152</td> <td>sergei starikov</td> <td>defense</td> <td>soviet union</td> <td>new jersey devils</td> <td>cska moscow (ussr)</td> </tr> <tr> <th>5</th> <td>153</td> <td>milan tichy</td> <td>defense</td> <td>czechoslovakia</td> <td>chicago blackhawks</td> <td>prince albert raiders (whl)</td> </tr> <tr> <th>6</th> <td>154</td> <td>jon pratt</td> <td>left wing</td> <td>united states</td> <td>minnesota north stars</td> <td>pingree high school (ushs-ma)</td> </tr> <tr> <th>7</th> <td>155</td> <td>rob sangster</td> <td>left wing</td> <td>canada</td> <td>vancouver canucks</td> <td>kitchener rangers (ohl)</td> </tr> <tr> <th>8</th> <td>156</td> <td>kevin plager</td> <td>right wing</td> <td>united states</td> <td>st. louis blues</td> <td>parkway north high school (ushs-mo)</td> </tr> <tr> <th>9</th> <td>157</td> <td>raymond saumier</td> <td>right wing</td> <td>canada</td> <td>hartford whalers</td> <td>trois rivieres draveurs (qmjhl)</td> </tr> <tr> <th>10</th> <td>158</td> <td>andy suhy</td> <td>defense</td> <td>united states</td> <td>detroit red wings</td> <td>western michigan university (ncaa)</td> </tr> <tr> <th>11</th> <td>159</td> <td>sverre sears</td> <td>defense</td> <td>united states</td> <td>philadelphia flyers</td> <td>princeton university (ncaa)</td> </tr> <tr> <th>12</th> <td>160</td> <td>greg spenrath</td> <td>defense</td> <td>canada</td> <td>new york rangers</td> <td>tri-city americans (whl)</td> </tr> <tr> <th>13</th> <td>161</td> <td>derek plante</td> <td>center</td> <td>united states</td> <td>buffalo sabres</td> <td>cloquet high school (ushs-mn)</td> </tr> <tr> <th>14</th> <td>162</td> <td>darcy martini</td> <td>defense</td> <td>canada</td> <td>edmonton oilers</td> <td>michigan technological university (ncaa)</td> </tr> <tr> <th>15</th> <td>163</td> <td>david shute</td> <td>left wing</td> <td>united states</td> <td>pittsburgh penguins</td> <td>victoria cougars (whl)</td> </tr> <tr> <th>16</th> <td>164</td> <td>rick allain</td> <td>defense</td> <td>canada</td> <td>boston bruins</td> <td>kitchener rangers (ohl)</td> </tr> <tr> <th>17</th> <td>165</td> <td>sean whyte</td> <td>right wing</td> <td>canada</td> <td>los angeles kings</td> <td>guelph platers (ohl)</td> </tr> <tr> <th>18</th> <td>166</td> <td>dean holoien</td> <td>right wing</td> <td>canada</td> <td>washington capitals</td> <td>saskatoon blades (whl)</td> </tr> <tr> <th>19</th> <td>167</td> <td>patrick lebeau</td> <td>left wing</td> <td>canada</td> <td>montreal canadiens</td> <td>st-jean lynx (qmjhl)</td> </tr> <tr> <th>20</th> <td>168</td> <td>kevin wortman</td> <td>defense</td> <td>united states</td> <td>calgary flames</td> <td>american international college (ncaa)</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "distinct player" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( distinct player ) where college/junior/club team = 'university of alaska anchorage (ncaa)' <table_name> : table | | pick # | player | position | nationality | nhl team | college/junior/club team | |---:|---------:|:----------------|:-----------|:---------------|:----------------------|:-----------------------------------------| | 0 | 148 | paul krake | goalie | canada | quebec nordiques | university of alaska anchorage (ncaa) | | 1 | 149 | phil huber | center | canada | new york islanders | kamloops blazers (whl) | | 2 | 150 | derek langille | defense | canada | toronto maple leafs | north bay centennials (ohl) | | 3 | 151 | jim solly | left wing | canada | winnipeg jets | bowling green state university (ncaa) | | 4 | 152 | sergei starikov | defense | soviet union | new jersey devils | cska moscow (ussr) | | 5 | 153 | milan tichy | defense | czechoslovakia | chicago blackhawks | prince albert raiders (whl) | | 6 | 154 | jon pratt | left wing | united states | minnesota north stars | pingree high school (ushs-ma) | | 7 | 155 | rob sangster | left wing | canada | vancouver canucks | kitchener rangers (ohl) | | 8 | 156 | kevin plager | right wing | united states | st. louis blues | parkway north high school (ushs-mo) | | 9 | 157 | raymond saumier | right wing | canada | hartford whalers | trois rivieres draveurs (qmjhl) | | 10 | 158 | andy suhy | defense | united states | detroit red wings | western michigan university (ncaa) | | 11 | 159 | sverre sears | defense | united states | philadelphia flyers | princeton university (ncaa) | | 12 | 160 | greg spenrath | defense | canada | new york rangers | tri-city americans (whl) | | 13 | 161 | derek plante | center | united states | buffalo sabres | cloquet high school (ushs-mn) | | 14 | 162 | darcy martini | defense | canada | edmonton oilers | michigan technological university (ncaa) | | 15 | 163 | david shute | left wing | united states | pittsburgh penguins | victoria cougars (whl) | | 16 | 164 | rick allain | defense | canada | boston bruins | kitchener rangers (ohl) | | 17 | 165 | sean whyte | right wing | canada | los angeles kings | guelph platers (ohl) | | 18 | 166 | dean holoien | right wing | canada | washington capitals | saskatoon blades (whl) | | 19 | 167 | patrick lebeau | left wing | canada | montreal canadiens | st-jean lynx (qmjhl) | | 20 | 168 | kevin wortman | defense | united states | calgary flames | american international college (ncaa) |

| | count ( "distinct player" ) | |---:|------------------------------:| | 0 | 1 |

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select units where petroleum coke-fired = '0.004' col : pollutant | units | emission standard | coal-fired | petroleum coke-fired row 1 : so2 | lb/mmbtu | ≤ 0.15 | 0.0-0.04 | 0.03-0.13 row 2 : nox | lb/mmbtu | ≤ 0.09 | 0.04-0.06 | 0.02 row 3 : solid particulate | lb/mmbtu | ≤ 0.011 | 0.004 | 0.007 row 4 : pm10 | lb/mmbtu | ≤ 0.011 | 0.006 | 0.004 row 5 : so3 | lb/hour | ≤ 1.1 | 0.43 | 0 row 6 : fluoride | lb/mmbtu | ≤ 1.57×10-4 | 1.06×10-4 | 0.95×10-4 row 7 : lead | lb/mmbtu | ≤ 2.6×10-5 | 0.56×10-5 | 0.59×10-5 row 8 : mercury | lb/mmbtu | ≤ 1.05×10-5 | 0.095×10-5 | 0.028×10-5

col : units row 1 : lb/mmbtu

select units where petroleum coke-fired = '0.004' <table_name> : table \begin{tabular}{llllll} \toprule & pollutant & units & emission standard & coal-fired & petroleum coke-fired \\ \midrule 0 & so2 & lb/mmbtu & ≤ 0.15 & 0.0-0.04 & 0.03-0.13 \\ 1 & nox & lb/mmbtu & ≤ 0.09 & 0.04-0.06 & 0.02 \\ 2 & solid particulate & lb/mmbtu & ≤ 0.011 & 0.004 & 0.007 \\ 3 & pm10 & lb/mmbtu & ≤ 0.011 & 0.006 & 0.004 \\ 4 & so3 & lb/hour & ≤ 1.1 & 0.43 & 0 \\ 5 & fluoride & lb/mmbtu & ≤ 1.57×10-4 & 1.06×10-4 & 0.95×10-4 \\ 6 & lead & lb/mmbtu & ≤ 2.6×10-5 & 0.56×10-5 & 0.59×10-5 \\ 7 & mercury & lb/mmbtu & ≤ 1.05×10-5 & 0.095×10-5 & 0.028×10-5 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & units \\ \midrule 0 & lb/mmbtu \\ \bottomrule \end{tabular}

select units where petroleum coke-fired = '0.004' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>pollutant</th> <th>units</th> <th>emission standard</th> <th>coal-fired</th> <th>petroleum coke-fired</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>so2</td> <td>lb/mmbtu</td> <td>≤ 0.15</td> <td>0.0-0.04</td> <td>0.03-0.13</td> </tr> <tr> <th>1</th> <td>nox</td> <td>lb/mmbtu</td> <td>≤ 0.09</td> <td>0.04-0.06</td> <td>0.02</td> </tr> <tr> <th>2</th> <td>solid particulate</td> <td>lb/mmbtu</td> <td>≤ 0.011</td> <td>0.004</td> <td>0.007</td> </tr> <tr> <th>3</th> <td>pm10</td> <td>lb/mmbtu</td> <td>≤ 0.011</td> <td>0.006</td> <td>0.004</td> </tr> <tr> <th>4</th> <td>so3</td> <td>lb/hour</td> <td>≤ 1.1</td> <td>0.43</td> <td>0</td> </tr> <tr> <th>5</th> <td>fluoride</td> <td>lb/mmbtu</td> <td>≤ 1.57×10-4</td> <td>1.06×10-4</td> <td>0.95×10-4</td> </tr> <tr> <th>6</th> <td>lead</td> <td>lb/mmbtu</td> <td>≤ 2.6×10-5</td> <td>0.56×10-5</td> <td>0.59×10-5</td> </tr> <tr> <th>7</th> <td>mercury</td> <td>lb/mmbtu</td> <td>≤ 1.05×10-5</td> <td>0.095×10-5</td> <td>0.028×10-5</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>units</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>lb/mmbtu</td> </tr> </tbody> </table>

select units where petroleum coke-fired = '0.004' <table_name> : table | | pollutant | units | emission standard | coal-fired | petroleum coke-fired | |---:|:------------------|:---------|:--------------------|:-------------|:-----------------------| | 0 | so2 | lb/mmbtu | ≤ 0.15 | 0.0-0.04 | 0.03-0.13 | | 1 | nox | lb/mmbtu | ≤ 0.09 | 0.04-0.06 | 0.02 | | 2 | solid particulate | lb/mmbtu | ≤ 0.011 | 0.004 | 0.007 | | 3 | pm10 | lb/mmbtu | ≤ 0.011 | 0.006 | 0.004 | | 4 | so3 | lb/hour | ≤ 1.1 | 0.43 | 0 | | 5 | fluoride | lb/mmbtu | ≤ 1.57×10-4 | 1.06×10-4 | 0.95×10-4 | | 6 | lead | lb/mmbtu | ≤ 2.6×10-5 | 0.56×10-5 | 0.59×10-5 | | 7 | mercury | lb/mmbtu | ≤ 1.05×10-5 | 0.095×10-5 | 0.028×10-5 |

| | units | |---:|:---------| | 0 | lb/mmbtu |

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select count ( * ) where first tops = '202/2' col : first tops | second tops row 1 : 102 | 101 row 2 : 142 | 108 row 3 : 146 | 109 row 4 : 150 | 122 row 5 : 163 | 110 row 6 : 167 | 108 row 7 : 171 | 101 row 8 : 175 | 116 row 9 : 179 | 120 row 10 : 183 | 123 row 11 : 187 | 126 row 12 : 201/1 | 201 row 13 : 202/2 | 207 row 14 : 211/2 | 207 row 15 : 221/2 | 202 row 16 : 223/1 | 201 row 17 : 225 | 203 row 18 : 106 | 105 row 19 : 143 | 100 row 20 : 147 | 111 row 21 : 160 | 104 row 22 : 164 | 101 row 23 : 168 | 101 & 111 row 24 : 172 | 116 row 25 : 176 | 117 row 26 : 180 | 124 row 27 : 184 | 123 row 28 : 188 | 126 row 29 : 201/2 | 202 row 30 : 202/3 | 205 row 31 : 211/3 | 205 row 32 : 221/3 | 203 row 33 : 223/2 | 202 row 34 : 261 | 251 row 35 : 140 | 104 row 36 : 144 | 101 row 37 : 148 | 114 row 38 : 161 | 107 & 108 row 39 : 165 | 111 row 40 : 169 | 104 row 41 : 173 | 115 row 42 : 177 | 115 row 43 : 181 | 124 row 44 : 185 | 125 row 45 : 189 | 126 row 46 : 201/3 | 203 row 47 : 203 | 204 row 48 : 212 | 204 row 49 : 222/1 | 206 row 50 : 223/3 | 203 row 51 : 141 | 105 row 52 : 145 | 103 row 53 : 149 | 121 row 54 : 162 | 101 row 55 : 166 | 104 row 56 : 170 | 105 row 57 : 174 | 118 row 58 : 178 | 119 row 59 : 182 | 123 row 60 : 186 | 127 row 61 : 190 | 130 row 62 : 202/1 | 206 row 63 : 211/1 | 206 row 64 : 221/1 | 201 row 65 : 222/2 | 205 row 66 : 224 | 207

col : count ( "*" ) row 1 : 1

select count ( * ) where first tops = '202/2' <table_name> : table \begin{tabular}{lll} \toprule & first tops & second tops \\ \midrule 0 & 102 & 101 \\ 1 & 142 & 108 \\ 2 & 146 & 109 \\ 3 & 150 & 122 \\ 4 & 163 & 110 \\ 5 & 167 & 108 \\ 6 & 171 & 101 \\ 7 & 175 & 116 \\ 8 & 179 & 120 \\ 9 & 183 & 123 \\ 10 & 187 & 126 \\ 11 & 201/1 & 201 \\ 12 & 202/2 & 207 \\ 13 & 211/2 & 207 \\ 14 & 221/2 & 202 \\ 15 & 223/1 & 201 \\ 16 & 225 & 203 \\ 17 & 106 & 105 \\ 18 & 143 & 100 \\ 19 & 147 & 111 \\ 20 & 160 & 104 \\ 21 & 164 & 101 \\ 22 & 168 & 101 & 111 \\ 23 & 172 & 116 \\ 24 & 176 & 117 \\ 25 & 180 & 124 \\ 26 & 184 & 123 \\ 27 & 188 & 126 \\ 28 & 201/2 & 202 \\ 29 & 202/3 & 205 \\ 30 & 211/3 & 205 \\ 31 & 221/3 & 203 \\ 32 & 223/2 & 202 \\ 33 & 261 & 251 \\ 34 & 140 & 104 \\ 35 & 144 & 101 \\ 36 & 148 & 114 \\ 37 & 161 & 107 & 108 \\ 38 & 165 & 111 \\ 39 & 169 & 104 \\ 40 & 173 & 115 \\ 41 & 177 & 115 \\ 42 & 181 & 124 \\ 43 & 185 & 125 \\ 44 & 189 & 126 \\ 45 & 201/3 & 203 \\ 46 & 203 & 204 \\ 47 & 212 & 204 \\ 48 & 222/1 & 206 \\ 49 & 223/3 & 203 \\ 50 & 141 & 105 \\ 51 & 145 & 103 \\ 52 & 149 & 121 \\ 53 & 162 & 101 \\ 54 & 166 & 104 \\ 55 & 170 & 105 \\ 56 & 174 & 118 \\ 57 & 178 & 119 \\ 58 & 182 & 123 \\ 59 & 186 & 127 \\ 60 & 190 & 130 \\ 61 & 202/1 & 206 \\ 62 & 211/1 & 206 \\ 63 & 221/1 & 201 \\ 64 & 222/2 & 205 \\ 65 & 224 & 207 \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where first tops = '202/2' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>first tops</th> <th>second tops</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>102</td> <td>101</td> </tr> <tr> <th>1</th> <td>142</td> <td>108</td> </tr> <tr> <th>2</th> <td>146</td> <td>109</td> </tr> <tr> <th>3</th> <td>150</td> <td>122</td> </tr> <tr> <th>4</th> <td>163</td> <td>110</td> </tr> <tr> <th>5</th> <td>167</td> <td>108</td> </tr> <tr> <th>6</th> <td>171</td> <td>101</td> </tr> <tr> <th>7</th> <td>175</td> <td>116</td> </tr> <tr> <th>8</th> <td>179</td> <td>120</td> </tr> <tr> <th>9</th> <td>183</td> <td>123</td> </tr> <tr> <th>10</th> <td>187</td> <td>126</td> </tr> <tr> <th>11</th> <td>201/1</td> <td>201</td> </tr> <tr> <th>12</th> <td>202/2</td> <td>207</td> </tr> <tr> <th>13</th> <td>211/2</td> <td>207</td> </tr> <tr> <th>14</th> <td>221/2</td> <td>202</td> </tr> <tr> <th>15</th> <td>223/1</td> <td>201</td> </tr> <tr> <th>16</th> <td>225</td> <td>203</td> </tr> <tr> <th>17</th> <td>106</td> <td>105</td> </tr> <tr> <th>18</th> <td>143</td> <td>100</td> </tr> <tr> <th>19</th> <td>147</td> <td>111</td> </tr> <tr> <th>20</th> <td>160</td> <td>104</td> </tr> <tr> <th>21</th> <td>164</td> <td>101</td> </tr> <tr> <th>22</th> <td>168</td> <td>101 & 111</td> </tr> <tr> <th>23</th> <td>172</td> <td>116</td> </tr> <tr> <th>24</th> <td>176</td> <td>117</td> </tr> <tr> <th>25</th> <td>180</td> <td>124</td> </tr> <tr> <th>26</th> <td>184</td> <td>123</td> </tr> <tr> <th>27</th> <td>188</td> <td>126</td> </tr> <tr> <th>28</th> <td>201/2</td> <td>202</td> </tr> <tr> <th>29</th> <td>202/3</td> <td>205</td> </tr> <tr> <th>30</th> <td>211/3</td> <td>205</td> </tr> <tr> <th>31</th> <td>221/3</td> <td>203</td> </tr> <tr> <th>32</th> <td>223/2</td> <td>202</td> </tr> <tr> <th>33</th> <td>261</td> <td>251</td> </tr> <tr> <th>34</th> <td>140</td> <td>104</td> </tr> <tr> <th>35</th> <td>144</td> <td>101</td> </tr> <tr> <th>36</th> <td>148</td> <td>114</td> </tr> <tr> <th>37</th> <td>161</td> <td>107 & 108</td> </tr> <tr> <th>38</th> <td>165</td> <td>111</td> </tr> <tr> <th>39</th> <td>169</td> <td>104</td> </tr> <tr> <th>40</th> <td>173</td> <td>115</td> </tr> <tr> <th>41</th> <td>177</td> <td>115</td> </tr> <tr> <th>42</th> <td>181</td> <td>124</td> </tr> <tr> <th>43</th> <td>185</td> <td>125</td> </tr> <tr> <th>44</th> <td>189</td> <td>126</td> </tr> <tr> <th>45</th> <td>201/3</td> <td>203</td> </tr> <tr> <th>46</th> <td>203</td> <td>204</td> </tr> <tr> <th>47</th> <td>212</td> <td>204</td> </tr> <tr> <th>48</th> <td>222/1</td> <td>206</td> </tr> <tr> <th>49</th> <td>223/3</td> <td>203</td> </tr> <tr> <th>50</th> <td>141</td> <td>105</td> </tr> <tr> <th>51</th> <td>145</td> <td>103</td> </tr> <tr> <th>52</th> <td>149</td> <td>121</td> </tr> <tr> <th>53</th> <td>162</td> <td>101</td> </tr> <tr> <th>54</th> <td>166</td> <td>104</td> </tr> <tr> <th>55</th> <td>170</td> <td>105</td> </tr> <tr> <th>56</th> <td>174</td> <td>118</td> </tr> <tr> <th>57</th> <td>178</td> <td>119</td> </tr> <tr> <th>58</th> <td>182</td> <td>123</td> </tr> <tr> <th>59</th> <td>186</td> <td>127</td> </tr> <tr> <th>60</th> <td>190</td> <td>130</td> </tr> <tr> <th>61</th> <td>202/1</td> <td>206</td> </tr> <tr> <th>62</th> <td>211/1</td> <td>206</td> </tr> <tr> <th>63</th> <td>221/1</td> <td>201</td> </tr> <tr> <th>64</th> <td>222/2</td> <td>205</td> </tr> <tr> <th>65</th> <td>224</td> <td>207</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where first tops = '202/2' <table_name> : table | | first tops | second tops | |---:|:-------------|:--------------| | 0 | 102 | 101 | | 1 | 142 | 108 | | 2 | 146 | 109 | | 3 | 150 | 122 | | 4 | 163 | 110 | | 5 | 167 | 108 | | 6 | 171 | 101 | | 7 | 175 | 116 | | 8 | 179 | 120 | | 9 | 183 | 123 | | 10 | 187 | 126 | | 11 | 201/1 | 201 | | 12 | 202/2 | 207 | | 13 | 211/2 | 207 | | 14 | 221/2 | 202 | | 15 | 223/1 | 201 | | 16 | 225 | 203 | | 17 | 106 | 105 | | 18 | 143 | 100 | | 19 | 147 | 111 | | 20 | 160 | 104 | | 21 | 164 | 101 | | 22 | 168 | 101 & 111 | | 23 | 172 | 116 | | 24 | 176 | 117 | | 25 | 180 | 124 | | 26 | 184 | 123 | | 27 | 188 | 126 | | 28 | 201/2 | 202 | | 29 | 202/3 | 205 | | 30 | 211/3 | 205 | | 31 | 221/3 | 203 | | 32 | 223/2 | 202 | | 33 | 261 | 251 | | 34 | 140 | 104 | | 35 | 144 | 101 | | 36 | 148 | 114 | | 37 | 161 | 107 & 108 | | 38 | 165 | 111 | | 39 | 169 | 104 | | 40 | 173 | 115 | | 41 | 177 | 115 | | 42 | 181 | 124 | | 43 | 185 | 125 | | 44 | 189 | 126 | | 45 | 201/3 | 203 | | 46 | 203 | 204 | | 47 | 212 | 204 | | 48 | 222/1 | 206 | | 49 | 223/3 | 203 | | 50 | 141 | 105 | | 51 | 145 | 103 | | 52 | 149 | 121 | | 53 | 162 | 101 | | 54 | 166 | 104 | | 55 | 170 | 105 | | 56 | 174 | 118 | | 57 | 178 | 119 | | 58 | 182 | 123 | | 59 | 186 | 127 | | 60 | 190 | 130 | | 61 | 202/1 | 206 | | 62 | 211/1 | 206 | | 63 | 221/1 | 201 | | 64 | 222/2 | 205 | | 65 | 224 | 207 |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : count ( "*" ) row 1 : 1

select count ( * ) where no. < 2 <table_name> : table \begin{tabular}{lllll} \toprule & no. & name & term of office & president(s) served under \\ \midrule 0 & 1 & william bennett & 1989 - 1991 & george h. w. bush \\ 1 & 2 & bob martinez & march 28, 1991 - january 20, 1993 & george h. w. bush \\ 2 & 3 & lee p. brown & january 1993 - december 12, 1995 & bill clinton \\ 3 & 4 & barry mccaffrey & february 29, 1996 - january 4, 2001 & bill clinton \\ 4 & 5 & john p. walters & december 7, 2001 - january 19, 2009 & george w. bush \\ 5 & 6 & gil kerlikowske & may 7, 2009 - march 6, 2014 & barack obama \\ 6 & acting & michael botticelli & march 6, 2014 - & barack obama \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where no. < 2 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>no.</th> <th>name</th> <th>term of office</th> <th>president(s) served under</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>william bennett</td> <td>1989 - 1991</td> <td>george h. w. bush</td> </tr> <tr> <th>1</th> <td>2</td> <td>bob martinez</td> <td>march 28, 1991 - january 20, 1993</td> <td>george h. w. bush</td> </tr> <tr> <th>2</th> <td>3</td> <td>lee p. brown</td> <td>january 1993 - december 12, 1995</td> <td>bill clinton</td> </tr> <tr> <th>3</th> <td>4</td> <td>barry mccaffrey</td> <td>february 29, 1996 - january 4, 2001</td> <td>bill clinton</td> </tr> <tr> <th>4</th> <td>5</td> <td>john p. walters</td> <td>december 7, 2001 - january 19, 2009</td> <td>george w. bush</td> </tr> <tr> <th>5</th> <td>6</td> <td>gil kerlikowske</td> <td>may 7, 2009 - march 6, 2014</td> <td>barack obama</td> </tr> <tr> <th>6</th> <td>acting</td> <td>michael botticelli</td> <td>march 6, 2014 -</td> <td>barack obama</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where no. < 2 <table_name> : table | | no. | name | term of office | president(s) served under | |---:|:-------|:-------------------|:------------------------------------|:----------------------------| | 0 | 1 | william bennett | 1989 - 1991 | george h. w. bush | | 1 | 2 | bob martinez | march 28, 1991 - january 20, 1993 | george h. w. bush | | 2 | 3 | lee p. brown | january 1993 - december 12, 1995 | bill clinton | | 3 | 4 | barry mccaffrey | february 29, 1996 - january 4, 2001 | bill clinton | | 4 | 5 | john p. walters | december 7, 2001 - january 19, 2009 | george w. bush | | 5 | 6 | gil kerlikowske | may 7, 2009 - march 6, 2014 | barack obama | | 6 | acting | michael botticelli | march 6, 2014 - | barack obama |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : rank row 1 : 11

select rank where team = 'lithuania' <table_name> : table \begin{tabular}{llllll} \toprule & rank & team & names & time & qualification \\ \midrule 0 & 1 & france & christophe capelle philippe ermenault jean-michel monin francis moreau & 4:09.570 & q \\ 1 & 2 & italy & adler capelli mauro trentini andrea collinelli cristiano citton & 4:09.695 & q \\ 2 & 3 & australia & bradley mcgee stuart o'grady timothy o'shannessey dean woods & 4:09.750 & q \\ 3 & 4 & ukraine & bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko & 4:11.545 & q \\ 4 & 5 & russia & eduard gritsun nikolay kuznetsov aleksey markov anton chantyr & 4:11.665 & q \\ 5 & 6 & united states & dirk copeland mariano friedick adam laurent michael mccarthy & 4:11.950 & q \\ 6 & 7 & spain & juan martinez juan llaneras santos gonzalez adolfo alperi & 4:12.780 & q \\ 7 & 8 & new zealand & gregory henderson brendon cameron timothy carswell julian dean & 4:15.140 & q \\ 8 & 9 & germany & robert bartko guido fulst danilo hondo heiko szonn & 4:15.140 & none \\ 9 & 10 & great britain & robert hayes matthew illingsworth bryan steel chris newton & 4:16.510 & none \\ 10 & 11 & lithuania & arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas & 4:16.050 & none \\ 11 & 12 & netherlands & jarich bakker robertus michie slippens richard rozendaal peter schep & 4:16.175 & none \\ 12 & 13 & denmark & frederik bertelsen jimmi madsen michael nielsen jacob piil & 4:16.175 & none \\ 13 & 14 & argentina & walter perez edgardo simon gonzalo garcia gabriel curuchet & 4:20.840 & none \\ 14 & 15 & south korea & dae-hong chun young chung jong-mo kim younk-sik noh & 4:25.215 & none \\ 15 & 16 & chile & jose medina luis sepulveda marco arriagada marcelo arriagada & 4:25.960 & none \\ 16 & 17 & colombia & john garcia marlon perez yovani lopez jos velasquez de la cuesta & 4:26.400 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & rank \\ \midrule 0 & 11 \\ \bottomrule \end{tabular}

select rank where team = 'lithuania' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>team</th> <th>names</th> <th>time</th> <th>qualification</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>france</td> <td>christophe capelle philippe ermenault jean-michel monin francis moreau</td> <td>4:09.570</td> <td>q</td> </tr> <tr> <th>1</th> <td>2</td> <td>italy</td> <td>adler capelli mauro trentini andrea collinelli cristiano citton</td> <td>4:09.695</td> <td>q</td> </tr> <tr> <th>2</th> <td>3</td> <td>australia</td> <td>bradley mcgee stuart o'grady timothy o'shannessey dean woods</td> <td>4:09.750</td> <td>q</td> </tr> <tr> <th>3</th> <td>4</td> <td>ukraine</td> <td>bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko</td> <td>4:11.545</td> <td>q</td> </tr> <tr> <th>4</th> <td>5</td> <td>russia</td> <td>eduard gritsun nikolay kuznetsov aleksey markov anton chantyr</td> <td>4:11.665</td> <td>q</td> </tr> <tr> <th>5</th> <td>6</td> <td>united states</td> <td>dirk copeland mariano friedick adam laurent michael mccarthy</td> <td>4:11.950</td> <td>q</td> </tr> <tr> <th>6</th> <td>7</td> <td>spain</td> <td>juan martinez juan llaneras santos gonzalez adolfo alperi</td> <td>4:12.780</td> <td>q</td> </tr> <tr> <th>7</th> <td>8</td> <td>new zealand</td> <td>gregory henderson brendon cameron timothy carswell julian dean</td> <td>4:15.140</td> <td>q</td> </tr> <tr> <th>8</th> <td>9</td> <td>germany</td> <td>robert bartko guido fulst danilo hondo heiko szonn</td> <td>4:15.140</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>great britain</td> <td>robert hayes matthew illingsworth bryan steel chris newton</td> <td>4:16.510</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>lithuania</td> <td>arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas</td> <td>4:16.050</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>netherlands</td> <td>jarich bakker robertus michie slippens richard rozendaal peter schep</td> <td>4:16.175</td> <td>none</td> </tr> <tr> <th>12</th> <td>13</td> <td>denmark</td> <td>frederik bertelsen jimmi madsen michael nielsen jacob piil</td> <td>4:16.175</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>argentina</td> <td>walter perez edgardo simon gonzalo garcia gabriel curuchet</td> <td>4:20.840</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>south korea</td> <td>dae-hong chun young chung jong-mo kim younk-sik noh</td> <td>4:25.215</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>chile</td> <td>jose medina luis sepulveda marco arriagada marcelo arriagada</td> <td>4:25.960</td> <td>none</td> </tr> <tr> <th>16</th> <td>17</td> <td>colombia</td> <td>john garcia marlon perez yovani lopez jos velasquez de la cuesta</td> <td>4:26.400</td> <td>none</td> </tr> </tbody> </table>

select rank where team = 'lithuania' <table_name> : table | | rank | team | names | time | qualification | |---:|-------:|:--------------|:-------------------------------------------------------------------------|:---------|:----------------| | 0 | 1 | france | christophe capelle philippe ermenault jean-michel monin francis moreau | 4:09.570 | q | | 1 | 2 | italy | adler capelli mauro trentini andrea collinelli cristiano citton | 4:09.695 | q | | 2 | 3 | australia | bradley mcgee stuart o'grady timothy o'shannessey dean woods | 4:09.750 | q | | 3 | 4 | ukraine | bohdan bondaryev oleksandr fedenko andriy yatsenko alexander simonenko | 4:11.545 | q | | 4 | 5 | russia | eduard gritsun nikolay kuznetsov aleksey markov anton chantyr | 4:11.665 | q | | 5 | 6 | united states | dirk copeland mariano friedick adam laurent michael mccarthy | 4:11.950 | q | | 6 | 7 | spain | juan martinez juan llaneras santos gonzalez adolfo alperi | 4:12.780 | q | | 7 | 8 | new zealand | gregory henderson brendon cameron timothy carswell julian dean | 4:15.140 | q | | 8 | 9 | germany | robert bartko guido fulst danilo hondo heiko szonn | 4:15.140 | none | | 9 | 10 | great britain | robert hayes matthew illingsworth bryan steel chris newton | 4:16.510 | none | | 10 | 11 | lithuania | arturas kasputis remigijus lupeikis mindaugus umaris arturas trumpauskas | 4:16.050 | none | | 11 | 12 | netherlands | jarich bakker robertus michie slippens richard rozendaal peter schep | 4:16.175 | none | | 12 | 13 | denmark | frederik bertelsen jimmi madsen michael nielsen jacob piil | 4:16.175 | none | | 13 | 14 | argentina | walter perez edgardo simon gonzalo garcia gabriel curuchet | 4:20.840 | none | | 14 | 15 | south korea | dae-hong chun young chung jong-mo kim younk-sik noh | 4:25.215 | none | | 15 | 16 | chile | jose medina luis sepulveda marco arriagada marcelo arriagada | 4:25.960 | none | | 16 | 17 | colombia | john garcia marlon perez yovani lopez jos velasquez de la cuesta | 4:26.400 | none |

| | rank | |---:|-------:| | 0 | 11 |

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select count ( * ) where name = 'the condominiums at north bank park' col : rank | name | height ft / m | floors | year | notes row 1 : 1 | rhodes state office tower | 629 / 192 | 41 | 1973 | has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s row 2 : 2 | leveque tower | 555 / 169 | 47 | 1927 | tallest building constructed in columbus in the 1920s row 3 : 3 | william green building | 530 / 162 | 33 | 1990 | tallest building constructed in columbus in the 1990s row 4 : 4 | huntington center | 512 / 156 | 37 | 1984 | tallest building constructed in columbus in the 1980s row 5 : 5 | vern riffe state office tower | 503 / 153 | 32 | 1988 | none row 6 : 6 | one nationwide plaza | 485 / 148 | 40 | 1976 | none row 7 : 7 | franklin county courthouse | 464 / 141 | 27 | 1991 | none row 8 : 8 | aep building | 456 / 139 | 31 | 1983 | none row 9 : 9 | borden building | 438 / 134 | 34 | 1974 | none row 10 : 10 | three nationwide plaza | 408 / 124 | 27 | 1989 | none row 11 : 11 | one columbus center | 366 / 112 | 26 | 1987 | none row 12 : 12 | columbus center | 357 / 109 | 25 | 1964 | tallest building constructed in columbus in the 1960s. was built as the bank one tower row 13 : 13 | capitol square | 350 / 107 | 26 | 1984 | none row 14 : 14 | continental center | 348 / 106 | 26 | 1973 | none row 15 : 15 | pnc bank building | 317 / 97 | 25 | 1977 | none row 16 : 16 | miranova condominiums | 314 / 96 | 26 | 2001 | tallest residential building in the state of ohio. tallest building built in the 2000s row 17 : 17 | fifth third center | 302 / 92 | 25 | 1998 | none row 18 : 18 | motorists mutual building | 286 / 87 | 21 | 1973 | none row 19 : 19 | midland building | 280 / 85 | 21 | 1970 | none row 20 : 20 | the condominiums at north bank park | 267 / 81 | 20 | 2007 | none row 21 : 21= | lincoln tower dormitory | 260 / 79 | 26 | 1967 | none row 22 : 21= | morrill tower dormitory | 260 / 79 | 26 | 1967 | none row 23 : 23 | hyatt regency columbus | 256 / 78 | 20 | 1980 | none row 24 : 24 | key bank building | 253 / 77 | 20 | 1963 | none row 25 : 25 | adam's mark hotel | 243 / 74 | 16 | 1961 | none row 26 : 26 | town center | 226 / 69 | 17 | 1974 | none row 27 : 27 | 8 east broad street | 212 / 64.6 | 17 | 1906 | none row 28 : 28 | huntington building | 202 / 59.4 | 13 | 1926 | none row 29 : 29 | ohio judicial center | 200 / 57.9 | 14 | 1933 | none row 30 : 30 | 16 east broad street | 180 / 64.4 | 13 | 1900 | none

col : count ( "*" ) row 1 : 1

select count ( * ) where name = 'the condominiums at north bank park' <table_name> : table \begin{tabular}{lllllll} \toprule & rank & name & height ft / m & floors & year & notes \\ \midrule 0 & 1 & rhodes state office tower & 629 / 192 & 41 & 1973 & has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s \\ 1 & 2 & leveque tower & 555 / 169 & 47 & 1927 & tallest building constructed in columbus in the 1920s \\ 2 & 3 & william green building & 530 / 162 & 33 & 1990 & tallest building constructed in columbus in the 1990s \\ 3 & 4 & huntington center & 512 / 156 & 37 & 1984 & tallest building constructed in columbus in the 1980s \\ 4 & 5 & vern riffe state office tower & 503 / 153 & 32 & 1988 & none \\ 5 & 6 & one nationwide plaza & 485 / 148 & 40 & 1976 & none \\ 6 & 7 & franklin county courthouse & 464 / 141 & 27 & 1991 & none \\ 7 & 8 & aep building & 456 / 139 & 31 & 1983 & none \\ 8 & 9 & borden building & 438 / 134 & 34 & 1974 & none \\ 9 & 10 & three nationwide plaza & 408 / 124 & 27 & 1989 & none \\ 10 & 11 & one columbus center & 366 / 112 & 26 & 1987 & none \\ 11 & 12 & columbus center & 357 / 109 & 25 & 1964 & tallest building constructed in columbus in the 1960s. was built as the bank one tower \\ 12 & 13 & capitol square & 350 / 107 & 26 & 1984 & none \\ 13 & 14 & continental center & 348 / 106 & 26 & 1973 & none \\ 14 & 15 & pnc bank building & 317 / 97 & 25 & 1977 & none \\ 15 & 16 & miranova condominiums & 314 / 96 & 26 & 2001 & tallest residential building in the state of ohio. tallest building built in the 2000s \\ 16 & 17 & fifth third center & 302 / 92 & 25 & 1998 & none \\ 17 & 18 & motorists mutual building & 286 / 87 & 21 & 1973 & none \\ 18 & 19 & midland building & 280 / 85 & 21 & 1970 & none \\ 19 & 20 & the condominiums at north bank park & 267 / 81 & 20 & 2007 & none \\ 20 & 21= & lincoln tower dormitory & 260 / 79 & 26 & 1967 & none \\ 21 & 21= & morrill tower dormitory & 260 / 79 & 26 & 1967 & none \\ 22 & 23 & hyatt regency columbus & 256 / 78 & 20 & 1980 & none \\ 23 & 24 & key bank building & 253 / 77 & 20 & 1963 & none \\ 24 & 25 & adam's mark hotel & 243 / 74 & 16 & 1961 & none \\ 25 & 26 & town center & 226 / 69 & 17 & 1974 & none \\ 26 & 27 & 8 east broad street & 212 / 64.6 & 17 & 1906 & none \\ 27 & 28 & huntington building & 202 / 59.4 & 13 & 1926 & none \\ 28 & 29 & ohio judicial center & 200 / 57.9 & 14 & 1933 & none \\ 29 & 30 & 16 east broad street & 180 / 64.4 & 13 & 1900 & none \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 1 \\ \bottomrule \end{tabular}

select count ( * ) where name = 'the condominiums at north bank park' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>rank</th> <th>name</th> <th>height ft / m</th> <th>floors</th> <th>year</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> <td>rhodes state office tower</td> <td>629 / 192</td> <td>41</td> <td>1973</td> <td>has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s</td> </tr> <tr> <th>1</th> <td>2</td> <td>leveque tower</td> <td>555 / 169</td> <td>47</td> <td>1927</td> <td>tallest building constructed in columbus in the 1920s</td> </tr> <tr> <th>2</th> <td>3</td> <td>william green building</td> <td>530 / 162</td> <td>33</td> <td>1990</td> <td>tallest building constructed in columbus in the 1990s</td> </tr> <tr> <th>3</th> <td>4</td> <td>huntington center</td> <td>512 / 156</td> <td>37</td> <td>1984</td> <td>tallest building constructed in columbus in the 1980s</td> </tr> <tr> <th>4</th> <td>5</td> <td>vern riffe state office tower</td> <td>503 / 153</td> <td>32</td> <td>1988</td> <td>none</td> </tr> <tr> <th>5</th> <td>6</td> <td>one nationwide plaza</td> <td>485 / 148</td> <td>40</td> <td>1976</td> <td>none</td> </tr> <tr> <th>6</th> <td>7</td> <td>franklin county courthouse</td> <td>464 / 141</td> <td>27</td> <td>1991</td> <td>none</td> </tr> <tr> <th>7</th> <td>8</td> <td>aep building</td> <td>456 / 139</td> <td>31</td> <td>1983</td> <td>none</td> </tr> <tr> <th>8</th> <td>9</td> <td>borden building</td> <td>438 / 134</td> <td>34</td> <td>1974</td> <td>none</td> </tr> <tr> <th>9</th> <td>10</td> <td>three nationwide plaza</td> <td>408 / 124</td> <td>27</td> <td>1989</td> <td>none</td> </tr> <tr> <th>10</th> <td>11</td> <td>one columbus center</td> <td>366 / 112</td> <td>26</td> <td>1987</td> <td>none</td> </tr> <tr> <th>11</th> <td>12</td> <td>columbus center</td> <td>357 / 109</td> <td>25</td> <td>1964</td> <td>tallest building constructed in columbus in the 1960s. was built as the bank one tower</td> </tr> <tr> <th>12</th> <td>13</td> <td>capitol square</td> <td>350 / 107</td> <td>26</td> <td>1984</td> <td>none</td> </tr> <tr> <th>13</th> <td>14</td> <td>continental center</td> <td>348 / 106</td> <td>26</td> <td>1973</td> <td>none</td> </tr> <tr> <th>14</th> <td>15</td> <td>pnc bank building</td> <td>317 / 97</td> <td>25</td> <td>1977</td> <td>none</td> </tr> <tr> <th>15</th> <td>16</td> <td>miranova condominiums</td> <td>314 / 96</td> <td>26</td> <td>2001</td> <td>tallest residential building in the state of ohio. tallest building built in the 2000s</td> </tr> <tr> <th>16</th> <td>17</td> <td>fifth third center</td> <td>302 / 92</td> <td>25</td> <td>1998</td> <td>none</td> </tr> <tr> <th>17</th> <td>18</td> <td>motorists mutual building</td> <td>286 / 87</td> <td>21</td> <td>1973</td> <td>none</td> </tr> <tr> <th>18</th> <td>19</td> <td>midland building</td> <td>280 / 85</td> <td>21</td> <td>1970</td> <td>none</td> </tr> <tr> <th>19</th> <td>20</td> <td>the condominiums at north bank park</td> <td>267 / 81</td> <td>20</td> <td>2007</td> <td>none</td> </tr> <tr> <th>20</th> <td>21=</td> <td>lincoln tower dormitory</td> <td>260 / 79</td> <td>26</td> <td>1967</td> <td>none</td> </tr> <tr> <th>21</th> <td>21=</td> <td>morrill tower dormitory</td> <td>260 / 79</td> <td>26</td> <td>1967</td> <td>none</td> </tr> <tr> <th>22</th> <td>23</td> <td>hyatt regency columbus</td> <td>256 / 78</td> <td>20</td> <td>1980</td> <td>none</td> </tr> <tr> <th>23</th> <td>24</td> <td>key bank building</td> <td>253 / 77</td> <td>20</td> <td>1963</td> <td>none</td> </tr> <tr> <th>24</th> <td>25</td> <td>adam's mark hotel</td> <td>243 / 74</td> <td>16</td> <td>1961</td> <td>none</td> </tr> <tr> <th>25</th> <td>26</td> <td>town center</td> <td>226 / 69</td> <td>17</td> <td>1974</td> <td>none</td> </tr> <tr> <th>26</th> <td>27</td> <td>8 east broad street</td> <td>212 / 64.6</td> <td>17</td> <td>1906</td> <td>none</td> </tr> <tr> <th>27</th> <td>28</td> <td>huntington building</td> <td>202 / 59.4</td> <td>13</td> <td>1926</td> <td>none</td> </tr> <tr> <th>28</th> <td>29</td> <td>ohio judicial center</td> <td>200 / 57.9</td> <td>14</td> <td>1933</td> <td>none</td> </tr> <tr> <th>29</th> <td>30</td> <td>16 east broad street</td> <td>180 / 64.4</td> <td>13</td> <td>1900</td> <td>none</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1</td> </tr> </tbody> </table>

select count ( * ) where name = 'the condominiums at north bank park' <table_name> : table | | rank | name | height ft / m | floors | year | notes | |---:|:-------|:------------------------------------|:----------------|---------:|-------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------| | 0 | 1 | rhodes state office tower | 629 / 192 | 41 | 1973 | has been the tallest building in columbus and the tallest mid-block skyscraper in ohio since 1973. tallest building constructed in columbus in the 1970s | | 1 | 2 | leveque tower | 555 / 169 | 47 | 1927 | tallest building constructed in columbus in the 1920s | | 2 | 3 | william green building | 530 / 162 | 33 | 1990 | tallest building constructed in columbus in the 1990s | | 3 | 4 | huntington center | 512 / 156 | 37 | 1984 | tallest building constructed in columbus in the 1980s | | 4 | 5 | vern riffe state office tower | 503 / 153 | 32 | 1988 | none | | 5 | 6 | one nationwide plaza | 485 / 148 | 40 | 1976 | none | | 6 | 7 | franklin county courthouse | 464 / 141 | 27 | 1991 | none | | 7 | 8 | aep building | 456 / 139 | 31 | 1983 | none | | 8 | 9 | borden building | 438 / 134 | 34 | 1974 | none | | 9 | 10 | three nationwide plaza | 408 / 124 | 27 | 1989 | none | | 10 | 11 | one columbus center | 366 / 112 | 26 | 1987 | none | | 11 | 12 | columbus center | 357 / 109 | 25 | 1964 | tallest building constructed in columbus in the 1960s. was built as the bank one tower | | 12 | 13 | capitol square | 350 / 107 | 26 | 1984 | none | | 13 | 14 | continental center | 348 / 106 | 26 | 1973 | none | | 14 | 15 | pnc bank building | 317 / 97 | 25 | 1977 | none | | 15 | 16 | miranova condominiums | 314 / 96 | 26 | 2001 | tallest residential building in the state of ohio. tallest building built in the 2000s | | 16 | 17 | fifth third center | 302 / 92 | 25 | 1998 | none | | 17 | 18 | motorists mutual building | 286 / 87 | 21 | 1973 | none | | 18 | 19 | midland building | 280 / 85 | 21 | 1970 | none | | 19 | 20 | the condominiums at north bank park | 267 / 81 | 20 | 2007 | none | | 20 | 21= | lincoln tower dormitory | 260 / 79 | 26 | 1967 | none | | 21 | 21= | morrill tower dormitory | 260 / 79 | 26 | 1967 | none | | 22 | 23 | hyatt regency columbus | 256 / 78 | 20 | 1980 | none | | 23 | 24 | key bank building | 253 / 77 | 20 | 1963 | none | | 24 | 25 | adam's mark hotel | 243 / 74 | 16 | 1961 | none | | 25 | 26 | town center | 226 / 69 | 17 | 1974 | none | | 26 | 27 | 8 east broad street | 212 / 64.6 | 17 | 1906 | none | | 27 | 28 | huntington building | 202 / 59.4 | 13 | 1926 | none | | 28 | 29 | ohio judicial center | 200 / 57.9 | 14 | 1933 | none | | 29 | 30 | 16 east broad street | 180 / 64.4 | 13 | 1900 | none |

| | count ( "*" ) | |---:|----------------:| | 0 | 1 |

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col : count ( "*" ) row 1 : 13

select count ( * ) where size (in kb) = 'none' <table_name> : table \begin{tabular}{lllllll} \toprule & version & date & development cycle & size (in kb) & download & notes \\ \midrule 0 & 0.1 & 9 june 1993 & beta & none & evolt & none \\ 1 & 0.2 & 14 june 1993 & beta & none & none & changelog \\ 2 & 0.3 & 16 june 1993 & beta & none & none & changelog \\ 3 & 0.4 & 18 june 1993 & beta & none & none & changelog \\ 4 & 0.5 & 24 june 1993 & beta & none & none & changelog \\ 5 & 0.6 & 30 june 1993 & beta & none & none & changelog \\ 6 & 0.8 & 5 november 1993 & beta & none & none & changelog (distinct version discontinued) \\ 7 & 0.9 & 12 november 1993 & beta-pre & none & none & none \\ 8 & 0.9 & 16 november 1993 & beta & none & none & changelog \\ 9 & 0.9 & 22 november 1993 & winsock alpha r9.2 & none & none & none \\ 10 & 1 & 17 february 1994 & release & none & evolt & none \\ 11 & 1.01 & none & release & none & none & none \\ 12 & 1.01a & 17 march 1994 & release & 521 & [5], evolt & changelog \\ 13 & 2 & none & alpha & none & none & development ceased \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & count ( "*" ) \\ \midrule 0 & 13 \\ \bottomrule \end{tabular}

select count ( * ) where size (in kb) = 'none' <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>version</th> <th>date</th> <th>development cycle</th> <th>size (in kb)</th> <th>download</th> <th>notes</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>0.1</td> <td>9 june 1993</td> <td>beta</td> <td>none</td> <td>evolt</td> <td>none</td> </tr> <tr> <th>1</th> <td>0.2</td> <td>14 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>2</th> <td>0.3</td> <td>16 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>3</th> <td>0.4</td> <td>18 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>4</th> <td>0.5</td> <td>24 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>5</th> <td>0.6</td> <td>30 june 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>6</th> <td>0.8</td> <td>5 november 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog (distinct version discontinued)</td> </tr> <tr> <th>7</th> <td>0.9</td> <td>12 november 1993</td> <td>beta-pre</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>8</th> <td>0.9</td> <td>16 november 1993</td> <td>beta</td> <td>none</td> <td>none</td> <td>changelog</td> </tr> <tr> <th>9</th> <td>0.9</td> <td>22 november 1993</td> <td>winsock alpha r9.2</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>10</th> <td>1</td> <td>17 february 1994</td> <td>release</td> <td>none</td> <td>evolt</td> <td>none</td> </tr> <tr> <th>11</th> <td>1.01</td> <td>none</td> <td>release</td> <td>none</td> <td>none</td> <td>none</td> </tr> <tr> <th>12</th> <td>1.01a</td> <td>17 march 1994</td> <td>release</td> <td>521</td> <td>[5], evolt</td> <td>changelog</td> </tr> <tr> <th>13</th> <td>2</td> <td>none</td> <td>alpha</td> <td>none</td> <td>none</td> <td>development ceased</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>count ( "*" )</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>13</td> </tr> </tbody> </table>

select count ( * ) where size (in kb) = 'none' <table_name> : table | | version | date | development cycle | size (in kb) | download | notes | |---:|:----------|:-----------------|:--------------------|:---------------|:-----------|:------------------------------------------| | 0 | 0.1 | 9 june 1993 | beta | none | evolt | none | | 1 | 0.2 | 14 june 1993 | beta | none | none | changelog | | 2 | 0.3 | 16 june 1993 | beta | none | none | changelog | | 3 | 0.4 | 18 june 1993 | beta | none | none | changelog | | 4 | 0.5 | 24 june 1993 | beta | none | none | changelog | | 5 | 0.6 | 30 june 1993 | beta | none | none | changelog | | 6 | 0.8 | 5 november 1993 | beta | none | none | changelog (distinct version discontinued) | | 7 | 0.9 | 12 november 1993 | beta-pre | none | none | none | | 8 | 0.9 | 16 november 1993 | beta | none | none | changelog | | 9 | 0.9 | 22 november 1993 | winsock alpha r9.2 | none | none | none | | 10 | 1 | 17 february 1994 | release | none | evolt | none | | 11 | 1.01 | none | release | none | none | none | | 12 | 1.01a | 17 march 1994 | release | 521 | [5], evolt | changelog | | 13 | 2 | none | alpha | none | none | development ceased |

| | count ( "*" ) | |---:|----------------:| | 0 | 13 |

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col : score row 1 : 1-1

select score where season = 2003 <table_name> : table \begin{tabular}{llllll} \toprule & season & winner & score & runners-up & venue \\ \midrule 0 & 2000 & san juan jabloteh & 1-0 & defence force & marvin lee stadium \\ 1 & 2001 & w connection & 1-0 & caledonia aia & manny ramjohn stadium \\ 2 & 2002 & defence force & 2-0 & w connection & hasely crawford stadium \\ 3 & 2003 & san juan jabloteh & 1-1 & w connection & manny ramjohn stadium \\ 4 & 2004 & w connection & 2-2 & defence force & manny ramjohn stadium \\ 5 & 2005 & w connection & 3-1 & san juan jabloteh & manny ramjohn stadium \\ 6 & 2006 & w connection & 3-1 & north east stars & manny ramjohn stadium \\ 7 & 2007 & w connection & 2-0 & caledonia aia & manny ramjohn stadium \\ 8 & 2008 & w connection & 2-2 & joe public & manny ramjohn stadium \\ 9 & 2009 & defence force & 1-0 & joe public & marvin lee stadium \\ 10 & 2010 & joe public & 1-1 & defence force & marvin lee stadium \\ 11 & 2011 & caledonia aia & 2-1 & t&tec & hasely crawford stadium \\ 12 & 2012 & caledonia aia & 2-1 & defence force & hasely crawford stadium \\ 13 & 2013 & central fc & 2-1 & defence force & hasely crawford stadium \\ \bottomrule \end{tabular}

\begin{tabular}{ll} \toprule & score \\ \midrule 0 & 1-1 \\ \bottomrule \end{tabular}

select score where season = 2003 <table_name> : table <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>season</th> <th>winner</th> <th>score</th> <th>runners-up</th> <th>venue</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>2000</td> <td>san juan jabloteh</td> <td>1-0</td> <td>defence force</td> <td>marvin lee stadium</td> </tr> <tr> <th>1</th> <td>2001</td> <td>w connection</td> <td>1-0</td> <td>caledonia aia</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>2</th> <td>2002</td> <td>defence force</td> <td>2-0</td> <td>w connection</td> <td>hasely crawford stadium</td> </tr> <tr> <th>3</th> <td>2003</td> <td>san juan jabloteh</td> <td>1-1</td> <td>w connection</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>4</th> <td>2004</td> <td>w connection</td> <td>2-2</td> <td>defence force</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>5</th> <td>2005</td> <td>w connection</td> <td>3-1</td> <td>san juan jabloteh</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>6</th> <td>2006</td> <td>w connection</td> <td>3-1</td> <td>north east stars</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>7</th> <td>2007</td> <td>w connection</td> <td>2-0</td> <td>caledonia aia</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>8</th> <td>2008</td> <td>w connection</td> <td>2-2</td> <td>joe public</td> <td>manny ramjohn stadium</td> </tr> <tr> <th>9</th> <td>2009</td> <td>defence force</td> <td>1-0</td> <td>joe public</td> <td>marvin lee stadium</td> </tr> <tr> <th>10</th> <td>2010</td> <td>joe public</td> <td>1-1</td> <td>defence force</td> <td>marvin lee stadium</td> </tr> <tr> <th>11</th> <td>2011</td> <td>caledonia aia</td> <td>2-1</td> <td>t&tec</td> <td>hasely crawford stadium</td> </tr> <tr> <th>12</th> <td>2012</td> <td>caledonia aia</td> <td>2-1</td> <td>defence force</td> <td>hasely crawford stadium</td> </tr> <tr> <th>13</th> <td>2013</td> <td>central fc</td> <td>2-1</td> <td>defence force</td> <td>hasely crawford stadium</td> </tr> </tbody> </table>

<table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>score</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1-1</td> </tr> </tbody> </table>

select score where season = 2003 <table_name> : table | | season | winner | score | runners-up | venue | |---:|---------:|:------------------|:--------|:------------------|:------------------------| | 0 | 2000 | san juan jabloteh | 1-0 | defence force | marvin lee stadium | | 1 | 2001 | w connection | 1-0 | caledonia aia | manny ramjohn stadium | | 2 | 2002 | defence force | 2-0 | w connection | hasely crawford stadium | | 3 | 2003 | san juan jabloteh | 1-1 | w connection | manny ramjohn stadium | | 4 | 2004 | w connection | 2-2 | defence force | manny ramjohn stadium | | 5 | 2005 | w connection | 3-1 | san juan jabloteh | manny ramjohn stadium | | 6 | 2006 | w connection | 3-1 | north east stars | manny ramjohn stadium | | 7 | 2007 | w connection | 2-0 | caledonia aia | manny ramjohn stadium | | 8 | 2008 | w connection | 2-2 | joe public | manny ramjohn stadium | | 9 | 2009 | defence force | 1-0 | joe public | marvin lee stadium | | 10 | 2010 | joe public | 1-1 | defence force | marvin lee stadium | | 11 | 2011 | caledonia aia | 2-1 | t&tec | hasely crawford stadium | | 12 | 2012 | caledonia aia | 2-1 | defence force | hasely crawford stadium | | 13 | 2013 | central fc | 2-1 | defence force | hasely crawford stadium |

| | score | |---:|:--------| | 0 | 1-1 |

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