tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: gstorey__12107__Mar01
Sheet: table2

NATURAL GAS EXPORTS BY TERM, REGION, AND CUSTOMER TYPE |  |  |  |  |  |  |  |  |  |  |  | TABLE 2
EXPORTATIONS DE GAZ NATUREL PAR TERME, RÉGION, ET CLIENT
 |  |  |  | AVERAGE PRICE |  |  |  |  |  | AVERAGE PRICE
 | VOLUME |  |  | PRIX MOYEN |  |  | VOLUME |  |  | PRIX MOYEN
 | (MILLIONS M3) |  |  | ($CDN/GJ) |  |  | (MILLIONS M3) |  |  | ($CDN/GJ)
 |  |  | % CHANGE |  |  | % CHANGE |  |  | % CHANGE |  |  | % CHANGE
 |  |  | VARIATION |  |  | VARIATION | 1999-11-01 00:00:00 | 2000-11-01 00:00:00 | VARIATION | 1999-11-01 00:00:00 | 2000-11-01 00:00:00 | VARIATION
 | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN % | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN % | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN % | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN %
TERM/TERME
LONG-TERM (FIRM)/LONG TERME (GARANTI) | 2449.4 | 1904.2 | -22.3 | 3.42 | 7.02 | 105 | 11477.7 | 9431.2 | -17.8 | 3.53 | 7.97 | 125.5
SHORT-TERM (FIRM)/COURT TERME (GARANTI) | 3610.2 | 4702.8 | 30.3 | 3.36 | 7.4 | 119.9 | 19150.8 | 22867.4 | 19.4 | 3.31 | 9.4 | 183.9
SHORT-TERM/COURT TERME (INTERRUPTIBLE) | 2452.7 | 2498 | 1.8 | 3.66 | 7.85 | 114.5 | 11726.1 | 15224.3 | 29.8 | 3.44 | 10.12 | 194.2
TOTAL - TERM/TERME | 8512.3 | 9105 | 7 | 3.47 | 7.44 | 114.8 | 42354.6 | 47522.9 | 12.2 | 3.41 | 9.35 | 174.4
REGION/RÉGION
CALIFORNIA/CALIFORNIE | 1632.1 | 1365.5 | -16.3 | 3.13 | 9.07 | 190.1 | 8653.8 | 7525.3 | -13 | 3.2 | 10.17 | 217.6
MIDWEST/MIDWEST | 3021.1 | 3439.9 | 13.9 | 3.28 | 7.02 | 114.2 | 15435.4 | 17829.1 | 15.5 | 3.23 | 8.88 | 174.7
MOUNTAIN/ROCHEUSES | 84.5 | 29 | -65.7 | 3.37 | 4.33 | 28.7 | 430.8 | 180.3 | -58.1 | 3.12 | 6.3 | 102.1
NORTHEAST/NORD-EST | 2508.2 | 2608.2 | 4 | 4.07 | 7.39 | 81.4 | 11589.6 | 14950 | 29 | 3.91 | 9.02 | 130.8
PACIFIC NORTHWEST/NORD-OUEST PACIFIQUE | 1266.4 | 1662.5 | 31.3 | 3.17 | 7.13 | 125.3 | 6245 | 7038.2 | 12.7 | 3.21 | 10.42 | 224.3
TOTAL - REGION/RÉGION | 8512.3 | 9105 | 7 | 3.47 | 7.44 | 114.8 | 42354.6 | 47522.9 | 12.2 | 3.41 | 9.35 | 174.4
CUSTOMER TYPE/CLIENT
END-USER/UTILISATEURS ULTIMES | 668.9 | 682.1 | 2 | 3.9 | 6.13 | 57.1 | 3355.6 | 3048.6 | -9.2 | 3.8 | 6.78 | 78.4
LDC/SDL | 2269.8 | 1752.9 | -22.8 | 3.56 | 7.34 | 105.9 | 11154.5 | 10119.6 | -9.3 | 3.48 | 8.97 | 157.6
MARKETING CO./DISTRIBUTEURS | 5306.3 | 6291.5 | 18.6 | 3.42 | 7.69 | 124.4 | 26346.6 | 32372.3 | 22.9 | 3.35 | 9.83 | 193.3
PIPELINE/PIPELINES | 267.2 | 378.6 | 41.7 | 2.38 | 6.27 | 163.9 | 1497.9 | 1982.4 | 32.3 | 2.93 | 7.34 | 150.1
TOTAL - CUSTOMER TYPE/CLIENT | 8512.3 | 9105 | 7 | 3.47 | 7.44 | 114.77 | 42354.6 | 47522.9 | 12.2 | 3.41 | 9.35 | 174.4
 | PRICE AT THE INTERNATIONAL BORDER |  |  |  |  |  |  | À LA FRONTIÈRE INTERNATIONALE
Spreadsheet: 59430d1259929914-how-to-automate-top-5-entries-in-a-worksheet-709631_befuddled_v2
Sheet: Aug09

Date | Item | Description |  |  |  | 2009-08-01 00:00:00 | Items | A | apples
 |  |  |  |  |  |  |  | B | bananas
 |  |  |  |  |  |  |  | C | carrots
 |  |  |  |  |  |  |  | D | dogs
 |  |  |  |  |  |  |  | E | elephants
 |  |  |  |  |  |  |  | F | fish
 |  |  |  |  |  |  |  | G | grapes
 |  |  |  |  |  |  |  | H | hyenas
 |  |  |  |  |  |  |  | I | iguanas
 |  |  |  |  |  |  |  | J | jesuits
Spreadsheet: 0c5635df-904e-4f67-b7d4-82f0338667fa
Sheet: NL C

National League Catchers
Name | Type | Type | Score
[NAME] | Arizona | A | 81.4671814671815
[NAME] | Atlanta | A | 78.7644787644788
Yadier Molina | St. Louis | A | 77.2200772200772
[NAME] | Philadelphia | A | 74.5173745173745
[NAME] | Cincinnati | A | 74.1312741312741
[NAME] | Los Angeles N | A | 72.3938223938224
Geovany Soto | Chicago N | A | 72.2007722007722
[NAME] | Colorado | B | 71.4285714285714
[NAME] | Pittsburgh | B | 69.1119691119691
[NAME] | Washington | B | 66.4092664092664
Ronny Paulino | Florida | B | 64.6718146718147
[NAME] | Arizona | B | 62.9343629343629
[NAME] | Cincinnati | B | 62.1621621621622
[NAME] | Florida | B | 61.7760617760618
[NAME] | Atlanta | B | 58.3011583011583
[NAME] | New York N | B | 58.3011583011583
Yorvit Torrealba | San Diego | B | 58.3011583011583
[NAME] | Washington | None | 57.1428571428571
[NAME] | San Diego | None | 56.3706563706564
[NAME] | Milwaukee | None | 51.7374517374517
[NAME] | New York N | None | 51.5444015444015
[NAME] | Colorado | None | 50.5791505791506
[NAME] | Los Angeles N | None | 43.4362934362934
[NAME] | Chicago N | None | 42.6640926640927
[NAME] | Philadelphia | None | 40.9266409266409
[NAME] | Houston | None | 37.0656370656371
[NAME] | New York N | None | 34.5559845559846
Eli Whiteside | San Francisco | None | 30.1158301158301
[NAME] | Milwaukee | None | 29.7297297297297
[NAME] | St. Louis | None | 29.3436293436293
[NAME] | Milwaukee | None | 28.3783783783784
[NAME] | Pittsburgh | None | 28.1853281853282
Wil Nieves | Washington | None | 27.992277992278
[NAME] | Cincinnati | None | 24.9034749034749
[NAME] | Florida | None | 21.8146718146718
[NAME] | Houston | None | 19.8841698841699
Dane Sardinha | Philadelphia | None | 19.6911196911197
A.J. Ellis | Los Angeles N | None | 9.84555984555985
Rosters courtesy of cbssportsline.com
Statistics courtesy of baseballreference.com
Contract info courtesy of Cot's Contracts
Free Agent
Free Agent with Option
Spreadsheet: 71761d1272487610-populating-tables-with-summary-data-using-vlookup-or-similar-excel-forum-problem
Sheet: Sheet1

Headcount data entered in Table 1 (column "Headcount") by staff group by level of pay. Question: how to complete Table 2 which is summary of all staff in Table 1 by level
Question: how to complete Table 2 which is a summary of all staff in Table 1 by level. This needs to be done automatically using VLOOKUP function or any other facility except PIVOT table, so that Table 2 updates automatically as data is entered into Table 1
Table 1 |  |  |  |  | Table 2
 |  |  |  |  | Total Staff
Staff group | Pay Level | Headcount |  |  | Pay Level | Headcount
Nurse | 1 | 3 |  |  | 1 | ?
Nurse | 2 | 5 |  |  | 2 | ?
Nurse | 3 | 7 |  |  | 3 | ?
Nurse | 4 | 7 |  |  | 4 | ?
Nurse | 5-6 | 10 |  |  | 5-6 | ?
Doctors | 1 | 4
Doctors | 2 | 1
Doctors | 3 | 2
Doctors | 4 | 3
Doctors | 5-6 | 15
Scientists | 1 | 3
Scientists | 2 | 5
Scientists | 3 | 1
Scientists | 4 | 7
Scientists | 5-6 | 13
Spreadsheet: darrell_schoolcraft__7324__imball0202
Sheet: PEPL

 | Hansford
 | 8042
Day | Measured | Scheduled
1 | -28994 | -28956
2 | -58020 | -57711
3 | -57789 | -57711
4 | -57818 | -57711
5 | -29948 | -29013
6 | -17354 | -18500
7 | -38858 | -38303
8 | -23897 | -23492
9 | -66545 | -67340
10 | -67813 | -67340
11 | -67191 | -67340
12 | -36674 | -36088
13 | -47122 | -47000
14 | -45072 | -45048
15 | -33797 | -32900
16 | -57765 | -57276
17 | -57995 | -57276
18 | -57788 | -57276
19 | -57778 | -57276
20 | -67624 | -78500
21
22
23
24
25
26
27
28
29
30
31
2002-01-31 00:00:00 |  |  | 19592
2002-02-20 00:00:00
CBS Dollars
 |  |  | 186633
Spreadsheet: 57032d1257204969-minimazation-from-matrices-example
Sheet: Sheet1

 |  |  | The sum of (Matrix 1 X axis * Matrix 1 Y axis) + (Matrix 2 X axis * Matrix 2 Y axis)
 |  |  | must equal : 6 (Note: This number will change based on the problem)
 |  |  | I want to minimize the X Axis results. Thus, the problem seems to be the minimization
 |  |  | of the sum of the squared matrix one dimensions + the squared matrix two dimensions.
 |  |  | From the minimazation of the X Axis results, I need to obtain the X Axis Matrix #1 result
 |  |  | and the X Axis Matrix #2 result.
 |  |  |  | Dimension A
Dimension A data will change |  |  |  | 26 | 4
based on the problem.
 |  |  |  | Matrix #1
 |  |  |  | X Axis
 |  |  |  | 0 | 1 | 2 | 3 | 4 | 5 | 6
 |  |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 |  |  | 1 | 0 | 30 | 56 | 82 | 108 | 134 | 160
 |  |  | 2 | 0 | 34 | 60 | 86 | 112 | 138 | 164
 | Y Axis |  | 3 | 0 | 38 | 64 | 90 | 116 | 142 | 168
 | Constraint |  | 4 | 0 | 42 | 68 | 94 | 120 | 146 | 172
 | 5 |  | 5 | 0 | 46 | 72 | 98 | 124 | 150 | 176
The Y axis constraint will
also vary for both matrices
based on the problem.
 |  |  |  | Inverse Dimension A
 |  |  |  | 4 | 26
 |  |  |  |  |  |  |  |  |  |  |  |  | Manual Solution:
 |  |  |  | Matrix #2
 |  |  |  | X Axis |  |  |  |  |  |  |  |  | Based on 6, the minimazation would be 46 from matrix #1 and
 |  |  |  | 0 | 1 | 2 | 3 | 4 | 5 | 6 |  |  | 30 from matrix #2.
 | Y Axis |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | Constraint |  | 1 | 0 | 30 | 34 | 38 | 42 | 46 | 50
 | 2 |  | 2 | 0 | 56 | 60 | 64 | 68 | 72 | 76
Spreadsheet: 839811d1692242519-simple-way-to-calculate-ltm-results-for-quarterly-data-that-isnt-contiguous-test-50-
Sheet: Sheet1

1Q21A | 1Q22A | 1Q23A |  | 2Q21A | 2Q22A | 2Q23A |  | 3Q21A | 3Q22A |  | 4Q21A | 4Q22A
1 | 5 | 9 |  | 2 | 6 | 10 |  | 3 | 7 |  | 4 | 8
 | Desired Result | [NAME] | FORMULATEXT
1Q22
2Q22
3Q22
4Q22
1Q23
2Q23
Spreadsheet: 752846d1635010180-extracting-a-set-of-random-values-with-no-duplicates-and-one-condition-example1
Sheet: Sheet1

Shipment ID | Agent |  | Agent | Shipment 1 | Shipment 2 | Shipment 3 | Shipment 4
21702270 | Agent 1
21713850 | Agent 1 |  | Agent 2
21697639 | Agent 1 |  | Agent 3
21792449 | Agent 1 |  | Agent 4
21629421 | Agent 1
21703858 | Agent 1
21738654 | Agent 1
21682726 | Agent 1
21661149 | Agent 1
21839494 | Agent 1
21897695 | Agent 1
21875651 | Agent 1
21815931 | Agent 1
21875651 | Agent 1
21803176 | Agent 1
21742842 | Agent 1
21667840 | Agent 1
21914114 | Agent 1
21162358 | Agent 2
21879642 | Agent 2
21315875 | Agent 2
21452311 | Agent 2
21441551 | Agent 2
21166667 | Agent 2
21392224 | Agent 2
21772161 | Agent 2
21660785 | Agent 2
21697254 | Agent 2
21697348 | Agent 2
21516411 | Agent 2
21844291 | Agent 3
21699634 | Agent 3
21774965 | Agent 3
21690248 | Agent 3
21468107 | Agent 3
21697268 | Agent 3
21482196 | Agent 3
21775168 | Agent 4
21384101 | Agent 4
21240872 | Agent 4
21818881 | Agent 4
21699634 | Agent 4
Spreadsheet: 111735d1308059060-sorting-lists-by-score-high-to-low-example
Sheet: Sheet1

 |  | E | A | P | U | TOTAL
 | Mayada | 0.384 | 0.4 | 0.09 | 0.11
 | [NAME] | 0.292 | 0.388 | 0.0837 | 0.11
 | Rawaa | 0.3080000000000001 | 0.36 | 0.0603 | 0.0979
 | Athraa | 0.356 | 0.224 | 0.0396 | 0.0968
 | [NAME] | 0.18 | 0.348 | 0.0693 | 0.0803
 | [NAME] | 0.352 | 0.396 | 0.072 | 0.1078
 | Worood | 0.4 | 0.4 | 0.081 | 0.1023
 | Fayhaa | 0.268 | 0.304 | 0.09 | 0.11
 | Ziyad | 0.396 | 0.356 | 0.0693 | 0.0803
 | [NAME] | 0.344 | 0.368 | 0.0801 | 0.0979
Spreadsheet: db56ec07-a2f6-4498-9f81-13f40e9ca8e5
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | RUN | T1 | BIKE | T2 | SKI | POSITION | TOTAL TIME
2127 | 10471 | Marte | Breen | NOR
2127 | 10470 | Marte | Hoivik | NOR
Spreadsheet: 764056d1642550478-consolidate-multiple-tabs-with-different-headers-not-using-power-query-sample-book-1
Sheet: Tab 3

Building | Size | Last Update | User ID
East | 4184 | 2021-10-01 | 5066
South | 10800 | 2021-10-01 | 5067
East | 1470 | 2021-05-10 | 5068
South | 0 | 2021-11-19 | 5069
Spreadsheet: 178988d1346973590-information-auto-fill-black-20forest-1-
Sheet: Sheet1

Ingredient | Cost | Per | Recipe | Cost
Self Raising Flour | 1.7 | [NAME] | 85g | 0.1446808510638298
Cocoa Powder | 2.99 | 250g | 4tbsp | 0.299
Caster Sugar | 1.65 | [NAME] | 110g | 0.1833333333333333
Stork | 2.1 | [NAME] | 110g | 0.2333333333333333
Eggs | 1.89 | 18 | 2 | 0.21
Black [NAME] | 2.2 | 340g |  | 2.2
Double Cream | 1.1 | 300ml | 200ml | 0.7333333333333334
[NAME] | 2.1 | 100g | 60g | 1.272727272727273
 |  |  |  | 5.276408123791104 | 0.439700676982592
Cases | 9.5 | 50 | 0.19 |  | 0.6297006769825919
Spreadsheet: 680468d1591037579-linking-cells-to-a-summary-new-mileage-auto-form-forum-copy
Sheet: Master sheet

 | Company Miles | Fuel cost | Litres | Private miles | Paid back | Cost per litre | Cost per mile | Cost for Private miles | paid in excess of fuel cost
2020-03-28 00:00:00
2020-04-04 00:00:00
2020-04-11 00:00:00
2020-04-18 00:00:00
2020-04-25 00:00:00
2020-05-02 00:00:00
2020-05-09 00:00:00
2020-05-16 00:00:00
2020-05-23 00:00:00
2020-05-30 00:00:00
2020-06-06 00:00:00
2020-06-13 00:00:00
2020-06-20 00:00:00
2020-06-27 00:00:00
2020-07-04 00:00:00
2020-07-11 00:00:00
2020-07-18 00:00:00
2020-07-25 00:00:00
2020-08-01 00:00:00
2020-08-08 00:00:00
2020-08-15 00:00:00
2020-08-22 00:00:00
2020-08-29 00:00:00
2020-09-05 00:00:00
2020-09-12 00:00:00
2020-09-19 00:00:00
2020-09-26 00:00:00
2020-10-03 00:00:00
2020-10-10 00:00:00
2020-10-17 00:00:00
2020-10-24 00:00:00
2020-10-31 00:00:00
2020-11-07 00:00:00
2020-11-14 00:00:00
2020-11-21 00:00:00
2020-11-28 00:00:00
2020-12-05 00:00:00
2020-12-12 00:00:00
2020-12-19 00:00:00
2020-12-26 00:00:00
2021-01-02 00:00:00
2021-01-09 00:00:00
2021-01-16 00:00:00
2021-01-23 00:00:00
2021-01-30 00:00:00
2021-02-06 00:00:00
2021-02-13 00:00:00
2021-02-20 00:00:00
2021-02-27 00:00:00
2021-03-06 00:00:00
2021-03-13 00:00:00
2021-03-20 00:00:00
2021-03-27 00:00:00
Total 2019 / 2020
Spreadsheet: kate_symes__18360__MeadMktplace (2)
Sheet: MeadMktplace

 |  |  | Firm | Volume | Firm | Volume | Non Firm | Volume | Non Firm | Volume
 | DATE |  | On [NAME] | [NAME] | [NAME] | [NAME] | On [NAME] | [NAME] | [NAME] | [NAME]
 | 2001-04-23 00:00:00 |  | 183.62 | 3296 | 101.96 | 1808
 | 2001-04-22 00:00:00 |  | 167 | 800 | 100 | 0 | 111.96 | 646 | 93 | 1461
 | 2001-04-21 00:00:00 |  | 153.2 | 2016 | 81.46 | 1808 | 127.35 | 1321 | 93.52 | 1342
 | 2001-04-20 00:00:00 |  | 153.2 | 2016 | 81.46 | 1808 | 156.62 | 1567 | 107.9 | 571
 | 2001-04-19 00:00:00 |  | 226.96 | 736 | 96.96 | 2528 | 159.32 | 1480 | 111.4 | 1098
 | 2001-04-18 00:00:00 |  | 226.96 | 736 | 96.96 | 2528 | 149.24 | 2414 | 129.74 | 1317
 | 2001-04-17 00:00:00 |  | 226.96 | 736 | 96.96 | 2528 | 154.56 | 1929 | 95.55 | 1346
 | 2001-04-16 00:00:00 |  | 221.9 | 336 | 121.2 | 768 | 133.03 | 1144 | 80.72 | 1323
 | 2001-04-15 00:00:00 |  | 225 | 800 | 80 | 1200 | 60.05 | 2368 | 44.12 | 1494
 | 2001-04-14 00:00:00 |  | 153.98 | 2736 | 79.16 | 1808 | 101.54 | 2179 | 71.44 | 1068
 | 2001-04-13 00:00:00 |  | 153.98 | 2736 | 79.16 | 1808 | 118.59 | 2350 | 92.08 | 1386
 | 2001-04-12 00:00:00 |  | 163.9 | 4464 | 96.03 | 2832 | 121.22 | 2500 | 98.14 | 1742
 | 2001-04-11 00:00:00 |  | 186.25 | 640 | 102.5 | 400 | 146.66 | 1921 | 101.73 | 1672
 | 2001-04-10 00:00:00 |  | 189.32 | 1184 | 98.94 | 1440 | 146.67 | 2390 | 93.48 | 1552
 | 2001-04-09 00:00:00 |  | 126.46 | 2896 | 105.72 | 1264 | 122.88 | 1015 | 86.46 | 925
 | 2001-04-08 00:00:00 |  | 130 | 0 | 98 | 0 | 97.91 | 2833 | 87.85 | 1659
 | 2001-04-07 00:00:00 |  | 183.6 | 2576 | 92.82 | 1704 | 114.42 | 1980 | 114.75 | 800
 | 2001-04-06 00:00:00 |  | 183.6 | 2576 | 92.93 | 1680 | 147.71 | 1463 | 91.2 | 1429
 | 2001-04-05 00:00:00 |  | 200.55 | 5984 | 102.44 | 2408 | 127.14 | 2549 | 98.45 | 1862
 | 2001-04-04 00:00:00 |  | 199.23 | 4384 | 103.75 | 2232 | 148.64 | 1692 | 81.66 | 1580
 | 2001-04-03 00:00:00 |  | 188.58 | 4064 | 116.57 | 1632 | 117.12 | 1130 | 85.69 | 262
 | 2001-04-02 00:00:00 |  | 238.59 | 1024 | 150.88 | 912 | 137.01 | 2361 | 111.15 | 1000
 | 2001-04-01 00:00:00 |  | 180 | 800 | 107 | 600 | 148.11 | 1110 | 121.38 | 1200
 | 2001-03-31 00:00:00 |  | 154.62 | 624 | 95.02 | 1832 | 208.73 | 2005 | 132.05 | 925
 | 2001-03-30 00:00:00 |  | 154.62 | 624 | 94.91 | 1832 | 157.25 | 2240 | 118.11 | 1415
 | 2001-03-29 00:00:00 |  | 150.35 | 1824 | 96.1 | 1672 | 134.29 | 2045 | 98.07 | 1330
 | 2001-03-28 00:00:00 |  | 133.2 | 3328 | 74.97 | 1544 | 115.44 | 1399 | 82.09 | 1685
 | 2001-03-27 00:00:00 |  | 105.94 | 1104 | 69.87 | 1232 | 119.31 | 1428 | 71.55 | 1817
 | 2001-03-26 00:00:00 |  | 278.99 | 1104 | 158.37 | 712 | 121.58 | 1216 | 59.09 | 901
 | 2001-03-25 00:00:00 |  | 195 | 0 | 150 | 0 | 83.27 | 1706 | 57.7 | 1655
 | 2001-03-24 00:00:00 |  | 240.51 | 624 | 143.75 | 880 | 122.71 | 3765 | 146.16 | 2205
Spreadsheet: 0d5d5926-a95c-4355-a1c3-717a5b0e60d4
Sheet: Sheet1

Unnamed: 0 | International Taekwon-Do Federation | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
 | Individual Black Belt Degree Application Form (4th to 8th degree)
 |  | Country:
new certificate application |  |  |  | replacement certificate
Yes or No |  |  |  | Yes or No
Candidate:
 | one (1) first name only |  |  |  | surname |  |  | Mr/Mrs/Miss
Address:
 | street |  |  |  | number | code | city
Date of Birth: |  |  |  |  | Nationality:
 | year | month | day
actual kup or degree: |  | requested degree: |  |  |  | promotion date:
e.mail: |  |  |  |  |  |  |  | attache
 |  |  |  |  |  |  |  | one photo
signature: |  |  |  |  |  |  |  | sized
 |  |  |  |  |  |  |  | 2x2 cm
candidate details | degree number | promotion date | examiner |  |  | organization
1st degree
2nd degree
3rd degree
4th degree
5th degree
6th degree
7th degree
8th degree
Examiner:
 | name |  |  |  | surname
Plaque Certificate number: |  |  |  |  | ITF degree number: |  | -    -
e.mail:
signature:
President:
(NA or AA) | name |  |  |  | surname
signature:
e.mail:
date:
 | year | month | day
NOTE:
1. This application will not be accepted without the proper plaque and certificate numbers.
2. Degree holders from a different organization must provide a copy the last issued degree certificate
3. If you make a mistake in the details then you will have to pay USD 30.00 for a replacement and
this applies to large and small certificates.
Spreadsheet: 848942d1699540028-pivot-table-how-to-add-an-extra-grand-total-column-for-min-and-max-excel-pivot-min-max
Sheet: Sheet3

Min of Price | Column Labels
Row Labels | Red | Blue | White | Pink | MIN | MAX | Min Store | [NAME]
Product 1 MAX | 139 | 144 | 149 | 154 | 139 | 154 | Red | Pink
Product 1 MIN | 124 | 129 | 134 | 139 | 124 | 139 | Red | Pink
Product 2 MAX | 140 | 202 | 150 | 155 | 140 | 155 | Red | Pink
Product 2 MIN | 125 | 130 | 135 | 140 | 125 | 140 | Red | Pink
Product 3 MAX | 141 | 146 | 151 | 156 | 141 | 156 | Red | Pink
Product 3 MIN | 126 | 131 | 136 | 141 | 126 | 141 | Red | Pink
Product 4 MAX | 192 | 147 | 114 | 157 | 114 | 192 | White | Red
Product 4 MIN | 177 | 132 | 99 | 142 | 99 | 177 | White | Red
Product 5 MAX | 143 | 148 | 153 | 158 | 143 | 158 | Red | Red
Product 5 MIN | 128 | 133 | 138 | 143 | 128 | 143 | Red | Red
MIN | 124 | 129 | 99 | 139 | 99
Spreadsheet: 25571d1216927193-only-showing-line-items-with-certain-char-counts-filteringtext
Sheet: Sheet1

Text | True/False
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
This text is less than 55 characters long. | 0
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
This text is less than 55 characters long. | 0
This text is less than 55 characters long. | 0
However, with this text we find it is greater than 55 characters | 1
However, with this text we find it is greater than 55 characters | 1
Spreadsheet: 57619d1257842779-macro-for-auto-report-in-excell-general-ledger
Sheet: 1006

 | 1006 - MAINT
 | DATE | A/C NAME | A/C NO | REF# | PARTICULARS | DR. | CR. | DR./ CR. | BALANCE |  |  |  |  | BANK | 1001
 | Opening Balance |  |  |  |  |  |  | - | 0 |  |  |  |  | CASH | 1002
 | 2009-11-11 00:00:00 | MAINT | #N/A | 4594 | MAINT OFFICE | 25 |  | Dr. | 25 |  |  |  |  | LOAN | 1003
 |  |  |  |  |  |  |  | - | 0
 |  |  |  |  | TOTAL | 25 | 0 | Dr. | 25
Spreadsheet: 680602d1591105621-statistic-layout-with-drop-down-list-with-multi-selections-statistic-layout-petmak-
Sheet: Sheet2

Store | Store 1
Bank Account | (Multiple Items)
Sum of Amount | Name | Trans. Int.
 | tblHistoricalData |  |  |  | tblHistoricalData Total | tblRecentData |  |  |  | tblRecentData Total
BIN# | A | D | E | P |  | A | D | E | P
474839 | 63000 | 4500 |  | 50 | 67550 |  | 104460 |  | 15 | 104475
513379 | 17400 | 1155 | 505 |  | 19060 | 11000 | 9105 | 2000 |  | 22105
Spreadsheet: 846479d1697653387-populate-worksheet-based-on-checkboxes-example-workbook
Sheet: DATA

 | Internal Code | Product | Course type | Price (£)
True | P1-OP | P1 | Operation | 50
 | P1-AD | P1 | Administration | 25
True | P1-DI | P1 | Diagnostics | 25
True | [NAME] | P2 | Operation | 50
True | P2-AD | P2 | Administration | 25
 | [NAME] | P2 | Diagnostics | 25
True | P3-AD | P3 | Administration | 30
 | P4-AD | P4 | Administration | 30
 | P5-AD | P5 | Administration | 25
 | P6-AD | P6 | Administration | 30
 | P6-DI | P6 | Diagnostics | 30
Spreadsheet: 122050d1316586952-vlookup-from-conditional-indirect-data-validation-list-test2
Sheet: FaceaFace

FaceaFace |  | FaceaFaceColors
Debbie | 125 | DP Dreamy Purple | 600
Digg Me | 126 | AUCI Aubergine / Citron | 601
E.O.D. | 127 | AUSB Aubergine/Sky Blue | 604
[NAME] | 128 | EG Eggplant / Green | 602
Flop | 129 | PG Purple Grain | 603
Hermitages | 130 | MBCG | 604
Human Nature | 131 | DPMC | 605
I.M.H.O. | 132 | AM Amethyst | 606
Interstellar | 133 | [NAME] | 607