tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 886680d1736775043-numbers-of-student-names-do-not-match-exactly-to-total-booking-shirts-barusaizbaju2025
Sheet: Sheet4

1 | ALIA MAISARA BINTI MOHD ANUAR | P | 28 | MERAH
2 | NUR SYAFIQAH AMANI BINTI KHAIZAM SUKRI | P | 28 | MERAH
3 | MUHAMMAD FIRDAUS BIN RASIDI | L | 30 | MERAH
4 | [NAME] | L | 30 | MERAH
5 | HARITH DARWISHY BIN MOHD NASRUL | L | 30 | MERAH
6 | NURUL AINA RAUDAH BINTI BAKRI | P | 32 | MERAH
7 | NURUL SYAFIKAH BINTI MOHD ZAMRI | P | 32 | MERAH
8 | MUHAMMAD DANIAL DANISH BIN NORHISHAM | L | 32 | MERAH
9 | NUR WAFA NADHIRAH BINTI MOHD SHARIFUDDIN | P | 32 | MERAH
10 | NUR ARRISSYA QAISARA BINTI MOHAMAD FAUZI | P | 36 | MERAH
1 | SAFIYA ARISSA BINTI KHAIRUL AZLI | P | 28 | BIRU
2 | MUHAMMAD ADIB AMSYAR BIN KHAIRUL FIRDAUS | L | 30 | BIRU
3 | NURAUFA AZ ZAHRA BINTI MOHD FACKRY | P | 30 | BIRU
4 | AQIL IZZANI BIN ARMAN | L | 30 | BIRU
5 | QHAISH NUR NASUHA BINTI ISZUAN HAFEEZ | P | 32 | BIRU
6 | MUHAMMAD MUZAYYAN RIZQI BIN MOHD FAKRULRUZI | L | 32 | BIRU
7 | [NAME] | L | 32 | BIRU
8 | HANIS ZULAIKHA BINTI AHMAD SHAKIR | P | 32 | BIRU
9 | AHMAD AMMAR BIN AHMAD ASYHRAF | L | 34 | BIRU
10 | DHIYA SAFIYYA BINTI MOHD SYAHIRAN | P | 36 | BIRU
1 | NUR FARZANA NUTREESYA BINTI KENDA | P | 30 | HIJAU
2 | ABDULLAH FAHIM BIN MOHD [NAME] | L | 32 | HIJAU
3 | MUHAMMAD AQIL ZAFRAN BIN MOHAMMAD NIZAM | L | 32 | HIJAU
4 | IRISS QALYSSA BINTI ZUBIR | P | 32 | HIJAU
5 | [NAME] | L | 32 | HIJAU
6 | HIDAYAH NUR ANGGUN BINTI AZARD | P | 32 | HIJAU
7 | NUR SYAHIDAH FAKHIRA BINTI MOHD FAUZI | P | 34 | HIJAU
8 | NUR AISYAH SAFIAH BINTI KHAIRUL ANUAR | P | 36 | HIJAU
1 | NUR ZAHRA AWATIF BINTI FAKHARUDIN | P | 30 | KUNING
2 | MUHAMMAD RIYYADH BIN MOHD RUZAIRI | L | 32 | KUNING
3 | NUR KHAIRUNNISA IRDINA BINTI KHAIRUDIN | P | 32 | KUNING
4 | ANEESA FAYHA BINTI MUHAMAD SHATHIRI | P | 32 | KUNING
5 | NUR ALYA QAISARA BINTI NAZARUDIN | P | 34 | KUNING
6 | MUHAMMAD ADAM FIRHAN BIN MOHAMAD HAIRIL RAFIZI | L | 34 | KUNING
7 | MUHAMMAD ALFIAN RIZQIE BIN AHMAD HAFIZ | L | 36 | KUNING
8 | NUR ADILA BINTI ZUL IKMAL | P | 36 | KUNING
Spreadsheet: 788161d1658307931-help-with-logic-regarding-nested-if-formulas-and-graphs-macd
Sheet: MACD

Moving Average Convergence Divergence
Date | Close | 12 Day EMA | 26 Day EMA | MACD | Signal | Histogram
2013-02-19 00:00:00 | 459.99
2013-02-20 00:00:00 | 448.85
2013-02-21 00:00:00 | 446.06
2013-02-22 00:00:00 | 450.81
2013-02-25 00:00:00 | 442.8
2013-02-26 00:00:00 | 448.97
2013-02-27 00:00:00 | 444.57
2013-02-28 00:00:00 | 441.4
2013-03-01 00:00:00 | 430.47
2013-03-04 00:00:00 | 420.05
2013-03-05 00:00:00 | 431.14
2013-03-06 00:00:00 | 425.66
2013-03-07 00:00:00 | 430.58
2013-03-08 00:00:00 | 431.72
2013-03-11 00:00:00 | 437.87
2013-03-12 00:00:00 | 428.43
2013-03-13 00:00:00 | 428.35
2013-03-14 00:00:00 | 432.5
2013-03-15 00:00:00 | 443.66
2013-03-18 00:00:00 | 455.72
2013-03-19 00:00:00 | 454.49
2013-03-20 00:00:00 | 452.08
2013-03-21 00:00:00 | 452.73
2013-03-22 00:00:00 | 461.91
2013-03-25 00:00:00 | 463.58
2013-03-26 00:00:00 | 461.14
2013-03-27 00:00:00 | 452.08
2013-03-28 00:00:00 | 442.66
2013-04-01 00:00:00 | 428.91
2013-04-02 00:00:00 | 429.79
2013-04-03 00:00:00 | 431.99
2013-04-04 00:00:00 | 427.72
2013-04-05 00:00:00 | 423.2
2013-04-08 00:00:00 | 426.21
2013-04-09 00:00:00 | 426.98
2013-04-10 00:00:00 | 435.69
2013-04-11 00:00:00 | 434.33
2013-04-12 00:00:00 | 429.8
2013-04-15 00:00:00 | 419.85
2013-04-16 00:00:00 | 426.24
2013-04-17 00:00:00 | 402.8
2013-04-18 00:00:00 | 392.05
2013-04-19 00:00:00 | 390.53
2013-04-22 00:00:00 | 398.67
2013-04-23 00:00:00 | 406.13
2013-04-24 00:00:00 | 405.46
2013-04-25 00:00:00 | 408.38
2013-04-26 00:00:00 | 417.2
2013-04-29 00:00:00 | 430.12
2013-04-30 00:00:00 | 442.78
2013-05-01 00:00:00 | 439.29
2013-05-02 00:00:00 | 445.52
2013-05-03 00:00:00 | 449.98
2013-05-06 00:00:00 | 460.71
2013-05-07 00:00:00 | 458.66
2013-05-08 00:00:00 | 463.84
2013-05-09 00:00:00 | 456.77
2013-05-10 00:00:00 | 452.97
2013-05-13 00:00:00 | 454.74
2013-05-14 00:00:00 | 443.86
2013-05-15 00:00:00 | 428.85
2013-05-16 00:00:00 | 434.58
2013-05-17 00:00:00 | 433.26
2013-05-20 00:00:00 | 442.93
2013-05-21 00:00:00 | 439.66
2013-05-22 00:00:00 | 441.35
Spreadsheet: 98528d66-5f79-4f79-b63d-ef032c36890f
Sheet: Sheet1

Date | Sport | Opponent | Time_Results
10/17/2009 | Women's Swimming | [NAME] | W, 126-105
10/24/2009 | Women's Swimming | at Penn State | L, 40-73
10/24/2009 | Women's Swimming | vs. Colgate | W, 74-39
11/06/2009 | Women's Swimming | CINCINNATI | W, 122-97
11/07/2009 | Women's Swimming | LOUISVILLE | L, 97-200
11/13/2009 | Women's Swimming | at Villanova | L, 106-135
11/14/2009 | Women's Swimming | at Rutgers | L, 125-158
11/19/2009 | Women's Swimming | at Maryland Diving Invitational | Results
11/20/2009 | Women's Swimming | at Maryland Diving Invitational | Results
11/21/2009 | Women's Swimming | at Maryland Diving Invitational | Results
12/03/2009 | Women's Swimming | at Ohio State Invitational | Third Place
12/04/2009 | Women's Swimming | at Ohio State Invitational | Third Place
12/05/2009 | Women's Swimming | at Ohio State Invitational | Third Place
12/06/2009 | Women's Swimming | at Ohio State Invitational | Third Place
01/02/2010 | Women's Swimming | vs. [NAME] (Coca Beach Invitational) | Results
01/09/2010 | Women's Swimming | PITT | W, 165-133
01/23/2010 | Women's Swimming | at Maryland | L, 108-133
01/30/2010 | Women's Swimming | VIRGINIA TECH | L, 138-156
01/30/2010 | Women's Swimming | DUQUESNE | W, 156-103
02/12/2010 | Women's Swimming | BIG EAST Diving Championships (Pittsburgh, Pa.) | Results
02/13/2010 | Women's Swimming | BIG EAST Diving Championships (Pittsburgh, Pa.) | Results
02/14/2010 | Women's Swimming | BIG EAST Diving Championships (Pittsburgh, Pa.) | Results
02/17/2010 | Women's Swimming | BIG EAST Swimming Championships (Pittsburgh, Pa.) | 6th place
02/18/2010 | Women's Swimming | BIG EAST Swimming Championships (Pittsburgh, Pa.) | 4th place
02/19/2010 | Women's Swimming | BIG EAST Swimming Championships (Pittsburgh, Pa.) | 3rd place
02/20/2010 | Women's Swimming | BIG EAST Swimming Championships (Pittsburgh, Pa.) | 3rd place
02/28/2010 | Women's Swimming | Ohio State [NAME] | 12 p.m.
03/05/2010 | Women's Swimming | Terrapin Invitational Last Chance Meet | 11 a.m.
03/06/2010 | Women's Swimming | Terrapin Invitational Last Chance Meet | 11 a.m.
03/12/2010 | Women's Swimming | [NAME] (Piscataway, N.J.) | TBA
03/13/2010 | Women's Swimming | [NAME] (Piscataway, N.J.) | TBA
03/14/2010 | Women's Swimming | [NAME] (Piscataway, N.J.) | TBA
03/17/2010 | Women's Swimming | Women's [NAME] (West Lafayette, Ind.) | TBA
03/18/2010 | Women's Swimming | Women's [NAME] (West Lafayette, Ind.) | TBA
03/19/2010 | Women's Swimming | Women's [NAME] (West Lafayette, Ind.) | TBA
03/20/2010 | Women's Swimming | Women's [NAME] (West Lafayette, Ind.) | TBA
Spreadsheet: aaf470bf-153a-4804-8f7b-f2ff9abb642b
Sheet: Sheet1

Table S10. Summary of small RNAs mapping on AR182 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Library | Total sum of abundances (raw values) | Total sum of abundances (normalized) | Distinct signatures | Distinct:Total ratio
B73 - ZMA1 | 838837 | 912747 | 146893 | 0.16
B73 - ZMA2 | 1010827 | 913955 | 275785 | 0.3
B73 - ZMA3 | 813614 | 838094 | 284839 | 0.34
K55 -MOP1 | 1956619 | 1012167 | 381907 | 0.38
K55 - WT | 902598 | 866139 | 319257 | 0.37
Sum | 5522495 | 4543102 | 1408681 | -
Average | 1104499 | 908620 | 281736 | 0.31
Spreadsheet: 106059d1303300950-fomula-for-selecting-text-110418algorithim-spreadsheet
Sheet: Sheet1

Software | Minimum O.S. | Comms Interface | CPU Processor Pentium | CPU MHz | [NAME] | HDD Memory MB | Display Resolution | DVD Drive | Serial Port | USB Port | Ethernet Port | Pointing Device
Gx Developer | Windows XP | RS-232 | 1 | 133 | 32 | 80 | 800 x 600 | 1 | 1 | 0 | 0 | 1
Iconics – Genesis | Windows XP |  | 4 | 1000 | 512 | 2000 | 800 x 600 | 1 | 1 | 1 | 1 | 1
Kepserver/ Linkmaster | Windows XP |  | 4 | 2000 | 1000 | 180 | 800 x 600 | 1 | 1 | 0 | 1 | 1
LS2Win/ DL2e | Windows XP | RS-232 | 1 | 1000 | 10 | 512 | 800 x 600 | 1 | 1 | 0 | 0 | 1
Office 2010 | Windows XP |  | 4 | 500 | 512 | 3500 | 1024 x 767 | 1 | 0 | 0 | 0 | 1
OS Weather | Windows XP |  | 4 | 1000 | 512 | 512 | 1024 x 767 | 1 | 0 | 0 | 0 | 1
Spectroradiometer | Windows XP | RS-232 | 1 | 1000 | 512 | 20000 | 1024 x 767 | 1 | 1 | 0 | 0 | 1
Virtual Weather | Windows XP | USB or TC/PIP, RS-232 | 1 | 1000 | 8 | 10 | 800 x 600 | 1 | 1 | 1 | 0 | 1
WMR100N | Windows XP | USB | 4 | 1000 | 512 | 512 | 1024 x 767 | 1 | 0 | 1 | 0 | 1
WMR200 | Windows XP | RS-232 | 4 | 1000 | 512 | 512 | 1024 x 767 | 1 | 1 | 0 | 0
Spreadsheet: 741251d1626936702-need-your-help-on-this-thanks-might-save-life-i-dont-know-some-functions-here-sample
Sheet: Instructions

 | NOTE** The client's financial year starts on 1st October and ends on 30th September,  so Q1 is October-November-December.
 | During your work please feel free to add columns to the Data sheet,  or new worksheet to the workbook if it helps.
 | Please complete the columns where the column header is red on the DATA tab.
 | Column J: Write a formula to automate the requisition status. The requisition can be 'Open' or 'Filled'. The role is considered as 'Filled' if it has Offer Accept date.
 | Column K: Here you should measure the Time to Hire or How many DAYS the Role has been OPEN. This is the difference between the Open Date and the Offer Accept Date for Filled roles, but for Open roles it would be time since Open Date until TODAY(). This formula should use only business days ( so excluding weekends).  NAME THE COLUMN "DAYS OPENED (Business Days)"
 | Column L: Using the same theory as the above exercise, calculate the Time to Hire or Number of days the Role has been open but this time we want to include the weekends, not just the business days. NAME THE COLUMN: "DAYS OPENED (CALENDAR DAYS)"
 | Column M: Use formula to determine the Year of the Offer Accept Date.
 | Column N: Use formula to determine the Month of the Offer Accept Date.
 | Column O: Use a formula to determine the Quarter of Offer Accept Date.
 | Column P: Use a formula to determine the Financial year when the offer was verbally accepted.
 | *Column M, N,O and P should be empty if the requisition status is 'Open'
 | *Please leave all formula in cells, do not paste as values*
 | Please complete the SUMMARY tab. ( make it formula driven, automated)
 | For Open Roles:
 | Current Open roles: number of the roles currently has the status 'Open'
 | Avg Days Open: for this calculation please use column K on the data tab
 | % Ageing Roles: all the open roles are opened more then 50 days age
 | Open roles by Region: You will find the Region for each and every role in column E on the Data tab.
 | CHART 1 : Create a chart which represent the open roles by department.
 | For Filled Roles:
 | Fill the data table. Filled roles by financial year, by quarter, by region.
 | The last 2 rows will be the Total Filled roles (sum of the regional data)
 | and the Average Time To Hire based on column K on the Data tab
 | CHART 2
 | Filled roles in Financial Year 2017 by Billing type
 | CHART 3
 | Filled roles in Financial Year 2017 by region
 | For Blank Canvas
 | Create a Financial Dashboard. A one pager that tells a data story the summary.
 | Example:
Spreadsheet: 824754d1680802868-sum-of-column-that-has-letters-and-numbers-in-the-same-cell-work
Sheet: Sheet1

Workers | 2023-03-27 00:00:00 | 2023-03-28 00:00:00 | 2023-03-29 00:00:00 | 2023-03-30 00:00:00 | 2023-03-31 00:00:00
[NAME] | W | W | W | W | W
[NAME] | W | GH04 | W | W | W
[NAME] | W | W | W | ST07 | W
[NAME] | W | W | VW05 | W | W
[NAME] | W | W | W | W | W
[NAME] | HW02 | HW02 | HW02 | HW02 | HW01
Bev | W | W | W | W | W
George | HW01 | HW01 | HW01 | HW01 | HW01
[NAME] | W | W | W | W | W
Full Day
Part Day
Spreadsheet: 526075d1499103315-extract-data-with-multiple-criteria-invoiced-june-2017
Sheet: DAP

Dap Invoiced Product Upliftment(May 2017)
Sales Territory | SLoc | Storage Location | Sold-to pt | Sold-to party | [NAME] | [NAME]. | PO date | [NAME].Doc. | Billing Date | Qty | Type | Product | 01->06.june.2017 | 7.6.2017 |  |  | Total Upliftment | Pending
[NAME] | 4248 | [NAME]  WH IX | 101275 | [NAME] | Tatepur_SP | 310015235 | 30.05.2017 | 90753515 | 31.05.2017 | 2.5 | [NAME] | DAP |  |  |  | 2.5
[NAME] | 3450 | Yazman WH | 103777 | [NAME] | Chandni Chowk_SP | 220117433 | 06.04.2017 | 90753687 | 31.05.2017 | 1.6 | ZMO3 | DAP |  | 1.6
 |  |  |  |  |  |  |  |  | Total
Spreadsheet: 824796d1680845636-formula-to-find-specific-data-using-multiple-drop-down-lists-copy-of-book1-3
Sheet: Sheet4

Qtr | (All)
FY | FY24
All | (All)
Account | (All)
Date | 2023-03-02 00:00:00
Row Labels | Sum of Qty | Sum of Q1 | Sum of Q2 | Sum of Q3 | Sum of Q4
In Forecast | 3 | 0 | 374653.74 | 0 | 0
Not In Forecast | 2 | 285781.09 | 0 | 0 | 0
Grand Total | 5 | 285781.09 | 374653.74 | 0 | 0
Spreadsheet: 199023d1355038664-if-nested-function-or-any-other-function-which-can-repeat-process-again-and-again-assignment
Sheet: Sheet1

Name | Assignment
A | 50 |  | For example I want to Assign name "A" in cloumn "C" in front of value sum equal to 89 and once name "A" is assigned then it repeats the action again and then Name "B" assign and continues till the process assigned all the Names of the Column A in Column C
B | 20
C | 30
D | 40
E | 60
F | 70
G | 300
H | 460
I | 240
J | 200
K | 2
 | 3
 | 4
 | 5
 | 6
 | 7
 | 87
 | 8
 | 9
 | 50
 | 20 | H
Spreadsheet: 677418d1589356974-vlookup-with-wildcard-not-working-formula
Sheet: SHEET1

DATE | Description | Money in | Money Out | MONEY IN REASON | NEW FORMULA | PREVIOUS FORMULA (WHICH WORKS)
2020-03-30 00:00:00 | FASTER PAYMENTS RECEIPT RAJ | 200
2020-03-20 00:00:00 | CARD PAYMENT TO WILKO RETAIL LIMITED,1.50 GBP, RATE 1.00/GBP ON 18-03-2020 |  | 1.5
2020-03-19 00:00:00 | CARD PAYMENT TO SELCO TRADING CTR,64.56 GBP, RATE 1.00/GBP ON 17-03-2020 |  | 50
2020-03-16 00:00:00 | DIRECT DEBIT PAYMENT TO THAMES WATER REF 123456789, MANDATE NO 0080 |  | 30
2020-03-16 00:00:00 | DIRECT DEBIT PAYMENT TO MORTGAGES 999999A, MANDATE NO 0085 |  | 150
2020-03-16 00:00:00 | DIRECT DEBIT PAYMENT TO BG SERVICES REF 987654159D, MANDATE NO 0079 |  | 30
2020-03-16 00:00:00 | DIRECT DEBIT PAYMENT TO REF GHTY7415, MANDATE NO 0059 |  | 300
2020-03-11 00:00:00 | ARRANGED OVERDRAFT USAGE FEE |  | 20
2020-02-19 00:00:00 | FASTER PAYMENTS RECEIPT RAJ | 3000
2020-02-19 00:00:00 | MAINTAINING THE ACCOUNT - MONTHLY FEE |  | 5
Spreadsheet: 578151d1528971867-need-help-with-data-in-a-grid-format-to-upload
Sheet: Result

Argentina | Andorra | Argentina | Belgium | Bolivia | Brazil | Chile | Colombia | Costa Rica | Cuba | Dominican Republic | Ecuador | El Salvador
Armenia
Aruba
Australia | Australia | Austria | Belgium | Canada | Chile | Croatia | Cyprus | Czech Republic | Denmark
Austria | Australia | Austria | Belgium | Bosnia and Herzegovina | Bulgaria | Canada | Chile | Croatia | Cyprus | Czech Republic | Denmark
Azerbaijan
Bahamas | [NAME] and [NAME] | Bahamas | Barbados | Belize | Dominica
Bahrain
Bangladesh
Barbados
Belarus
Belgium | Albania | Algeria | Argentina | Australia | Austria | Belgium | Bosnia and Herzegovina | Brazil | Canada | Chile | Croatia
Spreadsheet: 34193d1231342627-graph-help-data
Sheet: Data

 |  | 2008-10-01 00:00:00 | 2008-11-01 00:00:00 | 2008-12-01 00:00:00
 | Series 1 | 0.59 | 0.66 | 0.89
 | Series 2 | 0.65 | 0.79 | 0.94
 | Series 3 | 0.9 | 0.83 | 0.92
 | Series 4 | 0.64 | 0.72 | 0.86
 | Series 5 | 0.67 | 0.77 | 0.93
 | Series 6 | 0.68 | 0.76 | 0.94
 | Target | 0.8 | 0.8 | 0.8
Spreadsheet: 5b92e721-182f-4143-9c62-758c9d6fc206
Sheet: Sheet1

AGI | Stems | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Leaves | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Inflorescences | Unnamed: 14 | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Unnamed: 18
 | P15 |  | HcPro |  | P19 |  | P15 |  | HcPro |  | P19 |  | P15 |  | HcPro |  | P19
 | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD | Accumulation | Accumulation SD
At1g12320 |  |  |  |  |  |  | 2.153475136495048 | 0 | 2.757447337971551 | 0.01997708502651174 | 2.776626900959577 | 0
At2g38120 |  |  |  |  |  |  | 1.231144643875304 | 0.03689775958644358 | 0.6909564266537693 | 0.07144187395045919 | 3.78423141482566 | 0.09024322110414938
At2g47020 |  |  |  |  |  |  |  |  |  |  |  |  | 1.615148333600086 | 0.02266177333730506 | 1.017479692102687 | 0.04650124502609217 | 1.075494390457378 | 0.06217987942173139
At3g58780 | 2.107533488388469 | 0.1084242367484558 | 1.113850459156938 | 0.01265541124167686 | 1.226412617173349 | 0.1303637013225926 | 3.21169152745352 | 2.899232565465305 | 4.065219728672755 | 2.613407163571945 | 3.872682783931537 | 1.044377010855885
At4g08390 | 1.755914042582505 | 0.07522583739149219 | 1.719777854123225 | 0.03624939137171414 | 1.465213715683304 | 0.04236010163181422 | 0.7918686268908085 | 0.0137905425155067 | 5.669938306195447 | 0.2771241061985911 | 5.169408886616724 | 0.3156806015593791
At4g28490 | 1.684385337668774 | 0.111365706266124 | 0.9301630624917031 | 0.003281056971432027 | 1.386176639809416 | 0.05234541019034937 | 1.194715135156019 | 0.1032458995838419 | 2.018569602423741 | 0.06523308589854956 | 1.186462634908484 | 0.09033186147414492
At5g13550 | 1.769489662359292 | 0.1065907502577728 | 4.673309041599388 | 0.3642884066702509 | 1.903809186907544 | 0.1338885026279669
At1g67750 | 4.920786383387253 | 0.2386853279833616 | 2.919164589127726 | 0.1594551640586887 | 6.011719839461992 | 0.2647534491101455
At2g26560 |  |  |  |  |  |  |  |  |  |  |  |  | 3.942080522443245 | 0.07044533999063703 | 9.53167032361209 | 1.074224627172433 | 1.544768467764609 | 0.04873950973260448
At4g22470 | 1.528611958869774 | 0.7214421204521798 | 2.449049989547689 | 0.188930314019091 | 6.71681725432448 | 0.5193491062576912 | 0.7186361092894601 | 0 | 8.514961459626884 | 0.4033976408652944 | 4.542017716283515 | 0 | 2.392192243474809 | 0 | 2.792711736964259 | 0 | 3.185824218408706 | 0.130252683214118
At3g59210 |  |  |  |  |  |  |  |  |  |  |  |  | 0.962594443101752 | 0 | 2.392192243474809 | 0.07618303935304695 | 2.326777620777071 | 0
Spreadsheet: 119606d1314616382-average-incomes-to-matching-towns-file-for-excel-forum
Sheet: Sheet1

MEAN INCOME | Location | Average
89600 | STOCKPORT | 59163.99604352126
87300 | STALYBRIDGE | 60413.05637982196
87000 | WARRINGTON | 61461.29707112971
87000 | WILMSLOW | 62976.19047619047
85800 | WILMSLOW
85300 | WILMSLOW
85000 | WILMSLOW
84900 | WILMSLOW
50400 | WARRINGTON
50400 | WARRINGTON
50400 | WARRINGTON
57600 | Stockport
57500 | Stockport
57500 | Stockport
56800 | Stockport
56700 | Stockport
56700 | Stockport
55800 | Stockport
55500 | Stockport
55400 | STALYBRIDGE
55400 | STALYBRIDGE
55400 | STALYBRIDGE
55400 | STALYBRIDGE
55300 | STALYBRIDGE
55100 | STALYBRIDGE
55000 | STALYBRIDGE
68800 | SALFORD
68800 | SALFORD
Spreadsheet: 6d5f6414-a019-4944-9103-150a93625b3e
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
259949 | 8052 | Alec | Hill | NZL | 22015 | 00:17:46 | 00:06:02 | 00:59:26 | 00:04:42 | 00:33:08 | 1 | 02:01:01
259949 | 52617 | Wayne | Fong | USA | 22017 | 00:21:47 | 00:10:06 | 01:01:52 | 00:07:56 | [NAME] | 2 | 02:16:29
259949 | 14124 | [NAME] | D'Erbee | BEL | 22018 | 00:00:02 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | DNF | 00:00:00
259949 | 22385 | [NAME] | Dobrov | RUS | 22016 | 00:00:02 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | DNF | 00:00:00
Spreadsheet: 876314d1722998767-show-hide-rows-of-teams-as-match-pairs-regarding-data-1_show_or_hide_football_matches_pairs
Sheet: Sheet1 (EPL Week 17) (2)

Code | Team | Score | Home Team Score | Away Team Score | Total Score |  | Code | Team | Score
A1 | [NAME] | 0 |  |  |  |  | B1 | Newcastle United | 3
A2 | [NAME] | 2 |  |  |  |  | B2 | Fulham | 0
B1 | Newcastle United | 3 |  |  |  |  | C1 | Manchester City | 2
B2 | Fulham | 0 |  |  |  |  | C2 | Crystal Palace | 2
C1 | Manchester City | 2 |  |  |  |  | D1 | Chelsea | 2
C2 | Crystal Palace | 2 |  |  |  |  | D2 | Sheffield United | 0
D1 | Chelsea | 2 |  |  |  |  | [NAME] | West Ham United | 3
D2 | Sheffield United | 0 |  |  |  |  | G2 | [NAME] | 0
E1 | Bournemouth | 1 |  |  |  |  | I1 | Arsenal | 2
E2 | [NAME] | 1 |  |  |  |  | I2 | Brighton & Hove Albion | 0
F1 | Burnley | 0
F2 | Everton | 2
[NAME] | West Ham United | 3
G2 | [NAME] | 0
H1 | Brentford | 1
H2 | [NAME] | 2
I1 | Arsenal | 2
I2 | Brighton & Hove Albion | 0
J1 | Liverpool | 0
J2 | [NAME] | 0
 | Using PivotTable with Slicers, by first converting data into an Excel Table and added 3 helper columns with the following formulas:
Spreadsheet: 189348d1351166344-stacked-bar-chart-with-s-871164
Sheet: Sheet1

ReportDate | Daily Visits | Returns
2012-09-15 00:00:00 | 0 | 0
2012-09-16 00:00:00 | 1 | 0
2012-09-17 00:00:00 | 0 | 0
2012-09-18 00:00:00 | 0 | 0
2012-09-19 00:00:00 | 10 | 0.2
2012-09-20 00:00:00 | 23 | 0.130434782608696
2012-09-21 00:00:00 | 222 | 0.0765765765765766
2012-09-22 00:00:00 | 336 | 0.119047619047619
2012-09-23 00:00:00 | 359 | 0.133704735376045
2012-09-24 00:00:00 | 518 | 0.111969111969112
2012-09-25 00:00:00 | 538 | 0.087360594795539
2012-09-26 00:00:00 | 252 | 0.0595238095238095
2012-09-27 00:00:00 | 223 | 0.0852017937219731
2012-09-28 00:00:00 | 230 | 0.0521739130434783
2012-09-29 00:00:00 | 7 | 0.571428571428571
2012-09-30 00:00:00 | 4 | 0
2012-10-01 00:00:00 | 269 | 0.100371747211896
2012-10-02 00:00:00 | 184 | 0.114130434782609
2012-10-03 00:00:00 | 104 | 0.153846153846154
2012-10-04 00:00:00 | 46 | 0.152173913043478
2012-10-05 00:00:00 | 46 | 0.217391304347826
2012-10-06 00:00:00 | 37 | 0.135135135135135
2012-10-07 00:00:00 | 54 | 0.0185185185185185
2012-10-08 00:00:00 | 37 | 0.162162162162162
2012-10-09 00:00:00 | 12 | 0
2012-10-10 00:00:00 | 8 | 0.125
2012-10-11 00:00:00 | 2 | 0
2012-10-12 00:00:00 | 2 | 0
2012-10-13 00:00:00 | 2 | 0
2012-10-14 00:00:00 | 2 | 0
2012-10-15 00:00:00 | 3 | 0
2012-10-16 00:00:00 | 3 | 0
2012-10-17 00:00:00 | 2 | 0
2012-10-18 00:00:00 | 3 | 0
2012-10-19 00:00:00 | 5 | 0
2012-10-20 00:00:00 | 4 | 0
2012-10-21 00:00:00 | 4 | 0
Spreadsheet: 202354d1356527129-transpose-filldown-transpose_filldown-copy2
Sheet: Example 1 Your Solution

3 | 2
2 | 5
1 | 6
4 | 8
6 | 6
7 | 3
2 | 2
1 | 1
3 | 5
Spreadsheet: 135077d1325798390-funding-allocation-with-maximum-values-catallocation
Sheet: Sheet1

Total Funds | 19700000
Average: | 6566666.666666667
Categories | Active | [NAME] | Cost Per Units | Maximum Allocation | Units Allocated | Cost | Percentage
Cat1 | 1 | 1720 | 2848 | 4898560 |  | 0 | 0
Cat2 | 1 | 1284 | 65928 | 84651552 |  | 0 | 0
Cat3 | 0 | 4550 | 7600 | 34580000 |  | 0 | 0
Cat4 | 0 | 1842.12 | 45124 | 83123822.88 |  | 0 | 0
Cat5 | 1 | 877.2 | 45124 | 39582772.8 |  | 0 | 0
Cat6 | 0 | 3309 | 8126 | 26888934 |  | 0 | 0
Cat7 | 0 | 18796 | 4123 | 77495908 |  | 0 | 0
Cat8 | 0 | 788 | 5779 | 4553852 |  | 0 | 0
Cat9 | 0 | 96 | 5550 | 532800 |  | 0 | 0
Spreadsheet: 449396d1457131964-breaks-lunch-counter-copy-of-breakscounterv2
Sheet: Sheet1

Interval | Break | Lunch
00:00:00
00:30:00
01:00:00
01:30:00
02:00:00
02:30:00
03:00:00
03:30:00
04:00:00
04:30:00
05:00:00
05:30:00
06:00:00
06:30:00
07:00:00
07:30:00
08:00:00
08:30:00
09:00:00
09:30:00
10:00:00
10:30:00
11:00:00
11:30:00
12:00:00
12:30:00
13:00:00
13:30:00
14:00:00
14:30:00
15:00:00
15:30:00
16:00:00
16:30:00
17:00:00
17:30:00
18:00:00
18:30:00
19:00:00
19:30:00
20:00:00
20:30:00
21:00:00
21:30:00
22:00:00
22:30:00
23:00:00
23:30:00
1900-01-01 00:00:00
1900-01-01 00:30:00
1900-01-01 01:00:00
1900-01-01 01:30:00
1900-01-01 02:00:00
1900-01-01 02:30:00
1900-01-01 03:00:00
1900-01-01 03:30:00
1900-01-01 04:00:00
1900-01-01 04:30:00
1900-01-01 05:00:00
1900-01-01 05:30:00
1900-01-01 06:00:00
1900-01-01 06:30:00
1900-01-01 07:00:00
1900-01-01 07:30:00
1900-01-01 08:00:00
1900-01-01 08:30:00
1900-01-01 09:00:00
1900-01-01 09:30:00
1900-01-01 10:00:00
1900-01-01 10:30:00
1900-01-01 11:00:00
1900-01-01 11:30:00
1900-01-01 12:00:00