tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 085cee5b-3e8b-4072-b6ee-a134f723f4f2
Sheet: .

 | Broadside | London | Gentleman’s | Register1A | Register1B | Register1C | Register2 | Register3 | Register4 | Register5 | Register6A | Register7 | Register6B | Several | Plantations | Capitulations | Laws | Lands | Civil | Houston
London
Nerrors | 44
LED score | 177
Gentleman’s
Nerrors | 53 | 35
LED score | 201 | 92
Providence
Nerrors | 17 | 52 | 54
LED score | 47 | 188 | 200
Register1A
Nerrors | 96 | 83 | 60
LED score | 339 | 260 | 210
Register1B
Nerrors |  |  |  | 7
LED score |  |  |  | 25
Register1C
Nerrors |  |  |  | 0 | 7
LED score |  |  |  | 0 | 25
Register2
Nerrors |  |  |  | 0 | 7 | 0
LED score |  |  |  | 0 | 25 | 0
Register3
Nerrors |  |  |  | 8 | 5 | 8 | 8
LED score |  |  |  | 23 | 16 | 23 | 23
Register4
Nerrors |  |  |  | 11 | 4 | 11 | 11 | 3
LED score |  |  |  | 13 | 8 | 33 | 33 | 10
Register5
Nerrors |  |  |  | 13 | 6 | 13 | 13 | 5 | 2
LED score |  |  |  | 35 | 10 | 35 | 35 | 12 | 2
Register6A
Nerrors |  |  |  | 14 | 7 | 14 | 14 | 6 | 3 | 5
LED score |  |  |  | 37 | 12 | 37 | 37 | 14 | 4 | 6
Register7
Nerrors |  |  |  | 17 | 13 | 17 | 17 | 12 | 11 | 13 | 14
LED score |  |  |  | 33 | 28 | 33 | 33 | 30 | 22 | 24 | 26
Register6B
Nerrors |  |  |  | 17 | 10 | 17 | 17 | 9 | 6 | 8 | 9 | 15
LED score |  |  |  | 39 | 14 | 39 | 39 | 16 | 6 | 8 | 10 | 26
Several
Nerrors |  |  |  | 59 | 56 | 59 | 59 | 57 | –— | –— | –— | –— | –—
LED score |  |  |  | 133 | 130 | 133 | 133 | 134 | –— | –— | –— | –— | –—
Plantations
Nerrors |  |  |  | 19 | 17 | 19 | 19 | 15 | –— | –— | –— | –— | –— | 61
LED score |  |  |  | 54 | 53 | 54 | 54 | 53 | –— | –— | –— | –— | –— | 147
Capitulations
Nerrors |  |  |  | 81 | 82 | 81 | 81 | 79 | 82 | 84 | 83 | 83 | –— | 74 | 88
LED score |  |  |  | 275 | 290 | 275 | 275 | 276 | 286 | 288 | 288 | 282 | –— | 214 | 305
Laws
Nerrors |  |  |  | 36 | 32 | 36 | 36 | 32 | 32 | 34 | 33 | 35 | 32 | 65 | 37 | 92
LED score |  |  |  | 100 | 83 | 100 | 100 | 85 | 79 | 81 | 81 | 93 | 79 | 177 | 116 | 291
Lands
Nerrors |  |  |  | 53 | 53 | 53 | 53 | 53 | 53 | 55 | 54 | 51 | 53 | 74 | 54 | 100 | 31
LED score |  |  |  | 149 | 154 | 149 | 149 | 156 | 150 | 152 | 152 | 142 | 150 | 198 | 165 | 356 | 149
Civil
Nerrors |  |  |  | 116 | 113 | 116 | 116 | 114 | 113 | 115 | 114 | 109 | 112 | 101 | 114 | 102 | 111 | 106
LED score |  |  |  | 377 | 374 | 377 | 377 | 378 | 370 | 372 | 372 | 362 | 368 | 314 | 385 | 370 | 402 | 377
Houston
Nerrors |  |  |  | 78 | 72 | 78 | 78 | 72 | 72 | 74 | 73 | 70 | 70 | 84 | 77 | 95 | 73 | 73 | 98
LED score |  |  |  | 292 | 269 | 292 | 292 | 271 | 265 | 267 | 267 | 269 | 263 | 285 | 302 | 355 | 288 | 275 | 345
Select
Nerrors |  |  |  | 46 | 39 | 46 | 46 | 38 | 37 | 39 | 38 | 34 | 41 | 85 | 42 | 107 | 52 | 74 | 135 | 90
LED score |  |  |  | 139 | 114 | 139 | 139 | 116 | 108 | 110 | 110 | 116 | 112 | 228 | 141 | 379 | 148 | 239 | 464 | 333
Spreadsheet: 803366d1667410769-formula-to-summary-countif-greater-than-book3-hd
Sheet: Sheet1

Company Name | June | July | August | September | October
a |  | 2 |  | 4 | 1
b | 3 |  | 3 | 3 | 3 |  |  |  | June | 1
c | 1 |  | 1 |  | 1 |  |  |  | July | 5
d | 4 | 13 | 2 |  |  |  |  |  | August | 8
e |  |  |  | 19 | 2 |  |  |  | September | 11
f |  |  |  | 1 |  |  |  |  | October | 12
g |  |  | 1
h | 2 |  |  |  | 3
i |  | 22 | 91 | 32
j | 1
k |  | 2 | 1
l |  | 1 |  |  | 2
m | 1
n |  | 7 | 1
o |  |  | 10 | 5 | 4
p | 26 | 1
q |  |  | 6 | 6
r |  | 8 | 6 | 12
s |  |  |  | 1
t |  | 4 |  |  | 1
u |  | 1 | 3 | 10
v | 1
w | 3 | 4
x |  | 18
y |  |  | 13 | 5
z |  | 19 | 35
Spreadsheet: 837902d1690487517-formula-to-pull-the-codes-from-a-row-to-column-when-there-is-a-value-for-the-code-sample-book
Sheet: Sheet1

 |  |  |  |  |  | Vehicle Fuel | Miscellaneous Motor Expenses | Travelling | Hotels | U.K. Entertainment | Overseas Travelling | Postage and Carriage | Office Stationery
 |  | Date |  | Nominal code | 6900 | 7300 | 7304 | 7400 | 7402 | 7403 | 7405 | 7501 | 7502
 |  | 2023-07-01 00:00:00 |  | Travel to Client |  |  |  | 50
 |  | 2023-07-02 00:00:00 |  | Hotel |  |  |  |  | 250
 |  | 2023-07-03 00:00:00 |  | Fuel |  | 25
 |  | 2023-07-04 00:00:00 |  | Entertainment |  |  |  |  |  | 50
 |  | 2023-07-05 00:00:00 |  | Vehicle Fuel |  | 24.5
 |  | 2023-07-06 00:00:00 |  | Post Office |  |  |  |  |  |  |  | 5.5
 |  | 2023-07-07 00:00:00 |  | Post Office |  |  |  |  |  |  |  | 4.5
 |  |  |  |  |  | Vehicle Fuel | Miscellaneous Motor Expenses | Travelling | Hotels | U.K. Entertainment | Overseas Travelling | Postage and Carriage | Office Stationery | Nominal Code
 |  | Date |  | Nominal code | 6900 | 7300 | 7304 | 7400 | 7402 | 7403 | 7405 | 7501 | 7502
 |  | 2023-07-01 00:00:00 |  | Travel to Client |  |  |  | 50 |  |  |  |  |  |  | 7400
 |  | 2023-07-02 00:00:00 |  | Hotel |  |  |  |  | 250 |  |  |  |  |  | 7402
 |  | 2023-07-03 00:00:00 |  | Fuel |  | 25 |  |  |  |  |  |  |  |  | 7300
 |  | 2023-07-04 00:00:00 |  | Entertainment |  |  |  |  |  | 50 |  |  |  |  | 7403
 |  | 2023-07-05 00:00:00 |  | Vehicle Fuel |  | 24.5 |  |  |  |  |  |  |  |  | 7300
 |  | 2023-07-06 00:00:00 |  | Post Office |  |  |  |  |  |  |  | 5.5 |  |  | 7501
 |  | 2023-07-07 00:00:00 |  | Post Office |  |  |  |  |  |  |  | 4.5 |  |  | 7501
Spreadsheet: 599769d1543307628-sequential-quarterly-formula-book1
Sheet: Sheet1

 |  |  | 2018-01-27 00:00:00
or
Spreadsheet: 53060d1252994240-sort-and-match-book1
Sheet: Sheet1

 |  |  |  |  |  |  | 1 | 1
4 | 5 |  |  |  |  |  | 2 |  | 2
2 |  |  |  |  |  |  | 3 | 3
5 | 1 |  |  |  |  |  | 4
1 | 3 | 2 |  |  |  |  | 5 | 5
3 |  |  |  |  |  |  | #N/A | #N/A | #N/A
 |  |  |  |  |  |  | #N/A | #N/A | #N/A
 |  |  |  |  |  |  | #N/A | #N/A | #N/A
 |  |  |  |  |  |  | #N/A | #N/A | #N/A
 |  |  |  |  |  |  | #N/A | #N/A | #N/A
Spreadsheet: 719315d1613616694-possible-indirect-function-needed-or-any-feasible-method-indirect-match-other-sheets
Sheet: Template

Period | Invoice Period | Name | Invoice No | SK AK No | Account Name | EXP | USD | Billed Amount local CCY | Billed USD
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 666457 | Example | NA | AUD |  |  |  | << Here are your formulas.
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 666458 | Example | NA | AUD |  |  |  |  | Took me a while to construct.
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 666459 | Example | NA | AUD
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 666460 | Example | NA | USD
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 767987 | Example | BA | USD
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 767988 | Example | BA | EUR
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 767989 | Example | BA | EUR
January | 2021-01-01 00:00:00 | Example | 46547-[PHONE] | 767990 | Example | BA | USD
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 9765464 | Example | BA | DKK
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 9765465 | Example | BA | DKK
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 9765466 | Example | BA | USD
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 9765467 | Example | BA | NOK
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 9765468 | Example | BA | NOK
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 232134164 | Example | NA | NOK
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 232134165 | Example | NA | NOK
January | 2021-01-01 00:00:00 | Example | 166465789-[PHONE] | 232134166 | Example | NA | NOK
January | 2021-01-01 00:00:00 | Example | 98787-299467989 | 0046-997897654 | Example | NA | NOK
January | 2021-01-01 00:00:00 | Example | 98787-299467989 | 0046-997897655 | Example | NA | USD
January | 2021-01-01 00:00:00 | Example | 98787-299467989 | 0046-997897656 | Example | NA | EUR
January | 2021-01-01 00:00:00 | Example | 98787-299467989 | 0046-997897657 | Example | NA | EUR
January | 2021-01-01 00:00:00 | Example | 98787-299467989 | 0046-997897658 | Example | NA | EUR
January | 2021-01-01 00:00:00 | Example | 98787-299467989 | 0046-997897659 | Example | NA | EUR
January | 2021-01-01 00:00:00 | Example | [PHONE]-[PHONE] | 588000000 | Example | NA | USD
January | 2021-01-01 00:00:00 | Example | [PHONE]-[PHONE] | 588000001 | Example | NA | USD
January | 2021-01-01 00:00:00 | Example | [PHONE]-[PHONE] | 588000002 | Example | NA | USD
January | 2021-01-01 00:00:00 | Example | [PHONE]-[PHONE] | 588000003 | Example | NA | USD
January | 2021-01-01 00:00:00 | Example | 48-000046549 |  | Example | NA | EUR
January | 2021-01-01 00:00:00 | Example | 48-000047967 |  | Example | NA | EUR
January | 2021-01-01 00:00:00 | Example | 48-000046679 |  | Example | NA | EUR
Spreadsheet: 696271d1600737957-pivottable-formula-that-uses-values-from-pivot-table-book1-hjallis-
Sheet: Table

 | Modell | % | X |  | Modell | Sum of % | Count of X | %/X
 | A | 0.128 | 546
 | B | -0.023 | 231
 | B | 0.018 | 21
 | C | 0.05 | 21321
 | C | 0.01 | 21321
 | A | -0.05 | 2132
 | A | -0.25
 | A | -0.03 | 546
 | A | 0.02 | 51651
 | D | -0.05 | 10
 | D | -0.0423 | 4141
 | C | -0.01 | 41
 | A | -0.01 | 10
 | B | -0.01
 | B | 0.05 | 1
 | C | 0.02
 | C | 0.03 | 10
 | A | 0.02 | 35
 | A | 0.05
 | C | 0.04 | 10
 | A | 0.12
 | D | -0.05
 | D | 0.09 | 10
 | C | 0.0333
 | A | 0.12
 | B | 0.08 | 10
 | B | -0.0333 | 3554
 | C | 0.04
 | C | -0.05 | 10
 | C | -0.02 | 1514
 | A | 0.05 | 10
 | B | 0.02 | 5416
 | B | 0.02 | 10
 | C | 0.06 | 546
 | C | 0.04 | 10
 | C | 0.08 | 10
 | C | 0.1 | 4684
 | D | 0.11 | 10
Spreadsheet: 07296c68-386c-439e-ae6d-c17a93d8cce3
Sheet: Table of Contents

THE ALLSTATE CORPORATION
Investor Supplement - Fourth Quarter 2012
Table of Contents
 |  | PAGE
Consolidated
 | Statements of Operations | 1
 | Contribution to Income | 2
 | Revenues | 3
 | Statements of Financial Position | 4
 | Book Value Per Share | 5
 | Return on Shareholders' Equity | 6
 | Debt to Capital | 7
 | Statements of Cash Flows | 8
 | Analysis of Deferred Policy Acquisition Costs | 9-10
 | Historical Summary of Consolidated Operating and Financial Position Data | 11
Property-Liability Operations
 | Property-Liability Results | 12
 | Historical Property-Liability Results | 13
 | Underwriting Results by Area of Business | 14
 | Historical Underwriting Results by Area of Business | 15
 | [NAME] by Market Segment | 16
 | Allstate Brand [NAME]
 | Impact of Net Rate Changes Approved on [NAME]
 | Allstate Brand Profitability Measures
 | Encompass Brand Profitability Measures
 | Esurance Brand Profitability Measures and Statistics
 | Standard Auto Profitability Measures
 | Allstate Brand Standard Auto Loss Ratio of Top 5 States
 | Non-standard Auto Profitability Measures
 | Auto Profitability Measures
 | Homeowners Profitability Measures
 | Property-Liability Policies in Force
 | Allstate Brand Domestic Operating Measures and Statistics
 | Homeowners Supplemental Information
 | Effect of Catastrophe Losses on the Combined Ratio
 | Allstate Protection Catastrophe by Size of Event
 | Prior Year Reserve Reestimates
 | Historical Prior Year Reserve Reestimate | 33
 | Historical Property-Liability Loss Reserves | 34
 | Asbestos and Environmental Reserves | 35
Allstate Financial Operations and Reconciliations
 | Allstate Financial Results
 | Historical Allstate Financial Results | 37
 | Return on Attributed Equity | 38
 | Premiums and Contract Charges
 | Change in Contractholder Funds
 | Analysis of Net Income
 | Allstate Financial Weighted Average Investment Spreads
 | Allstate Financial Supplemental Product Information
Corporate and Other Results
Investments
 | Investments
 | Investment Portfolio Details | 46
 | Unrealized Net Capital Gains and Losses on Security Portfolio by Type | 47
 | Net Investment Income, Yields and Realized Capital Gains and Losses (Pre-tax)
 | Property-Liability Net Investment Income, Yields and Realized Capital Gains and Losses (Pre-tax)
 | Allstate Financial Net Investment Income, Yields and Realized Capital Gains and Losses (Pre-tax)
Definitions of Non-GAAP Measures
Spreadsheet: 63405d1264338537-running-count-in-horizontal-row-example
Sheet: Sheet1

 | cur rnds | fired | total rnds
gun 1 | 32333 |  |  | <-------------------- I want to keep this cell to be a running total, when I delete the last fired number (because after I shoot the weapn next time
gun 2 |  |  |  | I will need to enter the new number and I want the total rounds count to continure to keep a cumlative total.
gun 3
gun 4
Spreadsheet: 773670d1647987051-vlookup-if-a-word-from-a-list-is-in-the-string-of-a-cell-monthly-spending
Sheet: 01-2022

Date | Description | Amount | Category |  |  |  |  | If [NAME] | Returns
2022-01-03 00:00:00 | MERCHANT PAYMENT - JEWEL OSCO ON 011022 FROM CARD#: XXXXXXXXXXXX464X | -49.15 | [NAME] here. |  |  |  |  | [NAME] | Groceries
2022-01-03 00:00:00 | MERCHANT PAYMENT CITY FRESH MARKE - 5ON 010622 FROM CARD#: XXXXXXXXXXXX464X | -18.28 | [NAME] here. |  |  |  |  | Fresh Market | Bakery
2022-01-03 00:00:00 | RECURRING PURCHASE AT Spotify USA, New York, NY ON 010222 FROM CARD#: XXXXXXXXXXXX4643 | -10.89 | [NAME] here. |  |  |  |  | Spotify | Entertainment
2022-01-03 00:00:00 | RECURRING PURCHASE AT NETFLIX.COM, NETFLIX.COM, CA ON 010122 FROM CARD#: XXXXXXXXXXXX4643 | -9.8 | [NAME] here. |  |  |  |  | Netflix | Entertainment
2022-01-03 00:00:00 | RECURRING PURCHASE AT LEMONADE I* LEMONA, NEW YORK CITY, NY ON 010122 FROM CARD#: XXXXXXXXXXXX4643 | -6 | [NAME] here. |  |  |  |  | Lemonade | Insurance
Spreadsheet: chris_dorland__1613__Options Detail-ZARGON_JAN17
Sheet: Pivot

Sum of Value
Deal Num | Period | Total
VH6370.1 | 2002-01-01 00:00:00 | 0
 | 2002-02-01 00:00:00 | 0
 | 2002-03-01 00:00:00 | 0.2771
VH6370.1 Total |  | 0.2771
VH6370.2 | 2002-01-01 00:00:00 | -90451.8
 | 2002-02-01 00:00:00 | -113855.5231
 | 2002-03-01 00:00:00 | -128622.4692
VH6370.2 Total |  | -332929.7923
(blank) | (blank)
(blank) Total
Grand Total |  | -332929.5152
Spreadsheet: 889414d1740178672-sumif-countif-i-think-sumif-countif
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | In Cell AI, I need to sum all of the highlighted cells. And then divide by the count of the number of cells (I,Q,Y,AF) that contain data. All of the cells between A and AH have data. I would like a formula, I do not think my work will allow macros.
 | Data |  |  |  |  |  | Data | 1 | Data |  |  |  |  |  | Data | 2 | Data |  |  |  |  |  | Data | 3 | Data |  |  |  |  | Data | 4 | Data |  | 2.5 |  | (1+2+3+4)/4
 | Data |  |  |  |  |  | Data | 1 | Data |  |  |  |  |  | Data |  | Data |  |  |  |  |  | Data | 3 | Data |  |  |  |  | Data |  | Data |  | 2 |  | (1+3/)2
 | Data |  |  |  |  |  | Data | 1 | Data |  |  |  |  |  | Data | 2 | Data |  |  |  |  |  | Data |  | Data |  |  |  |  | Data | 4 | Data |  | 2.33 |  | (1+2+4)/3
Spreadsheet: 275970d1383701745-index-match-based-on-5-criteria-including-a-date-range-test
Sheet: INDEX&MATCH

LOOKUP TABLE |  |  |  |  |  |  |  | OUTPUT TABLE
Country | Product Code | Service Level | Service Type | Start Date | End Date | Annual Unit Price (USD) |  | Country | Product Code | Service Level | Service Type | Date | Annual Unit Price (USD)
Australia | CISCO2801 | 7 x 24 x 4 | Maintenance | 2011-02-01 00:00:00 | 2015-06-30 00:00:00 | 200 |  | Australia | WS-C6509-E | 7 x 24 x 4 | Maintenance | 2012-09-10 00:00:00
Australia | CISCO2801 | 7 x 24 x 4 | Part Supply | 2012-02-10 00:00:00 | 2015-06-30 00:00:00 | 150 |  | Australia | CISCO2801 | 7 x 24 x 4 | Part Supply | 2012-09-10 00:00:00
Australia | WS-C6509-E | 7 x 24 x 4 | Maintenance | 2012-03-15 00:00:00 | 2012-06-30 00:00:00 | 160 |  | Australia | WS-C6509-V-E | 7 x 24 x 4 | Part Supply | 2012-09-10 00:00:00
Australia | WS-C6509-E | 7 x 24 x 4 | Maintenance | 2012-07-01 00:00:00 | 2012-11-22 00:00:00 | 215
Australia | WS-C6509-E | 7 x 24 x 4 | Maintenance | 2013-04-11 00:00:00 | 2015-06-30 00:00:00 | 225 |  | =INDEX($G$3:$G$13;MATCH(1;(I3=$A$3:$A$13)*(J3=$B$3:$B$13)*(K3=$C$3:$C$13)*(L3=$D$3:$D$13)*(M3>=$E$3:$E$13)*(M3<=$A$3:$A$13);0))
Australia | WS-C6509-E | 7 x 24 x 4 | Part Supply | 2012-02-01 00:00:00 | 2015-06-30 00:00:00 | 115 |  | [NAME]
Australia | WS-C6509-V-E | 7 x 24 x 4 | Part Supply | 2012-02-01 00:00:00 | 2015-06-30 00:00:00 | 145
China | CISCO2801 | 7 x 24 x 4 | Maintenance | 2011-03-01 00:00:00 | 2015-06-30 00:00:00 | 122
China | CISCO2801 | 7 x 24 x 4 | Part Supply | 2012-06-11 00:00:00 | 2015-06-30 00:00:00 | 101
China | WS-C6509-E | 7 x 24 x 4 | Maintenance | 2011-03-15 00:00:00 | 2012-06-12 00:00:00 | 141
China | WS-C6509-E | 7 x 24 x 4 | Maintenance | 41091 | 42185 | 152
Spreadsheet: 884411d1733540092-formula-to-report-of-data-points-positive-or-negative-based-on-a-condition-golfshots-jt-
Sheet: Shots

Yards | Iron | -Lft / +Rgt | -Sht / +Lng | yrds from Pin | % from Pin | Date |  | Iron | [NAME] | [NAME] | % of Shots -Lft | % of Shots +Rgt | Avg -Sht / +Lng | % of Shots -Short | % of Shots +Long | [NAME] From Pin | [NAME] from Pin | % of Shots  <2.5% | % of Shots <=5%
165 | 7i | 6 | 2 |  |  | 2024-10-30 00:00:00 |  | 4i
135 | PW | 1 | -6.5 |  |  |  |  | 5i | 182.86 | 8 | 0 | 1 | -8.14 | 1 | 0 | 11.75647365474299 | 0.06140268253858212 | 0 | 0.2
110 | 50* | 0 | -5.5 |  |  |  |  | 6i | 177.08 | 0.6 | 0.6 | 0.4 | -1.92 | 0.6 | 0.4 | 8.952608434219831 | 0.04976561229641924 | 0.2 | 0.4
120 | 50* | 0 | 1.3 |  |  |  |  | 7i | 166.375 | 4.75 | 0 | 1 | -1.125 | 0.5 | 0.5 | 5.497783707928777 | 0.03283933275460021 | 0.25 | 1
130 | PW | 8 | 1.5 |  |  |  |  | 8i | 152.02 | 3 | 0 | 1 | -3.98 | 0.8 | 0.2 | 5.890777698176291 | 0.03745819889881634 | 0.2 | 0.6
175 | 6i | -9 | 7.5 |  |  |  |  | 9i | 141.02 | 0.8 | 0.4 | 0.6 | -2.98 | 0.6 | 0.4 | 4.510647623434767 | 0.03108035457725313 | 0.6 | 0.8
120 | 50* | -1 | 0.2 |  |  |  |  | PW | 127.8375 | 1.125 | 0.3125 | 0.6875 | -0.9124999999999998 | 0.5625 | 0.4375 | 5.191329451535836 | 0.04037809123124186 | 0.1875 | 0.75
190 | 5i | 10 | -8.3 |  |  |  |  | 50* | 113.3071428571429 | 0.1428571428571428 | 0.4285714285714285 | 0.3571428571428572 | -0.9785714285714283 | 0.5714285714285714 | 0.4285714285714285 | 3.492014733681959 | 0.03060675609523267 | 0.3571428571428572 | 0.9285714285714286
110 | 50* | -3 | -0.4 |  |  |  |  | 54* | 101.3 | 1 | 0.25 | 0.5 | -3.7 | 0.75 | 0.25 | 5.528246157704459 | 0.05264996340670913 | 0 | 0.75
140 | 9i | -1 | -0.5 |  |  |  |  | 58*
150 | 9i | 1 | -5.4
185 | 6i | -2 | -13.8
135 | PW | 1 | -3.5
105 | 54* | 0 | -4.2
130 | PW | 4 | -3.4
115 | 50* | -3 | -3.8
125 | PW | -9 | -2.1
170 | 7i | 6 | -4.7
115 | 50* | 1 | -3.4
120 | 50* | -1 | -2.4
195 | 5i | 10 | -7.6
130 | PW | 4 | -1.8
110 | 50* | -2 | 1.8
155 | 8i | 8 | -5.6
105 | 54* | -3 | 0.8
160 | 8i | 1 | -5.2
125 | PW | -2 | 2.6
180 | 6i | 6 | -2.5
145 | 9i | 2 | -11.2
200 | 4i | 7 | -1.9
165 | 7i | 4 | -2.8 |  |  | 2024-10-31 00:00:00
135 | PW | -5 | -2.1
110 | 50* | 3 | 2.5
120 | 50* | 3 | -7.1
130 | PW | 3 | -7.7
175 | 6i | -2 | 1.3
120 | PW | 2 | 2.1
190 | 5i | 9 | -5.8
110 | 50* | 0 | -0.9
140 | 9i | 3 | 1.7
150 | 8i | 1 | -0.2
185 | 5i | 2 | -8.3
135 | PW | 1 | -2.4
105 | 54* | 4 | -1.2
130 | PW | -3 | 1.5
115 | 50* | 4 | -1.6
125 | PW | 5 | -1.8
170 | 7i | 3 | 1
115 | 50* | -2 | 2.8
120 | PW | 3 | 6.4
195 | 5i | 9 | -10.7
130 | PW | 6 | 1.6
110 | 50* | 3 | 2.8
155 | 8i | 4 | 0.4
105 | 54* | 3 | -10.2
160 | 8i | 1 | -9.3
125 | PW | -1 | 1
180 | 6i | 10 | -2.1
145 | 9i | -1 | 0.5
200 | 4i | 25 | -1.6
Spreadsheet: 468436d1467295489-how-to-filter-three-or-more-tables-on-one-field-and-value-jobcard_forum
Sheet: Material

M_no | JC_no | JC_Mpos | Mstop_date | M_descr | Quantity | Part_no | Order_no | Reorder | M_Ucost | M_cost
1 | 1 | 1 | 2016-05-16 00:00:00 | Water pump [NAME] | 1 | 123 | 1 | n
2 | 1 | 2 | 2016-05-16 00:00:00 | Waiste | 1 |  | 2 | y
3 | 2 | 1 | 2016-05-18 00:00:00 | Waiste | 1 |  | 2 | y
Spreadsheet: 115468d1311082453-using-vlookup-and-choose-functions-together-vlookup-and-choose
Sheet: Summary

 | City | Mon | Tue | Wed | Thu | Fri
England | London | 0.3695428849440279 | 0.466577299164221 | 0.4669820918141565 | 0.4424507068310652 | 0.5197187878917569
 | [NAME] | 0.7115804673551929 | 0.6430968953491703 | 0.06593622420102507 | 0.7709848782672439 | 0.05381646260267381
Ireland | Dublin | 0.8420908806398106 | 0.385865763580246 | 0.7989911215964194 | 0.1031321984347766 | 0.07264782794110508
 | [NAME] | 0.6856452095929996 | 0.9329304128487923 | 0.520911587989187 | 0.08403264180571668 | 0.4959021739435052
Scotland | Edinburgh | 0.119641674269199 | 0.2122099978031049 | 0.3257154242932176 | 0.06250898369052105 | 0.1120558246072045
 | [NAME] | 0.0344059934838441 | 0.1125890048329012 | 0.9479434639225379 | 0.9640861832449232 | 0.5017326483910791
Wales | Cardiff | 0.7428062208594792 | 0.3112220609454885 | 0.7231875456429846 | 0.6362127597517286 | 0.4568405217269769
 | Swansea | 0.7276668487880062 | 0.6274489470093672 | 0.3874355789948076 | 0.2161483080057132 | 0.003859924108977619
Spreadsheet: 79b06ce2-c795-4782-8e13-ab0b397df2ed
Sheet: Sheet1

PRESIDENTIAL PRIMARY | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9
1996-02-20 00:00:00
Names on Checklist
 | Republican | Democratic | Libertarian | Undeclared | Total |  | Code A | Code B | Code C
Belknap | 15689 | 7941 | 119 | 8972 | 32721 |  | 1076 | 3185 | 1474
Carroll | 14236 | 5221 | 137 | 8714 | 28308 |  | 603 | 2518 | 1998
Cheshire | 15718 | 13450 | 116 | 12057 | 41341 |  | 1674 | 3610 | 2630
Coos | 7222 | 7059 | 38 | 5535 | 19854 |  | 456 | 1358 | 752
[NAME] | 19825 | 12309 | 134 | 14696 | 46964 |  | 1893 | 4110 | 2775
Hillsborough | 82657 | 66523 | 1033 | 50908 | 201121 |  | 8433 | 16532 | 10115
Merrimack | 33996 | 21616 | 341 | 18743 | 74696 |  | 3870 | 8954 | 6184
Rockingham | 66279 | 47191 | 992 | 49121 | 163583 |  | 5296 | 16630 | 9989
[NAME] | 20408 | 20473 | 296 | 15884 | 57061 |  | 2719 | 5229 | 2923
[NAME] | 9470 | 7485 | 51 | 5790 | 22796 |  | 635 | 2045 | 1257
Totals | 285500 | 209268 | 3257 | 190420 | 688445 |  | 26655 | 64171 | 40097
Code A: Number of persons who registered to vote at the polling place on Presidential Primary Election Day.
Code B: Number of undeclared voters voting on Presidential Primary Election Day.
Code C: Number of undeclared voters voting on Presidential Primary Election day who returned to
undeclared status before leaving the polling place.
Spreadsheet: 684190d1593187593-need-help-with-data-validation-and-lists-testing
Sheet: Data

Name | Occurrence | Date | Status | Notes | Issued | Helper | Helper 2
Filipe (208825)[C]
Filipe (208825)[C]
Spreadsheet: 40879d1239276821-top-10-from-two-criteria-houseleague1new
Sheet: Top 10

[NAME] |  |  |  |  | [NAME] |  |  |  |  | Florence Nightingale |  |  |  |  | Florence Nightingale |  |  |  |  | [NAME] |  |  |  |  | [NAME] |  |  |  |  | [NAME] |  |  |  |  | [NAME] |  |  |  |  | [NAME] |  |  |  |  | [NAME]
Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK |  | Tutor | Name | Running Total | RANK
Spreadsheet: 547245d1510424307-invoice-queue-sequence-invoice-sequence-group
Sheet: Sheet1

Date | Invoice | Queue |  | Queue | column E is hard coded for what I'm trying to make the formula in column C to have
2017-01-05 00:00:00 | 1234 |  |  | 1234-1
2017-01-06 00:00:00 | 1234 |  |  | 1234-1
2017-01-07 00:00:00 | 1234 |  |  | 1234-1
2017-01-08 00:00:00 | 1234 |  |  | 1234-1
2017-01-05 00:00:00 | 1235 |  |  | 1235-1
2017-01-06 00:00:00 | 1235 |  |  | 1235-1
2017-01-11 00:00:00 | 1235 |  |  | 1235-2
2017-01-21 00:00:00 | 1235 |  |  | 1235-3
2017-01-22 00:00:00 | 1235 |  |  | 1235-3
2017-01-06 00:00:00 | 1456 |  |  | 1456-1
2017-01-07 00:00:00 | 1456 |  |  | 1456-1