tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 02de5b7c-fb79-4784-b63c-b3409b1aa0e1
Sheet: EPR 1X CQY 

Reconciliations of GAAP to Non-GAAP Adjusted Financial Measures
(In millions, except EPS)
Third Quarter Ended June 30, 2013
 |  |  |  |  | Continuing Operations
 | Product Sales Revenue | Cost of  Interactive | Operating Expenses | Operating Income | Net Earnings (a) | Diluted EPS
GAAP measures | 259.2 | 26.9 | 214.2 | 122.9999999999999 | 65.69999999999995 | 0.25
% of revenue |  |  | 0.3699481865284974 | 0.2124352331606217
Acquisition-related charges: (b)
Contingent retention & earn-out | 0 | 0 | -19.2 | 19.2 | 12.8 | 0.05
Amortization of intangibles | 0 | -2.3 | -4.4 | 6.7 | 4.4 | 0.02
Proxy fees | 0 | 0 | -3.7 | 3.7 | 2.5 | 0.01
Building impairment | 0 | 0 | -1.5 | 1.5 | 1 | 0
Total non-GAAP adjustments | 0 | -2.3 | -28.8 | 31.1 | 20.7 | 0.08
Adjusted measures | 259.2 | 24.6 | 185.4 | 154.0999999999999 | 86.39999999999995 | 0.33
% of revenue |  |  | 0.3202072538860103 | 0.2661485319516407
Nine Months Ended June 30, 2013
 |  |  |  |  | Continuing Operations
 | Product Sales Revenue | Cost of  Interactive | Operating Expenses | Operating Income | Net Earnings (a) | Diluted EPS
GAAP measures | 772.9000000000001 | 75.1 | 617 | 370.7000000000003 | 209.2000000000003 | 0.79
% of revenue |  |  | 0.3609875965363913 | 0.2168850924409082
Acquisition-related charges: (b)
Contingent retention & earn-out | 0 | 0 | -58.59999999999999 | 58.59999999999999 | 39.09999999999999 | 0.14
Amortization of intangibles | 0 | -6.899999999999999 | -13.3 | 20.2 | 13.5 | 0.05
Proxy fees | 0 | 0 | -7.6 | 7.6 | 5.1 | 0.02
Impairment | 0 | 0 | -3.1 | 3.1 | 2.1 | 0.01
Royalty settlement | -5 | 0 | 0 | -5 | -5 | -0.02
Certain discrete tax items (benefits) | 0 | 0 | 0 | 0 | -5.9 | -0.02
Total non-GAAP adjustments | -5 | -6.899999999999999 | -82.59999999999998 | 84.49999999999999 | 48.9 | 0.18
Adjusted measures | 767.9000000000001 | 68.19999999999999 | 534.4 | 455.2000000000003 | 258.1000000000003 | 0.9700000000000001
% of revenue |  |  | 0.3126608939854902 | 0.2663234261642876
(a) Adjustments tax effected at 33%, except no tax effect on royalty settlement
(b) Primarily related to DoubleDown
Spreadsheet: 479006d1473176991-streetnumbers-even-and-odd-welldone2
Sheet: Tabelle1

Code | von | bis | Code3 | Code2 | Kennziffer | Column1 |  |  |  |  | STCODE | [NAME]. | Code | Code2 | Richtig | Richtig
81379 KIS | 61 | 75 | 43 | 270 |  |  |  |  |  |  | 81379 KIS | 1 |  |  | 44 | 550
81379 KIS | 1 | 59 | 44 | 550 |  |  |  |  |  |  | 81379 KIS | 74 |  |  | 43 | 270
81379 KIS | 2 | 60 | 44 | 550 |  |  |  |  |  |  | 81379 KIS | 155 |  |  | 43 | 285
81379 KIS | 61 | 75 | 43 | 270 |  |  |  |  |  |  | 81379 KIS | 148 |  |  | 43 | 285
81379 KIS | 62 | 82 | 43 | 480 |  |  |  |  |  |  | 81379 KIS | 160 |  |  | 43 | 290
81379 KIS | 77 | 101 | 43 | 270 |  |  |  |  |  |  | 81379 KIS | 4 |  |  | 44 | 550
81379 KIS | 84 | 124 | 43 | 270 |  |  |  |  |  |  | 81476 LIM | 10 |  |  | 42 |  |  |  | [NAME] (ein Streetrange 1 bis [NAME] normaler sverweis
81379 KIS | 103 | 123 | 43 | 280 |  |  |  |  |  |  | 82041 NOR | 88 |  |  | 83 | 160 |  |  | [NAME] (ein Streetrange 1 bis [NAME] normaler sverweis
81379 KIS | 125 | 144 | 43 | 280 |  |  |  |  |  |  | 83561 MUC | 24 |  |  | 82 | 360
81379 KIS | 145 | 157 | 43 | 285 |  |  |  |  |  |  | 83561 MUC | 13 |  |  | 80 | 100
81379 KIS | 146 | 150 | 43 | 285 |  |  |  |  |  |  | 83561 MUC | 14 |  |  | 81 | 370
81379 KIS | 152 | 8888 | 43 | 290 |  |  |  |  |  |  | 83561 MUC | 19 |  |  | 81 | 110
81379 KIS | 159 | 9999 | 43 | 290 |  |  |  |  |  |  | 83561 MUC | 26 |  |  | 82 | 360
81476 LIM | 1 | 9999 | 42 | 970 |  |  |  |  |  |  | 83561 MUC | 88 |  |  | 79 | 350
82041 NOR | 1 | 9999 | 83 | 160 |  |  |  |  |  |  | 83561 MUC | 99 |  |  | 83 | 150
83561 MUC | 1 | 15 | 80 | 100
83561 MUC | 2 | 20 | 81 | 370
83561 MUC | 17 | 21 | 81 | 110
83561 MUC | 22 | 28 | 82 | 360
83561 MUC | 23 | 9999 | 83 | 150
83561 MUC | 30 | 8888 | 79 | 350
Ich benötige eine [NAME] STCODE in der Matrix findet in A:F und gleichzeitig in der gefundenen Zeile prüft ob die [NAME].  in J:J in Streetrange B:C passt und dann als [NAME] die richtige [NAME].
Spreadsheet: 808498d1670498826-combine-2-sheets-grade-676-mpyaa
Sheet: WASTANI WA UFAULU KISHULE

HALMASHAURI YA WILAYA [NAME]
MATOKEO YA MTIHANI WA KUMALIZA MUHULA WA PILI DARASA LA [NAME], 2022
[NAME] SHULE KWA KIGEZO CHA WASTANI WA ALAMA
NA | SHULE | KATA | WALIOFANYA |  |  | WALIOFAULU |  |  | A |  |  | B |  |  | C |  |  | % [NAME] | WASTANI WA ALAMA | D |  |  | E |  |  | % YA WALIOFELI | [NAME] SHULE
 |  |  | WAV | WAS | JML | WAV | WAS | JML | WAV | WAS | JML | WAV | WAS | JML | WAV | WAS | JML |  |  | WAV | WAS | JML | WAV | WAS | JML
1 | NAMELOCK
2 | KINUA |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4
3 | NJIAPANDA |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6
4 | OLOIMUGI |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2
5 | KAZINGUMU
6 | [NAME]
7 | MUUNGANO
8 | Nhati
9 | MWITIKIRA
10 | NDEDO
Spreadsheet: 27579d1220961447-unique-values-buy-sell-market-unique
Sheet: Sheet1

Market | Side | Price
Paris | Buy | 15.635
Paris | Buy | 15.64
Paris | Buy | 15.64
Paris | Buy | 15.64
Paris | Sell | 15.61
Paris | Sell | 15.61
MADRID | Sell | 17.11
MADRID | Buy | 17.12
MADRID | Buy | 17.12
MADRID | Sell | 17.14
MADRID | Buy | 17.16
MADRID | Sell | 17.15
MADRID | Sell | 17.15
MADRID | Buy | 17.18
MADRID | Buy | 17.18
MADRID | Buy | 17.18
MADRID | Sell | 17.16
MADRID | Sell | 17.16
MADRID | Buy | 17.11
MADRID | Buy | 17.11
MADRID | Buy | 17.11
MADRID | Buy | 17.11
MADRID | Buy | 17.11
MADRID | Buy | 17.09
MADRID | Sell | 17.04
MADRID | Sell | 17.04
MADRID | Buy | 17.04
MADRID | Buy | 16.99
MADRID | Sell | 17
MADRID | Buy | 17
MADRID | Buy | 16.98
MADRID | Sell | 17.01
MADRID | Sell | 17.01
MADRID | Sell | 16.97
MADRID | Sell | 16.97
MADRID | Buy | 16.97
MADRID | Buy | 16.97
MADRID | Buy | 16.97
MADRID | Sell | 16.97
MADRID | Sell | 16.97
MADRID | Sell | 16.97
MADRID | Buy | 16.92
MADRID | Buy | 16.92
MADRID | Buy | 16.92
MADRID | Buy | 16.92
MADRID | Sell | 16.92
MADRID | Sell | 7.09
MADRID | Buy | 7.07
MADRID | Buy | 7.07
Spreadsheet: 827489d1682725477-counta-based-on-non-empty-cell-or-row-samples-for-excell-forum-tms
Sheet: Sheet1

Account Name | Account | Date | Description | X | Amount | Balance | X2 | Category Type | Category
 |  | 2023-01-01 00:00:00 |  |  | -83.75 | 801.14 |  | Expenses | Petrol
 |  | 2023-01-01 00:00:00 |  |  | -17.9 | 783.24 |  | Expenses | Groceries
 |  | 2023-01-03 00:00:00 |  |  | -40.21 | 743.03 |  | Expenses | Groceries
 |  | 2023-01-04 00:00:00 |  |  | 1700 | 2443.03
 |  | 2023-01-04 00:00:00 |  |  | 1700 | 4143.03
 |  | 2023-01-04 00:00:00 |  |  | -385 | 3758.03 |  | Savings | [NAME]
Total
All
Categorised
Non-categorised
Spreadsheet: 844864d1696509690-running-total-that-outputs-0-if-the-sum-is-negative-and-applying-max-caps-aggregate-excess
Sheet: Sheet1 (2)

 |  |  | Stop Loss | Agg | [NAME]
 |  | CLAIMED AMOUNT | 250000 | 1500000
 |  | 350000
 |  | 75000
 |  | 110000
 |  | 435000
 |  | 0
 |  | 500000
 |  | 0
 |  | 0
 |  | 300000
 |  | 600000
 |  | 300000
 |  | 95000
Spreadsheet: 377208d1423840391-determining-minimum-of-ranges-separated-by-blanks-2015-02-13-excelforum-oeldere-
Sheet: Blad1

value | group | count |  |  |  |  | Rijlabels | Min van value
1226 |  |  |  |  |  |  | Group 1 | 1226
1666 |  |  |  |  |  |  | Group 2 | 1846
1233 |  |  |  |  |  |  | Group 3 | 1555
 |  |  |  |  |  |  | Eindtotaal | 1226
1846
1899
1555
1963
1877
1856
Spreadsheet: 51a8397e-af83-4763-914c-492bf31a601a
Sheet: Sheet1

State [NAME] (North Dakota) | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
Downloaded at 5/20/2013 3:50:26 PM
Precincts Reporting: 528/528 - Total Ballots Cast: 102886
2008 Primary Election - OFFICIAL RESULTS
District | [NAME] | [NAME] | [NAME] | Whitney Hauz | TOTALS
District 02 | 1 | 0 | 0 | 0 | 1
District 03 | 0 | 0 | 0 | 0 | 0
District 04 | 0 | 0 | 0 | 0 | 0
District 05 | 0 | 1 | 0 | 0 | 1
District 06 | 0 | 0 | 0 | 0 | 0
District 11 | 0 | 0 | 0 | 0 | 0
District 13 | 0 | 0 | 0 | 0 | 0
District 20 | 0 | 0 | 0 | 0 | 0
District 21 | 0 | 0 | 0 | 0 | 0
District 22 | 0 | 0 | 0 | 0 | 0
District 27 | 0 | 0 | 0 | 0 | 0
District 36 | 0 | 0 | 0 | 0 | 0
District 37 | 0 | 0 | 0 | 0 | 0
District 38 | 0 | 0 | 0 | 0 | 0
District 40 | 0 | 0 | 0 | 0 | 0
District 41 | 0 | 0 | 0 | 0 | 0
District 44 | 1 | 0 | 1 | 1 | 3
Results provided by the Office of North Dakota Secretary of State | 0 | 0 | 1 | 0 | 1
District 46 | 0 | 0 | 0 | 0 | 0
TOTAL | 2 | 1 | 2 | 1 | 6
Spreadsheet: 269a13f2-9502-4450-a1a4-76aecf399c1b
Sheet: Sheet1

Table 1--U.S. cotton supply and use estimates | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7
 |  |  | 2011/12
Item | 2010/11 |  | Jan. |  | Feb. |  | Mar.
 | Million acres
Upland:
Planted | 10.77 |  | 14.426 |  | 14.426 |  | 14.426
Harvested | 10.497 |  | 9.444 |  | 9.444 |  | 9.444
 | Pounds
Yield/harvested acre | 805 |  | 754 |  | 754 |  | 754
 | Million 480-lb. [NAME]
Beginning stocks | 2.929 |  | 2.572 |  | 2.572 |  | 2.572
Production | 17.6 |  | 14.828 |  | 14.828 |  | 14.828
Total supply   1/ | 20.531 |  | 17.405 |  | 17.405 |  | 17.415
[NAME] use | 3.874 |  | 3.575 |  | 3.475 |  | 3.375
Exports | 13.881 |  | 10.35 |  | 10.35 |  | 10.35
Total use | 17.755 |  | 13.925 |  | 13.825 |  | 13.725
Ending stocks  2/ | 2.572 |  | 3.496 |  | 3.596 |  | 3.701
 | Percent
Stocks-to-use ratio | 14.5 |  | 25.1 |  | 26 |  | 27
 | 1,000 acres
Extra-long staple:
Planted | 204.2 |  | 306.4 |  | 306.4 |  | 306.4
Harvested | 201.7 |  | 303.9 |  | 303.9 |  | 303.9
 | Pounds
Yield/harvested acre | 1200 |  | 1336 |  | 1336 |  | 1336
 | 1,000 480-lb. [NAME]
Beginning stocks | 18 |  | 28 |  | 28 |  | 28
Production | 504 |  | 846 |  | 846 |  | 846
Total supply   1/ | 529 |  | 879 |  | 879 |  | 874
[NAME] use | 26 |  | 25 |  | 25 |  | 25
Exports | 495 |  | 650 |  | 650 |  | 650
Total use | 521 |  | 675 |  | 675 |  | 675
Ending stocks  2/ | 28 |  | 204 |  | 204 |  | 199
 | Percent
Stocks-to-use ratio | 5.4 |  | 30.2 |  | 30.2 | 30.2 | 29.4
1/ Includes imports.  2/ Includes unaccounted.
Last update:  03/12/12.
Sources: USDA, World Agricultural Outlook Board; and USDC,
U.S. Census Bureau.
Spreadsheet: 690952d1597393033-rank-in-order-of-size-per-client-ranking-5-highest-from-list-of-multiple-groups-and-indexing-associated-columns
Sheet: report

 |  |  | Client | banana
 | Name | Balance | Unit | Status
Spreadsheet: 65950d1266576356-lookup-formula-demo-v2
Sheet: NO2

 | Name | Birthday |  |  | Address | phone | Start date
 |  |  |  |  | Job | Cell | Quit Date
Feb | MrE | 1975 | Feb | 13 | Don't know street | 55223222 | 2007-03-02 00:00:00
Feb |  |  |  |  | Secretary | 905555221
Mar | MrD | 1978 | Mar | 30 | Have not a clue Rd | 22555 | 2008-04-06 00:00:00
Mar |  |  |  |  | Manager | 905555221
Apr | MrS | 1979 | Apr | 31 | Wouldn't know how to to get there Street | 552222552 | 2010-01-02 00:00:00
Apr |  |  |  |  | sales clerk | 905555221
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Spreadsheet: 766562d1643940278-reverse-vlookup-index-match-combo-unsure-how-to-proceed-excel-help-file
Sheet: Sheet1

 | LaneSet | [NAME] | Store |  | [NAME] | Associate | Lanes
 | 0 | 1 | a |  | 1 | 123 | 2 | 3 | 4 | 0 | 0
 | 1 | 2 | b |  | 2 | 3456 | 5 | 6 | 7 | 0 | 0
 | 1 | 3 | c |  | 3 | 765 | 8 | 9 | 10 | 11 | 0
 | 1 | 4 | d |  | 4 | 231 | 12 | 13 | 0 | 0 | 0
 | 2 | 5 | e |  | 5 | 9854 | 14 | 15 | 16 | 0 | 0
 | 2 | 6 | f |  | 6 | 962 | 17 | 18 | 19 | 29 | 0
 | 2 | 7 | g
 | 3 | 8 | h
 | 3 | 9 | i
 | 3 | 10 | j
Spreadsheet: 1cd11b2c-12a7-4b11-ae84-d5354438c094
Sheet: 11c

Product | AUD** | CAD | CHF | DKK | KRW | NOK | NZD | SEK | ZAR | TOTAL
Basis*
FRA |  |  |  | 156 |  |  |  |  |  | 156
IRS- [NAME] | 696 | 620 | 226 |  |  |  | 112 | 172 | 260 | 2086
OIS
VNS
Zero Coupon
TOTAL | 696 | 620 | 226 | 156 |  |  | 112 | 172 | 260 | 2242
Estimated swap transaction volumes, week ending November 16, by product type and major currency (in number of transactions), all participant types, cleared and uncleared.
Total(s) may be less than total shown for this asset class in the All Swaps reports and/or other CFTC Swaps Report tables if products were excluded from this table that (a) presented disclosure risk or (b) did not belong in the categories shown.
*See Data Dictionary for product descriptions.
**See Data Dictionary for major currency descriptions.
***N/A indicates that data are not currently available.
Note: Transaction volumes currently include house and client trades by FCMs in the interest rate asset class.
The Commission requests feedback on the format and content of this CFTC Swaps Report table. Submit comments to [EMAIL].
Spreadsheet: 52559d1252413933-help-with-a-formula-referencing-multiple-tabs-sept-09-sales-and-labor
Sheet: Sept Wk 3

Date | 2009-09-13 00:00:00 | 2009-09-14 00:00:00 | 2009-09-15 00:00:00 | 2009-09-16 00:00:00 | 2009-09-17 00:00:00 | 2009-09-18 00:00:00 | 2009-09-19 00:00:00
 | Sunday | Monday | Tuesday | Wednesday | Thursday | Friday | Saturday
Net Sales*
WTD Net Sales |  | 0 | 0 | 0 | 0 | 0 | 0
MTD Net sales | 55173 | 55173 | 55173 | 55173 | 55173 | 55173 | 55173
LY Sales | 7707 | 4453 | 5524 | 6164 | 7264 | 8828 | 13176
LY [NAME] |  | 12160 | 17684 | 23848 | 31112 | 39940 | 53116
LY Sales MTD | 115959 | 120412 | 125936 | 132100 | 139364 | 148192 | 161368
Comp $ +/- | -7707 | -4453 | -5524 | -6164 | -7264 | -8828 | -13176
WTD Comp  $ +/- |  | -12160 | -17684 | -23848 | -31112 | -39940 | -53116
MTD Comp $ +/- | -60786 | -65239 | -70763 | -76927 | -84191 | -93019 | -106195
Comp %  +/- | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
WTD Comp  % +/- |  | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
MTD Comp % +/- |  | -1.18244431152919 | -1.28256574773893 | -1.39428706069998 | -1.525945661827343 | -1.685951461765719 | -1.924763924383303
Food/Bev Sales
WTD F&B |  | 0 | 0 | 0 | 0 | 0 | 0
LBW Sales
WTD LBW |  | 0 | 0 | 0 | 0 | 0 | 0
Alcohol Sales Mix   * | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
WTD Alc Mix |  | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
BOH Labor $
WTD BOH Labor $ |  | 0 | 0 | 0 | 0 | 0 | 0
BOH Labor Hours
WTD BOH Labor Hrs |  | 0 | 0 | 0 | 0 | 0 | 0
FOH Labor $
WTD FOH Labor $ |  | 0 | 0 | 0 | 0 | 0 | 0
FOH Labor Hours
WTD FOH Labor Hrs |  | 0 | 0 | 0 | 0 | 0 | 0
BOH Labor %   * | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
WTD BOH % |  | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
BOH Productivity | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
WTD BOH Prod |  | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
FOH Labor %   * | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
WTD FOH % |  | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
FOH Productivity | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
WTD FOH Prod |  | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
[NAME]
Lunch Sales WTD |  | 0 | 0 | 0 | 0 | 0 | 0
[NAME] | 3602 | 1679 | 1460 | 1702 | 2791 | 2383 | 4198
[NAME] |  | 5281 | 6741 | 8443 | 11234 | 13617 | 17815
"+/-" LY | -3602 | -1679 | -1460 | -1702 | -2791 | -2383 | -4198
"+/- [NAME] |  | -5281 | -6741 | -8443 | -11234 | -13617 | -17815
DATE | 2009-09-07 00:00:00
DAILY SALES: $ | #N/A
[NAME] SALES: $ | #N/A
+/- [NAME] | #N/A
WTD SALES: $ | #N/A
MTD SALES: $ | #N/A
FOOD & BEV $ | #N/A
LIQUOR MIX: % | #N/A
WTD LIQUOR MIX: % | #N/A
FOH: $ | #N/A
FOH HOURS | #N/A
FOH LABOR: % | #N/A
FOH PROD: $ | #N/A
WTD FOH LABOR: % | #N/A
BOH: $ | #N/A
BOH HOURS | #N/A
BOH LABOR: % | #N/A
BOH PROD: $ | #N/A
WTD BOH LABOR: % | #N/A
LUNCH: $ | #N/A
LUNCH VS LY | #N/A
 | high 30s
Spreadsheet: 121930d1316514099-excel-2007-solved-how-to-group-and-sort-data-forumxl
Sheet: Sheet1

Chassis | Network Element Name | Slot No | Product ID | SNMP Name | Current Termination Milestone
jr1 | PN1 | Chassis | JP1 | CS1 | 1 Yr to Termination |  |  |  |  | total | terminated
jr1 | PN1 | 1 | JP2 | CS2 | 6 months to Termination |  |  |  | jr1
jr1 | PN1 | 1 | JP3 | CS3 |  |  |  |  | jr2
jr1 | PN1 | 2 | [NAME] | CS4 | Terminated |  |  |  | [NAME]
jr1 | PN1 | 3 | JP5 | CS5 | Terminated
jr1 | PN1 | 3 | JP6 | CS6 | 1 Yr to Termination
jr1 | PN1 | 4 | JP7 | CS7
jr1 | PN1 | 6 | JP8 | CS8
jr1 | PN1 | 7 | JP9 | CS9
jr1 | PN1 | 8 | JP10 | CS10 | Terminated
jr1 | PN1 | 8 | JP11 | CS11 | 1 Yr to Termination
jr1 | PN1 | 9 | [NAME] | CS12 | Terminated
jr1 | PN1 | 9 | [NAME] | CS13 | 1 Yr to Termination
jr2 | PN2 | Chassis | [NAME] | CS14 | 1 Yr to Termination
jr2 | PN2 | 1 | JP15 | CS15 | 6 months to Termination
jr2 | PN2 | 1 | JP16 | CS16
jr2 | PN2 | 2 | JP17 | CS17 | Terminated
jr2 | PN2 | 3 | JP18 | CS18 | Terminated
jr2 | PN2 | 6 | JP19 | CS19 | Terminated
jr2 | PN2 | 6 | [NAME] | CS20 | 1 Yr to Termination
jr2 | PN2 | 7 | JP21 | CS21 | Terminated
jr2 | PN2 | 7 | JP22 | CS22 | 1 Yr to Termination
jr2 | PN2 | 8 | JP23 | CS23 | Terminated
jr2 | PN2 | 8 | [NAME] | CS24 | 1 Yr to Termination
jr2 | PN2 | 9 | JP25 | CS25 | Terminated
jr2 | PN2 | 9 | JP26 | CS26 | 1 Yr to Termination
[NAME] | PN3 | Chassis | JP27 | CS27
[NAME] | PN3 | 1 | JP28 | CS28
[NAME] | PN3 | 2 | [NAME] | CS29
[NAME] | PN3 | 3 | JP30 | CS30
[NAME] | PN3 | 4 | JP31 | CS31
[NAME] | PN3 | 5 | JP32 | CS32
[NAME] | PN3 | 5 | JP33 | CS33
[NAME] | PN3 | 5 | JP34 | CS34
[NAME] | PN3 | 7 | [NAME] | CS35
[NAME] | PN3 | 7 | [NAME] | CS36
[NAME] | PN3 | 8 | JP37 | CS37
[NAME] | PN3 | 8 | JP38 | CS38
[NAME] | PN3 | 9 | JP39 | CS39
[NAME] | PN3 | 9 | [NAME] | CS40
Spreadsheet: 390747d1429750449-copying-one-table-to-another-automatically-test2
Sheet: Sheet1

Product | C Month Prv Yr | YTD Prev Yr | C Month | YTD | 2014 | 2015 | Primary Market | Secondary Market | Measure | 2014/Jan | 2014/Feb | 2014/Mar | 2014/Apr | 2014/May | 2014/Jun | 2014/Jul | 2014/Aug | 2014/Sep | 2014/Oct | 2014/Nov | 2014/Dec | 2015/Jan | 2015/Feb | 2015/Mar
Spreadsheet: 115348d1310998974-transferring-results-and-drop-down-lists-hospitalformdata
Sheet: Output Tab 2010

7 | Line Number of Current Hospital
Hospital: | Hospital G
Hospital Number: | 000007
FYE: | 2011-12-31 00:00:00
1) Data 1 |  |  |  |  |  | 54412
2) Multiply by 1.4 |  |  |  |  |  | 76176.79999999999
3)     Data 2 - 2009 |  |  | 45745.44
Data 3 - 2009 |  |  | 455447.49
4)  Data 2 |  |  |  |  |  | 45745.44
Multiply by factor (Data 4) |  |  |  |  |  | 1.0333
Result 1 - 2010 |  |  |  |  |  | 47268.76315200001
Data 3 |  |  |  |  |  | 455447.49
Multiply by factor (Data 4) |  |  |  |  |  | 1.0333
Result 2 - 2010 |  |  |  |  |  | 470613.891417
Spreadsheet: 848215d1698979193-how-to-calculate-a-pay-rate-that-is-affected-by-2-different-pay-conditions-pay-calculator_normal-pay-without-extra-days
Sheet: Early-Late Penalty Calculator

 |  |  | EARLY/LATE PENALTY RATE HOURS
 |  |  | Start | End | Total | Normal | Penalty | ROUNDED
WEEK 1
 |  |  | 00:00:00 | 00:00:00 | 0 | 0
 |  |  | 00:00:00 | 00:00:00 |  | 0
 |  |  |  |  |  | Week 1 - Total :
 |  |  | EARLY/LATE PENALTY RATE HOURS
 |  |  | Start | End | Total | Normal | Penalty | ROUNDED
WEEK 2
 |  |  | 00:00:00 | 00:00:00 | 0 | 0
 |  |  | 00:00:00 | 00:00:00 | 0 | 0
 |  |  |  |  |  | Week 2 - Total :
Spreadsheet: 883400d1732022990-overview-of-dates-mier_2024-test-212-spill-365-aligw
Sheet: Car

Roof |  |  |  |  | Wheels |  |  |  |  | Lights
Recived | Vendor | Purchase number | Date for delevry |  | Recived | Vendor | Purchase number | Date for delevry |  | Recived | Vendor | Purchase number | Date for delevry
False | [NAME] | 50005 | 2024-11-17 00:00:00 |  | False | [NAME] | 50007 | 2024-11-19 00:00:00 |  | False | [NAME] | 50014 | 2024-11-21 00:00:00
False | July | 50006 | 2024-12-25 00:00:00 |  | False | [NAME] | 50008 | 2024-11-20 00:00:00 |  | False | [NAME] | 50015 | -
Spreadsheet: 376609d1423663070-colomns-showing-as-text-not-number-currency-21355
Sheet: 21355_Vanessa English

CUSTOMER NAME: | xx |  | ORDER NUMBER: | 21355 |  | EMAIL ADDRESS: | x
ADDRESS: | xx |  | VERIFIED: | 0
DATE: | 42218
SKU | QTY | IPC EAN | ITEM TITLE | Unit | Value | SALES RANK | ITEM WEIGHT | DI | CA | DI/CA | MI | PA | PI/CA
 | 1 | 4005209091183 | [NAME] (Wii) | £0.10 | £1.54 | 2772 | 136.36
 | 1 | 5051272005694 | [NAME] the Builder: Festival of Fun (Wii) | £0.10 | £0.06 | 13266 | 136.36
 | 1 | 5050582849172 | One Day [DVD] [2011] | £0.10 | £0.45 | 1788 | 90.91
 | 1 | 5031366017772 | Driving Test Success ALL Tests 2009/2010 Edition (PC) | £0.01 | £0.01 | 697 | 81.82
 | 1 | 5037999006558 | Sim City 3000 - UK Edition (PC CD) | £0.10 | £0.01 | 5465 | 81.82
 | 1 | 805529445338 | Zoo Tycoon Triple Pack: Includes [NAME], [NAME] and Marina Mania (PC CD) | £0.10 | £0.01 | 6221 | 181.82
Spreadsheet: 856188d1705527774-if-a-word-is-in-a-cell-add-the-amount-in-that-row-to-a-total-fake-sheet
Sheet: Sheet1

Date | Category | Company | Cost |  |  |  |  | [NAME] | Total
2024-01-01 00:00:00 | Grocery | Food Store | 360.22 |  |  |  |  | Grocery
2024-01-01 00:00:00 | Home | Home Depot | 483.33 |  |  |  |  | Eating Out
2024-01-01 00:00:00 | Health | The Drugs | 59.82 |  |  |  |  | Fuel
2024-01-01 00:00:00 | Clothing | Shoes R US | 82 |  |  |  |  | Clothing
2024-01-01 00:00:00 | Entertainment | Movie + | 12.22 |  |  |  |  | Health
2024-01-01 00:00:00 | Clothing | Mitts R US | 27.26 |  |  |  |  | Beauty
 |  |  |  |  |  |  |  | Home
 |  |  |  |  |  |  |  | Utilities*
 |  |  |  |  |  |  |  | Insurance^
 |  |  |  |  |  |  |  | Car
 |  |  |  |  |  |  |  | Entertainment
Spreadsheet: 220532d1363187385-vlookup-or-other-tools-to-retun-more-than-1-match-from-2-criteria-sample
Sheet: Sheet1

ID | Name | Point | Session |  | Desired result: |  | ID | Name | Session
1111 | Viking | 5 | 1 |  |  |  | 111 | Viking | 1
2222 | [NAME] | 6 | 1
1111 | Viking | 10 | 2
Spreadsheet: 115160d1310751544-min-max-values-for-first-column-relative-to-second-columns-values-beforeafter
Sheet: After

Zip code | Number | Same ZIP? | Same Number? | Duplicate |  | Min ZIP | [NAME] | Number
1 | 0.4354 | 0 | 0 | No |  | 1 | 4 | 0.4354
2 | 0.4354 | 0 | 1 | No |  | 4 | 4 | 0.4827
3 | 0.4354 | 0 | 1 | No |  | 5 | 7 | 0.4354
4 | 0.4354 | 0 | 1 | No |  | 7 | 7 | 0.4827
4 | 0.4827 | 1 | 0 | No |  | 8 | 16 | 0.4354
5 | 0.4354 | 0 | 0 | No |  | 16 | 16 | -0.1991
6 | 0.4354 | 0 | 1 | No |  | 17 | 18 | 0.4354
6 | 0.4354 | 1 | 1 | No |  | 18 | 18 | -0.1991
7 | 0.4354 | 0 | 1 | No
7 | 0.4827 | 1 | 0 | No
9 | 0.4354 | 0 | 0 | No
10 | 0.4354 | 0 | 1 | No
11 | 0.4354 | 0 | 1 | No
12 | 0.4354 | 0 | 1 | No
14 | 0.4354 | 0 | 1 | No
15 | 0.4354 | 0 | 1 | No
16 | 0.4354 | 0 | 1 | No
16 | -0.1991 | 1 | 0 | No
17 | 0.4354 | 0 | 0 | No
17 | 0.4354 | 1 | 1 | No
18 | 0.4354 | 0 | 1 | No
18 | -0.1991 | 1 | 0 | No
Spreadsheet: 268014d1380360296-reverse-finding-matches-to-a-number-solver
Sheet: Sheet1

1050 | 1 |  | 4500
1000 | 0
1100 | 1
1000 | 1
1200 | 1
3000 | 0
1850 | 0
1150 | 0
50 | 1
100 | 1