tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 871624d1718047747-how-to-copy-paste-all-rows-and-columns-of-data-from-one-sheet-to-another-sheet-2024_commissions_dale-inc-commission-report
Sheet: Sheet8

DALE INC COMMISSION REPORT / DAVIS WINDOWS AND DOOR SALES / AUGUST / 2024
# | CHECK # | CHECK AMOUNT INCLUDING TAX | % PAID BY CUSTOMER | CUSTOMER | JOB NAME | PRODUCT SOLD | INVOICE / SALES ORDER / ESTIMATE # | SUB-TOTAL | COST | GROSS PROFIT $$$ | GROSS PROFIT % | COMMISION RATE | COMMISSION AMOUNT | ORDERED | RECEIVED
1 | ???? | 192744.3 | 1 | AQUA | [NAME] | WINDOWS & DOORS | QQ #11094 | 192744.3 | 152268 |  |  | 0.2
 |  |  |  | 06/05/24 - lunch w/ Sean & they are still working on this job…     05/21/24 - emailed estimate…
2 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.25
3 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
4 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.25
5 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
6 | ???? | 265284.81 | 1 | CHRIS CLARK | WIGGINS | WINDOWS & DOORS | QQ #11094 | 265284.81 | 209575 |  |  | 0.2
7 | ???? | 381815.19 | 1 | REGAL STEPHENS | EMERICK | WINDOWS & DOORS | QQ #11094 | 381815.19 | 301634 |  |  | 0.2
 |  |  |  | 06/02/24 - emailed estimate… |  |  |  | .
8 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
9 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
10 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
11 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
12 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
13 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
14 |  |  |  |  |  |  |  | 0 | 0 |  |  | 0.3
# | CHECK # | CHECK AMOUNT INCLUDING TAX | % PAID BY CUSTOMER | CUSTOMER | JOB NAME | PRODUCT SOLD | INVOICE / SALES ORDER / ESTIMATE # | SUB-TOTAL | COST | GROSS PROFIT $$$ | GROSS PROFIT % | COMMISION RATE | COMMISSION AMOUNT | ORDERED | RECEIVED
Spreadsheet: 587966d1535409474-need-to-get-totals-of-sub-components-in-bill-of-materials-test
Sheet: Sheet1

SEQ | PART NUMBER | [NAME] | QTY | TOTAL
1 | 10-123456-B | KIT,CRADLE A | 2
1.1 | 2-246-A | CRADLE A | 1
1.2 | 3-123-0 | SCREW A | 2
2 | 10-123456-B | KIT,CRADLE B | 22
2.1 | 2-246-B | CRADLE B | 1
2.2 | 3-123-0 | SCREW A | 2
3 | 10-123456-C | KIT,CRADLE C | 13
3.1 | 2-246-B | CRADLE B | 1
3.2 | 3-123-0 | SCREW A | 2
3.3 | 4-246-0 | WASHER A | 2
4 | 50-123-00 | VALVE | 1
5 | 50-246-00 | PLATE | 2
SEQ | PART NUMBER | [NAME] | QTY | TOTAL
1 | 10-123456-B | KIT,CRADLE A | 2 | 2
1.1 | 2-246-A | CRADLE A | 1 | 2
1.2 | 3-123-0 | SCREW A | 2 | 4
2 | 10-123456-B | KIT,CRADLE B | 22 | 22
2.1 | 2-246-B | CRADLE B | 1 | 22
2.2 | 3-123-0 | SCREW A | 2 | 44
3 | 10-123456-C | KIT,CRADLE C | 13 | 13
3.1 | 2-246-B | CRADLE B | 1 | 13
3.2 | 3-123-0 | SCREW A | 2 | 26
3.3 | 4-246-0 | WASHER A | 2 | 26
4 | 50-123-00 | VALVE | 1 | 1
5 | 50-246-00 | PLATE | 2 | 2
Spreadsheet: 41296d1239792899-vlookup-from-multiple-sheets-shift-schedule
Sheet: WARE HOUSE

WARE HOUSE
[NAME]. | SAP NO. | NAME | SECTION
 | 588 |  |  | A,
 | 234 |  |  | a.
 | 430 |  |  | a.
 | 360 |  |  | a.
 | 312 |  |  | a.
 | 776 |  |  | a.
 | 1071 |  |  | a.
 | 377 |  |  | b.
 | 775 |  |  | b.
 | 636 |  |  | b.
 | 1158 |  |  | b.
 | 1339 |  |  | b.
 |  | 'A' SHIFT
 |  | 'B' SHIFT
 |  | 'C' SHIFT
 |  | 'G' SHIFT
 |  | TOTAL:
Spreadsheet: 114742d1310473436-excel-2007-sorting-data-based-on-formula-results-premier-league-darts
Sheet: Records

Checkout | 2011-01-14 00:00:00 | 59 | Eggman
High Score | 2011-01-14 00:00:00 | 81 | Snook & Legohead
High Score | 2011-01-21 00:00:00 | 99 | [NAME]
Checkout | 2011-01-27 00:00:00 | 71 | Legohead
High Score | 2011-02-11 00:00:00 | 115 | [NAME]
High Score | 2011-02-11 00:00:00 | 115 | Eggman
High Score | 2011-04-15 00:00:00 | 125 | Legohead
High Score |  | 128 | Eggman
Checkout |  | 74 | Legohead
Spreadsheet: 848824d1699457587-breaking-down-an-average-by-month-latest
Sheet: Case Review 2024

Worker | Client ID | Date Assigned | Date Assessed | Intake Assigned to Assessment Opened | Date to Current | Assessment Opened to Moved to Current | Transfer To | [NAME] | Case Aide Involvement | Date Transfer Form Submitted | Moved to Current to Transfer Date (initate [NAME]) | Date Transferred Out | Intake Assigned to Transferred Out | [NAME] | DME Received | Sent Back for Corrections | Comments
Spreadsheet: 185253d1349604180-extracting-uk-postcodes-from-string-of-text-to-import-into-microsoft-autoroute-getpostcodes-novba-
Sheet: Sheet1

String | Result | Actual Code |  | Teethless mama
%M11AA15504002468914814826 | M11AA | M1 1AA |  | M11AA15 | M11A A15
%0WS13QE15504002468914814826 | [NAME] | WS1 3QE |  | [NAME] | WS1 3QE
%0HU91TQ15504002468914814826 | HU91TQ | HU9 1TQ |  | HU91TQ | HU9 1TQ
%0WS13QE15504002468914814826 | [NAME] | WS1 3QE |  | [NAME] | WS1 3QE
%00EC1A1BB15504002468914814826 | EC1A1BB | EC1A 1BB |  | EC1A1 | EC 1A1
Spreadsheet: f3703712-1433-4375-b038-db805f51a3dd
Sheet: 10b

Product | EUR** | GBP | [NAME] | USD | TOTAL
Basis*
FRA
IRS- [NAME]
OIS
VNS
Zero Coupon
TOTAL | N/A*** | N/A | N/A | N/A | N/A
Estimated net notional amount outstanding, August 9 weekly snapshot, by product type and supermajor currency (millions of USD), cleared swaps only, all participant types and tenors.
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 Explanatory Notes for more detail.
*See Data Dictionary for product descriptions.
**See Explanatory Notes for currency descriptions.
***N/A indicates that data are not currently available.
The Commission requests feedback on the format and content of this CFTC Swaps Report table. Submit comments to [EMAIL].
Spreadsheet: 884388d1733511277-multiple-ifs-book1
Sheet: Information

Length | [NAME] | Height | Gross Weight
48 | 40 | 44 | 572
48 | 40 | 66 | 580
54 | 42 | 99 | 1246
48 | 40 | 54 | 272
48 | 40 | 54 | 273
48 | 48 | 88 | 862
48 | 40 | 42 | 547
48 | 42 | 42 | 555
48 | 43 | 47 | 802
48 | 40 | 57 | 231
48 | 40 | 67 | 302
48 | 44 | 63 | 301
48 | 46 | 97 | 946
48 | 48 | 88 | 781
48 | 48 | 86 | 713
48 | 48 | 73 | 1137
48 | 40 | 27 | 300
48 | 40 | 32 | 102
48 | 42 | 33 | 117
48 | 42 | 33 | 117
In the original document, there are 100+ lines. Some days only 1 or 2 are used. Other days, almost 100.
Spreadsheet: 703280d1604927675-sum-the-repeating-values-and-just-transfer-the-unique-values-to-another-column-book1
Sheet: Sheet1

A | B | C
12 | 123 | 373
12 | 124
12 | 126
1 | 335 | 335
2 | 2154 | 2154
5 | 124 | 124
42 | 12 | 47
42 | 35
Spreadsheet: 721820d1614878078-aggregate-narrowed-down-gives-different-result-sample
Sheet: Sheet1

A | 2 |  |  | A |  | A
B | 5 |  |  |  |  |  |  | A
C | 4 |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  | C
 |  |  |  |  |  |  |  | C
 |  |  |  |  |  |  |  | C
 |  |  |  |  |  |  |  | C
Spreadsheet: 0a55c7bc-4c79-4307-9b10-e48858ff91c9
Sheet: Sheet1

Battle ID | Date & Time | Side | Victory | Score | Opp. Score | Opp. ID | Opp. Name | Scenario ID | Front | Start Date | End Date | Name EN | Name FR
42610957 | 2014-08-06 11:04:17 | AXIS | 0 | 1 | 5 | 1615380 | player1615380 | 6160 | western | 1944-06-06 | 1944-06-06 | Sword Beach | Sword Beach
42611060 | 2014-08-06 11:24:15 | ALLIES | 0 | 2 | 5 | 1615380 | player1615380 | 6160 | western | 1944-06-06 | 1944-06-06 | Sword Beach | Sword Beach
42613313 | 2014-08-06 16:13:08 | ALLIES | 0 | 0 | 6 | 1604857 | BreakerMorant | 12506 | eastern | 1941-07-21 | 1941-07-31 | [NAME] | Percée russe
42623466 | 2014-08-07 09:37:18 | AXIS | 0 | 3 | 6 | 384175 | ssegrubnad | 6155 | western | 1944-09-19 | 1944-09-19 | Arracourt | Arracourt
42623586 | 2014-08-07 09:47:34 | ALLIES | 1 | 6 | 3 | 384175 | ssegrubnad | 6155 | western | 1944-09-19 | 1944-09-19 | Arracourt | Arracourt
42638466 | 2014-08-08 14:55:26 | ALLIES | 0 | 4 | 6 | 1591724 | Gladiatore | 7272 | mediterranean | 1942-12-01 | 1942-12-01 | Tunisia | Tunisie
42642487 | 2014-08-08 21:13:15 | AXIS | 1 | 5 | 0 | 1594070 | [NAME] | 7366 | mediterranean | 1942-05-27 | 1942-05-27 | Panzers [NAME] | Panzer contre [NAME]
42642655 | 2014-08-08 21:29:50 | ALLIES | 0 | 4 | 5 | 1594070 | [NAME] | 7366 | mediterranean | 1942-05-27 | 1942-05-27 | Panzers [NAME] | Panzer contre [NAME]
42650000 | 2014-08-09 12:21:01 | AXIS | 0 | 5 | 7 | 1394475 | Franzac | 7668 | pacific | 1945-02-26 | 1945-03-06 | The Meat Grinder | Le Hachoir à viande
42651931 | 2014-08-09 16:00:08 | AXIS | 1 | 6 | 4 | 220477 | baby68 | 7429 | mediterranean | 1941-06-15 | 1941-06-17 | [NAME] | [NAME]
42663038 | 2014-08-10 11:38:02 | ALLIES | 1 | 4 | 1 | 1435229 | INTERJULIE | 6158 | western | 1944-06-06 | 1944-06-06 | Pegasus Bridge | Pegasus Bridge
42678913 | 2014-08-11 14:51:54 | ALLIES | 1 | 6 | 1 | 1616413 | célestin poux | 6749 | western | 1944-06-06 | 1944-06-06 | [NAME] | [NAME]
42679171 | 2014-08-11 15:29:18 | AXIS | 1 | 6 | 4 | 1616413 | célestin poux | 6749 | western | 1944-06-06 | 1944-06-06 | [NAME] | [NAME]
42682969 | 2014-08-11 21:03:56 | AXIS | 1 | 5 | 4 | 1612655 | player1612655 | 6157 | western | 1944-11-19 | 1944-11-23 | Saverne Gap | [NAME]
42683318 | 2014-08-11 21:27:16 | ALLIES | 1 | 5 | 4 | 1612655 | player1612655 | 6157 | western | 1944-11-19 | 1944-11-23 | Saverne Gap | [NAME]
42710507 | 2014-08-13 20:23:43 | ALLIES | 0 | 2 | 5 | 506159 | Hurletout | 6157 | western | 1944-11-19 | 1944-11-23 | Saverne Gap | [NAME]
42710721 | 2014-08-13 20:38:10 | AXIS | 0 | 3 | 5 | 506159 | Hurletout | 6157 | western | 1944-11-19 | 1944-11-23 | Saverne Gap | [NAME]
42718411 | 2014-08-14 09:55:10 | ALLIES | 1 | 6 | 2 | 1007284 | Temple58 | 12493 | western | 1944-12-30 | 1944-12-30 | [NAME] | [NAME]
42722558 | 2014-08-14 18:22:00 | ALLIES | 1 | 6 | 3 | 701256 | player701256 | 6749 | western | 1944-06-06 | 1944-06-06 | [NAME] | [NAME]
42722815 | 2014-08-14 18:51:44 | AXIS | 0 | 5 | 6 | 701256 | player701256 | 6749 | western | 1944-06-06 | 1944-06-06 | [NAME] | [NAME]
Spreadsheet: tracy_geaccone__40401__GPM 101021  101073 Recalculation
Sheet: July 2000

KN Processing |  | GPM Agency Agreement |  |  | Prepared by [NAME]
Bushton Plant |  | TFDV Volume & Dollar Calculation
 |  | For
 |  | 2000-07-01 00:00:00
Contract #101021 |  |  | NNG Numbers |  |  | Oneok Numbers |  |  | Difference
 | Total Deliveries |  |  | 3909475 |  |  | 3909475
 |  | Deliveries to Inlet | 3742015 |  |  | 3742015
 |  | Deliveries to PVR
 |  | Non-Fuel Deliveries
 |  | Fuel Retention
 | Total Receipts |  | 3910385 |  |  | 3910385
 |  | [NAME] | 0.0445 |  |  | 0.0445
 |  | Less Fuel Retained
Transport Revenue [NAME]
Contract #101073
 | Total Deliveries |  |  | 898061 |  |  | 972693
 |  | Deliveries to Inlet | 0
 |  | Deliveries to PVR | 858039 |  |  | 929635
 |  | Non-Fuel Deliveries
 |  | Fuel Retention
 | Total Receipts |  | 922197 |  |  | 922197
 |  | [NAME] | 0.0445 |  |  | 0.0445
 |  | Less Fuel Retained
Transport Revenue [NAME]
 |  | Total Both Contracts
 |  | Index |  | 3.844 |  |  | 3.8445
 |  | Total Revenue Due
Total Revenue Billed |  | 101021 |  | 36987.21
 |  | 101073
 |  |  |  |  |  |  | 17425.26
 |  | Amount Due NNG (GPM)
Charge given by NNG on prior reconciliation
 |  | Amount Due NNG (GPM)
Spreadsheet: 156487d1337307663-excel-2007-complicated-hlookup-or-vlookup-based-on-many-values-data-referal
Sheet: input

Input 1 | Input 2 | Input 3 | Concatenate |  | Results:
A | A | C | A / A / C |  | Color: | Green
 |  |  |  |  | [NAME]: | 60
 |  |  |  |  | Price: | $60,00
Alternatively, you can integrate Concatenate into the formula do away with the "Concatenate" column
Input 1 | Input 2 | Input 3 |  |  | Results:
A | A | B |  |  | Color: | Red
 |  |  |  |  | [NAME]: | 50
 |  |  |  |  | Price: | $50,00
Spreadsheet: 0631d7b6-9649-410f-8baf-7baf5f9d96bf
Sheet: +65 Seeding List

65+ MS (38)
No | Member ID | LastName | FirstName | Country | Gender | Seed
1 | 75686 | KNOTT | [NAME] | CAN | M | 1
2 | 90498 | EDDY | [NAME] | ENG | M | 2
3 | 58494 | DABELSTEEN | Per | DEN | M | 3/4
4 | 64487 | GARRETT | [NAME] | ENG | M | 3/4
5 | 76503 | NYBERGH | [NAME] | FIN | M | 5/8
6 | 52438 | HONNEN | [NAME] | GER | M | 5/8
7 | 61393 | HIROTA | Akira | JPN | M | 5/8
8 | 78927 | LILAND | Knut  Sverre | NOR | M | 5/8
65+ WS (17)
No | Member ID | LastName | FirstName | Country | Gender | Seed
1 | 2830 | [NAME] | Liudmila | RUS | F | 1
2 | 68079 | KATAITO | Yasuko | JPN | F | 2
3 | 87296 | BONNAY | Viviane | FRA | F | 3/4
4 | 52529 | STERLIE | [NAME] | DEN | F | 3/4
65+ MD (26)
No | Member ID 1 | Member ID 2 | Lastname 1 | Firstname 1 | Lastname 2 | Firstname 2 | Country 1 | Country 2 | Gender 1 | Gender 2 | Seed
1 | 64685 | 85194 | THONGDEJSRI | Chaisak | CHINTANASERI | Seri | THA | THA | M | M | 1
2 | 61393 | 57893 | HIROTA | Akira | MATSUDA | Shinjiro | JPN | JPN | M | M | 2
3 | 59462 | 90498 | HUTCHINSON | [NAME] | EDDY | [NAME] | ENG | ENG | M | M | 3/4
4 | 58435 | 64487 | COX | [NAME] | GARRETT | [NAME] | ENG | ENG | M | M | 3/4
65+ WD (11)
No | Member ID 1 | Member ID 2 | Lastname 1 | Firstname 1 | Lastname 2 | Firstname 2 | Country 1 | Country 2 | Gender 1 | Gender 2 | Seed
1 | 52563 | 52562 | STEENBERG | Grethe | GARBRECHT | [NAME] | DEN | DEN | F | F | 1
2 | 52542 | 52545 | KNOTZSCH | Renate | GABRIEL | Renate | GER | GER | F | F | 2
65+ XD (23)
No | Member ID 1 | Member ID 2 | Lastname 1 | Firstname 1 | Lastname 2 | Firstname 2 | Country 1 | Country 2 | Gender 1 | Gender 2 | Seed
1 | 68519 | 92359 | BROTHERS | Ian | O’NEILL | [NAME] | ENG | ENG | M | F | 1
2 | 58470 | 68079 | TERASAKI | Yoshio | KATAITO | Yasuko | JPN | JPN | M | F | 2
3 | 52529 | 81075 | STERLIE | [NAME] | DANIELSEN | [NAME] | DEN | DEN | F | M | 3/4
4 | 72576 | 91967 | TANTUM | [NAME] | AWCOCK | [NAME] | ENG | ENG | M | F | 3/4
Spreadsheet: 488660d1478770318-formula-for-extracting-unique-list-from-different-sheets-ef
Sheet: Sheet3

Unsorted | Sorted
Spreadsheet: michelle_lokay__26570__imbalsumm0012
Sheet: GPM

 | 23995 |  | 22051
 | 59687 |  | 10703
Day | Measured | Scheduled | Measured | Scheduled
1 | 28264 | 25000 | 31781 | 23797
2 | 29161 | 25000 | 29371 | 24000
3 | 30146 | 25000 | 29555 | 24000
4 | 30908 | 25000 | 24416 | 24000
5 | 31508 | 28000 | 23106 | 24000
6 | 30317 | 25000 | 24595 | 24000
7 | 29575 | 30000 | 25649 | 24000
8 | 29617 | 30000 | 25060 | 25501
9 | 30362 | 30000 | 26626 | 27000
10 | 35274 | 30000 | 25597 | 27000
11 | 35915 | 30000 | 24828 | 27000
12 | 29963 | 30000 | 25769 | 27000
13 | 1184 | 5000 | 25774 | 27000
14 |  |  | 25865 | 26000
15 |  |  | 25976 | 26000
16 | 29610 | 30000 | 25974 | 24000
17 | 28821 | 30000 | 19551 | 24000
18 | 30239 | 30000 | 23507 | 24000
19 | 25557 | 25000 | 25532 | 24000
20 | 15 |  | 25092 | 24000
21 |  |  | 23790 | 24000
22 |  |  | 23862 | 24000
23 |  |  | 25747 | 24000
24 |  |  | 22211 | 24000
25 |  |  | 24878 | 24000
26
27
28
29
30
31
2000-11-30 00:00:00 | Balance
2000-12-25 00:00:00 | Balance
 | Contract #
 | 22864 |  |  |  | -58339.66
 | 20379 |  |  |  | -51695.87
 | 21459 |  |  |  | 10570.56
 | 26357 |  |  |  | 44144.84
 | 21544 |  |  |  | 61340.16
 | 24532 |  |  |  | 1048039.53
Spreadsheet: 812376d1673109507-formule-voor-extra-cel-resultaten
Sheet: resultaten

 | Poule | 1
 | Naam | car |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | set | car | % car
 |  |  |  |  |  |  |  |  | set pnt |  |  | car |  |  | set pnt |  |  | car |  |  | set pnt |  |  | car
1 | [NAME] | 11 |  |  |  |  |  |  | 1 | 0 | 0 | 11 | 8 | 10 | 1 | 1 |  | 11 | 11 |  | 1 | 1 |  | 11 | 11
 |  |  | set pnt |  |  | car |  |  |  |  |  |  |  |  | set pnt |  |  | car |  |  | set pnt |  |  | car
2 | [NAME] | 9
 |  |  | set pnt |  |  | car |  |  | set pnt |  |  | car |  |  |  |  |  |  |  |  | set pnt |  |  | car
3 | [NAME] | 7
 |  |  | set pnt |  |  | car |  |  | set pnt |  |  | car |  |  | set pnt |  |  | car
4 | Henri | 7
Spreadsheet: 844307d1696018599-when-a-cell-is-updated-need-the-amount-in-the-cell-to-populate-into-another-cell-ctest
Sheet: Sheet1

 | 5th | 6th | 7th | 8th | 9th | 10th | 11th | 12th | 13th | 14th | 15th | 16th
bonus 1 | 15000
bonus 2 |  |  |  | 20000 |  |  |  |  |  |  |  |  |  |  | 2000
bonus 3 |  | 11000
bonus 4 |  |  |  |  |  |  | 18000 |  |  |  |  |  |  |  | 18000
bonus 5 |  |  |  |  |  |  |  | 78000
bonus 6 |  |  |  |  | 60000
bonus 7
bonus 8
bonus 9 |  |  |  |  | all amounts start off as green
bonus 10 |  |  |  |  | when they go blue - they need to appear in the blue column
Spreadsheet: 129943d1321980988-excel-2007-conditional-formatting-help-compare-two-values-then-highlight-within-a-column-cf-query
Sheet: Sheet1

List A | List B | Outcome |  |  |  |  | List A | List B | Outcome
Apple | Apple | Need B to highlight red |  |  |  |  | Apple | Apple | Need B to highlight red | EXACT EXAMPLE!
Pears | Pears | Need B to highlight red |  |  |  |  | Pears | Pears | Need B to highlight red
Oranges | Oranges | Need B to highlight red |  |  |  |  | Oranges | Oranges | Need B to highlight red
Apples | Apples | Need B to highlight red |  |  |  |  | Apples | Apples | Need B to highlight red
Pears | Pears | Need B to highlight red |  |  |  |  | Pears | Pears | Need B to highlight red
Apples | Apple | Need B to highlight red |  |  |  |  | Apples | Apple | Need B to highlight red
Oranges | Pears | Need B to highlight Orange |  |  |  |  | Oranges | Pears | Need B to highlight Orange
Apples | Oranges | Need B to highlight Orange |  |  |  |  | Apples | Oranges | Need B to highlight Orange
Pears | Apples | Need B to highlight Orange |  |  |  |  | Pears | Apples | Need B to highlight Orange
Apples | Pears | Need B to highlight Orange |  |  |  |  | Apples | Pears | Need B to highlight Orange
Spreadsheet: 113819d1309696577-re-excel-2007-count-of-certain-letter-within-a-cells-text-string-udf-count_instances_of_a_word_in_string_-countword-
Sheet: Sheet1

word to count > | car
 | Not Case Sensitive | Case Sensitive
I have a toy car. The car is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 2 | 2
I have a toy Car. The car is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 2 | 1
I have a toy (car). The car is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 2 | 2
I have a toy CAR. The CAR is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 2 | 0
I HAVE A TOY CAR. THE CAR IS BLUE. IT CAME IN A CARDBOARD BOX. IT'S FROM THE CARTOON MOVIE CARS. | 2 | 0
i have a toy car. the car is blue. it came in a cardboard box. it's from the cartoon movie cars. | 2 | 2
I Have A Toy Car. The Car Is Blue. It Came In A Cardboard Box. It'S From The Cartoon Movie Cars. | 2 | 0
I have toy cars. The car9 is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 0 | 0
I have toy cars. The ([NAME] is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 1 | 1
I have toy cars. The car 9 is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 1 | 1
I have toy cars. The Car 9 is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 1 | 0
I have toy cars. 1 car, car 9, is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 2 | 2
I have toy cars. 1car, car 9, is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 1 | 1
I have a toy car. The "Car" is blue. It came in a cardboard box. It's from the cartoon movie Cars. | 2 | 1
car/Car/cars/Cars. | 2 | 1
CAR/CAR/CARS/CARS. | 2 | 0
car/car/cars/cars. | 2 | 2
Car/Car/Cars/Cars. | 2 | 0
I have a toy car. The "Car" is blue. It came in a cardboard box. The box has been scarred during storage. | 2 | 1
Looking for the letter "a" | a
this text contains no single character but it does have the relevant letter. | 0 | 0
this text contains a single instance of the relevant letter. | 1 | 1
this text contains A single instance of the relevant letter, but it is not the correct case. | 1 | 0
Spreadsheet: 44666d1243439570-pulling-information-from-one-spreadsheet-to-another-excelprob2
Sheet: Unique

Ingredient_Name | Count | RONE | RTWO | RTHREE | RFOUR | RFIVE | RSIX | RSEVEN | REIGHT
Basil | 8 | 159 | 219 | 204 | 144 | 129 | 189 | 174 | 114 | <-- example
Beef
Bell Pepper
[NAME]
Chicken
Coconut Milk
Eggs
Fish
[NAME]
[NAME]
Mint
Onion
Pork
Spinach
[NAME]
Spreadsheet: 672524d1586896784-using-the-countif-function-to-count-items-in-a-drop-down-list-countif-example
Sheet: Action Items

 |  | CountIF | [NAME] and ASSIGNED anytime in January 2020 and is Rank 1. Full criteria needed before results can be returned
 |  |  | Answer ->
 | ACTION ITEM | RANK | PRIORITY | OWNER | ASSIGNED | DUE | Deadline | DONE | STATUS | NOTES
 | Task 1 | 1 | HIGH | [NAME] | 2020-01-02 00:00:00 | 2020-01-06 00:00:00 | Missed | √ | 1
 | Task 2 | 1 | HIGH | [NAME] | 2020-01-13 00:00:00 | 2020-01-14 00:00:00 | Missed | √ | 1
 | Task 3 | 3 | MEDIUM | Sue | 2020-01-14 00:00:00 | 2020-01-15 00:00:00 | Missed
 | Task 4 | 3 | MEDIUM | [NAME] | 2020-02-15 00:00:00 | 2020-02-22 00:00:00 | Missed
 | Task 5 | 3 | MEDIUM | [NAME] | 2020-01-16 00:00:00 | 2020-01-17 00:00:00 | Met | √ | 1
 | Task 6 | 1 | HIGH | [NAME] | 2020-03-15 00:00:00 | 2020-03-17 00:00:00 | Met | √ | 1
 | Task 7 | 3 | MEDIUM | [NAME] | 2020-03-19 00:00:00 | 2020-03-21 00:00:00 | Missed | √ | 1
 | Task 8 | 1 | HIGH | Dill | 2020-03-17 00:00:00 | 2020-04-22 00:00:00 | In progress |  | 0.75
Spreadsheet: 694968d1599924370-determination-of-service-degradation-determine-service-degradation
Sheet: Sheet1

Service Id | Train Id | Status Desc | [NAME] | Headway | Duration of Service degradation when headway > 2 mins ( Excel Formula) | Duration of Service degradation when headway>2 mins (Manual) | Remarks
3687 | 1370 | [NAME] | 08:01:02 | 00:00:00
3609 | 1291 | [NAME] | 08:02:54
3529 | 1242 | [NAME] | 08:07:14 |  |  |  | Service Degradation starts.
3215 | 1147 | [NAME] | 08:09:29
3520 | 1231 | [NAME] | 08:11:46
3621 | 1304 | [NAME] | 08:16:02
3509 | 1221 | [NAME] | 08:18:30
3655 | 1338 | [NAME] | 08:20:32
3542 | 1254 | [NAME] | 08:23:00
3020 | 1019 | [NAME] | 08:24:58 |  |  |  | Service degradation ends Duration of Service Degradation = 08:14:58 -08:07:14 = 17mins 44 seconds
3525 | 1237 | [NAME] | 08:27:25 |  |  |  | Start of Service Degradation
3686 | 1367 | [NAME] | 08:29:26
3714 | 1389 | [NAME] | 08:31:36
3618 | 1300 | [NAME] | 08:33:45
3711 | 1388 | [NAME] | 08:35:57
3544 | 1255 | [NAME] | 08:38:08
3607 | 1290 | [NAME] | 08:42:26
3707 | 1383 | [NAME] | 08:44:20 |  |  |  | End of Service degradation Duration of Service Degradation = 08:44:20 -08:27:25 = 17mins 44 seconds
3557 | 1270 | [NAME] | 08:46:31 |  |  |  | Start of Service Degradation
3723 | 1399 | [NAME] | 08:48:55
3555 | 1268 | [NAME] | 08:53:17
3008 | 1008 | [NAME] | 08:55:27
3623 | 1306 | [NAME] | 08:57:49
3055 | 1055 | [NAME] | 08:59:54
3501 | 1214 | [NAME] | 09:02:12
3702 | 1377 | [NAME] | 09:04:08 |  |  |  | End of Service degradation Duration of Service Degradation = 09:04:48 -08:46:31 = 18mins 17 seconds
3718 | 1393 | [NAME] | 09:08:09 |  |  |  | Service Degradation starts.
3048 | 1048 | [NAME] | 09:10:09
3613 | 1296 | [NAME] | 09:12:15
3545 | 1257 | [NAME] | 09:14:23
3664 | 1345 | [NAME] | 09:16:15 |  |  |  | Service degradation ends Duration of Service Degradation = 09:16:15 -09:08:09= 8mins 06 seconds
3639 | 1322 | [NAME] | 09:18:13 |  |  | 00:00:00
3658 | 1339 | [NAME] | 09:20:14 |  |  |  | Start of Service Degradation
3615 | 1298 | [NAME] | 09:24:09
3560 | 1271 | [NAME] | 09:28:18 |  |  |  | Service degradation ends Duration of Service Degradation = 09:16:15 -09:08:09= 8mins 04seconds
3551 | 1263 | [NAME] | 09:30:16
3720 | 1396 | [NAME] | 09:32:04
3709 | 1386 | [NAME] | 09:35:56 |  |  |  | Service Degradation Starts
3633 | 1315 | [NAME] | 09:37:48 |  |  |  | Service Degradation Ends Duration of Service Degradation = 09:37:48 - 09:35:56 = 1mins 52 seconds
3569 | 1282 | [NAME] | 09:41:17 |  |  |  | Service Degradation Starts
3627 | 1309 | [NAME] | 09:45:23
3601 | 1283 | [NAME] | 09:47:23
3548 | 1259 | [NAME] | 09:49:35 |  |  |  | Service Degradation Ends Duration of Service Degradation = 09:49:35 - 09:41:17 = 8mins 18 seconds
3521 | 1233 | [NAME] | 09:51:22 |  |  |  | Service Degradation Ends Duration of Service Degradation = 09:51:22 - 09:41:17 = 10mins 05 seconds
3649 | 1332 | [NAME] | 09:53:24 |  |  |  | Service Degradation Starts
3553 | 1266 | [NAME] | 09:55:22 |  |  |  | Service Degradation Ends Duration of Service Degradtion: = 09:55:22 - 09:53:24 = 1min 58 seconds
3637 | 1320 | [NAME] | 09:57:13
3513 | 1226 | [NAME] | 09:59:12