tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 777764d1650599704-sumproduct-for-qtrly-data-test
Sheet: Data

 | Target | Actual | Actual | Actual | Actual | Actual | Actual | Actual | Actual | Actual | Actual | Actual | Actual
 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 |  |  |  |  | Select month | 8 | Month in Qtr | 3
 |  | 4 | 4 | 4 | 3 | 3 | 3 | 2 | 2 | 2 | 1 | 1 | 1 |  |  |  |  | Whats the qtr | 4 | Month in Year | 12
KPI # | Target | 2022-03-01 00:00:00 | 2022-02-01 00:00:00 | 2022-01-01 00:00:00 | 2021-12-01 00:00:00 | 2021-11-01 00:00:00 | 2021-10-01 00:00:00 | 2021-09-01 00:00:00 | 2021-08-01 00:00:00 | 2021-07-01 00:00:00 | 2021-06-01 00:00:00 | 2021-05-01 00:00:00 | 2021-04-01 00:00:00 |  |  |  |  | Target Col | 7
1a | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
2 | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |  |  |  | Monthly cal | # of KPI
3a | 0.98 | 0.97 | 1 | 1 | 0.9856115107913669 | 0.9976649153531816 | 1 | 1 | 0.9960063897763578 | 0.999219968798752 | 1 | 1 | 1 |  |  |  | Monthly cal | Achieved
4a | 0.99 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
4b | 0.985 | 0.9981 | 0.9969 | 0.9968 | 0.9989642672190575 | 0.9994172494172494 | 0.9984472049689441 | 1 | 0.9990892531876139 | 0.9981710105166895 | 0.9989310529128808 | 0.9988864142538976 | 0.9982030548068284
5a | 0.98 | 0.983 | 0.9822 | 0.9739 | 0.9831154684095861 | 0.9899777282850779 | 0.9891219891219891 | 0.9932126696832579 | 0.9840396257567419 | 0.9872241579558653 | 1 | 0.9901685393258427 | 0.9919163100332857 |  |  |  | qtrly cal | # of KPI |  | not very elegant but cant seem to count with array over several columns?
6 | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.9982030548068284 |  |  |  | qtrly cal | Achieved |  | ???
7 | 0.98 | 0.9943 | 0.9903 | 0.9933 | 0.9972766884531591 | 0.9944444444444445 | 0.9953416149068323 | 0.996629213483146 | 0.9968123861566485 | 0.997624703087886 | 0.9978621058257616 | 0.9927868852459016 | 0.9927868852459016
1a | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
2 | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |  |  |  | YTD | # of KPI |  | not very elegant but cant seem to count with array over several columns?
3a | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |  |  |  | YTD | Achieved |  | ???
4a | 0.99 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
4b | 0.985 | 1 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 0.99 | 1 | 0.99 | 1 | 1 | 1
5a | 0.98 | 0.995 | 1 | 1 | 0.9924242424242424 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
7 | 0.98 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.9937888198757764 | 0.9937888198757764
1a | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.5789473684210527 | 0.9666666666666667 | 1 | 1 | 1 | 1
Spreadsheet: 175388d1345508590-sort-data-into-specific-domain-range-brackets-ef165_demonstration
Sheet: Sheet2

Before
Raw Data |  |  |  |  |  | 1 | (1:5):(1:5) |  | 2 | (6:10):(1:5) |  | 3 | (1:5):(6:10) |  | 4 | (6:10):(6:10)
Qx | Qy |  | [NAME] | seq |  | Qx | Qy |  | Qx | Qy |  | Qx | Qy |  | Qx | Qy
1 | 10
1 | 9
1 | 8
1 | 7
1 | 6
1 | 5
1 | 4
1 | 3
1 | 2
1 | 1
2 | 10
2 | 9
2 | 8
2 | 7
2 | 6
2 | 5
2 | 4
2 | 3
2 | 2
2 | 1
3 | 10
3 | 9
3 | 8
3 | 7
3 | 6
3 | 5
3 | 4
3 | 3
3 | 2
3 | 1
4 | 10
4 | 9
4 | 8
4 | 7
4 | 6
4 | 5
4 | 4
4 | 3
4 | 2
4 | 1
5 | 10
5 | 9
5 | 8
5 | 7
5 | 6
5 | 5
5 | 4
5 | 3
5 | 2
5 | 1
6 | 10
6 | 9
6 | 8
6 | 7
6 | 6
6 | 5
6 | 4
6 | 3
6 | 2
6 | 1
7 | 10
7 | 9
7 | 8
7 | 7
7 | 6
7 | 5
7 | 4
7 | 3
7 | 2
7 | 1
8 | 10
8 | 9
8 | 8
8 | 7
8 | 6
8 | 5
8 | 4
8 | 3
8 | 2
8 | 1
9 | 10
9 | 9
9 | 8
9 | 7
9 | 6
9 | 5
9 | 4
9 | 3
9 | 2
9 | 1
10 | 10
10 | 9
10 | 8
10 | 7
10 | 6
10 | 5
10 | 4
10 | 3
10 | 2
10 | 1
Spreadsheet: 154173d1336274359-more-than-one-countif-jrios_sample_05may12_01
Sheet: Master

DSI North Operations Log
Opener |  |  |  |  |  |  |  | Day of the Week |  | Monday
Closer |  |  |  |  |  |  |  | Date
Routes |  | Driver |  | Assistant |  | Stops / Pieces | Door | Carpet | Phone | Area
Zip Codes
98001 | 98001 | 98002 | 98002 | 98002 | 98002 | 98002 | 98003
Spreadsheet: 888759d1739334283-dates-book1
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  | Won/Loss | Date from Quote to Sale | Date from Quote from Loss
Quote Date | Quote Number | Customer |  | Contact | Equipment / Part Description | Site Visit Yes/No |  | Awarded to CWMF Yes/No | Order / Decline Date
2025-01-23 00:00:00 | 7095 | ABC6 |  | [NAME] | chain | YES |  | YES | 2025-02-06 00:00:00 | 1
2025-01-01 00:00:00 | 7096 | BCA2 |  | [NAME] doe | bearing | NO |  | No | 2025-01-29 00:00:00
2025-01-25 00:00:00 | 7097 | ABC7 |  | [NAME] | screw | YES |  | Yes | 2025-02-08 00:00:00 | 1
2025-02-15 00:00:00 | 7098 | BCA3 |  | [NAME] | bearing | NO |  | No | 2025-02-18 00:00:00
Spreadsheet: 752732d1634914301-count-range-if-specific-cell-contains-specific-text-example-spreadsheet
Sheet: Sheet1

Date | long string of text [Company1]
1st May | aehra [Company 1]
2nd May | iavabv[Company 2]
3rd May | cfukfy [Company 1]
4th May | fmyrr [Company 1]
5th May | cmtyy [Company 1]
6th May | nfsrty [Company 2]
7th May | psjhg [Company 2]
8th May | zutyn [Company 2]
9th May | putyna [Company 1]
10th May | wueyn [Company 1]
 | 5
The total is five because cell B1 contains the word "company 1" and then the word [company 1] appears five times in the range B2 - B11
Spreadsheet: 1c238db8-173c-498c-9563-f4eb6bbf25d2
Sheet: 8c

Product1 | 0-34 | 3-6 | 6-12 | 12-24 | 24-60 | 60-120 | 120-360 | 360+ | TOTAL
Basis | 9 | 10 | 26 | 42 | 50 | 93 | 79 | 5 | 314
Cap/Floor | 1 | 0 | 23 | 30 | 69 | 37 | 9 | 0 | 169
Debt Option | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Exotic | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Fixed-Fixed | 1 | 1 | 0 | 0 | 2 | 3 | 1 | 0 | 8
Fixed-Float | 139 | 82 | 3335 | 1639 | 5406 | 11966 | 7766 | 3751 | 34082
FRA | 132 | 568 | 1003 | 905 | 5 | 0 | 0 | 0 | 2613
Inflation | 8 | 1 | 12 | 16 | 28 | 20 | 51 | 2 | 138
OIS | 161 | 46 | 109 | 82 | 194 | 116 | 25 | 0 | 733
Swaption | 0 | 0 | 0 | 53 | 238 | 295 | 564 | 146 | 1296
TOTAL
Spreadsheet: 46727d1245672410-replacing-text-according-to-a-table-b1
Sheet: Sheet1

 | ID
 | 1C
 | 1C |  |  |  |  | replace  this number with this text
 | 1C
 | 1C |  |  |  |  | 1 | disk
 | 1C |  |  |  |  | 2 | box
 | 1C |  |  |  |  | 3 | cpu
 | 1C |  |  |  |  | 4 | card
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 1A
 | 1C
 | 15
 | 15
 | 15
 | 1C
 | 1C
 | 02
 | 02
 | 02
 | 1C
 | 1A
 | 1A
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 1C
 | 06
 | 1C
 | 1C
 | 1C
 | 06
 | 06
 | 1C
 | 13
 | 04
 | 04
 | 03
 | 15
 | 06
 | 06
 | 06
 | 06
 | 09
 | 09
 | 06
 | 06
 | 16
 | 12
 | 09
 | 04
 | 03
 | 03
 | 03
 | 03
 | 03
 | 01
 | 01
 | 01
 | 01
 | 03
 | 01
 | 03
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 06
 | 13
Spreadsheet: 275493d1383549530-how-to-vlookup-with-multiple-criteria-vlookup
Sheet: Sheet1

Order ID #(DUPLICATE) | Order Amount | UNIQUE OrderID SUBTOTAL | Order amount < $50,000 | Order Amount between $10,000 & $50,000
235611 | 1625
240425 | 11572.72
242686 | 4290
242686 | 12285
242686 | 14742
242686 | 5733
242686 | 257.4
242686 | 384.8
242686 | 6054.75
242686 | 6054.75
242686 | 8073
242686 | 11466
242709 | 35400
242709 | 5400
242894 | 228
244543 | 6531.47
244543 | 6116.86
244563 | 13062.94
Spreadsheet: 732343d1620902071-highest-and-lowest-value-in-an-ever-changing-number-of-rows-spx500usd-60_data_ex
Sheet: Blatt 1 - OANDA_SPX500USD, 60

time | SIDE | high +0,3 | [NAME] | close | H/L | RSI
2019-01-03T09:00:00Z |  | 2478.3 | 2468.5 | 2469.4 |  | 39.038838576197
2019-01-03T10:00:00Z |  | 2472.9 | 2465.5 | 2468 |  | 38.6184034187126
2019-01-03T11:00:00Z |  | 2473.9 | 2464.5 | 2470.4 |  | 39.7856817281039
2019-01-03T12:00:00Z |  | 2479.7 | 2469.5 | 2479.2 |  | 43.8934904790084
2019-01-03T13:00:00Z |  | 2489.7 | 2477.5 | 2487.4 |  | 47.4041021667817
2019-01-03T14:00:00Z |  | 2492.3 | 2473.7 | 2478.4 |  | 44.2157622561343
2019-01-03T15:00:00Z |  | 2478.7 | 2445.9 | 2459.4 |  | 38.4789309629954
2019-01-03T16:00:00Z |  | 2488.3 | 2455.9 | 2477.2 |  | 45.4421194759444
2019-01-03T17:00:00Z |  | 2479.7 | 2466.1 | 2476.2 |  | 45.1407340873466
2019-01-03T18:00:00Z |  | 2476.7 | 2453.3 | 2457.6 |  | 51.0939004871753
2019-01-03T19:00:00Z |  | 2472.7 | 2450.7 | 2454.6 |  | 58.8936335882237
2019-01-03T20:00:00Z |  | 2460.5 | 2441.9 | 2447 |  | 64.5866705832953
2019-01-03T21:00:00Z |  | 2453.9 | 2445.1 | 2450.2 |  | 65.0629715423514
2019-01-03T23:00:00Z |  | 2454.9 | 2446.7 | 2448.4 |  | 38.1504420121559
2019-01-04T00:00:00Z |  | 2450.5 | 2436.9 | 2440.6 |  | 36.1470673244036
2019-01-04T01:00:00Z |  | 2451.7 | 2439.5 | 2447.6 |  | 39.1577211165131
2019-01-04T02:00:00Z |  | 2454.7 | 2443.9 | 2454.2 |  | 41.8710810590937
Spreadsheet: 675210d1588194361-conditional-formatting-stock-levels-conditional
Sheet: analysis

Process | Reference | Stock | Planned | 2020-07-01 00:00:00 | 2020-07-02 00:00:00 | 2020-07-03 00:00:00 | 2020-07-04 00:00:00 | 2020-07-05 00:00:00 | 2020-07-06 00:00:00 | 2020-07-07 00:00:00 | 2020-07-08 00:00:00 | 2020-07-09 00:00:00 | 2020-07-10 00:00:00 | 2020-07-11 00:00:00 | 2020-07-12 00:00:00 | 2020-07-13 00:00:00 | 2020-07-14 00:00:00
P 1 | REF 1 | 5000 | 2000 | 1000 | 500 | 500 | 750 | 800 | 650 | 540 | 1000 | 1000 | 141 | 306 | 0 | 934 | 430
P 2 | REF 2 | 0 | 1500 | 500 | 500 | 500 | 450 | 600 | 800 | 87 | 956 | 402 | 556 | 73 | 0 | 573 | 371
 |  |  |  | REF 1: L2 (1.000) and [NAME] (1.000) are red, but blue should be because the planned (D2) is 2,000.
 |  |  |  | REF 2: Stock (C3) 0 for this the red color between E and R, but planned (D3) 1,500 for this I want E2, F2 and G2 to be blue, others will remain red
Spreadsheet: 265489d1379296164-referencing-a-table-to-another-sheet-based-on-a-specific-table-value-test_workbook
Sheet: Qlt_data_single_SCVs

One_or_many | Name | MRN | Accesssion | Date_culture | Culture_# | Spirometry | FEV1 | FEV1% | FVC | FVC% | Discharge_other | FEV1 | FEV1% | FVC | FVC% | Wt_kg | Wt_percentile | BMI | #_CFPE 3 months prior to SCVs | #_CFPE 3 months after to SCVs | [NAME] | Time_between_CFPE | Abx_before_CFPE | Abx_during_CFPE | Abx_after_CFPE | Abx_change_hx | Abx_changes_in admission | ID consult? | [NAME] | ICU stay | Intubated | Chest_tube | G-tube | New_pathogen | New_resistance | Comments
Spreadsheet: 218917d1362606337-race-points-formula-race-points
Sheet: Sheet1

 | RACE 1 |  |  | RACE 2 |  |  | RACE 3 |  |  | RACE 4 |  |  | RACE 5 |  |  | RACE 6 |  |  | RACE 7 |  |  | RACE | DROP | SEASON
Racer | Q | E | S | Q | E | S | Q | E | S | Q | E | S | Q | E | S | Q | E | S | Q | E | S | BONUS | RACES | TOTAL
1 | 100 | 400 | 50 | 150 | 300 | 100 | 150 | 300 | 50 | 150 | 400 | 50 | 150 | 100 | 50 | 100 |  | 50 |  |  |  |  |  | 2500
2 | 0 | 0 | 0 | 75 | 400 | 50 | 0 | 0 | 0 | 100 | 300 | 50 | 75 | 300 | 50 | 150 |  | 50 |  |  |  |  |  | 1600
3 | 50 | 100 | 50 | 40 | 100 | 50 | 100 | 200 | 50 | 40 | 100 | 50 | 50 | 100 | 50 | 75 | 100 | 50 |  |  |  |  |  | 1165
4 | 150 | 300 | 100 | 100 | 200 | 50 | 0 | 0 | 0 | 35 | 100 | 50 | 0 | 0 | 0 | 0 | 0 | 0 |  |  |  |  |  | 1085
5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 75 | 200 | 50 | 100 | 200 | 50 | 50 | 100 | 50 |  |  |  |  |  | 875
6 | 40 | 100 | 50 | 35 | 100 | 50 | 75 | 100 | 50 | 30 | 100 | 50 | 0 | 0 | 0 | 0 | 0 | 0 |  |  |  |  |  | 780
7 | 0 | 0 | 0 | 50 | 100 | 50 | 0 | 0 | 0 | 50 | 200 | 50 | 0 | 0 | 0 | 0 | 0 | 0 |  |  |  |  |  | 500
8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 | 200 | 50 |  |  |  |  |  | 290
Spreadsheet: 805036d1668500948-replacing-value-with-a-blank-in-a-formula-excel-query
Sheet: MngntShift

[NAME] for the Period:  October 2022 |  |  |  |  |  | 07:00:00 | 16:00:00
Date | Employee
 | Time In | Time Out | Hours
2022-10-01 00:00:00
2022-10-02 00:00:00
2022-10-03 00:00:00
2022-10-04 00:00:00
2022-10-05 00:00:00
2022-10-06 00:00:00
2022-10-07 00:00:00
2022-10-08 00:00:00
2022-10-09 00:00:00
2022-10-10 00:00:00
2022-10-11 00:00:00
2022-10-12 00:00:00
2022-10-13 00:00:00
2022-10-14 00:00:00
2022-10-15 00:00:00
2022-10-16 00:00:00
2022-10-17 00:00:00
2022-10-18 00:00:00
2022-10-19 00:00:00
2022-10-20 00:00:00
2022-10-21 00:00:00
2022-10-22 00:00:00
2022-10-23 00:00:00
2022-10-24 00:00:00
2022-10-25 00:00:00
2022-10-26 00:00:00
2022-10-27 00:00:00
2022-10-28 00:00:00
2022-10-29 00:00:00
2022-10-30 00:00:00
2022-10-31 00:00:00
Spreadsheet: 852943d1702919666-solved-validate-month-based-on-contract-dates-and-calculate-correct-number-of-weeks-on-date-issue-new
Sheet: Sheet1

Name | Start contract | End contract | Contract weeks | Hours a week |  | begin month | end month | Months |  | 2024-01-01 00:00:00 | 2024-02-01 00:00:00 | 2024-03-01 00:00:00 | 2024-04-01 00:00:00 | 2024-05-01 00:00:00 | 2024-06-01 00:00:00 | 2024-07-01 00:00:00 | 2024-08-01 00:00:00 | 2024-09-01 00:00:00 | 2024-10-01 00:00:00 | 2024-11-01 00:00:00 | 2024-12-01 00:00:00
Piet | 2024-01-01 00:00:00 | 2024-04-15 00:00:00 |  | 30
Kees | 2024-01-15 00:00:00 | 2024-03-04 00:00:00 |  | 20
Jan | 2024-10-08 00:00:00 | 2024-12-31 00:00:00 |  | 25
Spreadsheet: 4542e1db-51d0-460f-b6a2-9f68f617afe4
Sheet: Sheet1

Test Referenced | Entry Type | Mayo ID | Description | Reporting Description | Method | Collection Container | Temperature | Stability | [NAME] | Unit of Measure | [NAME] | Minimum Volume | Reject Due To | Reference Values | Days/Times Performed | Analytic Time | Maximum Lab Time | CPT Units | CPT Code | LOINC® Code | LOINC® Attributes | Always Performed | Orderable Separately | Performing Location
FGORG | Test | FGORG | Turkey IgG | Turkey IgG | Enzyme Immunoassay (FEIA) | Plain, Red-Top Tube: Red |  |  | 0.5 | mL | Draw blood in a plain red-top tube(s), serum gel tube(s) is acceptable. Spin down and send 0.5 mL of serum refrigerated in a plastic vial. | 0.5 mL | Hemolysis	NA Thawing	Warm OK; Cold OK Lipemia	NA Icterus	NA Other	NA | <2 mcg/mL   The reference range listed on the report is the lower limit of quantitation for the assay. The clinical utility of food-specific IgG tests has not been established. These tests can be used in special clinical situations to select foods for evaluation by diet elimination and challenge in patients who have food-related complaints. It should be recognized that the presence of food-specific IgG alone cannot be taken as evidence of food allergy and only indicates immunologic sensitization by the food allergen in question. This test should only be ordered by physicians who recognize the limitations of the test.    Test Performed by: Viracor-IBT Laboratories                              1001 NW Technology Dr.                              Lee's Summit, MO 64086 | Monday through Friday | 3 days | 5 - 7 days | 1 | 86001 |  |  |  |  | Viracor-IBT Laboratories
FGORG | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 28 days
FGORG | Result | FGORG | Turkey IgG | Turkey IgG | Alphanumeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | In Process
Spreadsheet: 85772d1285804626-inputting-data-filldown
Sheet: Sheet2

Ex1 | 0 | 9
Ex1 | 10 | 19
Ex1 | 20 | 29
Ex1 | 30 | 39
Ex1 | 40 | 49
Ex1 | 50 | 59
Ex1 | 60 | 69
Ex1 | 70 | 79
Ex1 | 80 | 89
Ex1 | 90 | 99
Ex2 | 0 | 9 | formulas here then drag down
Ex2 | 10 | 19
Ex2 | 20 | 29
Ex2 | 30 | 39
Ex2 | 40 | 49
Ex2 | 50 | 59
Ex2 | 60 | 69
Ex2 | 70 | 79
Ex2 | 80 | 89
Ex2 | 90 | 99
Ex3 | 0 | 9
Ex3 | 10 | 19
Ex3 | 20 | 29
Ex3 | 30 | 39
Ex3 | 40 | 49
Ex3 | 50 | 59
Ex3 | 60 | 69
Ex3 | 70 | 79
Ex3 | 80 | 89
Ex3 | 90 | 99
Ex4 | 0 | 9
Ex4 | 10 | 19
Ex4 | 20 | 29
Ex4 | 30 | 39
Ex4 | 40 | 49
Ex4 | 50 | 59
Ex4 | 60 | 69
Ex4 | 70 | 79
Ex4 | 80 | 89
Ex4 | 90 | 99
Ex5 | 0 | 9
Ex5 | 10 | 19
Ex5 | 20 | 29
Ex5 | 30 | 39
Ex5 | 40 | 49
Ex5 | 50 | 59
Ex5 | 60 | 69
Ex5 | 70 | 79
Ex5 | 80 | 89
Ex5 | 90 | 99
Ex6 | 0 | 9
Ex6 | 10 | 19
Ex6 | 20 | 29
Ex6 | 30 | 39
Ex6 | 40 | 49
Ex6 | 50 | 59
Ex6 | 60 | 69
Ex6 | 70 | 79
Ex6 | 80 | 89
Ex6 | 90 | 99
Ex7 | 0 | 9
Ex7 | 10 | 19
Ex7 | 20 | 29
Ex7 | 30 | 39
Ex7 | 40 | 49
Ex7 | 50 | 59
Ex7 | 60 | 69
Ex7 | 70 | 79
Ex7 | 80 | 89
Ex7 | 90 | 99
Ex8 | 0 | 9
Ex8 | 10 | 19
Ex8 | 20 | 29
Ex8 | 30 | 39
Ex8 | 40 | 49
Ex8 | 50 | 59
Ex8 | 60 | 69
Ex8 | 70 | 79
Ex8 | 80 | 89
Ex8 | 90 | 99
Ex9 | 0 | 9
Ex9 | 10 | 19
Ex9 | 20 | 29
Ex9 | 30 | 39
Ex9 | 40 | 49
Ex9 | 50 | 59
Ex9 | 60 | 69
Ex9 | 70 | 79
Ex9 | 80 | 89
Ex9 | 90 | 99
Ex10 | 0 | 9
Ex10 | 10 | 19
Ex10 | 20 | 29
Ex10 | 30 | 39
Ex10 | 40 | 49
Ex10 | 50 | 59
Ex10 | 60 | 69
Ex10 | 70 | 79
Ex10 | 80 | 89
Ex10 | 90 | 99
Ex11 | 0 | 9
Ex11 | 10 | 19
Ex11 | 20 | 29
Ex11 | 30 | 39
Ex11 | 40 | 49
Ex11 | 50 | 59
Ex11 | 60 | 69
Ex11 | 70 | 79
Ex11 | 80 | 89
Ex11 | 90 | 99
Ex12 | 0 | 9
Ex12 | 10 | 19
Ex12 | 20 | 29
Ex12 | 30 | 39
Ex12 | 40 | 49
Spreadsheet: 221457d1363560864-assign-blank-cell-when-formula-value-totals-zero-formula
Sheet: Sheet1

C | D
 |  | CD
C
C
 | D
C
C | D
C
Spreadsheet: darrell_schoolcraft__7319__imball0202
Sheet: SidR

 | [NAME]
 | POI 1190 - Keystone Plant Outlet
Day | Measured | Scheduled
1 | 46181 | 46125
2 | 45310 | 45501
3 | 45365 | 45393
4 | 45289 | 45501
5 | 29956 | 32422
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
2002-01-31 00:00:00 |  |  | 4386
2002-02-05 00:00:00
CBS Volume
 |  |  | 1925
Spreadsheet: 862782d1710407351-formula-to-show-two-months-in-one-cell-weeklyschedule
Sheet: Schedule

 |  |  |  | Week: | 2024-03-17 00:00:00
 |  | Mar | 2024
 |  |  | SHIFT | RDO
 |  | This line should remain blank and hidden
 |  | GRAVE/MIDS | MIN-3
 |  |  |  | S/S | X |  |  |  |  |  | X
 |  | JOY |  | S/M | X | VAC | VAC | VAC | VAC | VAC | VAC
 |  | [NAME] |  | T/W | T | T | X | X | T | T | H
 |  | KAVIKA |  | W/T | T | T | H | X | X | H | T
 |  | RICHARD |  | T/F | H | H | T | T | OT-H | OT-T | T
 |  | [NAME] T - LEAD |  | F/S | FMLA | FMLA | FMLA | FMLA | FMLA | X | X
 |  | O.T. |  |  |  |  | T | T | T
 |  | O.T. |  |  |  |  |  | H
 |  |  |  |  | H - HANGAR |  |  |  | T - TERM
 |  |  |  |  | JURY |  |  |  | HO - HOLIDAY OFF
 |  |  |  |  | CB - COMPANY BUSINESS |  |  |  | ANP
 |  |  |  |  | TVL - TRAVEL |  |  |  | TDW -T TERM TRADE DAY WORKING
 |  |  |  |  | TDY - TEMPORARY DUTY |  |  |  | TDO - TRADE DAY OFF
 |  |  |  |  | [NAME] TRAINING |  |  |  | VAC
 |  |  |  |  | HOLT - HOLIDAY TAKEN |  |  |  | DAT
 |  |  |  |  | T/T @ TERM |  |  |  | SK - SICK
 |  |  |  |  | OT-T |  |  |  | OT-H
 |  |  |  |  | FMLA |  |  |  | TDW-H - HGR TRADE DAY WORKING
Spreadsheet: 867381d1714204677-help-on-lookup-to-pull-most-recent-value-based-on-most-recent-date-for-larger-dataset-sample_workbook1-etaf-1
Sheet: calculations

 | Against smaller dataset, formula works
 | cust_id | change_datetime_phone1 | street1
 | 111
 | Against larger dataset, I am getting an error
 | cust_id | change_datetime_phone1 | street1
 | 111 |  | 1154 |  |  |  |  |  | 2024-04-25 21:37:11
 | 112 |  | 1238
 | 113 |  | 1322
 | 114 |  | 1406 |  |  | ????
 | 115 |  | 1490
 | 116
 | 117
 | 118
Spreadsheet: 54734d1254798676-detect-duplicate-number-in-a-column-duplicate
Sheet: Sheet1

SEQUENCE NUMBER | REMARKS
10
20
30
40
50 | DUPLICATE
60
70
80
90
100
110
120
130
140
150
160
170 | DUPLICATE
180
190
200
210
220
230
50 | DUPLICATE
170 | DUPLICATE
Spreadsheet: 135887d1326293373-sumif-and-with-a-filter-excel-upload-paste-into-pivot-table
Sheet: Changed Front Sheet

 | test 40 Expenses
 |  | £
 |  | 0
 | Media Research | 233.1
 | [NAME] | 0
 | Travel | 50.88
 | Conference Call | 0
 | Entertainment | 93.03999999999999
 | Accommodation | 0
 | Share Price Listing The Independent | 0
 | Licensing Fee | 0
 | Subsistence | 0
 | Miscellaneous* | 0
 | Grand Total | 377.02
 | Grand Total | 377.02
 | *Webcast Event | 7364
Spreadsheet: 726335d1617174776-conditional-sum-formula
Sheet: Sheet1

 | a | b | *c
 | 1 | 10
 | 0 | 9 | 0
 | 0 | 8 | 0
 | 0 | 7 | 0
 | 1 | 5
 | 0 | 2 | 0
 | 0 | 1 | 0
 | 1 | 8
 | 0 | 9 | 0
 | 0 | 0 | 0
 | 0 | 5 | 0
 | 0 | 5 | 0
Spreadsheet: abdbe197-9867-4999-bf80-1f1edad55d46
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
42993951 | 2014-09-02 21:56:23 | AXIS | 1 | 7 | 4 | 122523 | [NAME] | 7597 | eastern | 1941-10-18 | 1941-10-18 | Gates of Moscow | Aux portes [NAME]
42994183 | 2014-09-02 22:25:37 | ALLIES | 1 | 7 | 4 | 122523 | [NAME] | 7597 | eastern | 1941-10-18 | 1941-10-18 | Gates of Moscow | Aux portes [NAME]
43007023 | 2014-09-03 22:16:48 | ALLIES | 0 | 7 | 10 | 709316 | sbchurchill | 7662 | eastern | 1942-10-22 | 1942-10-22 | Red Barricades Factory | Les Barricades Rouges
43008097 | 2014-09-03 23:03:24 | AXIS | 1 | 10 | 5 | 709316 | sbchurchill | 7662 | eastern | 1942-10-22 | 1942-10-22 | Red Barricades Factory | Les Barricades Rouges
43046297 | 2014-09-06 18:43:39 | AXIS | 1 | 6 | 3 | 1305673 | gnomedude | 6152 | western | 1944-12-20 | 1944-12-22 | [NAME] | St. Vith
43046528 | 2014-09-06 19:15:42 | ALLIES | 0 | 5 | 6 | 1305673 | gnomedude | 6152 | western | 1944-12-20 | 1944-12-22 | [NAME] | St. Vith
43144277 | 2014-09-13 20:00:09 | ALLIES | 1 | 6 | 4 | 1115749 | EODboy | 6749 | western | 1944-06-06 | 1944-06-06 | [NAME] | [NAME]
43144505 | 2014-09-13 20:20:17 | AXIS | 1 | 6 | 2 | 1115749 | EODboy | 6749 | western | 1944-06-06 | 1944-06-06 | [NAME] | [NAME]
43176316 | 2014-09-15 23:24:20 | AXIS | 1 | 7 | 6 | 377160 | docsteve | 7594 | eastern | 1943-07-05 | 1943-07-09 | Ponyri | Ponyri
43176696 | 2014-09-15 23:46:37 | ALLIES | 1 | 7 | 1 | 377160 | docsteve | 7594 | eastern | 1943-07-05 | 1943-07-09 | Ponyri | Ponyri
Spreadsheet: 878910d1726239677-formula-algorithm-to-establish-accurate-target-forecasting-revenue-example
Sheet: Data

 | Week | 2024-05-04 00:00:00 | 2024-05-11 00:00:00 | 2024-05-18 00:00:00 | 2024-05-25 00:00:00 | 2024-06-01 00:00:00 | 2024-06-08 00:00:00 | 2024-06-15 00:00:00 | 2024-06-22 00:00:00 | 2024-06-29 00:00:00 | 2024-07-06 00:00:00 | 2024-07-13 00:00:00 | 2024-07-20 00:00:00 | 2024-07-27 00:00:00 | 2024-08-03 00:00:00 | 2024-08-10 00:00:00 | 2024-08-17 00:00:00 | 2024-08-24 00:00:00 | 2024-08-31 00:00:00 | 2024-09-07 00:00:00 | 2024-09-14 00:00:00 | 2024-09-21 00:00:00 | 2024-09-28 00:00:00 | 2024-10-05 00:00:00 | 2024-10-12 00:00:00 | 2024-10-19 00:00:00 | 2024-10-26 00:00:00 | 2024-11-02 00:00:00 | 2024-11-09 00:00:00 | 2024-11-16 00:00:00 | 2024-11-23 00:00:00 | 2024-11-30 00:00:00 | 2024-12-07 00:00:00 | 2024-12-14 00:00:00 | 2024-12-21 00:00:00 | 2024-12-28 00:00:00 | 2025-01-04 00:00:00 | 2025-01-11 00:00:00 | 2025-01-18 00:00:00 | 2025-01-25 00:00:00 | 2025-02-01 00:00:00 | 2025-02-08 00:00:00 | 2025-02-15 00:00:00 | 2025-02-22 00:00:00 | 2025-03-01 00:00:00 | 2025-03-08 00:00:00 | 2025-03-15 00:00:00 | 2025-03-22 00:00:00 | 2025-03-29 00:00:00
 |  | Week 5 | Week 6 | Week 7 | Week 8 | Week 9 | Week 10 | Week 11 | Week 12 | Week 13 | Week 14 | Week 15 | Week 16 | Week 17 | Week 18 | Week 19 | Week 20 | Week 21 | Week 22 | Week 23 | Week 24 | Week 25 | Week 26 | Week 27 | Week 28 | Week 29 | Week 30 | Week 31 | Week 32 | Week 33 | Week 34 | Week 35 | Week 36 | Week 37 | Week 38 | Week 39 | Week 40 | Week 41 | Week 42 | Week 43 | Week 44 | Week 45 | Week 46 | Week 47 | Week 48 | Week 49 | Week 50 | Week 51 | Week 52
Revenue | Prior Year | 519135 | 646047 | 1074350 | 865550.84 | 884868 | 978237 | 997818 | 688072 | 1025771 | 584645 | 1101091 | 752790 | 1227834 | 836305 | 373982 | 868979 | 799721 | 626696 | 6940 | 678124 | 1063475 | 1125524 | 1674390 | 1073117 | 1030989 | 1159279 | 1266052 | 906706 | 690496 | 625446 | 1030261 | 246847 | 672328 | 897300 | 824255 | 1220261 | 652280 | 926358 | 754250 | 607855 | 785899 | 654852 | 571480 | 734925 | 810227 | 745051.32 | 836137.1826000001 | 836933.635252
 | Target | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21
 | Actual | 975097 | 1252780.63 | 899637.75 | 1264998.15 | 1072123.37 | 1487692.02 | 879096.99 | 899395.51 | 1013152.71 | 480886.67 | 651359.67 | 472135.74 | 720614.91 | 1502484.26
# Appointments | Prior Year | 126 | 126 | 118 | 122 | 119 | 119 | 125 | 132 | 127 | 121 | 128 | 125 | 147 | 143
 | Target | 140 | 140 | 140 | 140 | 140 | 140 | 140 | 160 | 160 | 160 | 160 | 160 | 160 | 165
 | Actual | 155 | 178 | 195 | 205 | 195 | 189 | 179 | 178 | 142 | 130 | 152 | 166 | 194 | 195
The actuals are weekly actuals
I am not 100% sure there are any seasonality patterns that hold true given the variability within prior year actuals and current year actuals
I think that higher # of appointments should mean higher revenue within 2-4 weeks, but I need analysis prove/disprove
Ultimately would like a formula / algorithm to better forecast revenue