tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 18357df8-b6cf-42c0-8b56-eb8a55eb4a2f
Sheet: Whites

 |  |  |  |  |  | SEER (11 [NAME]) and US Mortality |  |  | Unadjusted Results |  | Mortality Adjustment Terms |  |  | Adjusted for Mortality
 |  |  | Age-Adjusted Rates (2000 US) |  |  | Age-Adjusted Rates (2000 US) |  |  | Expected | Unadjusted | Registry |  | [NAME] | Expected | Interim
 |  |  |  |  | Inc/Mort |  |  | Inc/Mort | Incidence | Percent |  | Adjust. |  | Incidence | Percent
 |  | Cancer Site | Incidence | Mortality | Ratio | Incidence | Mortality | Ratio | Rate | Complete | [NAME] | Term | [NAME] | Rate | Complete
Male | White | Oral Cavity and Pharynx
Male | White | Esophagus
Male | White | Stomach
Male | White | Colon and Rectum
Male | White | Liver
Male | White | Pancreas
Male | White | [NAME] and Bronchus
Male | White | Melanomas of the Skin
Male | White | Prostate*
Male | White | Bladder (including in situ)
Male | White | Kidney and Renal Pelvis
Male | White | Brain and Other Nervous System
Male | White | [NAME]
Male | White | Non-Hodgkin Lymphoma
Male | White | Multiple Myeloma
Male | White | [NAME]
 |  |  |  |  |  | SEER (11 [NAME]) and US Mortality |  |  | Unadjusted Results |  | Mortality Adjustment Terms |  |  | Adjusted for Mortality
 |  |  | Age-Adjusted Rates (2000 US) |  |  | Age-Adjusted Rates (2000 US) |  |  | Expected | Unadjusted | Registry |  | [NAME] | Expected | Interim
 |  |  |  |  | Inc/Mort |  |  | Inc/Mort | Incidence | Percent |  | Adjust. |  | Incidence | Percent
 |  | Cancer Site | Incidence | Mortality | Ratio | Incidence | Mortality | Ratio | Rate | Complete | [NAME] | Term | [NAME] | Rate | Complete
Female | White | Oral Cavity and Pharynx
Female | White | Esophagus
Female | White | Stomach
Female | White | Colon and Rectum
Female | White | Liver
Female | White | Pancreas
Female | White | [NAME] and Bronchus
Female | White | Melanomas of the Skin
Female | White | Breast*
Female | White | Cervix
Female | White | Corpus and Uterus, NOS
Female | White | Ovary
Female | White | Bladder (including in situ)
Female | White | Kidney and Renal Pelvis
Female | White | Brain and Other Nervous System
Female | White | [NAME]
Female | White | Non-Hodgkin Lymphoma
Female | White | Multiple Myeloma
Female | White | [NAME]
 |  | Overall Total + Breast + Prostate
 |  | Notes:
 |  | The cancer rates for Male Prostate (Whites and Blacks) and Melanomas of the Skin (Blacks) are not included in the completeness estimates.
 |  | The cancer rates for [NAME] (Whites and Blacks)  are not included in the completeness estimates.
 |  | To include rates for prostate, melanomas, or breast it is necessary to unprotect the worksheet (go to tools, protection, unprotect worksheet)
 |  | Rates are per 100,000 and age-adjusted to the 2000 US Std Population (19 age groups - Census P25-1130) standard.
 |  | Sites are based on SEER Site Recode with Kaposi and mesothelioma
Spreadsheet: cf9e3be3-da88-42cc-aa9d-86b5860ee5f3
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
7844 | 16115 | Marleen | Stroomer | NED | 185 | 00:21:54 | 00:02:14 | 01:25:30 | 00:01:44 | 00:48:38 | 1 | 02:39:58
7844 | 53581 | [NAME] | Buttner | GER | 186 | 00:22:38 | 00:02:29 | 01:51:13 | 00:02:38 | 00:50:48 | 2 | 03:09:44
Spreadsheet: 725585d1616757398-help-on-adjusting-excel-formula-to-calculate-more-date-sales-ledger-2021bb
Sheet: Customers statement

Current solution calculate 100 record on the sheets. I want it to calculate at least 5000 record on the sheets.
I have tried to adjust the formula but I have failed. Please help me.
 | ST 001
Date | Receipt Number | Invoice Number | Debit | Credit | Cumulative Balance |  |  | Sheet | Row
Desired Outcome
 | ST 001
Date | Receipt Number | Invoice Number | Debit | Credit | Cumulative Balance
2020-01-01 00:00:00 |  | C001 | 400
2020-01-10 00:00:00 |  | 1 | 2000
2020-01-12 00:00:00 | R010 | C001 |  | 300
2020-01-14 00:00:00 | R012 | 3 |  | 1000
2020-05-12 00:00:00 |  | 5 | 2300
2020-09-09 00:00:00 |  | 9 | 2500
Spreadsheet: 59781d1260336972-excel-2007-separating-data-to-other-worksheets-insurance-sales
Sheet: Sheet1

Company | Date Paid | Insured | Amt Paid | Agent
hartford | 2009-12-02 00:00:00 | [NAME] | 50 | [NAME]
allstate | 2009-12-03 00:00:00 | [NAME] | 60 | dennis
hartford | 2009-12-04 00:00:00 | [NAME] | 20 | [NAME]
allstate | 2009-12-05 00:00:00 | [NAME] | 34 | house
hartford | 2009-12-06 00:00:00 | [NAME] | 100 | bob
allstate | 2009-12-07 00:00:00 | [NAME] | 110 | jill
hartford | 2009-12-08 00:00:00 | [NAME] | 134 | [NAME]
Spreadsheet: adf6c1fd-2032-4192-a840-f32925cd2209
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
43482007 | 2014-10-07 21:01:30 | ALLIES | 0 | 5 | 6 | 688270 | Mouchotte72 | 12505 | western | 1945-02-17 | 1945-02-20 | Moyland Wood | [NAME]
43482209 | 2014-10-07 21:17:26 | AXIS | 0 | 4 | 6 | 688270 | Mouchotte72 | 12505 | western | 1945-02-17 | 1945-02-20 | Moyland Wood | [NAME]
Spreadsheet: 123306d1317546375-budget-v-spend-pivot-table-can-this-be-automated-marketing-budgets-working-test-file-v4
Sheet: Spend_Data

Property | Type | Category | Sub-Category | Cost | Spend Date | Budget Date
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
 | Spend
Spreadsheet: darron_c_giron__7953__Killed Deals
Sheet: Summary

 |  |  |  |  |  |  |  |  | P&L IMPACT |  | POSITION IMPACT
2002-01-15 00:00:00 | Killed Titanic and Yr 2003 Hub Deals |  |  |  |  |  |  |  | -153000 |  | 0
2002-01-15 00:00:00 | Booked Annuity from PGL to keep book whole.  Value was deducted from Hub fees owed PGL |  |  |  |  |  |  |  | 153000 |  | 0
2002-01-16 00:00:00 | Killed NSS1 Deals with Peoples |  |  |  |  |  |  |  |  |  | -475
2002-01-16 00:00:00 | Killed NSS1 Deals with NSS2 |  |  |  |  |  |  |  |  |  | -1.5
2002-01-16 00:00:00 | Killed NSS2 Deals with NSS1 |  |  |  |  |  |  |  |  |  | 2
2002-01-16 00:00:00 | Killed NSS1 Physical Deals with ENA |  |  |  |  |  |  |  |  |  | 149
2002-01-17 00:00:00 | Reclassified EMW deals with ENA from Physical to Financial |  |  |  |  |  |  |  | 0 |  | 0
2002-01-17 00:00:00 | Booked Inventory Transfer with PGL |  |  |  |  |  |  |  | 26208000 |  | 0
2002-01-17 00:00:00 | Killed EMW Index Deals with ENA |  |  |  |  |  |  |  | 0 |  | 0
2002-01-18 00:00:00 | Killed NSS2 Deals with PGL |  |  |  |  |  |  |  | -20877941.9465 |  | -639
2002-01-28 00:00:00 | Book New Deals to [NAME] enovate's exposure to EMW
2002-01-28 00:00:00 | Book New Deals to [NAME] exposure to enovate |  |  |  |  |  |  |  | 172090 |  | -48
2002-01-30 00:00:00 | Value to TP-NSS when deals with EMW killed |  |  |  |  |  |  |  | 108930.24
2002-01-30 00:00:00 | Value to EMW when deals with TP-NSS killed |  |  |  |  |  |  |  | -108930.24
2002-01-30 00:00:00 | Killed TP-NSS Deals with PGL |  |  |  |  |  |  |  | 0
2002-01-30 00:00:00 | Killed TP-NSS Deals with ENA |  |  |  |  |  |  |  | -119934
2002-01-30 00:00:00 | Released [NAME] Value |  |  |  |  |  |  |  | 1203603.37 |  | 0
2002-01-30 00:00:00 | Killed EMW to ENA Financial Deals |  |  |  |  |  |  |  | -25070927.7534 |  | 1217
 |  |  |  |  |  |  | [NAME] |  | -5209932
Spreadsheet: 143707d1330531698-mulitiple-lookups-returning-value-into-one-cell-seperated-by-commas-test-data
Sheet: Sheet1

AREA ID | AREA
25 | Networking
27 | Security
34 | Databases
35 | Cloud
36 | Risk
38 | BI
43 | PM
44 | Engineering
47 | IB
54 | Security
56 | Risk
57 | Desktop
63 | DR
66 | Systems HR
67 | Systems
Spreadsheet: 24391d1214638980-scrolling-tidrapport
Sheet: Juni2008

 |  | TIDRAPPORT
 |  | Name: |  |  | Anställnings nummer |  |  | År: |  | Månad:
Datum | Projekt | Ort | Resa från hemmet |  |  | Arbetad tid ([NAME]) | Resa till hemmet |  |  | [NAME] ([NAME]) | Orsak till ledighet
 |  |  | Avresa kl. | Framme kl. | Restid (min) |  | Avresa kl. | Framme kl. | Restid (min)
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
 |  |  |  |  | 0 |  |  |  | 0
Summa: |  | totalt resa från hemmet (min) |  | 0 | totalt resa till hemmet (min) |  | 0 |  | Totalt resa ([NAME]) | 1900-01-01 00:00:00
Underskrift: |  |  |  |  |  |  |  |  | Attest:
Spreadsheet: chris_germany__2580__CGLF_2000Apr
Sheet: Eff Apr '00

Only enter rates into bordered cells.  All others are computed.
 | TO
FROM | CGAS | Mainline | Onshore | Offshore
CGAS | 0.02184
Mainline |  | 0.0282
Onshore |  |  | 0.00603
Offshore |  |  |  | 0.00489
Spreadsheet: 90170d1289931183-cannot-get-formulas-to-populate-a-protected-worksheet-when-inserting-rows-bcs-scope-list-template
Sheet: Building18

Building18
 | Reference No. | Year | Priority | BCS Reference | Items | Existing Conditions | Recommendations | New Const. | Additions | Alteration | Major Systems | Major Repair | Energy | Bond | Capital | Estimated Cost with Incidental
 |  | SITE ISSUES
 |  | ARCHITECTURAL ISSUES
 |  | MECHANICAL ISSUES
 |  | PLUMBING ISSUES
 |  | ELECTRICAL ISSUES
Spreadsheet: 813984d1674088789-stack-columns-stack_columns-2-
Sheet: HAVE

NAME | OPERATOR | SAMPLE 1 | OPERATOR | SAMPLE 2 |  |  |  | NAME | OPERATOR | VALUE
X | = | 1 | < | 3 |  |  |  | X | = | 1 |  |  | = | 1
Y | = | 2 | = | 1 |  |  |  | Y | = | 2 |  | Y | = | 2
Z | < | 1 | = | 4 |  |  |  | Z | < | 1 |  | Z | < | 1
 |  |  |  |  |  |  |  | X | < | 3 |  | X | < | 3
 |  |  |  |  |  |  |  | Y | = | 1 |  | Y | = | 1
 |  |  |  |  |  |  |  | Z | = | 4 |  | Z | = | 4
Spreadsheet: 842684d1694695102-extract-data-from-rows-to-column-order-file-hd
Sheet: Output

Acct No | Qty | Price
M1 | 2 | 2 |  |  | 2 | 2
M4 | 3 | 1 |  | M4 | 3 | 1
M5 | 2 | 3 |  | M5 | 2 | 3
M2 | 5 | 1 |  | M2 | 5 | 1
M3 | 2 | 6 |  | M3 | 2 | 6
M1 | 3 | 3 |  | M1 | 3 | 3
M2 | 2 | 1 |  | M2 | 2 | 1
M3 | 3 | 1 |  | M3 | 3 | 1
M4 | 1 | 1 |  | M4 | 5 | 1
Spreadsheet: 881675d1729796181-four-linked-index-match-worksheets-and-col-a-misalignment-with-manually-entered-data-grant-tracker-2024-design-v2
Sheet: Prospecting (1)

Grant/Award Name | Grantor/Funder Name | ULEC Staff [NAME] | [NAME] | Apply Y/N | Application Due Date | Application Submitted Date | [NAME] | [NAME] for
Fake Grant Name 1 | Fake Grantor 1 | [EMAIL] | Fake Description 1 | Y | 2024-03-31 00:00:00 | 2024-03-01 00:00:00 | 100000 | 50000
Fake Grant Name 2 | Fake Grantor 2 | [EMAIL] | Fake Description 2 | Y
Fake Grant Name 3 | Fake Grantor 3 | [EMAIL] | Fake Description 3 | Y
Fake Grant Name 4 | Fake Grantor 4 | [EMAIL] | Fake Description 4 | Y
Fake Grant Name 5 | Fake Grantor 5 | [EMAIL] | Fake Description 5 | N
Fake Grant Name 6 | Fake Grantor 6 | [EMAIL] | Fake Description 6 | Y
Fake Grant Name 7 | Fake Grantor 7 | [EMAIL] | Fake Description 7 | N
Fake Grant Name 8 | Fake Grantor 8 | [EMAIL] | Fake Description 8 | N
Fake Grant Name 9 | Fake Grantor 9 | [EMAIL] | Fake Description 9 | Y
Spreadsheet: 00c0c2f0-05da-41bb-bb41-df9500ec2dd1
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | EcoCheck Data: All Data for 2010 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9
Estuary | Chlorophyll a | Aquatic Grasses | [NAME] | [NAME] | Water Clarity | Phytoplankton Index | Water Quality Index | Biotic Index | Bay Health Index
Choptank River | 8.982 | 4.12 | 90.739 | 30.86565 | 48.984 | 13.86 | 49.56833333 | 16.28188333 | 32.92510833
[NAME] | 26.606 | No Growth Zone | 50.229 | Insufficient Data | 0 | 0 | 25.61166667 | Insufficient Data | 19.2
[NAME] | 56.771 | 47.43 | 95.583 | 60 | 9.634 | 23.39 | 53.996 | 43.60666667 | 48.80133333
Lower Bay | 12.619 | 46.44 | 88.352 | 71.43 | 18.539 | 62.18 | 39.83666667 | 60.01666667 | 49.92666667
Lower Eastern Shore (Tangier) | 15.838 | 34.35 | 81.677 | 56.79599 | 12.211 | Insufficient data | 36.57533333 | 45.572995 | 41.07416417
Lower Western Shore (MD) | 1.514 | 9.75 | 56.057 | 0 | 0 | 13.13 | 19.19033333 | 7.626666667 | 13.4085
Mid Bay | 24.855 | 15.35 | 71.627 | 20.34005 | 26.363 | 93.64 | 40.94833333 | 43.11001667 | 42.029175
Overall Bay | 21.946 | 36.99928571 | 80.81401 | 46.7 | 18.457 | 49.5 | 40.40567 | 44.3997619 | 42.40271595
Patapsco and Back Rivers | 0 | 0 | 52.63 | 45.45455 | 0 | 0 | 17.54333333 | 15.15151667 | 16.347425
Patuxent River | 5.866 | 11.87 | 67.444 | 24 | 4.87 | 28.41 | 26.06 | 21.42666667 | 23.74333333
Potomac River | 25.797 | 46.07 | 76.17 | 32 | 14.626 | 8.6 | 38.86433333 | 28.89 | 33.87716667
Rappahannock River | 19.79 | 83.2 | 82.592 | 20 | 3.907 | 47.16 | 35.42966667 | 50.12 | 42.77483333
[NAME] | 44.958 | 91.38 | 80.543 | 72 | 27.743 | 23.87 | 51.08133333 | 62.41666667 | 56.749
Upper Eastern Shore | 14.213 | 29.19 | 77.809 | 27.8183 | 8.365 | 15.66 | 33.46233333 | 24.22276667 | 28.84255
Upper Western Shore | 31.891 | 71.68 | 100 | 25 | 2.61 | Insufficient data | 44.83366667 | 48.34 | 46.58683333
York River | 24.224 | 27.16 | 71.15 | 44 | 12.493 | 11.71 | 35.95566667 | 27.62333333 | 31.7895
Spreadsheet: 799195d1664979904-pull-specific-values-tied-to-names-to-two-separate-columns-with-exclusion-tips-respond-
Sheet: Sheet1

 | Team Member | Total eTips | Upsell Total | Google Tally | Absences Tally | eTip Payout | Comm. Payout | Adjustments |  |  | TIP | OTHER REASON |  | TIP (Assume shared equally) | OTHER REASON (Assume shared equally)
 | [NAME] | 71.26 | 292.62
 | Blake | 284.34 | 790
 | [NAME] | 70
 | [NAME] | 49.63
 | Adjustments
 | Employee |  |  |  | Reason | Amount (Each Employee)
 | [NAME] | Blake |  |  | Tip | 10 |  | Absences | 0.33
 | [NAME] |  |  |  | Tip | 30 |  | Processing Fee | 0.95
 | [NAME] |  |  |  | Called In | 20 |  | Commissions | 0.2
 | Blake | [NAME] |  |  | Tip | 15
 | [NAME] |  |  |  | Reimbursement | 50
 | [NAME] |  |  |  | Called In | 20
 | [NAME] | Sy |  |  | Lost Tool | -10
 | [NAME] |  |  |  | Bonus | 50
 | Already Done: | "Adjustments" in column I already pull automatically from B11:G20 based on employee name (B11:F20) relative to it matching the name in B3:B6 and sums the total amount with every instance of an adjustment in G11:G20 |  |  |  | "Adjustments" in column I already pull automatically from B11:G20 based on employee name (B11:F20) relative to it matching the name in B3:B6 and sums the total amount with every instance of an adjustment in G11:G20
 | Goals/Trying to Do: | Trying to get only "Tip" instances listed in F11:F20 to get added to "eTip Payout" (column G). "eTip Payout" from column G already pulls from "Total eTips" in C3:C6 |  |  |  | All other "Reasons" that are listed in F11:F20, I'm trying to get pulled into "Adjustments" I3:I6 that match names in both spots
 |  | All other "Reasons" that are listed in F11:F20, I'm trying to get pulled into "Adjustments" I3:I6 that match names in both spots
 |  | So I basically need to find out how to find certain tip instances while excluding all other "Reasons" and vice versa
Spreadsheet: 799813d1665324341-average-and-array-formula-not-using-duplicate-values-golf-handicap
Sheet: HCI Tracker

Date | HCI
2022-08-08 00:00:00 | 15.1
2022-08-10 00:00:00 | 15.1
2022-08-11 00:00:00 | 15.1
2022-08-14 00:00:00 | 15.1
2022-08-20 00:00:00 | 15.3
2022-08-23 00:00:00 | 14.3
2022-09-03 00:00:00 | 14.3
2022-09-10 00:00:00 | 13.7
2022-09-13 00:00:00 | 13.4
2022-09-18 00:00:00 | 13.4
2022-09-20 00:00:00 | 13.4
2022-09-26 00:00:00 | 13.4
Spreadsheet: 121911d1316506539-figuring-out-the-percentage-of-a-number-sample
Sheet: Sheet1

 | Downsizing | 19
 | Static | 97
 | Slow growth | 418
 | Rapid growth | 365
Spreadsheet: 155378d1336778193-excel-2007-multiple-occurrences-lookup-to-find-greatest-value-book1
Sheet: Sheet1

Unit ID | Service Plan | Coverage Hr Code | Total [NAME]
PA0002 | BR | N | 105
PA0002 | GO | N | 105
PA0002 | GO | I | 98
PA0002 | GO | I | 98
PA0002 | FL | G | 53
PA0002 | FL | A | 45
Spreadsheet: 882623d1730996758-income-tax-using-lambda-and-let-functions-tax-income-using-lambda-and-let-jt-
Sheet: Sheet1

 |  | $ |  | $ |  | Rates |  | $
 | From | 0 | to | 100 | multiply by rate | 0 | Deduct | 0
 | From | 100.01 | to | 300 |  | 0.2 |  | 20
 | From | 300.01 | to | 1000 |  | 0.25 |  | 35
 | From | 1000.01 | to | 2000 |  | 0.3 |  | 85
 | From | 2000.01 | to | 3000 |  | 0.35 |  | 185
 | From | 3000.01 | and above |  |  | 0.4 |  | 335
 |  |  | Allowable Deduction
 |  |  | 0.045
 |  |  |  |  | Desired Solution
 | Employee Name | Salary | Allowable Deduction | Taxable Income | Income Tax
 | [NAME] | 190
 | Kelly | 150 | 6.75 | 143.25
 | Gloria | 150 | 6.75 | 143.25
 | Amanda | 170 | 7.649999999999999 | 162.35
 | [NAME] | 170 | 7.649999999999999 | 162.35
 | [NAME] | 170 | 7.649999999999999 | 162.35
 | Tonya | 170 | 7.649999999999999 | 162.35
 | [NAME] | 170 | 7.649999999999999 | 162.35
 | Total
 | TIN or Personal ID of Employee | Employed From date | Employed To date | Current Salary, wages, fees, Commissions etc (regular earnings) |  | Other Exemptions on Current Salary, wages, fees, Commissions etc (regular earnings) |  | Current Overtime |  | Current Disabled persons credit |  | Current Elderly person credit |  | Cumulative Bonus (from last tax period
 |  |  |  | USD | ZWL | USD | ZWL | USD | ZWL | USD | ZWL | USD | ZWL | USD | ZWL
 | 08-965660 G73 | 01/04/2021 | To Date | 190 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 08-2101012 E39 | 01/04/2021 | To Date | 150 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 08-2046598 J39 | 01/04/2021 | To Date | 150 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 58-364250 B27 | 01/10/2021 | To Date | 170 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 08-2014259H35 | 2024-01-02 00:00:00 | To Date | 170 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 08-719754 S03 | 01/09/2021 | To Date | 170 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 08-2052740 K03 | 01/10/2022 | To Date | 170 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 08-2144816S66 | 2024-02-08 00:00:00 | To Date | 170 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Spreadsheet: 858111d1706874939-week-number-returns-value-error-when-cell-is-blank-calendar-test
Sheet: Feb

 |  |  | Wk No.
 |  |  | Day
Spreadsheet: 789617d1659243414-how-to-sum-multiple-rows-based-on-a-condition-sum-multiple-rows-aligw
Sheet: Sheet1

 |  |  |  |  | 2022 | 2023 | 2024 | 2025 | 2026 | 2027
 |  |  |  | E | 402106.6676415102 | 340066.1228313082 | 337734.4619490685 | 335261.1742278402 | 333150.1671436302 | 331128.9753225231
 |  |  |  | Y | 226434.9485849061 | 191301.9276987849 | 197290.6771694411 | 195806.7045367041 | 194540.1002861781 | 193327.3851935139
 |  |  |  | S | 312897.4022291697 | 265320.3236179281 | 279023.2237529548 | 281795.3732199063 | 284299.9642423125 | 286516.3163584081
 |  |  |  |  | What I want to achieve is this
 |  |  |  |  |  |  |  | AliGW
 |  |  |  |  | 2023
 |  |  |  |  | 2024
Spreadsheet: 679126d1590210912-looking-for-data-which-has-identic-value-in-other-columns-sample
Sheet: SheetA

CODE | TIME A | TIME B
XYZ | 1.2 | ?
ZYX | 2.6 | ?
YZX | 1.3 | ?
ZYY | 1.5 | ?
The Result Should Be
CODE | TIME A | TIME B
XYZ | 1.2 | 1.2
ZYX | 2.6 | 2.6
YZX | 1.3 | Not Match
ZYY | 1.5 | Not Found
Spreadsheet: 785817d1656704651-if-statements-for-multiple-dates-and-date-ranges-that-correspond-to-different-formulas-excel-example
Sheet: Detail by Workstream

 | 2022-04-01 00:00:00 | 2022-05-01 00:00:00 | 2022-06-01 00:00:00 | 2022-07-01 00:00:00 | 2023-02-01 00:00:00 | Seniority | [NAME] | Monthly Cost | Start Date | 2022-01-01 00:00:00 | 2022-02-01 00:00:00 | 2022-03-01 00:00:00 | 2022-04-01 00:00:00 | 2022-05-01 00:00:00 | 2022-06-01 00:00:00 | 2022-07-01 00:00:00 | 2022-08-01 00:00:00 | 2022-09-01 00:00:00 | 2022-10-01 00:00:00 | 2022-11-01 00:00:00 | 2022-12-01 00:00:00 | 2022 Fcst | 2023-01-01 00:00:00 | 2023-02-01 00:00:00 | 2023-03-01 00:00:00 | 2023-04-01 00:00:00 | 2023-05-01 00:00:00 | 2023-06-01 00:00:00 | 2023-07-01 00:00:00 | 2023-08-01 00:00:00 | 2023-09-01 00:00:00 | 2023-10-01 00:00:00 | 2023-11-01 00:00:00 | 2023-12-01 00:00:00 | 2023 Fcst |  | Notes:
Position | Phase 1 | Phase 2 | Phase 3 | Phase 4 | Phase 5
Employee 1 |  |  | 0 |  |  | Director |  |  | 2022-08-01 00:00:00
Employee 2 |  |  |  |  |  | Director |  |  | 2022-03-01 00:00:00
Spreadsheet: 1ebfd002-ed2e-42e6-9eed-a30c67b20971
Sheet: Sheet1

2008-11-04 00:00:00 | UNITED STATES SENATOR | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Belknap County | [NAME], r | Shaheen, d | Blevens, lib | Others
Alton | 1802 | 1285 | 77
Barnstead | 1117 | 1197 | 73
Belmont | 1599 | 1749 | 89
Center Harbor | 388 | 317 | 19
Gilford | 2371 | 2054 | 71
Gilmanton | 997 | 1064 | 51
[NAME] | 844 | 704 | 24
[NAME] | 542 | 668 | 31
[NAME] 3 | 558 | 607 | 25
[NAME] | 514 | 652 | 35
[NAME] | 440 | 642 | 25
[NAME] 6 | 840 | 718 | 30
Meredith | 1921 | 1725 | 133
New Hampton | 629 | 591 | 51
Sanbornton | 826 | 935 | 62
[NAME] | 778 | 1023 | 63
TOTALS | 16166 | 15931 | 859
Carroll County | [NAME], r | Shaheen, d | Blevens, lib | Others
Albany | 185 | 233 | 13
[NAME] | 828 | 941 | 37
[NAME] | 256 | 189 | 11
Chatham | 116 | 90 | 8
Conway | 2102 | 2806 | 190
Eaton | 120 | 149 | 2
[NAME] | 369 | 404 | 47
Freedom* | 470 | 417 | 19
Hale's Location | 98 | 25 | 2
Hart's Location | 15 | 14 | 0
[NAME] | 293 | 381 | 17
[NAME] | 576 | 783 | 39
Moultonborough | 1822 | 1085 | 92
Ossipee | 1071 | 970 | 113
Sandwich | 426 | 546 | 22
Tamworth | 685 | 843 | 58
Tuftonboro | 928 | 626 | 51
Wakefield | 1343 | 1151 | 134
Wolfeboro | 2262 | 1775 | 96
TOTALS | 13965 | 13428 | 951
Spreadsheet: 190472d1351664183-vlookup-using-text-in-multiple-cells-as-lookup-value-example-7-
Sheet: Sheet1

Hex Bolt FT CL4.8
 | M5 | M6 | M8
10
12
12
14
16
18
VLOOKUP using text in multiple cells as lookup value?
Spreadsheet: 85048d1285117882-if-function-automatically-calculate-wins-in-football-spreadsheet-autocalc-pick-sheet
Sheet: Sheet1

PICKS FOR WEEK
NAME |  |  |  |  |  |  |  |  |  |  | WINS
[NAME] | GB | MIA | CHI | ATL | KC | MIA | WAS | NYJ | IND | SF
[NAME] | PHI | TEN | DAL | CAR | MIN | CIN | SD | WAS | NE | SEA
[NAME] | BAL | PIT | KC | MIN | SEA | WAS | SD | NE | IND | NO
Games
Winner | GB | MIA | KC | CHI | ATL | TB | DET | CIN | PIT | DEN | OAK | WAS | NYJ | SD | IND | SF
[NAME] | BUF | MIN | CLE | DAL | ARI | CAR | PHI | BAL | TEN | SEA | STL | HOU | NE | JAX | NYG | NO
Spreadsheet: 855022d1704744355-vba-code-to-make-my-classes-schedule-for-number-of-days-with-available-faculty-test-file
Sheet: Sheet1

faculty available NAME | No of days Program | Subjects | which faculty takes which class | each day classes | each session hr | Session start date | DATE ON WHICH SOME FACULTY IS NOT AVAIBALE | FACULTY NAME WHO IS NOT AVAILABLE
[NAME] | 21 | a1 | ANUJ | 4 | 1.3 | 2023-12-29 00:00:00 | 2023-12-30 00:00:00 | ANUJ |  |  |  |  |  | tab of vba to click
RAGHAV |  | a2 | RAGHAV |  |  |  | 2024-01-01 00:00:00 | GOKUL
NITIN |  | a3 | ANUJ |  |  |  |  |  |  |  |  |  |  | on clicking [NAME]
GOKUL |  | a4 | GOKUL |  |  |  |  |  |  |  |  |  |  | the result permutations and schedule will come at sHEET 2 of same workbook
 |  | a5 | NITIN
 |  | a6 | RAGHAV
 |  | a7 | ANUJ
 |  | [NAME] | GOKUL
 |  | a9 | RAGHAV
 |  | a10 | NITIN
 |  | a11 | ANUJ
 |  | a12 | GOKUL
 |  | a13 | RAGHAV
 |  | a14 | GOKUL
 |  | a15 | NITIN
 |  | a16 | ANUJ
 |  | a17 | GOKUL
 |  | a18 | NITIN
 |  | a19 | RAGHAV
 |  | a20 | GOKUL
 |  | a21 | NITIN
[NAME] | 2 | b1 | ANUJ | 4 | 1.3 | 2024-01-02 00:00:00
RAGHAV |  | b2 | GOKUL
NITIN |  | b3 | RAGHAV
GOKUL |  | b4 | NITIN
 |  | [NAME] | GOKUL
 |  | b6 | RAGHAV
 |  | b7 | NITIN
 |  | b8 | ANUJ