tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 328564d1403947543-how-to-colour-a-cell-based-on-few-conditions-cell-values-of-other-cells-in-the-same-row-example
Sheet: NA1

Step | Activity description |  | Jan |  |  |  |  | Feb |  |  |  | March |  |  |  | April
 |  |  | W1 | [NAME] | W3 | W4 | W5 | W6 | W7 | W8 | W9 | W10 | W11 | W12 | W13 | W14
Step1 |  | plan | planned | planned | planned | planned | planned
Step1 |  | Actual
Step1 | Activity1 | plan | planned
Step1 | Activity1 | Actual | Finished on time
Step1 | Activity2 | plan |  | planned | planned
Step1 | Activity2 | Actual |  | Finished with a delay | Finished on time
Step1 | Activity3 | plan |  | planned | planned
Step1 | Activity3 | Actual |  | Finished on time | Delay
Step1 | Activity4 | plan |  |  |  | planned
Step1 | Activity4 | Actual |  |  |  | Finished with a delay
[NAME] |  | plan |  |  | planned | planned | planned | planned | planned
[NAME] |  | Actual
[NAME] | activity 1 | plan | planned | planned | planned
[NAME] | activity 2 | Actual | Finished on time | Finished on time | Finished on time
[NAME] | activity 3 | plan |  |  |  | planned
[NAME] | activity 4 | Actual |  |  |  | Finished with a delay
[NAME] | activity 5 | plan |  |  |  |  | planned
[NAME] | activity 6 | Actual |  |  |  |  | Delay
[NAME] | activity 7 | plan |  |  |  |  |  |  | planned
[NAME] | activity 8 | Actual |  |  |  |  |  |  | Finished with a delay
Spreadsheet: 52369d1252065326-countif-and-or-statements-to-multiple-cells-with-multiple-condtions-condition-formula
Sheet: Sheet3

 |  |  |  |  |  |  |  |  | Bucket 1 | Bucket 2 | Bucket 3 | Bucket 4
Fiber | Cust 1 | Cust 2 | Status | Data 1 | Data 2 | Data 3 | Data 4 | Data 5 | <=5 | >5 <=9 | >9 | No Data |  | A Value of 1 should be placed on the [NAME] for the following rows( fibers):
1 | XYZ |  |  |  |  |  |  |  |  |  |  |  |  | Bucket 1
2 |  | FGH | PF | 1 | 3 | 2 | 6 | 4 |  |  |  |  |  | Bucket 1
3 |  |  |  | 2 | 7 | 3 | 9 | 2 |  |  |  |  |  | Bucket 1
4 |  | XYZ | PF | 4 | 3 | 2 | 3 | 7 |  |  |  |  |  | Bucket 2
5 |  |  |  | 2 | 2 | 3 | 3 | 9 |  |  |  |  |  | Bucket 2
6 |  |  |  | 2 | 4 | 9 | 2 | 12 |  |  |  |  |  | Bucket 3
7 | CDE |  | PF | 3 | 2 | 7 | 8 | 13 |  |  |  |  |  | Bucket 3
8 |  |  |  |  |  |  |  |  |  |  |  |  |  | Bucket 4
9 |  |  |  | 2 | 5 |  | 8 | 4 |  |  |  |  |  | Bucket 4
Bucket 1 Criteria
Cust 1 and or Cust 2 have a value, status is not equal to PF and Data 1, 3 and 5 can be empty
If [NAME] is PF then Cust 1 or Cust 2 is not a condition to be met to catagorize what bucket the values get placed under
If Cust 1 and or Cust 2 are blank and status is blank and Data 1, 3 and 5 have values under or equal to 5
Data 1, 3 and 5 must have values equal to or less than 5
Bucket 2 Criteria
If Cust 1 or Cust 2 are blank and there are no blank values in Data 1, 3 and 5 and one of the values is greater than 5 but less than or equal to 9
If there is a value in Cust 1 and or Cust 2 but Status is PF and there is data in Data 1, 3, and 5 and one of the values is greater than 5 but less than or equal to 9
If just one cell in Data 1, 3, and 5 is greater than 5 but less than or equal to 9
Bucket 3 Criteria
If Cust 1 or Cust 2 are blank and there are no blank values in Data 1, 3 and 5 and one of the values is greater than 9
If there is a value in Cust 1 and or Cust 2 but Status is PF and there is data in Data 1, 3, and 5 and one of the values is greater than 9
If just one cell in Data 1, 3, and 5 is greater than 9
Bucket 4 Criteria
There is no value in Cust 1 and or Cust 2 and there is a missing value in Data, 1 or Data 3 or Data 5
There is no values in Cust 1and or Cust 2 and no values in Data 1, 3, and 5
I tried using the =IF(COUNTIF(  statement but since I do not have an array for a range it wouldn’t work
I tried using the IF(OR(AND(    but couldn’t get all the conditions to me met
Spreadsheet: 798187d1664359143-preparing-incentive-sheet-for-workers-based-on-criteria-incentive-sheet-query-etaf
Sheet: Sheet2

Level | Score | Rate | Late Coming Max | [NAME] | % incentive
Operator | 17.5 | 125 | 4 | 0.9 | 1
Operator | 16.5 | 90 | 4 | 0.9 | 1
Operator | 15.5 | 50 | 4 | 0.9 | 1
Operator | 17.5 | 125 | 7 | 0.9 | 0.4
Operator | 16.5 | 90 | 7 | 0.9 | 0.4
Operator | 15.5 | 50 | 7 | 0.9 | 0.4
Operator | 17.5 | 125 | 10 | 0.9 | 0.1
Operator | 16.5 | 90 | 10 | 0.9 | 0.1
Operator | 15.5 | 50 | 10 | 0.9 | 0.1
Operator | 17.5 | 125 | 4 | 0.75 | 0.2
Operator | 16.5 | 90 | 4 | 0.75 | 0.2
Operator | 15.5 | 50 | 4 | 0.75 | 0.2
Operator | 17.5 | 125 | 7 | 0.75 | 0.1
Operator | 16.5 | 90 | 7 | 0.75 | 0.1
Operator | 15.5 | 50 | 7 | 0.75 | 0.1
Operator | 17.5 | 125 | 10 | 0.75 | 0
Operator | 16.5 | 90 | 10 | 0.75 | 0
Operator | 15.5 | 50 | 10 | 0.75 | 0
Worker | 17.5 | 80 | 4 | 0.9 | 1
Worker | 16.5 | 60 | 4 | 0.9 | 1
Worker | 15.5 | 40 | 4 | 0.9 | 1
Worker | 17.5 | 80 | 7 | 0.9 | 0.4
Worker | 16.5 | 60 | 7 | 0.9 | 0.4
Worker | 15.5 | 40 | 7 | 0.9 | 0.4
Worker | 17.5 | 80 | 10 | 0.9 | 0.1
Worker | 16.5 | 60 | 10 | 0.9 | 0.1
Worker | 15.5 | 40 | 10 | 0.9 | 0.1
Worker | 17.5 | 80 | 4 | 0.75 | 0.2
Worker | 16.5 | 60 | 4 | 0.75 | 0.2
Worker | 15.5 | 40 | 4 | 0.75 | 0.2
Worker | 17.5 | 80 | 7 | 0.75 | 0.1
Worker | 16.5 | 60 | 7 | 0.75 | 0.1
Worker | 15.5 | 40 | 7 | 0.75 | 0.1
Worker | 17.5 | 80 | 10 | 0.75 | 0
Worker | 16.5 | 60 | 10 | 0.75 | 0
Worker | 15.5 | 40 | 10 | 0.75 | 0
Spreadsheet: 277990d1384508459-extracting-a-continuous-list-based-on-criteria-help-req-file-1-index-small-
Sheet: Sheet1

Place | Pop |  | HIGH | MEDIUM | LOW
Delhi | 1.6753235
Jammu and Kashmir | 1.2548926
Uttarakhand | 1.0116752
Himachal Pradesh | 0.6856509
Tripura | 0.3671032
Meghalaya | 0.2964007
Manipur | 0.2721756
Nagaland | 0.1980602
Goa | 0.1457723
Arunachal Pradesh | 0.1382611
[NAME] | 0.1244464
Mizoram | 0.1091014
Chandigarh | 0.1054686
Sikkim | 0.0607688
Andaman and Nicobar Islands | 0.0379944
Dadra and [NAME] | 0.0342853
Daman and Diu | 0.0242911
Lakshadweep | 0.0064429
Spreadsheet: 792623d1661012156-help-regarding-arrange-text-data-into-coloums-demo
Sheet: Sheet1

 |  |  | Output required
Text
 | cheese blend | sachet | tombo | chocolate syrup | pizza pasta | Mild and sweet mayonaise
Regarding order, ordered 1 case sachets, 1 case tombo, 1 case chocolate syrup, 1 case pizza pasta, 1 case cheese blend
regarding order, ordered 5 case pizza pasta and 1 case tombo ketchup
regarding order, ordered 6  cheese blend , 3 pizza pasta 6 mild and sweet mayonaise.
met regarding order, ordered 10 cases of cheese blend and will give feedback later
Spreadsheet: 868441d1715175527-sort-function-broken-keep-dreaming-league-standings
Sheet: 6 - MAY 7

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | W |  | L |  | PTS |  | PF |  | PA
JASON | 5 |  |  |  | 7 |  |  | 10 |  |  |  | 3 |  |  |  | 7 |  |  |  | 10 |  |  |  | 4
[NAME] | 10 |  |  |  |  | 10 |  |  | 10 |  |  |  |  | 6 |  |  | 6 |  |  |  | 4 |  |  |  |  | 7
WAYNE |  | 10 |  |  | 10 |  |  |  |  | 10 |  |  | 6 |  |  |  | 10 |  |  |  |  | 10 |  |  | 10
PAUL |  |  | 5 |  |  | 6 |  |  |  |  | 4 |  |  |  | 5 |  |  |  |  | 6 |  |  |  |  | 1 |  |  | 10
MOUNTNEY |  |  |  | 7 |  |  |  | 7 |  |  |  |  | 10 |  |  |  |  | 6 |  |  | 10 |  | 10 |  |  |  |  | 5
MAYFIELD |  |  |  | 10 |  |  |  |  | 6 |  |  | 10 |  |  | 10 |  |  |  | 6 |  |  | 7 |  |  |  |  | 4
[NAME] |  |  | 10 |  |  |  | 10 |  |  | 6 |  |  |  | 10 |  |  |  | 10 |  |  |  |  |  | 10 |  |  | 10
MIKE |  | 6 |  |  |  |  | 5 |  |  |  | 10 |  |  |  |  | 10 |  |  | 10 |  |  |  | 7 |  |  | 10
 | 1-2 | 3-8 | 4-7 | 4-5 | 1-3 | 2-4 | 5-6 | 1-5 | 2-6 | 3-7 | 4-8 | 1-6 | 3-5 | 2-7 | 4-6 | 1-8 | 2-3 | 5-7 | 6-8 | 1-4 | 2-5 | 3-6 | 5-8 | 1-7 | 3-4 | 2-8 | 6-7 | 4-5
Spreadsheet: 766150d1643782981-appending-more-than-two-columns-using-one-dynamic-array-or-spilled-formula-book11
Sheet: Sheet1

 | From Here |  |  |  |  |  |  | To -
Balls
Dolls
Toy gun |  |  |  |  |  |  |  | Dolls | Low | Two
Robot |  |  |  |  |  |  |  | Toy gun | Middle | Three
Clay |  |  |  |  |  |  |  | Robot | Left | Four
 |  | One |  |  |  |  |  | Clay | Right | Five
 |  | Two |  |  |  |  |  |  |  | Six
 |  | Three
 |  | Four
 |  | Five
 |  | Six | High
 |  |  | Low
 |  |  | Middle
 |  |  | Left
 |  |  | Right
Spreadsheet: 734493d1622203594-take-the-most-recent-month-from-my-data-and-the-days-and-the-qty-associated-with-it-work-in-progress
Sheet: Sheet1

Date | Quantity Inspected
2021-01-07 00:00:00 | 80
2021-01-07 00:00:00 | 80
2021-01-07 00:00:00 | 79 |  |  | Month | QTY
2021-01-07 00:00:00 | 80 |  |  | 1
2021-01-07 00:00:00 | 80 |  |  | 2
2021-01-07 00:00:00 | 80 |  |  | 3
2021-01-08 00:00:00 | 478 |  |  | 4
2021-01-08 00:00:00 | 558 |  |  | 5
2021-01-08 00:00:00 | 638 |  |  | 6
2021-01-08 00:00:00 | 718 |  |  | 7
2021-01-08 00:00:00 | 1918 |  |  | 8
2021-01-20 00:00:00 | 1918 |  |  | 9
2021-01-22 00:00:00 | 400 |  |  | 10
2021-01-27 00:00:00 | 973 |  |  | 11
2021-02-19 00:00:00 | 1853 |  |  | 12
2021-02-20 00:00:00 | 853
2021-05-10 00:00:00 | 4093
2021-05-11 00:00:00 | 4173
2021-05-11 00:00:00 | 4253
2021-05-11 00:00:00 | 4413
2021-05-12 00:00:00 | 675
2021-04-12 00:00:00 | 561
Spreadsheet: 675077d1588151783-excel-formula-counting-time-of-late-excel-test
Sheet: data

 |  |  | punch record | punch record | punch record | punch record | punch record
ID | times of late |  | 2020-04-01 00:00:00 | 2020-04-02 00:00:00 | 2020-04-03 00:00:00 | 2020-04-04 00:00:00 | 2020-04-05 00:00:00
S05 | 3 |  | 0:35:00 |  | 0:30:00 |  | 0:01:00
 |  |  | 1st late > 30 minutes, will COUNT 1 time of late |  | 1st + 2nd late > 30 minutes, will COUNT 2 times of late |  | 1st + 2nd + 3rd late > 30 minutes, will COUNT 3 times of late
S06 | 2 |  | 0:00:00 | 0:20:00 | 0:00:00 | 0:30:00 | 0:01:00
 |  |  |  | 1st late < 30 minutes, will NOT count time of late |  | 1st + 2nd late > 30 minutes, will COUNT 1 times of late | 1st + 2nd + 3rd late > 30 minutes, will COUNT 2 times of late
S07 | 0 |  | 0:00:00 | 0:01:00 | 0:01:00 | 0:01:00 | 0:00:00
 |  |  |  | 1st late < 30 minutes, will NOT count time of late | 1st+2nd late < 30 minutes, will NOT count time of late | 1st+2nd+3rd late < 30 minutes, will NOT count time of late
Spreadsheet: 692345d1598285751-need-to-extract-data-and-skip-blanks-machine-shop-schedules_excel-forum
Sheet: Plating Cost Calculator

 |  |  |  |  | PURCHASE ORDER ENTRY (Do not populate gray cells) |  |  |  |  |  |  | (Eastern!T2="X",Eastern!C2,0) | IFERROR(INDEX(Eastern!$T$2:$T$100,SMALL(IF(ISTEXT(Eastern!$T$2:$T$100),ROW(Eastern!$T$1:$T$100),""),ROW(Eastern!C2))),"")
CNC / LASER ENTRY (Do not populate gray cells) |  |  |  |  | PO SUBTOTAL |  |  | Expedite: SAME DAY
 |  |  |  |  | PO WASTE FEE (5% of SUBTTL) |  |  | Expedite: NEXT DAY
P/N | L | W | REV | QTY | Total Dimensions | Cost per Part | Total QTY Cost
PN (MANUALLY ENTERED) | 8.423 | 6.762 | A1 | 4
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
www.atlaspm.xxx/toms-tutorials-for-excel/toms-tutorials-for-excel-listing-noncontiguous-data-without-blanks/
Spreadsheet: 599914d1543357044-change-cell-colour-based-on-the-value-of-one-cell-2019-cohort-qla
Sheet: Foundation Reading

 |  |  |  |  |  |  |  |  |  |  |  | Section B - Questions in Spanish
 | Question | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16
 | Out of | 4 | 4 | 3 | 4 | 3 | 2 | 4 | 3 | 2 | 4 | 4 | 3 | 4 | 4 | 3 | 9
 | Topic | Literary extract | Jobs | Describing family members | Job applications | Job descriptions and instructions | Technology | Sport | Festivals | Festivals, transport and recycling | Food | Free time | [NAME] and agreements | School Life | Literary Extract | Ambitions for the future | Translation (SP>EN)
 | OP1
 | OP3
 | OP1
 | OP3
 | OP2
 | OP1
 | OP3 | 1 | 3 | 2 | 0 | 1 | 1 | 2 | 2 | 0 | 0 | 3 | 1 | 2 | 4 | 2 | 1
 | OP3 | 1 | 3 | 2 | 1 | 0 | 1 | 2 | 0 | 0 | 0 | 0 | 1 | 2 | 1 | 0 | 1
 | OP1
 | OP2
 | OP3
 | OP3
 | OP2
 | OP1
 | OP2
 | OP3
 | OP1
 | OP2
 | OP1
 | OP3
 | OP2
 | OP2
 | OP1
 | OP2
 | OP1
 | OP2
 | OP3 | 2 | 3 | 3 | 0 | 0 | 2 | 2 | 1 | 0 | 0 | 2 | 1 | 2 | 1 | 2 | 1
 | OP1
 | OP1
 | OP3
 | OP2
 | OP1
 | OP2
 | OP2
 | OP2
 | OP2
 | OP2
 | OP2
 | OP3
 | OP2
 | OP2
 | OP3
 | OP2
 | OP3
 | OP2
 | OP3 | 2 | 1 | 3 | 0 | 0 | 1 | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 2 | 1 | 3
 | OP3
 | OP2
 | OP3
 | OP3
 | OP1
 | OP1 | 0 | 3 | 3 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 3 | 2 | 0 | 2 | 1 | 2
 | OP2
 | OP2
 | OP2
 | OP1
 | OP2
 | OP1
 | OP2
 | OP3 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0
 | OP3 | 0 | 2 | 2 | 1 | 0 | 2 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0
 | OP1
 | OP2
 | OP1
 | OP1
 | OP1
Spreadsheet: 838272d1690887152-working-hours-calculation-book1
Sheet: Sheet1

Start | End | Total Hours/Mins | Actual Working Hours | Rationale
2023-07-03 08:00:00 | 2023-07-03 14:55:00 |  | 6 | All time within working hours so straight forward calculation
2023-07-03 08:00:00 | 2023-07-04 12:00:00 |  | 20 | Applicable hours - 08:00-23:00 on first day, 07:00-12:00 on second day
2023-07-03 17:00:00 | 2023-07-06 16:00:00 |  | 47 | Applicable hours - 17:00-2300 on first day, 07:00-2300 on second and third day, 07:00-16:00 on fourth day
2023-07-07 16:00:00 | 2023-07-09 18:00:00 |  | 29 | Applicable hours - 16:00-23:00 on first day, 07:00-2300 on second day, 08:00-16:00 on third day (Sunday)
Spreadsheet: chris_stokley__3913__ways to book deals in the short term
Sheet: Sheet1

Different Ways of Booking Retail Transactions
For the short term, there are two ways of booking bundled transactions into the system for valuation and position
purposes.
Methodology #1
Allocate the entire customer contract price associated with a transaction to one specific risk type - preferably
the wholesale price.  Any other price component of the transaction would be valued as a $0 fixed price against
its corresponding curve.
Methodology #2
Allocate portions of the customer contract price to each risk type.  The system will value the difference
between the fixed price assigned to each risk component and its corresponding curve.
There is no difference between position or sensitivity reporting for methodologies 1 and 2.  The only
difference will be the initial bucketing of P&L on day one.  If the individual price components of a
transaction are allocated to different people, #1 is not acceptable.  However, if one desk is responsible for
all commodity risks (not including volumetric, which is the responsibility of the Site Profile desk), #1 may
be used and is markedly easier in terms of a tactical solution for deal entry.
Examples of initial booking and subsequent curve shift calculations for each follows below:
Assumptions |  |  | Day 1 | Day 2 | Day 3
Load (MWhrs) |  |  | 1 | 1 | 1
Customer contract price |  |  | 50 | 50 | 50
Wholesale curve price |  |  | 40 | 41 | 36
Ancillary curve price |  |  | 2 | 3 | 4
Congestion curve price |  |  | 3 | 4 | 3
Bundled curve price
Fixed prices booked in system |  |  | Methodology 1 | Methodology 2
Wholesale fixed price |  |  | 45 | 50
Ancillary fixed price |  |  | 2 | 0
Congestion fixed price |  |  | 3 | 0
Total price
Booking Methodology #1
Methodology #1 MTM values |  |  | Day 1 | Day 2 | Day 3
Wholesale book
Ancillary book
Congestion book
Total book value
Methodology #1 curve shift |  |  | Day 1 | Day 2 | Day 3
Wholesale curve shift |  |  | 0
Ancillary curve shift |  |  | 0
Congestion curve shift |  |  | 0
Total curve shift
Booking Methodology #2
MTM values |  |  | Day 1 | Day 2 | Day 3
Wholesale book
Ancillary book
Congestion book
Total book value
Curve shift |  |  | Day 1 | Day 2 | Day 3
Wholesale curve shift |  |  | 0
Ancillary curve shift |  |  | 0
Congestion curve shift |  |  | 0
Total curve shift
RESULTS
Book value comparison |  |  | Day 1 | Day 2 | Day 3
Wholesale book
Ancillary book
Congestion book
Total book value
Curve shift comparison |  |  | Day 1 | Day 2 | Day 3
Wholesale curve shift
Ancillary curve shift
Congestion curve shift
Total curve shift
Spreadsheet: 64818cae-afa7-43c8-9dbe-173956d84b89
Sheet: Spring 2016

2015-2016 Class Schedule |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | You may select up to three classroom attributes.  Select only course requirements, as the number of available classrooms will be reduced with each attribute selected.
EdD
Spring 2016
Subject | Course and Title | Subtitle/Alternate Title | Section | [NAME] | Part of Term | Dates | Days | Times | Credits | Instructor(s) | Instructor ID | FT or Adj | Contract Code | Percentage | Registration Approval | [NAME] | Blackboard Y/N | Campus: [NAME], [NAME], Online, Blended |  |  |  | Cross list?   SUBJ CRSE SEC | Comments
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Classroom Attribute A | Classroom Attribute B | Classroom Attribute C
Spreadsheet: mary_fischer__25619__77L
Sheet: E20.XLS

ENRON CORP AND CONSOLIDATED SUBSIDIARIES
COMPANY # 077L
COMPANY NAME   PBM Mechanical Inc.
ANALYSIS OF OTHER INCOME AND DEDUCTIONS
FOR THE 6 MONTHS ENDED 6-30-2001
 |  |  |  |  |  |  |  |  |  | E-20
[NAME] |  | 1ST QTR |  | 2ND QTR |  | 3RD QTR |  | 4TH QTR |  | YEAR TO DATE
OTHER INCOME - OTHER
(PROVIDE DETAIL OF INDIVIDUAL ITEMS
IN EXCESS OF $200,000.)
Misc Inc.  Coded to Gain/Loss Acct in error |  | 511 |  | 6
Total Other Income - Other
(MUST TIE TO HYPERION ACCOUNT 1690)
Income Accts:  DR/(CR)
Reverse signs from Hyperion
[NAME] |  | 1ST QTR |  | 2ND QTR |  | 3RD QTR |  | 4TH QTR |  | YEAR TO DATE
OTHER DEDUCTIONS - OTHER
(PROVIDE DETAIL OF INDIVIDUAL ITEMS
IN EXCESS OF $200,000.)
Total Other Deductions - Other
(MUST TIE TO HYPERION ACCOUNT 1775)
Asset/Expense Accts:  DR/(CR)
Same signs as Hyperion
 |  |  |  |  |  |  |  |  |  | E-20
Spreadsheet: 813149d1673582111-cost-allocation-schedule-once-trigger-engaged-sample-cost-allocation
Sheet: Sheet1

 |  | Challenge: | I want the cost of the project to begin allocating the project cost ($1m) in the month the project starts (March 2023).
 |  | Project cost: | 1000000
 |  | Month | Cost Allocation |  |  |  | 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 | 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 | 2025-01-01 00:00:00 | 2025-02-01 00:00:00 | 2025-03-01 00:00:00 | 2025-04-01 00:00:00 | 2025-05-01 00:00:00 | 2025-06-01 00:00:00 | 2025-07-01 00:00:00 | 2025-08-01 00:00:00 | 2025-09-01 00:00:00 | 2025-10-01 00:00:00 | 2025-11-01 00:00:00 | 2025-12-01 00:00:00
 |  | 1 | 0.02
 |  | 2 | 0.05 |  |  | Project starts ("1") |  |  | 1
 |  | 3 | 0.05
 |  | 4 | 0.08 |  |  | Desired result
 |  | 5 | 0.12
 |  | 6 | 0.165
 |  | 7 | 0.165
 |  | 8 | 0.12
 |  | 9 | 0.08
 |  | 10 | 0.05
 |  | 11 | 0.05
 |  | 12 | 0.05
 |  | Total
Spreadsheet: 709710d1608512260-compare-to-cells-bouwcenter-poule-f1-2021-v3
Sheet: Coureurs

44 - [NAME], Mercedes
77 - Valtteri Bottas, Mercedes
55 - [NAME], Ferrari
16 - [NAME], Ferrari
11 - Sergio Perez, Red Bull-Honda
33 - Max Verstappen, Red Bull-Honda
4 - Lando Norris, [NAME]
3 - Daniel Ricciardo, [NAME]
14 - Fernado Alonso, [NAME]
31 - Esteban Ocon, Alpine-Renault
5 - Sebastian Vettel, [NAME]
18 - Lance Stroll, [NAME]
10 - [NAME], Tauri-Honda
22 - [NAME], Tauri-Honda
7 - Kimi Raikkonen, [NAME]
99 - Antonio Giovinazzi, [NAME]
47 - Mick Schumacher, Haas-Ferrari
9 - Nikita Mazepin, [NAME]
6 - [NAME], Williams-Mercedes
63 - [NAME], Williams-Mercedes
Spreadsheet: 823953d1680207798-matching-two-columns-and-returning-the-third-s666-pq-matching-two-columns-and-returning-the-third-v2
Sheet: Lists

Regular Outgoings List
DescriptionKey | Amount | Category
UKI T/A DIRECTLINE | -10 | wife
UKI T/A DIRECTLINE | -20 | me
UKI T/A DIRECTLINE | -30 | dog
UKI T/A DIRECTLINE | -40 | extra
Savings Account | -50 | To Savings
SAVINGS ACCOUNT | 60 | From Savings
BRITISH GAS | -20 | Energy
WATER | -150 | Energy
EE LIMITED |  | Mobile
INSURANCE | -20 | Car Insurance
TESCO STORES |  | Food
SAINSBURYS S/MKTS |  | Food
AMZNMKTPLACE |  | Amazon
Spreadsheet: 474868d1470939093-identify-duplicate-values-in-multiple-columns-duplicates
Sheet: Sheet1

firm | 2000-08-01 00:00:00 | firms | 2000-09-01 00:00:00 | firms | 2000-10-01 00:00:00 | firms | 2000-11-01 00:00:00 | firms | 2000-12-01 00:00:00
SOUTH AFN.COAL MNG.HDG. (~U$) | 0.19 | SOUTH AFN.COAL MNG.HDG. (~U$) | 0.19 | SOUTH AFN.COAL MNG.HDG. (~U$) | 0.18 | SOUTH AFN.COAL MNG.HDG. (~U$) | 0.17 | ORION REAL ESTATE (~U$) | 0.16
MINE RESTORATION INVS. (~U$) | 0.21 | MINE RESTORATION INVS. (~U$) | 0.21 | MINE RESTORATION INVS. (~U$) | 0.2 | MINE RESTORATION INVS. (~U$) | 0.19 | MINE RESTORATION INVS. (~U$) | 0.19
VILLAGE MAIN REEF DEAD - 02/06/15 (~U$) | 0.39 | BUILDMAX (~U$) | 0.48 | SILVERBRIDGE HDG. (~U$) | 0.26 | SILVERBRIDGE HDG. (~U$) | 0.33 | SILVERBRIDGE HDG. (~U$) | 0.24
QUANTUM PROPERTY GROUP (~U$) | 0.64 | QUANTUM PROPERTY GROUP (~U$) | 0.54 | VILLAGE MAIN REEF DEAD - 02/06/15 (~U$) | 0.4 | QUANTUM PROPERTY GROUP (~U$) | 0.35 | QUANTUM PROPERTY GROUP (~U$) | 0.27
AFRICAN DAWN CAP. (~U$) | 0.71 | AFROCENTRIC INV. (~U$) | 0.56 | QUANTUM PROPERTY GROUP (~U$) | 0.41 | VILLAGE MAIN REEF DEAD - 02/06/15 (~U$) | 0.38 | VILLAGE MAIN REEF DEAD - 02/06/15 (~U$) | 0.36
NICTUS BEPERK (~U$) | 0.71 | AFRICAN DAWN CAP. (~U$) | 0.71 | BUILDMAX (~U$) | 0.46 | BUILDMAX (~U$) | 0.44 | BUILDMAX (~U$) | 0.43
BAUBA PLATINUM (~U$) | 0.77 | AWETHU BREWERIES (~U$) | 0.73 | AFROCENTRIC INV. (~U$) | 0.58 | AWETHU BREWERIES (~U$) | 0.55 | SANTOVA (~U$) | 0.58
AFROCENTRIC INV. (~U$) | 0.81 | NICTUS BEPERK (~U$) | 0.77 | AFRICAN DAWN CAP. (~U$) | 0.68 | AFROCENTRIC INV. (~U$) | 0.74 | AFRICAN DAWN CAP. (~U$) | 0.72
ECSPONENT (~U$) | 0.86 | SILVERBRIDGE HDG. (~U$) | 0.81 | NICTUS BEPERK (~U$) | 0.73 | AFRICAN & OS.ENTS. (~U$) | 0.76 | AFROCENTRIC INV. (~U$) | 0.73
AWETHU BREWERIES (~U$) | 0.9 | ECSPONENT (~U$) | 0.96 | AFRICAN & OS.ENTS. (~U$) | 0.79 | SANTOVA (~U$) | 0.78 | BAUBA PLATINUM (~U$) | 0.73
BUILDMAX (~U$) | 0.9 | SPANJAARD (~U$) | 0.99 | ECSPONENT (~U$) | 1.01 | NICTUS BEPERK (~U$) | 0.86 | ISA (~U$) | 0.75
PSV (~U$) | 0.9 | SANTOVA (~U$) | 1.3 | AWETHU BREWERIES (~U$) | 1.05 | ECSPONENT (~U$) | 0.87 | AFRICAN & OS.ENTS. (~U$) | 0.76
SILVERBRIDGE HDG. (~U$) | 0.9 | AFRICAN & OS.ENTS. (~U$) | 1.31 | ADAPTIT HOLDINGS (~U$) | 1.18 | ISA (~U$) | 0.96 | NICTUS BEPERK (~U$) | 0.86
PURPLE CAPITAL (~U$) | 1.23 | PURPLE CAPITAL (~U$) | 1.35 | BAUBA PLATINUM (~U$) | 1.22 | AFRICAN DAWN CAP. (~U$) | 0.99 | ECSPONENT (~U$) | 0.87
AFRICAN & OS.ENTS. (~U$) | 1.3 | ISA (~U$) | 1.4 | ISA (~U$) | 1.23 | BAUBA PLATINUM (~U$) | 1.16 | AWETHU BREWERIES (~U$) | 0.88