tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 118377d1313638842-matching-indexed-data-from-one-spreadsheet-to-another-example
Sheet: Destination

Item Name | Item ID |  | 41000 |  | 41005 |  | 111100
 |  |  | RECORD #1 |  | RECORD #2 |  | RECORD #3
A | 10
B | 11
C | 12
D | 13
E | 14
F | 15
G | 16
H | 17
I | 18
J | 19
 |  | DataSet |  |  |  | DataSet
 | 100
 | 101
 | 102
 | 103
 | 104
 | 105
 | 106
 | 107
 | 108
 | 109
 | 110
Spreadsheet: 110419d1307084504-offset-to-find-duplicates-offset
Sheet: Sheet1

[NAME] |  | Duplicate
[NAME] |  | [NAME]
[NAME] |  | Fred
[NAME] |  | [NAME]
Fred |  | [NAME]
Fred |  | test
Fred |  | 0
Fred |  | 0
Mark |  | 0
[NAME] |  | 0
[NAME] |  | 0
[NAME]
[NAME]
[NAME]
[NAME]
test
test
Spreadsheet: 724889d1616432022-sum-of-a-sveral-rows-with-the-same-name-book1-1-
Sheet: Sheet1

 |  |  |  |  |  |  | total
 |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  |  | Ealing
 |  | [NAME] | column2 |  |  |  | Fulham
 | [NAME] | 40 | 1 |  |  |  | Harlseden
 | Ealing | 74 | 4 |  |  |  | [NAME]
 | Fulham | 57 | 3 |  |  |  | [NAME]
 | Harlseden | 17 | 0 |  |  |  | Hounslow
 | [NAME] | 3 | 0 |  |  |  | Kingston
 | [NAME] | 43 | 5 |  |  |  | [NAME]
 | Hounslow | 45 | 14 |  |  |  | [NAME]
 | Kingston | 5 | 4 |  |  |  | Uxbridge
 | [NAME] | 35 | 10 |  |  |  | Wandsworth
 | [NAME] | 13 | 14 |  |  |  | Wembley
 | Uxbridge | 42 | 2
 | Wandsworth | 15 | 0
 | Wembley | 19 | 14
 | [NAME] | 10 | 4
 | Ealing | 78 | 8
 | Fulham | 38 | 0
 | Harlseden | 10 | 0
 | [NAME] | 2 | 1
 | [NAME] | 28 | 13
 | Hounslow | 67 | 18
 | Kingston | 4 | 5
 | [NAME] | 36 | 8
 | [NAME] | 6 | 7
 | Uxbridge | 31 | 17
 | Wandsworth | 15 | 0
 | Wembley | 30 | 16
 | [NAME] | 29 | 1
 | Ealing | 83 | 9
 | Fulham | 32 | 3
 | Harlseden | 8 | 8
 | [NAME] | 4 | 0
 | [NAME] | 25 | 19
 | Hounslow | 54 | 8
 | Kingston | 0 | 10
 | [NAME] | 9 | 8
 | [NAME] | 4 | 10
 | Uxbridge | 23 | 10
 | Wandsworth | 6 | 4
 | Wembley | 26 | 18
Spreadsheet: 106211d1303394313-predicting-values-for-non-linear-set-of-data-complexforcastminmax
Sheet: Sheet1

Name | Column 1 | Column 2 |  | Using Forecast by including all values | Using Forecast with specific interval needed
Test 1 | 0 | 1133909
Test 2 |  | 1357848
Test 3 |  | 1426248
Test 4 |  | 1435511
Test 5 |  | 1735982
Test 6 |  | 2046423
Test 7 | 28.6 | 2599644
Test 8 | 28.6 | 2731462 |  |  | This column represents the values I need, but I do not want to set this up manually for every interval.
Test 9 |  | 2953229 |  |  | I need the formula to be able to find the correct interval.
Test 10 |  | 3538803
Test 11 |  | 4453796
Test 12 |  | 6054951
Test 13 |  | 6055103
Test 14 |  | 6055169
Test 15 |  | 6055192
Test 16 |  | 6328295
Test 17 |  | 6328606
Test 18 |  | 6328663
Test 19 | 33.5 | 6545742
Test 20 | 28 | 6700482
Test 21 | 35.4 | 7020916
Test 22 |  | 7027381
Test 23 |  | 7027686
Test 24 |  | 7157449
Test 25 |  | 7158485
Test 26 |  | 7321401
Test 27 | 37.4 | 7355582
 |  |  |  |  | Test 1 | 0 | 1133909
 |  |  |  |  | Test 7 | 28.6 | 2599644
 |  |  |  |  | Test 8 | 28.6 | 2731462
 |  |  |  |  | Test 19 | 33.5 | 6545742
 |  |  |  |  | Test 20 | 28 | 6700482
 |  |  |  |  | Test 21 | 35.4 | 7020916
 |  |  |  |  | Test 27 | 37.4 | 7355582
Spreadsheet: 34748d1232059776-formula-to-display-leftmost-cell-in-a-row-with-a-value-new-microsoft-excel-worksheet
Sheet: Sheet1

 | 2009-01-05 00:00:00 | 2009-01-04 00:00:00 | 2009-01-03 00:00:00 | 2009-01-02 00:00:00 | 2009-01-01 00:00:00
A | 2 |  |  |  | 7
B |  | 4 | 5
C |  |  | 1 | 4
D | 6 |  | 3
E |  |  |  | 3 | 2
A | 2
B | 4
C | 1
D | 6
E | 3
Spreadsheet: sara_shackleton__37335__ownership_int
Sheet: Sheet1

RAPTOR - PUBLIC EQUITY
As of 8/31/00
 | COMMON SHARES |  |  | WARRANTS |  |  | TOTAL |  |  |  |  | PREFERRED |  |  | TOTAL
 |  |  |  |  |  |  | SHARES |  | OWNERSHIP |  |  |  |  |  | SHARES |  | OWNERSHIP
COUNTERPARTY | GROSS | NET |  | GROSS | NET |  | OUTSTANDING |  | INTEREST |  |  | GROSS | NET |  | OUTSTANDING |  | INTEREST
ACTIVE POWER (IPO) | 952382.88 | 952382.88 | D | 324000 | 324000 | D | 37662399 | D
ACTIVE POWER (8/3) |  |  |  | 75000 | 75000 | D |  |  |  |  |  | 220459 | 220459
BEAU CANADA | 7000000 | 4200000 |  |  |  |  | 91981000 | A
PLACE RESOURCES | 1235000 | 741000 |  |  |  |  | 14900000 | A
BRIGHAM RESOURCES | 1052632 | 657895 |  | 1000000 | 625000 |  | 16712908 | B
INLAND RESOURCES | 292098 | 146049 |  |  |  |  | 2897732 | B |  |  |  | 121973 |  |  |  | F
QUEEN SANDS | 2634952 | 1580971 |  |  |  |  | 80688538 | C |  |  |  | 9600000 | 5760000 |  | 9602173 | C
CARRIZO |  |  |  | 250000 | 156250 |  | 14029000 | A
3TEC |  |  |  | 130000 | 78000 |  | 14434000 | A
BONUS | 650000 | 325000 |  |  |  |  | 55984000 | A
PARADIGM | 119782 | 59891 |  |  |  |  | 13191904 | E
TETONKA | 4097122 | 2048561 |  |  |  |  | 27606000 | A
QUICKSILVER | 1340405 | 804243 |  |  |  |  | 18077865 | A
Notes:
A | From Bloomberg, dated 7/31/00
B | Agreed to the June 30, 2000 10Q filing, both the June 30, 2000 Qtr end date amount and the updated 10Q amount.
C | Agreed to the June 30, 2000 10Q filing,  June 30, 2000 date only, not the updated amount on the cover.
D | The amounts shown above for Active Power are as of 8/8/00, when the company went public.
 | The warrants and preferred stock converted at 4.32:1 on that date. Prior to 8/8/00 and on 8/3/00
 | we held 75,000 warrants for common stock and 220,459 shares of series E convertible preferred
 | stock.  The total shares outstanding was obtained from the company's S-1 (A4) filed on 8/7/00.
E | From June 30, 2000 6-K.  6/30/00 balances.
F | Total preferred shares outstanding for Inland Resources could not be found from external sources.
Spreadsheet: 818237d1676655642-conditional-formatting-triggered-using-week-numbers-test-32-
Sheet: Sheet1

 |  |  |  |  |  | w/b | 2023-01-02 00:00:00
 |  |  |  |  |  | w/e
FRUIT |  |  |  |  | Amount | Frequency | week 1 | week 2 | week 3 | week 4 | week 5 | week 6 | week 7 | week 8
Apple |  |  |  |  | 1 | 2x | O |  |  | O |  | C
Orange |  |  |  |  | 2 | 2x |  |  | C |  | C |  | D
Lemon |  |  |  |  | 1 | 3x |  | O |  |  |  | O
Grapes |  |  |  |  | 20 | 2x |  | C |  |  |  |  | D | D
[NAME] |  |  |  |  | 1 | 1x |  |  |  | C |  | C |  | D
Spreadsheet: 0fd37f62-bc7f-4d57-bff6-765e70aa7c26
Sheet: Sheet1

Add student achievement/value-added | 66
Unknown, need more information | 36
Add peer observation/evaluation, including mentoring | 34
Much change needed; will start with default model | 22
Add whatever is required/mandated by law to comply | 19
No or very little change to existing process | 16
Include all teachers (tenured, experienced); more observations | 11
Create survey/feedback mechanism | 9
Connect directly to professional development & PLC's | 8
Add portfolio option | 7
Emphasize evaluator training for consistency/formality | 7
Hire more admin. for evaluations | 4
Place heavier emphasis on improvement/remediation | 4
Add personal reflection | 2
Add individual growth plan | 2
Add informal/short observations or walk-throughs | 2
Move to standards-based model | 2
Create appeals process | 1
Spreadsheet: 79233d1279533591-lookup-issue-dd-postcodes
Sheet: Sheet1

Ticket | Postcode | Town | Country
[NAME] | DD81JH |  | Scotland
[NAME] | DD81JH |  | Scotland
[NAME] | DD81JH |  | Scotland
[NAME] | DD81JH |  | Scotland
Spreadsheet: 07a6c842-3097-42b3-827b-60bbbc88b124
Sheet: Sheet1

Supplementary Table 5.  Reproducibility of STRUCTURE runs on the Asia Pacific dataset | Unnamed: 1 | Unnamed: 2
Number of Clusters |  | Individual Similarity coefficients
[NAME] | 5 out of 10 [NAME] and Kol form separate clusters | 0.93 - 0.98
 | 2 out of 10 Aita and New Ireland form separate clusters | 0.97
 | 2 out of 10 Instead of Anem, Europe (French) forms a separate cluster | 0.95
 | 1 out of 10 New Ireland assignment proportions are closer to Bougainville than [NAME]
[NAME] | 6 out of 10 New Ireland forms a separate cluster | 0.93 - 0.97
 | 2 out of 10 Instead of New Ireland, the French form a separate cluster | 0.97
 | 2 out of 10 Instead of [NAME], the French form a separate cluster | 0.81
K=9 | 5 out of 10 Kol/Sulka form a separate cluster | 0.96 - 0.97
 | 4 out of 10 French form a separate cluster | 0.92 - 0.94
 | 1 out of 10 Tolai forms a separate cluster
[NAME] | 15 out of 20 French form a separate cluster | 0.90 - 0.96
 | 2 out of 20 [NAME] form a separate cluster instead of the French | 0.96
 | 1 out of 20 [NAME] come out instead of the French
 | 1 out of 20 Tolai/Mussau/Lavongai form a separate cluster instead of the French
 | 1 out of 20 [NAME] for a separate cluster instead of the [NAME]
[NAME] | 3 out of 10 Tolai form a separate cluster | 0.95
 | 2 out of 10 Melamela/Nakanai(Bileki) for a separate cluster | 0.86
 | 2 out of 10 [NAME] form a separate cluster | 0.94
 | 1 out of 10 Tolai and Lavongai form separate clusters  (instead of the French)
 | 1 out of 10 Nasioi form separate cluster
 | 1 out of 10 Taroko forms a separate cluster
Spreadsheet: cara_semperger__1442__BPA_COB_DECEMBER
Sheet: MONTH

 |  |  | To: BPA [NAME]
 |  |  | From:
 |  |  | [NAME](503)464-3902
 |  |  | [NAME] (503)464-3831
 |  |  | [NAME] (503)464-3814
2001-12-01 00:00:00
 | COB CONTRACT [NAME]
 | HLH
 | MONTH | 25 | C#21896 | X | BPA | ENRON | BPA | X | C#23996 | 25
 | MONTH | 25 | C#23545 | X | BPA | ENRON | BPA | X | [NAME] | 25
 | MONTH | 25 | C#23545 | X | BPA | ENRON | BPA | X | C#23939 | 25
 | LLH
 | MONTH | 25 | C#21896 | X | BPA | ENRON | BPA | X | C#23763 | 25
 | MONTH | 25 | C#23545 | X | BPA | ENRON | BPA | X | C#23764 | 25
 | MONTH | 25 | C#23545 | X | BPA | ENRON | BPA | X | C#23622 | 25
 | MONTH | 25 | BPA C#23547-PGE | X | MIECO | ENRON | BPA | X | C#23420 | 25
 | MONTH | 25 | BPA C#23547-PGE | X | MIECO | ENRON | BPA | X | C#23610 | 25
 | MONTH | 25 | BPA C#23548-PGE | X | MIECO | ENRON | BPA | X | [NAME] | 25
 | MONTH | 25 | BPA C#23548-PGE | X | MIECO | ENRON | BPA | X | [NAME] | 25
Spreadsheet: 40732d1239130521-sumproduct-question-piechartmappingexample
Sheet: Breakdown Det

Account Mapping
Period
2
Major Account | Minor Account | Name of GL Account | Account Number | Monthly Ammount
Direct Material | Freight | COGS - OTHER MATERIALS | 400300 | 0
Direct Material | Freight | COGS - PACKAGING | 400600 | -851.72
Direct Material | Freight | PPV OUTSIDE SERVICES | 500500 | -376.14
Direct Material | Freight | PPV PACKAGING | 500600 | 4036.4
Direct Material | Freight | O/S FREIGHT | 500800 | 3072.45
Spreadsheet: 0141deab-3747-41aa-bc01-b2965e0d5a3b
Sheet: TR_TOUTPC

Tariff - Through or Out Service Penalty Charges
TR_TOUTPC_<customer id>_<settlement date>_<version>.CSV
Date: <mm/dd/yyyy> and Version: <mm/dd/yyyy hh:[NAME]:ss> GMT
Customer ID | [NAME] Number | [NAME] Name | OASIS Assignment Reference Number | Point of Receipt | Point of Delivery | Transmission Priority | Duration | Day | Hour | Reservation Amount | Scheduled Amount | Through or Out Excess Use Penalty Charge | ISO OATT Schedule 1 Excess Use Penalty Charge | ISO SFT Schedule 1 Excess Use Penalty Charge
Number | String | String | Number | String | String | String | String | Date | Date | MW | MW | $ | $ | $
Spreadsheet: 868195d1714947107-calculating-start-time-when-shifts-go-past-midnight-schedule-example
Sheet: Sheet1

Date | ID | Start | Stop | Duration | Schedule Code
2102024 | 316048 | 21:00:00 | 01:00:00
2102024 | 316048 | 01:30:00 | 05:00:00
2102024 | 316048 | 05:30:00 | 08:00:00
2102024 | 312969 | 22:00:00 | 01:30:00 |  |  |  |  |  | 2102024-316048
2102024 | 312969 | 02:00:00 | 05:30:00 |  |  |  |  |  | 2102024-312969
2102024 | 312969 | 06:00:00 | 09:00:00 |  |  |  |  |  | 2102024-313972
2102024 | 313972 | 21:00:00 | 00:00:00 |  |  |  |  |  | 2102024-21396
2102024 | 313972 | 04:31:00 | 07:00:00 |  |  |  |  |  | 2102024-22114
2102024 | 21396 | 22:34:00 | 00:00:00 |  |  |  |  |  | 2102024-22189
2102024 | 21396 | 01:00:00 | 02:30:00 |  |  |  |  |  | 2102024-22255
2102024 | 21396 | 03:04:00 | 04:30:00 |  |  |  |  |  | 0
2102024 | 21396 | 04:32:00 | 07:00:00
2102024 | 22114 | 15:31:00 | 20:00:00
2102024 | 22114 | 20:30:00 | 00:00:00
2102024 | 22189 | 15:30:00 | 19:30:00
2102024 | 22189 | 20:04:00 | 00:00:00
2102024 | 22255 | 22:31:00 | 03:00:00
Spreadsheet: 167053d1341882803-how-to-pick-up-the-numbers-from-the-data-but-not-duplicate-them-by-formula-pt123count-of-sales
Sheet: Sheet1

Sales No | Data
Sales1 | 100
Sales2 | 20
Sales3 | 100 |  | Row Labels | Count of Data2 | Sum of Data
Sales4 | 100 |  | 20 | 1 | 20
Sales5 | 200 |  | 40 | 2 | 80
Sales6 | 200 |  | 100 | 3 | 300
Sales7 | 300 |  | 200 | 2 | 400
Sales8 | 400 |  | 300 | 1 | 300
Sales9 | 555 |  | 400 | 1 | 400
Sales10 | 40 |  | 500 | 1 | 500
Sales11 | 500 |  | 555 | 3 | 1665
Sales12 | 663 |  | 663 | 1 | 663
Sales13 | 555 |  | Grand Total | 15 | 4328
Sales14 | 555
Sales15 | 40
Spreadsheet: 798360d1664444058-using-multiple-variables-for-a-several-functions-from-a-table-tepeln-z-a-
Sheet: Hárok1

 |  |  |  |  |  |  | okná
miestnosť |  |  |  | stena |  |  |  |  | horizontálne tienidlo |  | vertikálne tienidlo |  |  |  |  | strop
číslo miestnosti | [NAME] | účel miestnosti | teplota interiéru | [NAME] stien | U vonk. stien | [NAME] | šírka okna | [NAME] | dĺžka | vzdialenosť od ostenia | dĺžka | vzdialenosť od ostenia | U okna | [NAME] | [NAME] | U stropu (len pri poslednom podlaží)
 | 100 |  | 20 | 50 | 0.22 | J | 1.35 | 1.8 | 0.45 | 0 |  |  | 0.85 | [NAME] | žiadny | 0
[NAME] (W)
a) Tepelné zisky od vnútorných zdrojov tepla
a1.) [NAME] od ľudí
[NAME] (-) |  |  |  | [NAME] človeka (W) pre teplotu
muži | [NAME] | [NAME] | celkovo | aktivita | teplota vn. vzduchu | teplo     (W)
2 | 2 |  |  | sediaci, mierne aktívny | 21
a2.) [NAME] od svietidiel
[NAME] osvetlená svietidlami |  |  |  | [NAME] (W/m2)
[NAME] miestnosti | [NAME] osvetlenia denným svetlom |  | A                    (m2) | Pracovisko | q        (W/m2)
 | [NAME] |  |  | skladisko, byty, reštaurácie, divadlá
a3.) [NAME] od elektromotorov
spotrebič č. | 1 | 2 | 3
typ | Chladnička 100l
[NAME] (W)
[NAME]) [NAME] od elektrických a elektronických zariadení
spotrebič č. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10
typ | počítač s monitorom | počítač s monitorom | [NAME] |  |  |  |  |  |  |  | iné (zadaj)
[NAME] (W)
ks | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
b) Tepelné zisky od vonkajších zdrojov tepla
b1.) [NAME] oknami
[NAME] | [NAME] | [NAME] radiácie
[NAME] |  | teplota
[NAME] (m2) | súčiniteľ prechodu tepla | vnútorný vzduch | vonkajší vzduch
radiácia |  |  |  |  |  |  |  |  | súčiniteľ tienenia
[NAME] | šírka presklenia | dĺžka horizontálneho tienidla | dĺžka vertikálneho tienidla | vzdialenosť horizontálneho tienenia od ostenia | vzdialenosť vertikálneho tienenia od ostenia | rozdiel azimuitov | dĺžka vodorov. tieňa | dĺžka zvislého tieňa | [NAME] | [NAME] | spolu | [NAME]
b2.) [NAME] stenami a stropmi
stena
 |  | teplota
súčiniteľ prestupu tepla | [NAME] steny | interiér | exteriér | [NAME]
strop (ak je to posledné podlažie)
 |  | teplota
súčiniteľ prestupu tepla | [NAME] stropu | interiér | exteriér | [NAME]
 |  |  | 33.6
Spreadsheet: 135748d1326216575-auto-transfer-data-from-master-sheet-to-individual-worksheets-nbastatistics
Sheet: NJ

New Jersey |  |  |  |  | NJ
Away Games |  | 6 | Home Games |  | 4
Points Scored | Points Allowed |  | Points Scored | Points Allowed
90 |  |  | 70
78 |  |  | 94
98 |  |  | 90
82 |  |  | 101
70
97
Spreadsheet: 151504d1334946311-using-vlookup-funtion-within-if-statement-test_1
Sheet: DataLists

 |  |  |  | 2 LAKH |  |  | SERVICE TAX EXTRA
 |  |  |  |  |  |  |  |  |  |  |  |  | Age | Sum Insured (in Lacks) | No of Persons
1A | MEMBER | 0-25YRS | 26-35YRS | 36-40YRS | 41-45YRS | 46-50 YRS | 51-55 YRS | 56-60 YRS | 61-65 YRS | Sum |  |  | 0-25YRS | 2 | 1A
1C | MEMBER-1 | 2575 | 3075 | 3575 | 4275 | 6625 | 7275 | 9074 | 10123 | 2 |  |  | 26-35YRS | 3 | 1C
2A | MEMBER-2 | 3353 | 4073 | 4733 | 5573 | 9288 | 10198 | 13164 | 14985 | 2 |  |  | 36-40YRS | 4 | 2A
1A+1C | MEMBER-3 | 4016 | 4944 | 5749 | 6665 | 11108 | 12200 | 15759 | 17944 | 2 |  |  | 41-45YRS | 5 | 1A+1C
2C | MEMBER-4 | 4612 | 6007 | 6876 | 7975 | 13292 | 14602 | 18562 | 21140 | 2 |  |  | 46-50 YRS | 7.5 | 2C
2A+1C |  |  |  |  |  |  |  |  |  |  |  |  | 51-55 YRS | 10 | 2A+1C
3A |  |  |  |  |  |  |  |  |  |  |  |  | 56-60 YRS | 15 | 3A
1A+2C |  |  |  |  |  |  |  |  |  |  |  |  | 61-65 YRS |  | 1A+2C
3C |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3C
1A+3C |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1A+3C
2A+2C |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2A+2C
3A+1C |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3A+1C
4A |  |  |  |  |  |  |  |  |  |  | Age | Members | [NAME] | Amount | 4A
4C |  |  |  |  |  |  |  |  |  |  | 0-25 | Member1 | 2 | 2575 | 4C
1A |  |  |  |  |  |  |  |  |  |  |  | Member2 |  |  | 1A
 |  |  |  |  |  |  |  |  |  |  |  | Member3
 |  |  |  | 3 LAKH |  |  | SERVICE TAX EXTRA |  |  |  |  | Member4
 | MEMBER | 0-25YRS | 26-35YRS | 36-40YRS | 41-45YRS | 46-50 YRS | 51-55 YRS | 56-60 YRS | 61-65 YRS
 | MEMBER-1 | 3625 | 4275 | 4775 | 5715 | 7992 | 8779 | 10545 | 13250
 | MEMBER-2 | 4718 | 5363 | 6129 | 7445 | 11202 | 12303 | 15817 | 19874
 | MEMBER-3 | 5420 | 6413 | 7332 | 8764 | 13404 | 14726 | 18943 | 23812
 | MEMBER-4 | 6227 | 7547 | 8631 | 10322 | 16048 | 17634 | 22694 | 28064
Spreadsheet: 747953d1631801356-removed-duplicate-values-from-2-lists-to-give-only-the-unique-values-in-list-3-example-1
Sheet: Example

Header1 | Header2 |  | Header3 | Header4 |  | Header3 | Header4
A | 1 |  | A | 1 |  |  |  |  | Only want columns G and H to pull through values that are not duplicated between Columns A and B and Columns D and E so the expected result would be pulling what I have typed into G and H.
B | 2 |  | C | 3
C | 3 |  | E | 5
D | 4 |  | G | 7
E | 5 |  | I | 9
F | 6 |  | K | 11
G | 7 |  | M | 13
H | 8 |  | O | 15
I | 9 |  | Q | 17
J | 10 |  | S | 19
K | 11 |  | U | 21
L | 12 |  | W | 23
M | 13 |  | Y | 25
N | 14
O | 15
P | 16
Q | 17
R | 18
S | 19
T | 20
U | 21
V | 22
W | 23
X | 24
Y | 25
Z | 26
Spreadsheet: 834996d1688219723-excel-get-the-data-after-comparision-sample
Sheet: Sheet1

PRODUCTS | AVAILABLE | IF PRODUCT IS AVAILABLE IN MORE THAN 5 STATES |  |  | ZONE | STATE | STATE | STATE | STATE | STATE | STATE | STATE | STATE
APPLE | State(s) - DELHI | NO |  |  | North | Jammu Kashmir | [NAME] | Delhi | Punjab | Himachal Pradesh | Chandigarh | [NAME]
ORANGE | All India | YES |  |  | Central | Uttar Pradesh | Madhya Pradesh | Chhattisgarh | Uttarakhand
MANGO | State(s) - KARNATAKA, TAMIL NADU, JAMMU & KASHMIR, DELHI, MAHARASHTRA, GUJARAT, ANDHRA PRADESH, UTTAR PRADESH, KERALA, WEST BENGAL, HARYANA, CHANDIGARH, PUNJAB, GOA, HIMACHAL PRADESH, BIHAR, MADHYA PRADESH, SIKKIM, ODISHA, RAJASTHAN, CHHATTISGARH, UTTARAKHAND, [NAME] | YES |  |  | East | Bihar | Odisha | Jharkhand | West Bengal | Sikkim
BANANA | State(s) - GUJARAT | NO |  |  | West | Gujarat | Daman Diu | Maharashtra | Dadra Nagar Haveli | Goa
GRAPES | State(s) - DELHI | NO |  |  | South | Karnataka | Kerala | [NAME] | Telangana | [NAME] | [NAME] | Andaman Nicobar | Lakshadweep
PINAPPLE | State(s) - UTTAR PRADESH | NO |  |  | Northeast | Manipur | Mizoram | Tripura | Nagaland | Meghalaya | Assam | Arunachal Pradesh
PEANUT | State(s) - UTTAR PRADESH | NO
TOMATO | State(s) - MADHYA PRADESH | NO
POTATO | All India | YES
CARROT | State(s) - MADHYA PRADESH | NO
OIL | State(s) - JAMMU & KASHMIR, DELHI, HARYANA, CHANDIGARH, PUNJAB, HIMACHAL PRADESH, RAJASTHAN | YES
 | NOTE
 | THE PRDUCT IS AVAILABLE IN SOME STATES BUT I WANT THE ONLY THOOSE PRODUCTS WHICH ARE AVALABLE IN MORE THAN 5 STATES.
Spreadsheet: 81781d1281951522-changing-cell-or-weighting-values-if-more-than-consecutive-cells-the-same-value-example-spreadsheet-for-forum
Sheet: Job Summaries

 |  |  | Louis |  |  |  | Oli |  |  | [NAME] |  |  | [NAME]
Job No. | Address | Description | Hours | Cost | Charged at | Total Charge | Hours | Cost | Charged at | Hours | Cost | Charged at | Hours | Cost | Charged at
SPM0357 |  |  | 0.5 | 5.77 | 22 | 11
SPM0033 |  |  | 8.5 | 98.08999999999999 | 22 | 187
[NAME] |  |  | 5.5 | 63.47 | 22 | 121
 |  |  | 0
 |  |  |  | 2
Spreadsheet: 135345d1325960219-count-if-count-20if-1-
Sheet: Sheet1

 | sat | [NAME] | mon | tue | wed | thu | fri | sat | [NAME] | mon | tue | wed |  | p | ot | a
a | p | p | p | a | a | a | ot | ot | p | p | ot | p
b | p | p | a | p | a | p | ot | ot | p | p | ot | a
c | ot | p | ot | a | a | p | p | ot | p | p | a | a
Spreadsheet: daren_farmer__5099__Hot Loads May 00-01
Sheet: May 2001

 | 2001 | 2001 | 2001 | 2001 | 2001
 | 5 | 5 | 5 | 5 | 5
 | 14 | 15 | 16 | 17 | 18
 | 2 | 3 | 4 | 5 | 6
Hour 1 | 25850.5714285714 | 27163.2 | 28030.0714285714 | 29592.5833333333 | 29707.2
Hour 2 | 24176.3571428571 | 25546.6428571428 | 26314.0714285714 | 27930.7857142857 | 27884.3571428571
Hour 3 | 23283.3333333333 | 24457.0666666666 | 25221.6666666666 | 26755.0666666666 | 26519.4666666666
Hour 4 | 22837.1428571428 | 23835.0714285714 | 24685.7857142857 | 26004 | 25762.5
Hour 5 | 22961.9333333333 | 23750.7142857142 | 24643.4666666666 | 25841.9333333333 | 25743.0666666666
Hour 6 | 24338.9285714285 | 25061.8 | 25911.3571428571 | 27051.4285714285 | 26929.0714285714
Hour 7 | 27060 | 27811.8571428571 | 28777.9285714285 | 29840.9285714285 | 29535.3333333333
Hour 8 | 28654.5 | 29265.5 | 30275.5 | 31306.9333333333 | 30922.9285714285
Hour 9 | 30195.2666666666 | 30642.8 | 31448.8 | 32170 | 32136.8666666666
Hour 10 | 32242.5 | 32305.0714285714 | 32856.1428571428 | 34628.7272727272 | 34006.2142857142
Hour 11 | 34198.1333333333 | 34026.2857142857 | 34795.2666666666 | 36070.2857142857 | 36354.7857142857
Hour 12 | 35830.2307692307 | 35675.6666666666 | 36832.4285714285 | 37483.8666666666 | 38075.8
Hour 13 | 37793.5384615384 | 37140.5 | 38680.4666666666 | 39374.6428571428 | 39833.5714285714
Hour 14 | 39195.8666666666 | 38689.7857142857 | 40545.7142857142 | 41291.1428571428 | 41670.3333333333
Hour 15 | 40454.0714285714 | 40204.4 | 42280.3571428571 | 42816.7333333333 | 43332.5714285714
Hour 16 | 41462.1428571428 | 41649.8571428571 | 43808.3333333333 | 44144.2142857142 | 44233.7142857142
Hour 17 | 42284.9285714285 | 42603.3571428571 | 44786.4285714285 | 44923.3571428571 | 44380.4
Hour 18 | 42081 | 42554.7142857142 | 44925.2666666666 | 44771.5333333333 | 43566.2142857142
Hour 19 | 41033.5333333333 | 41384.0666666666 | 43912.4285714285 | 43489.5714285714 | 41840.8666666666
Hour 20 | 39135.7857142857 | 39574.2857142857 | 42143.8571428571 | 41338.8666666666 | 39909
Hour 21 | 38477.2666666666 | 38752.4666666666 | 41155.3571428571 | 40682.6428571428 | 38957.6428571428
Hour 22 | 37281.8571428571 | 37726.9285714285 | 39976.5384615384 | 39676.5 | 38023
Hour 23 | 33858.8 | 34419.5714285714 | 36319 | 36265.3333333333 | 35532.7142857142
Hour 24 | 30119.8571428571 | 30717.0666666666 | 32579.5714285714 | 32590.1428571428 | 32452.6
[NAME] | 86 | 87 | 91 | 91 | 91
 | 60 | 56 | 68 | 70 | 69
Dallas | 85 | 85 | 87 | 88 | 88
 | 65 | 66 | 69 | 72 | 68
Houston | 87 | 86 | 88 | 87 | 89
 | 64 | 61 | 66 | 69 | 69
Weighted | 85.95 | 85.7 | 88 | 88.05 | 88.85
Average | 63.85 | 62.5 | 67.65 | 70.5 | 68.55
Spreadsheet: 875174d1721749685-what-causes-exceptionally-long-times-to-edit-this-spreadsheet-excel-triage2
Sheet: Sheet1

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