tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: chris_germany__2666__4-6-2000 enroncestransactions
Sheet: Sheet1

 |  |  |  |  |  |  | ENRON - CES  SALES & PURCHASES
For April 6, 2000 business
 |  |  | DELIVERY POINT |  |  | VOLUME |  | PRICE |  | INDEX SPOT POINT OF SALE
Sell Backs: |  |  |  |  |  |  |  |  |  | Gas daily 4/6 pricing
 |  |  | CNG-North -Nimo West |  |  | 71 |  | GD index |  | 3.09 | + variable
 |  |  | CNG-North -Nimo East |  |  | 113 |  | GD index |  | 3.09 | + variable
 |  |  | CNG-South-Hope Gas |  |  | 3 |  | GD index |  | 3.09 | + variable
 |  |  | [NAME] |  |  | 10 |  | GD index |  | 3.13
 |  |  | [NAME] |  |  | 25 |  | GD index |  | 3.13
 |  |  | Algonquin - Boston gas |  |  | 500 |  | GD index |  | 3.13
 |  |  | Texas Gas - CGE |  |  | 700 |  | GD index |  | 2.83 | + variable
 |  |  | AGL-Sonat |  |  | 4136 |  | negotiated |  | 2.965
Additional Purchases
 |  |  | Tetco M-3 PECO |  |  | 334 |  | GD index |  | 3.17
 |  |  | National Fuel- PA |  |  | 90 |  | Negotiated |  | To be determined
TCO - FSS Storage inj/with changes
 |  |  | Scheduled for Injection |  |  |  | Revised Injection Schedule
 |  | 2000-04-06 00:00:00 |  | 21282 |  |  |  | 13181 |  | due to 8116 increased demand on TCO at citygates
Spreadsheet: 883182d1731679915-use-the-other-formula-instead-of-vlookup-formula-file-a-vehile-ecel-help-forum-2
Sheet: form

 |  |  | ABC INTERNATIONAL COMPANY
 |  |  | OPERATIONAL VEHICLE DUTY SLIP No: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | =VLOOKUP($B4,$B$84:$AK$165,COLUMN(E1),0) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | =VLOOKUP($L$5,data!$A$4:$P$17,4,FALSE)
Name |  |  |  |  |  |  |  | Employe No. |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | =INDIRECT("'"&D6&"'!h21")
Designation |  |  |  |  |  |  |  | Type of Vehicle Required: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | '  =INDIRECT(sheet_name&"!A1") |  |  | =VLOOKUP(Sheet1!#REF!,Sheet1!F4:F24,1,)
Date: |  |  | 2024-11-12 00:00:00 |  |  |  | From |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | =IF(Sheet1!#REF!=F4,Sheet1!F4,Sheet1!E4)
Place / Address where vehicle required: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | =IF($L$5=data!A2,data!D2,data!D3)
Purpose:-
Place be visited: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | =VLOOKUP($B$9,data!$A$1:$F$11,2,FALSE)
Applied By                                  Recommended By                        Approved By
Vehicle No. |  |  |  |  |  |  |  |  | Make |  |  |  | Power(CC)
[NAME] at the start of duty:-- |  |  |  |  |  |  |  |  |  |  |  |  | at the end of duty
Total running of this visit:-
Signature of Driver |  |  |  |  |  |  |  |  |  |  |  |  | Signature of [NAME]
 |  |  | I used here [NAME] formula, I want to use another formula for dynmic range and spell all the values
 |  |  | from sheet2(data)…
Spreadsheet: 183948d1349100436-need-help-with-conditional-formatting-problem-please-help-tf-performance-2-latest-q3
Sheet: Sheet3

Ops # | Month | Date | Year | Client | Buyer | Cargo Type | Nominated Cargo Quantity (MT) | Support Craft | Invoiced Ammount ($) | Commenced Fendering | Completed Fendering | Total Fendering Time | Mooring Master
685 | September | Danco Investment Ltd | 2011 | Vitol | [NAME] | AGO | 5538 | Mensah | 9345 | 05:45:00 | 06:40:00 | 00:55:00 | Goodness [NAME]
656 | September |  | 2011 | Vitol | SK shipping | AGO | 4200 | Mensah | 11244.79 | 07:00:00 | 08:00:00 | 01:00:00 | [NAME]
644 | September |  | 2011 | Vitol | Vitol | AGO | 2150 | Mensah | 9802.08 | 07:36:00 | 08:06:00 | 00:30:00
633 | August |  | 2011 | Vitol | SK shipping | AGO | 4200 | Commodore | 11862.5 | 16:10:00 | 17:00:00 | 00:50:00 | [NAME]
629 | August |  | 2011 | Vitol | Agri | AGO | 6150 | Commodore | 12307.29 |  |  | 00:00:00 | Young Ogori
625 | August |  | 2011 | Vitol | Sahara | AGO | 10000 | Mensah | 12772.22 | 06:25:00 | 07:35:00 | 01:10:00 | Philly Okanre
622 | August |  | 2011 | Vitol | Nepal | AGO | 5000 | Mensah | 11212.5 | 17:54:00 | 18:42:00 | 00:48:00 | Philly Okanre
613 | August |  | 2011 | Vitol | Agri | AGO | 6000 | Commodore | 10616.67 | 06:40:00 | 07:55:00 | 01:15:00 | Constain Okain
610 | August |  | 2011 | Vitol | Agri | AGO | 6600 | Commodore | 8352.5 | 08:30:00 | 09:35:00 | 01:05:00 | Young Ogori
563 | July |  | 2011 | Vitol | Imad | AGO | 6000 | Other | $5,059.90 | 10:12:00 | 11:25:00 | 01:13:00 | Young Ogori
562 | July |  | 2011 | Vitol | Capital | AGO | 6000 | Other | $5,036.11 | 09:10:00 | 10:20:00 | 01:10:00 | [NAME]
Spreadsheet: b486f3e6-ccc4-4985-9ba0-fba84847db1a
Sheet: Sheet1

Gene | eQTL | eQTL Pvalue | Tissue | Top metabolic network SNP | r2 | D'
AQP9 | rs1695336 | 0.0046 | liver | rs16939881 | 0.97 | 0.98
AQP9 | rs1825955 | 0.0048 | adipose | rs16939881 | 0.17 | 0.94
SERPINA1 | rs11628917 | 6e-10 | blood | rs1303 | 0.47 | 0.99
SERPINA1 | rs11628917 | 6e-10 | blood | rs28929474 | 0 | 1
SERPINA1 | rs1303 | 0.01 | blood | rs1303 | - | -
SERPINA1 | rs1884549 | 0.0043 | liver | rs1303 | 0.38 | 0.99
SERPINA1 | rs1884549 | 0.0043 | liver | rs28929474 | 0 | 1
Spreadsheet: 673960d1587604477-extract-numbers-from-cell-to-result-in-one-cell-or-3-cells-excel-question-1
Sheet: Sheet1

Description
21-7-14 Turf Royale Turf & Ornamental Yara Wes | 21-7-14
Landscaper's BioNutrition 3-0-3 (20lb) | 3-0-3
Cal-Tec 9% 6-0-0 Growth Products (2.5gal) | 6-0-0
Bonus 0-0-7 w/ .86% Pendi (50lb) | 0-0-7
or
21-7-14 Turf Royale Turf & Ornamental Yara Wes | 21 | 7 | 14
Landscaper's BioNutrition 3-0-3 (20lb) | 3 | 0 | 3
Cal-Tec 9% 6-0-0 Growth Products (2.5gal) | 6 | 0 | 0
Bonus 0-0-7 w/ .86% Pendi (50lb) | 0 | 0 | 7
Spreadsheet: 267510d1380098755-ignore-if-blank-and-check-multiple-cells-for-equal-values-0a219
Sheet: Sheet1

Header1 | Header2 | Header3 | Header4 | Header5 | Header6 | Header7 | Header8 | Header9
2 |  | 2 |  |  |  |  | 2
2 |  | 2 |  |  | 2 |  |  | 2
1 | 2 | 1 |  |  |  | 1
1 |  |  |  | 1 |  |  | 1
Spreadsheet: 742035d1627484590-formula-to-return-true-if-values-are-opposite-and-equal-in-col-h-formula-to-return-true-if-exact-match-found-for-debit-and-credit-value
Sheet: Sheet1

Reference | Source | Run | A/C | Date | Debit | Credit | Balance |  | True / False
MLO1 | Purchase Ledger |  |  | 2021-07-12 00:00:00 | 0 | 2362.98
KLZ112 | Purchase Ledger |  |  | 2021-07-13 00:00:00 | 2362.98 | 0
788215 | Sales Ledger |  |  | 2021-07-28 00:00:00 | 0 | 2362.98
ML10565 | Purchase Ordering |  |  | 2021-07-07 00:00:00 | 11061.18 | 0 | 11061.18
ML10568 | Sales Ledger |  |  | 2021-07-28 00:00:00 | 0 | 11061.18 | -11061.18
Spreadsheet: 272180d1382257170-need-formulas-over-my-head-sample-worksheet
Sheet: Sheet1

 |  | 1 |  |  | 2
S3 QUALITY | Job ID: |  |  | Job ID:
ASSURANCE REPORT | D Date/Time: |  |  | D Date/Time:
 | T Date/Time: |  |  | T Date/Time:
 | Turnaround Time: |  |  | Turnaround Time:
Error Categories
CRITICAL ERRORS | #Errors: | Error Value | Total Value | #Errors: | Error Value | Total Value
Incorrect Physician Identification |  | 3 |  |  | 3
Omitted Medical Dictation |  | 3 |  |  | 3
NONCRITICAL ERRORS
Abuse of Blanks |  | 1.5 |  |  | 1.5
Medical Context Error |  | 1.5 |  |  | 1.5
MINOR ERRORS
Typographical Error |  | 0.5 |  |  | 0.5
Punction Error |  | 0.5 |  |  | 0.5
Total Error Score
TOTAL QA SCORE
AVERAGE QA SCORE
AVERAGE TURNAROUND TIME
Spreadsheet: 123682d1317806238-subsidiaries-or-not-example-5-
Sheet: Sheet1

Firm_id | UK | US | Aruba | Tanzania | Morocco | Firm investment in country with Smoking Ban | teylyn |  | Country | No Smoking Ban
1 | 3 | 4 | 0 | 1 | 0 | 1 |  |  | UK | 0
2 | 0 | 0 | 1 | 0 | 1 | 1 |  |  | US | 0
3 | 0 | 0 | 0 | 0 | 0 | 0 |  |  | Aruba | 1
4 | 1 | 0 | 0 | 0 | 0 | 0 |  |  | Tanzania | 1
5 | 25 | 13 | 1 | 0 | 0 | 1 |  |  | Morocco | 1
Spreadsheet: 41296d1239792899-vlookup-from-multiple-sheets-shift-schedule
Sheet: PAINTING

PAINTING
[NAME]. | SAP NO. | NAME | SECTION
1 | 171 |  |  | A.
Spreadsheet: 163116d1340196871-averaging-issues-with-div-0-and-excluding-0s-in-linked-workbooks-and-e-o-row-foreach-mo-combined-monthly-ytd-reporting
Sheet: Cooling Water Control

 |  | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME]
 |  | Cl₂ | pH | Cond. | MoO4 | pH | Cond. | Flow | Cl₂ | pH | Cond. | O-PO4 | pH | Cond. | Flow
Month | [NAME] | .3-.5 [NAME] | 8.2-8.4 | 2600-2800 uS | .55-.65ppm | Controller | Controller |  | .3-.5 [NAME] | 8.2-8.4 | 950-1000 ppm | 20-25 ppm | Controller | Controller
 |  | 0.3 | 8.2 | 2600 | 0.55 |  |  |  | 0.3 | 8.2 | 950 | 20
 |  | 0.5 | 8.4 | 2800 | 0.65 |  |  |  | 0.5 | 8.4 | 1000 | 25
January | Total Average
 | % Outside Parameters
February | Total Average
 | % Outside Parameters
March | Total Average
 | % Outside Parameters
April | Total Average
 | % Outside Parameters
May | Total Average
 | % Outside Parameters
June | Total Average
 | % Outside Parameters
July | Total Average
 | % Outside Parameters
August | Total Average
 | % Outside Parameters
September | Total Average
 | % Outside Parameters
October | Total Average
 | % Outside Parameters
November | Total Average
 | % Outside Parameters
December | Total Average
 | % Outside Parameters
Yearly | Total Average
Yearly | [NAME] Outside Parameters
Spreadsheet: 0aa9d922-a698-41bc-aa92-d34a32b067cd
Sheet: Sheet1

Ledigheds- og jobindikatorer. Antal langtidsledige personer. A-dagpenge | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
 |  | 2011-06-01 00:00:00 | 2012-06-01 00:00:00
 |  | Antal langtidsledige | Antal langtidsledige
 |  | personer | personer | Udvikling i antal | Udvikling i pct.
Hele landet | A-kasse i alt | 46312 | 41853 | -4459 | -0.09628174123337364
 | Lærernes A-kasse | 512 | 750 | 238 | 0.46484375
 | Socialpædagogernes landsdækkende A-Kasse | 288 | 401 | 113 | 0.3923611111111111
 | BUPL, A-kasse | 520 | 710 | 190 | 0.3653846153846154
 | FOA - Fag og Arbejdes A-kasse | 1692 | 2096 | 404 | 0.2387706855791962
 | Danske Sundhedsorganisationers A-kasse | 183 | 224 | 41 | 0.2240437158469945
 | Funktionærernes og Servicefagenes A-kasse | 316 | 376 | 60 | 0.189873417721519
 | CA, A-kasse | 633 | 693 | 60 | 0.0947867298578199
 | Akademikernes A-Kasse | 1418 | 1511 | 93 | 0.06558533145275035
 | [NAME], A-Kasse For [NAME] | 540 | 565 | 25 | 0.04629629629629629
 | Frie Funktionærers A-kasse | 450 | 464 | 14 | 0.03111111111111111
 | FTF- A-kasse | 1429 | 1463 | 34 | 0.02379286214135759
 | [NAME] A-kasse | 1742 | 1761 | 19 | 0.01090700344431688
 | Magistrenes A-Kasse | 1267 | 1267 | 0 | 0
 | A-kasse-Journalistik, Komm & Sprog | 681 | 668 | -13 | -0.01908957415565345
 | Min A-kasse | 652 | 632 | -20 | -0.03067484662576687
 | Kristelig A-Kasse | 4994 | 4711 | -283 | -0.05666800160192231
 | HK /Danmarks A-kasse | 5381 | 5002 | -379 | -0.07043300501765472
 | ASE | 2031 | 1867 | -164 | -0.08074839980305268
 | Ledernes A-kasse | 1008 | 905 | -103 | -0.1021825396825397
 | Ingeniørernes A-Kasse | 891 | 736 | -155 | -0.1739618406285073
 | Business Danmarks A-Kasse | 440 | 356 | -84 | -0.1909090909090909
 | Fødevareforbundet NNF´s A-kasse | 728 | 578 | -150 | -0.206043956043956
 | [NAME] (3F) A-kasse | 13771 | 10680 | -3091 | -0.2244571926512236
 | Metalarbejdernes A-Kasse | 2535 | 1938 | -597 | -0.2355029585798817
 | Teknikernes A-Kasse | 1154 | 855 | -299 | -0.2590987868284229
 | Byggefagenes A-Kasse | 581 | 377 | -204 | -0.351118760757315
 | El-Fagets A-Kasse | 467 | 263 | -204 | -0.436830835117773
 | A-kasse uoplyst | 8 | 4 | -4 | -0.5
Spreadsheet: tracy_geaccone__40232__enron corp infomation request
Sheet: EGS EXP

 |  | October |  | November |  | December |  | January |  | February |  | March | April | May | June | July | August | September | October | November | December | Total | Comments
Salaries
Benefits
Payroll Taxes
Corporate Allocations & Other |  |  |  |  |  |  |  | 0.9 | 1.9 | 0.9 | 3.9 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9 | 0.9
Travel
Employee-Related Communications |  |  |  | 0.074 |  | 0.074 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Other Employee Expenses |  |  |  |  |  |  |  | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2
Supplies and Computer Expenses |  | 0.316 |  | 0.316 |  | 0.316 |  | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2
Rent & Utilities |  | 0 |  | 0 |  | 0 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Other |  | 0.4 |  | 0.392 |  | 0.392 |  | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812 | 0.812
Subtotal
Depreciation
Amortizations |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Taxes Other Than Income |  | 2.1 |  |  |  |  |  | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1
Outside Services |  |  |  |  |  |  |  | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 | 1.8 |  |  |  |  | 1.8 | 1.8 | 1.8
Rent & Utilities |  | 1.1 |  | 1.1 |  | 1.1 |  | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646 | 0.646
Advertising |  | 0.079 |  | 0.05 |  | 0.05 |  | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1
Other |  | 0 | 1e-09 | 1e-09 |  | 1e-09 |  | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09 | 1e-09
Subtotal
2001 Forecast Expense
Spreadsheet: 0d30fca3-4d53-4644-8f89-48b1c5e9dfcf
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
MNU | Test | MNU | Manganese, 24 Hour, [NAME] | Manganese, 24 Hr, U | Dynamic Reaction Cell-Inductively Coupled Plasma-Mass Spectrometry (DRC-ICP-MS) | [NAME], 24-hour graduated: 24Urine |  |  | 10 | mL | Collection Container/Tube: Clean, plastic urine container with no metal cap or glued insert Submission Container/Tube: Plastic, 10-mL urine tube (Supply T068) or clean, plastic aliquot container with no metal cap or glued insert  [NAME]: 10 mL Collection Instructions: 1. Collect urine for 24 hours. 2. No preservative. 3. See Metals Analysis-Collection and Transport in Special Instructions for complete instructions. 4. Refrigerate specimen within 4 hours of completion of 24-hour collection. Additional Information: 1. 24-Hour volume is required. 2. See [NAME] in Special Instructions for multiple collections. 3. High concentrations of gadolinium and iodine are known to interfere with most metals tests. If gadolinium- or iodine-containing contrast media has been administered, a specimen should not be collected for 96 hours.   Urine Preservative Collection Options Ambient	Yes Refrigerated	Preferred Frozen	Yes 6N HCl	No 50% Acetic Acid	No Na2CO3	No Toluene	No 6N HNO3	No Boric Acid	No Thymol	No | 0.4 mL | Hemolysis	NA Thawing	Warm OK; Cold OK Lipemia	NA Icterus	NA Other	NA | 0-15 years: not established > or =16 years: 0.1-1.2 mcg/specimen | Tuesday, Thursday; 3 p.m. | 1 day | 5 days | 1 | 83785 |  |  |  |  | Rochester
MNU | [NAME] | URINE | [NAME] |  |  |  | Refrigerated | 28 days
MNU | Order Question | TM26 | Collection Duration |  | Plain Text
MNU | Order Question | VL24 | [NAME] |  | Plain Text
MNU | Result | 8080 | Manganese, 24 Hr, U | Manganese, 24 Hr, U | Numeric |  |  |  |  | mcg/spec |  |  |  |  |  |  |  |  |  | 8203-2
MNU | Result | TM26 | Collection Duration | Collection Duration | Alphanumeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 13362-9
MNU | Result | VL24 | [NAME] | [NAME] | Alphanumeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3167-4
MNU | Result | 867 | Mn Concentration | Mn Concentration | Numeric |  |  |  |  | mcg/L |  |  |  |  |  |  |  |  |  | 21382-7
Spreadsheet: 171712d1343832998-copy-highlighted-cells-highlight-cells-a
Sheet: Sheet1

JAN | 2345
FEB | 2765
MAR | 3753
APR | 1254
MAY | 2534
JUN | 3154
JUL | 2242
AUG | 1542
SEP | 2645
OCT | 1645
NOV | 2534
DEC | 3664
Spreadsheet: 70946d1271701708-reference-formula-or-array-formula-gas-price-decrease-study
Sheet: Sheet1

Transaction number/Date-Time | Category | UPC | Product Name | Units | Dollars | Total Food Sold with Gas Purchase
1234 | Gas | 636 | Unleaded | 10.5 | 26.145 | 0 | 0
1234 | Juice | 232 | B 6/12L | 1 | 6.99 | 0 | 0
1234 | Food | 445 | Snickers | 2 | 0.99 | 0.99 | 1
1234 | Water | 566 | Evian | 1 | 4.99 | 0 | 0
1235 | Gas | 636 | Unleaded | 12 | 29.88 | 0 | 0
1235 | Juice | 235 | B L 1/24C | 2 | 3.98 | 0 | 0
1235 | Food | 441 | Donut | 3 | 3.5 | 3.5 | 1
1236 | Juice | 237 | N L 30 | 1 | 15.99 | 0 | 0
1236 | Food | 113 | Chips | 1 | 1.99 | 0 | 0
1236 | Soda | 745 | Pepsi 2 ltr | 2 | 3.29 | 0 | 0
1237 | Gas | 636 | Unleaded | 10.5 | 26.145 | 0 | 0
1237 | Food | 113 | Chips | 1 | 1.99 | 1.99 | 1
1237 | Soda | 745 | Pepsi 2 ltr | 2 | 3.29 | 0 | 0
 |  |  |  |  |  | 6.48
Spreadsheet: 808681d1670586842-adding-a-blank-space-to-an-concatenated-if-statement-book1
Sheet: Sheet1

cf:doc-reference | Journal Abbreviation | Year | Issue | Volume | Pages
 | Altern Ther Health Med | 2021 |  |  | AT6133
 | J Complement Integr Med | 2020 | 3 | 17
 | J Back Musculoskelet Rehabil | 2019 | 453-461 | 3 | 32
 | Appl Psychol Health Well Being | 2020 | 2 | 12 | 493-512
 | [NAME] | 2021 | 2 | 7 | 290-298
Spreadsheet: 78731d1279054402-service-contract-schedule-service-contracts
Sheet: Sheet1

 | Service Contracts 2009-2010
 |  |  | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
Contact No. | Company | Product
020 5555 666 | Smith & Son | Steel Suppliers £1600 |  |  |  |  |  |  | Renew
01582 663669 | Johnson Chemicals | Chemical Products |  |  |  |  |  |  |  |  |  |  |  | Renew
07523 336580 | Arkwright | Paper |  |  |  |  |  | Renew
01559 665897 | Callanan | Radios |  |  |  |  |  |  |  |  |  |  | Renew
020 2546 332 | Richards Technologies | [NAME] |  |  |  |  |  | Renew
07732 66982 | AB Air Conditioning | [NAME] |  |  |  |  |  |  |  |  |  |  | Renew
01698 774521 | Roots | Gardening Services |  |  |  |  |  |  |  |  | Renew
Spreadsheet: 58733d1259000993-balance-workload-issue
Sheet: Sheet1

Name | Total(initial) | Total after Balancing |  |  | Data
abc | 0 | 3 |  | Name | Sum of Total(initial) | % of Total(initial) | Sum of Total after Balancing | % of Total after Balancing
mno | 3 | 3 |  | abc | 0 | 0 | 3 | 0.3333333333333333
xyz | 2 | 3 |  | mno | 3 | 0.6 | 3 | 0.3333333333333333
 |  |  |  | xyz | 2 | 0.4 | 3 | 0.3333333333333333
 |  |  |  | Grand Total | 5 | 1 | 9 | 1
I will show simple examples of manual procedure.
Example 1:Orders balanced initially. (Only for uderstanding purpose).
New Orders: 6
Name | Total before updating new order | Total after updating new order |  | Data
abc | 1 | 3 | Name | Sum of Total before updating new order | % Total before updating new order | Sum of Total after updating new order | % Total after updating new order
mno | 1 | 3 | abc | 1 | 0.3333 | 3 | 0.3333
xyz | 1 | 3 | mno | 1 | 0.3333 | 3 | 0.3333
 |  |  | xyz | 1 | 0.3333 | 3 | 0.3333
 |  |  | Grand Total | 3 | 1 | 9 | 1
Here in example1, every person has orders 1 initially and is balanced.
Now new orders available is 6 and must be equally distributed to all.
So total new orders (6) divided by total number of persons(3) equal to two (2).
i.e 6/3 = 2
i.e quotient is added with column named "Total before updating new order" to get results in column named "Total after updating new order" so that their percentage share is equal i.e 33.33%.
Example 2: Orders unbalanced initially. (Real issue or problem)
New Orders:4
Name | Total(initial) | Total after Balancing |  |  | Data
abc | 0 | 3 |  | Name | Sum of Total(initial) | % of Total(initial) | Sum of Total after Balancing | % of Total after Balancing
mno | 3 | 3 |  | abc | 0 | 0 | 3 | 0.3333
xyz | 2 | 3 |  | mno | 3 | 0.6 | 3 | 0.3333
 |  |  |  | xyz | 2 | 0.4 | 3 | 0.3333
 |  |  |  | Grand Total | 5 | 1 | 9 | 1
Manual procedure:
Person having maximum share (Name: 'mno' with 3 orders & percentage share is 60 %) must be neglected or not considered.
Person having minimum share (Name: 'abc' with 0 orders & percentage share is 0%) must be considered.
I have simple logic to do this using for loop & if loop condition or statements, but not sure how to use it or to program. Here is the logic:
If Person with minimum orders i.e abc having 0 orders Then he must get first order out of available New Orders(Here New Orders is 4).
During first iteration: Person 'abc' order must INCREMENT from 0 to 1 and similarly New Orders must DECREMENT from 4 to 3. since one out of 4 new orders is given to person with minimum share.
During second iteration: Person 'abc' still has minimum share(i.e 1) and again he will get another order from New orders. Now person 'abc' has 2 orders(i.e incremented from 1 to 2) and remaining New Orders will be 2(i.e decremented from 3 to 2).
During third iteration: Person 'abc' and 'xyz' has equal share of orders 2 respectively. Now New orders must be shared or distributed according to rowwise.
Spreadsheet: 41250d1239739584-updating-dates-on-separate-tabs-based-on-date-in-first-tab-form-booking-sheets-all-1
Sheet: Tours

Boeing Tour - AM |  |  |  |  | 2009-05-08 00:00:00
 | Driver: |  |  |  | Vehicle: |  |  |  |  |  | Prepaid
P/U Time | Booked by |  | Hotel |  | Party | A | C | CT | MF | Amt | CC | [NAME]
 | Cell#:                                Room #                     Notes:
 | Cell#:                                Room #                     Notes:
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Pricing
Retail: | Adult | 56 | Child | 46 | Reseller: | Adult |  | 44.8 |  | Ch |  | 36.8
Resellers: Alcatraz Media, [NAME], Look Tours, Sightseeing World, TourCorp
``
Spreadsheet: 676662d1588922491-index-based-on-date-and-value-index-based-on-date-and-value-2-
Sheet: Sheet1

 | Value1 | Value2 |  |  |  |  |  |  | DATA
2019-09-02 00:00:00 |  |  | Index all values from the DATA |  |  |  |  |  | Value1 | Value2
 |  |  |  |  |  |  |  | 2019-09-05 00:00:00 | Week1 | Week2
 |  |  |  |  |  |  |  | 2019-09-10 00:00:00 | Week2
 |  |  |  |  |  |  |  | 2019-09-24 00:00:00 | Week4 | Week5
 |  |  |  |  |  |  |  | 2019-09-30 00:00:00 | Week5 | Week6
 |  |  |  |  |  |  |  | 2019-10-11 00:00:00 | Week6
 |  |  |  |  |  |  |  | 2019-10-19 00:00:00 | Week7 | Week8
 |  |  |  |  |  |  |  | 2019-10-22 00:00:00 |  | Week9
 |  |  |  |  |  |  |  | 2019-10-29 00:00:00 | Week9 | Week10
 |  |  |  |  |  |  |  | 2019-11-07 00:00:00 | Week10 | Week11