tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 850617d1701016054-counting-number-of-complaints-cases-etc-per-employee-example-workbook
Sheet: Conduct

Case Recorded | Case Reference | Employee ID
2008-03-30 00:00:00 | MC/00001/08 | 2345
2008-03-29 00:00:00 | MC/00002/08 | 7895
2008-03-30 00:00:00 | MC/00003/08 | 7895
2008-03-30 00:00:00 | MC/00003/08 | 8374
2008-04-01 00:00:00 | MC/00004/08 | 9384
2008-04-02 00:00:00 | MC/00005/08 | 7895
2008-04-02 00:00:00 | MC/00005/08 | 7895
2008-04-04 00:00:00 | MC/00006/08 | 9889
2008-04-05 00:00:00 | [NAME] | 4857
2008-04-06 00:00:00 | MC/00008/08 | 3849
2008-06-23 00:00:00 | MC/00010/08 | 999
2008-06-23 00:00:00 | MC/00010/08 | 8845
2008-06-25 00:00:00 | MC/00011/08 | 5006
2008-06-26 00:00:00 | MC/00012/08 | 2365
2008-06-26 00:00:00 | MC/00012/08 | 3423
2008-06-26 00:00:00 | MC/00012/08 | 3423
Spreadsheet: 12356145-416f-47ad-b144-739587d00bad
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11
 | Time Series Workbook
 | 5671.0 Lending Finance, Australia
 | TABLE 13. LENDING FINANCE SEASONAL FACTORS, BY PURPOSE
Related Information: | Summary Publication | Explanatory Notes | Inquiries
 | Glossary
Data Item Description |  |  | Series Type | Series ID | Series Start | Series End | No. Obs. | Unit | Data Type | [NAME]. | Collection Month
Commercial finance for fixed loan facilities ; |  |  | Original | A2433160J | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Commercial finance for revolving credit facilities ; |  |  | Original | A2433161K | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Total lease finance commitments ; |  |  | Original | A2433163R | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Personal finance for fixed loan facilities ; |  |  | Original | A2433157V | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Personal finance for revolving credit facilities ; |  |  | Original | A2433158W | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Investment housing, Construction of dwellings for rent and resale ; |  |  | Original | A2434908R | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Investment housing, Purchase for rent/resale by individuals ; |  |  | Original | A2434909T | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
Investment housing, Purchase for rent/resale by others ; |  |  | Original | A2434910A | 1985-01-01 00:00:00 | 2010-02-01 00:00:00 | 302 | Number | FACTOR | Month | 1
© Commonwealth of Australia  2009
Spreadsheet: kevin_hyatt__19618__FERC Cashflow
Sheet: Cashflow

Sun Devil Pipeline Project
Summary Cashflow Report
Status Thru:
[NAME] |  |  |  |  |  |  |  | Total
DIRECT COSTS | Month 1 | Month 2 | Month 3 | Month 4 | Month 5 | Month 6 | Month 7
Bulk Material
Taxes (On Material)
Freight (Pipe & Fittings)
Installation
Inspection
TOTAL DIRECT COSTS
INDIRECT COSTS
Environmental
Construction Management
Engineering/P.M./Dist. Labor
ROW
AFUDC
Contingency
TOTAL INDIRECT COSTS
PERIOD TOTAL
CUMULATIVE TOTAL
 | Month 1 | Month 2 | Month 3 | Month 4 | Month 5 | Month 6 | Month 7 | Year 2001
Original Plan
Actual
Forecast
 | 0.01973355016262197 | 0.1688766574931198 | 0.1688766574931198 | 0.1687202902176633 | 0.1558981736302227 | 0.1587127845884413 | 0.1591818864148111
Period | 174716.7295518488 | 1495198.636418357 | 1495198.636418357 | 1493814.193236489 | 1380289.852323243 | 1405209.829596882 | 1409363.159142489
Spreadsheet: 797981d1664253973-criteria-based-lookup-criteria-based-lookup
Sheet: Sheet1

 | Problem :
 | Sr. no | Commitment no | Site | brand | Charges
 | 1 | abc123 | All site | 234 | 0.25
 | 2 | abc238 | All site | 352 | 0.18
 | 3 | abc894 | All site | 412418424 | 0.14
 | 4 | abc412 | Only sites [ 1110,1210,1310 &2410] | all brands | 0.13
 | 5 | abc415 | All other sites excldg  [1110,1210,1310,2410] | all brands excluding   234,352,412,418,424 | 0.1
 | I have ten sites
 | and around twenty five brands
 | Five commitment numbers  , having certain percentage of charges , I need to allocate that percentage across different
 | site and brand combination based on the commitment numbers
 |  | Expected Solution [ I need a formula in cell E24 to I33]  which will pick up  charges based on  commitment no / brand and site number
 |  | I will have 25 tables similar to this in which only the brand numbers will change , based in which the charges also should change
 |  | Table 1 -Brand 234
 |  | Brand  # | Site # | Commitment no
 |  |  |  | abc123 | abc238 | abc894 | abc412 | abc415
 |  | 234 | 1110 | 0.25 |  |  | 0.13
 |  | 234 | 1120 | 0.25 |  |  |  | 0.1
 |  | 234 | 1210 | 0.25 |  |  | 0.13
 |  | 234 | 1310 | 0.25 |  |  | 0.13
 |  | 234 | 2100 | 0.25 |  |  |  | 0.1
 |  | 234 | 2410 | 0.25 |  |  | 0.13
 |  | 234 | 2270 | 0.25 |  |  |  | 0.1
 |  | 234 | 3100 | 0.25 |  |  |  | 0.1
 |  | 234 | 3130 | 0.25 |  |  |  | 0.1
 |  | 234 | 4100 | 0.25 |  |  |  | 0.1
Spreadsheet: 884008d1732873967-formulas-shows-name-textverkitten
Sheet: verketten

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | OUT1 | OUT2
LEAGUE | DATE | HOME | AWAY | POS | HM-ADVANTAGE | FORM6 | RF | RP |  | 1 | X | 2 |  |  | 1 | 2 |  |  |  |  |  |  | [NAME] [NAME]
[NAME] | Fr 22 Nov | Getafe | Valladolid | 1 | 1 | 1 | 1 | 1
[NAME] | Sa 23 Nov | [NAME] | RealBetis | 2 | X | 2 | 1 | 1
[NAME] | Sa 23 Nov | AtleticoMadrid | Alaves | 1 | 1 | 1 | 1 | 1
[NAME] | Sa 23 Nov | Girona | Espanyol | 1 | 1 | 1 | 1 | 1
[NAME] | Sa 23 Nov | LasPalmas | Mallorca | 2 | 1 | 1 | 1 | 1
[NAME] | Sa 23 Nov | CeltaVigo | FCBarcelona | 2 | 2 | 2 | 1 | 1
[NAME] | Su 24 Nov | Osasuna | Villarreal | 2 | 2 | 2 | 1 | 1
[NAME] | Su 24 Nov | [NAME] | RayoVallecano | 1 | X | 1 | 1 | 1
[NAME] | Su 24 Nov | Leganes | RealMadrid | 2 | 2 | 2 | 1 | 1
[NAME] | Su 24 Nov | AthleticBilbao | RealSociedad | 1 | 2 | X | 2 | 2
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | #[NAME]?
Spreadsheet: 01ba2b2b-8aa0-4a82-94d9-0d69bdf07444
Sheet: Sheet1

Table S1 | DNA concentrations  for tiger and leopard samples extracted with and without addition of carrier [NAME] and stored by different preservation protocols | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12
 |  | Silica |  |  |  | Ethanol |  |  |  | Two-step
Days | without carrier RNA | with carrier RNA | without carrier RNA | with carrier RNA | without carrier RNA | with carrier RNA | without carrier RNA | with carrier RNA | without carrier RNA | with carrier RNA | without carrier RNA | with carrier RNA
 | Leopard(n=2) | leopard(n=3) | tiger(n=2) | tiger(n=3) | Leopard(n=2) | leopard(n=3) | tiger(n=2) | tiger(n=3) | Leopard(n=2) | leopard(n=3) | tiger(n=2) | tiger(n=3)
1 | 15.9(±11.3) | 191.3(±108.7) | 36.7(±23.5) | 1018.9(±408) | 449.4(±82.7) | 608.4(±205) | 451.3(±113.4) | 20690.9(±9954.8) | 690.1(±207.1) | 4011.1(±2183) | 748.7(±197.1) | 39340.4(±15823.7)
3 | 7.5(±7.8) | 127.3(±88.5) | 7.7(±7.7) | 235.9(±95.2) | 52.7(±44.6) | 380.3(±117.7) | 232.1(±118) | 5563.5(±2434.6) | 331.4(±245.7) | 634.8(±181.5) | 291.6(±197.1) | 12124.7(±4067.5)
5 | 5.2(±5.1) | 40.7(±42.6) | 2.6(±1.7) | 132.3(±89) | 17.5(±0.7) | 69.9(±28) | 81.2(±29.1) | 1849.1(±682.8) | 74.3(±14.2) | 151.1(±24.2) | 125.3(±18.3) | 2632.6(±431.3)
7 | 2.14(±1.22) | 4.1(±2.7) | 1.4(±0.2) | 28.6(±2.6) | 7.6(±2) | 11.5(±4) | 20.8(±10.1) | 675.2(±84.2) | 18.6(±0.7) | 49.7(±15.8) | 59.4(±40.7) | 796.3(±63.2)
9 | 1.04(±0.01) | 1.5(±0.4) | 1.2(±0.2) | 9.7(±4.3) | 7.2(±2) | 5.3(±1.5) | 8.9(±5.9) | 248.7(±19.6) | 10.0(±6.2) | 10.6(±3.5) | 19.2(±3.9) | 273.7(±10.7)
Spreadsheet: 66416d1267068325-formatting-drop-down-list-dependentlists3
Sheet: Choices

Sample Depenedent Drop Boxes
Classes | Types | Animals |  | Problematic - make a change in [NAME] and the following cells remain with now-incorrect values
Canine | Tigers | [NAME] |  | NOTE: Problem if you make selections in the boxes above, and then go back and change an earlier box
 |  |  |  | it does not change the others, so you could end up with Canine - Tiger - Bald Eagle.
Classes | Types | Animals |  | Better - change A8 or [NAME] and the following cells clear their values
Aquatic | Sharks | Great White |  | SOLUTION: A WorkSheet_change macro can be used to watch for changes in the earliest boxes and then
 |  |  |  | clear the previous made in later boxes that are now no longer valid.
 |  |  |  | Right-click on the sheetname tab and VIEW CODE to see the macro.
 |  |  |  | On this page we use Validation List of
 |  |  |  | Allow: =Animals
 |  |  |  | for both [NAME] and A8 versions.
 |  |  |  | Then, the validation list for B3 uses an INDIRECT formula
 |  |  |  | Allow:  =INDIRECT(A3)
 |  |  |  | so the word chosen becomes the active "list" and the animal
 |  |  |  | names are brought over. The same thing is used in the
 |  |  |  | validation list for C3:
 |  |  |  | Allow:  =INDIRECT(B3)
 |  |  |  | This technique could go on indefinitely.
 |  |  |  | The "LISTS" are on the next sheet.
Spreadsheet: 803819d1667725548-how-to-do-fast-replacing-of-row-number-accross-different-columns-copy-of-baza-nova-verzija-racuni-1-
Sheet: R12

Ime artikla
Spreadsheet: stacey_white__38843__West Limits Fax
Sheet: Limits

NA WEST POWER VaR
 |  |  |  |  | Increase/ | Average Daily
 | Portfolio | Portfolio | Trader | VaR | (Decrease) | VaR Limits | VaR Limit | Violation
 | Name | Name | Name | ($) | in VaR | ($) | ($)
 | ALL REGIONS
 | NA WEST POWER | POWER-WEST-TOTL | [NAME] | 14744852.12710266 | 6412735.797812579 | 4900000 | 20000000
 | WEST-LT | POWER-WEST-LT | [NAME] | 12092977.5388802 | 6083163.280159551 | 3800000 | 7900000 | VIOLATION
 | WEST-LT | POWER-WEST-LT | [NAME] | 12092977.5388802 | 6083163.280159551 | 3800000 | 20000000
 | WEST-ST | POWER-WEST-ST1 | [NAME] | 2970720.619810839 | -91874.18943724409 | 1700000 | 5000000
 | CANADA | FT-CAND-PWR-1 | [NAME] | 21702347.42711522 | 550659.1652897857 |  | 25000000
 | TOTAL WEST POWER |  | [NAME] | 35834353.18705507 | 9156458.136169583 |  | 35000000
 | TOTAL NA POWER |  | [NAME] | 43656525.57256559 | 8707395.160545416 |  | 50000000
 | WEST POWER LONG TERM
 | MANAGEMENT | POWER-WM-LT | [NAME] | 2526217.352748202 | -55811.77278559096 | 1300000 | 5000000
 | CALIFORNIA | POWER-CA-LT | [NAME] | 894668.5257784347 | -993.186212165514 | 1300000 | 5000000
 | NORTHWEST REGION | POWER-NW-LT | [NAME] | 9839814.508781612 | 6090420.465730841 | 3100000 | 10000000
 | SOUTHWEST REGION | POWER-SW-LT | [NAME] | 5307167.483448652 | 893982.3894690117 | 1300000 | 5000000 | VIOLATION
 | WEST-LT | POWER-WEST-LT |  | 12092977.5388802 | 6083163.280159551 | 3800000 | 20000000
 | WEST POWER SHORT TERM
 | CA-ST | POWER-CA-ST | [NAME] Richter | 1132431.371722808 | -2039.621576785808 | 1000000 | 2000000
 | NW-ST | POWER-NW-ST | [NAME] | 861823.3138541188 | -528744.4425880897 | 1000000 | 2000000
 | SW-ST | POWER-SW-ST | [NAME]/[NAME] | 1199305.70948039 | 459060.9652885514 | 1000000 | 2000000
 | WEST-ST | POWER-WEST-ST1 | [NAME] | 2970720.619810839 | -91874.18943724409 | 1700000 | 5000000
Spreadsheet: 157533d1337785138-recurring-values-in-formulas-example
Sheet: Sheet1

1 |  | 0.19
2
3
4 |  | 0.79
5 |  | 0.99
6
7 |  | 1.36
8 |  | 1.59
9
10 |  | 1.99
11 |  | 2.19
12
13 |  | 2.59
14 |  | 2.79
15
16 |  | 3.19
17 |  | 3.39
18
19 |  | 3.79
20 |  | 3.99
Spreadsheet: 926a7795-a337-4d94-97e0-bf6d74a16755
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
INHP | Test | INHP | Isoniazid, Serum/Plasma | Isoniazid | High-Performance Liquid Chromatography (HPLC) | Plain, Red-Top Tube: Red |  |  | 2 | mL | Submit only 1 of the following specimens:  Serum Draw blood in a plain, red-top tube(s). (Serum gel tube is not acceptable.) Spin down and send 2 mL of serum frozen in plastic vial. Note:  	1. Indicate serum on request form. 		2. Label specimen appropriately (serum).   [NAME] blood in a lavender-top (EDTA) tube(s). ([NAME] is not acceptable.) Spin down and send 2 mL of EDTA plasma frozen in plastic vial. Note:  	1. Indicate plasma on request form.                   	2. Label specimen appropriately (plasma). | 0.7 mL | Specimens other than	Serum, plasma Anticoagulants other than	Plain red-top, EDTA Hemolysis	NA Thawing	Warm reject; Cold reject Lipemia	NA Icteric	NA | Reporting limit determined each analysis   Synonym(s): INH   Usual therapeutic range in the treatment of tuberculosis:  1-7 mcg/mL. Toxic symptoms present at approximately  20 mcg/mL and greater.      Test Performed by: NMS Labs                                       3701 Welsh Road                                       PO Box 433A                                       Willow Grove, PA 19090-0437 | Wednesday | 1 day | 3 - 9 days | 1 | 82491 |  |  |  |  | NMS Labs
INHP | [NAME] | VARIES | Varies |  |  |  | Frozen | 30 days
INHP | Result | [NAME] | Isoniazid | Isoniazid | Alphanumeric |  |  |  |  | mcg/mL |  |  |  |  |  |  |  |  |  | 3697-0
INHP | Result | Z1471 | Reporting Limit | Reporting Limit | Alphanumeric |  |  |  |  | mcg/mL |  |  |  |  |  |  |  |  |  | In Process
Spreadsheet: 95466d1295037358-lookup-report-back-a-value-and-column-header-tooleyr-ef760122-sdg10
Sheet: Sheet1

Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | You sold | In Month
100 |  |  |  |  |  |  |  |  |  |  |  | 100 | Jan
 | 200 |  |  |  |  |  |  |  |  |  |  | 200 | Feb
 |  | 300 |  |  |  |  |  |  |  |  |  | 300 | Mar
 |  |  | 400 |  |  |  |  |  |  |  |  | 400 | Apr
 |  |  |  | 500 |  |  |  |  |  |  |  | 500 | May
 |  |  |  |  | 600 |  |  |  |  |  |  | 600 | Jun
 |  |  |  |  |  | 700 |  |  |  |  |  | 700 | Jul
 |  |  |  |  |  |  | 800 |  |  |  |  | 800 | Aug
 |  |  |  |  |  |  |  | 900 |  |  |  | 900 | Sep
 |  |  |  |  |  |  |  |  | 1000 |  |  | 1000 | Oct
 |  |  |  |  |  |  |  |  |  | 1100 |  | 1100 | Nov
 |  |  |  |  |  |  |  |  |  |  | 1200 | 1200 | Dec
Today, 03:05 PM
tooleyr - EF760122 - SDG10.xls
Registered User   Join Date: 14 Jan 2011
Location: Minneapolis, MN
MS Office Version:Excel 2003
Posts: 1
lookup/report back a value and column header
http://www.excelforum.com/excel-general/760122-lookup-report-back-a-value-and-column-header.html
Hello,
Sorry if this has already been asked/answered.
I'm trying to look across 12 columns of data (one for each month of year)
and report the value in one of those columns, as well as the column header of the particular column with the value in it.
Only one of the 12 columns will have a value in it, by the way. Basic sales analysis - you sold X items in month [NAME] and Y are reported off to the right of the 12 columns.
Thanks in advance for any advice/suggestions!
Spreadsheet: louise_kitchen__22711__North America Plan 01-09 inc AA adj (2)
Sheet: Power Logistics

 | Power Logistics
 | 2002 Plan
 |  |  |  |  |  |  |  | Energy Operations
 |  | 2001-09-01 00:00:00 |  | 2001 |  | % of | 2002 |  | Per HC | New HC | Adj Comp |  |  |  |  | 2002
 |  | YTD Actual |  | Forecast |  | Total Exp | Plan |  |  |  |  |  |  |  |  | Plan
ENACOMP | Compensation
 | Analyst & Associate | 0
ENABENTX | Benefits & Payroll Taxes
ENAEMPEX | Employee Expense |  |  |  |  |  |  | Other
ENAT&EEX | Travel & Entertainment Expense |  |  |  |  |  | 38749.48560000001
ENAOUTSV | Outside Services | 0 |  |  |  |  | 0 | Total |  |  |  |  | 36500125
ENASUPP | Supplies Expense
ENAMKTEX | Marketing |  |  |  |  |  | 0
ENACONTR | Charitable Contributions |  |  |  |  |  | 0 | [NAME] | 37500 |  |  |  | 1.25
ENARENT | Rent |  |  |  |  |  |  | Admins | 52500
ENATECH | Technology |  |  | 145000 |  |  |  | Staff | 56250
ENATRANS | Transportation |  |  |  |  |  | 0 | Associate | 75000
ENAOTHEX | Other Expenses |  |  |  |  |  | 0 | Analysts | 60000
ENATAXES | Taxes Other than Income |  |  |  |  |  | 0 | Specialist | 65000
ENATOTDR | Total Direct Expenses |  |  |  |  |  |  | Sr Specialist | 82500
 |  |  |  |  |  |  |  | Managers | 100000
 | Headcount |  |  | 114 |  |  | 13 | Directors | 145000
 |  |  |  |  |  |  |  | Sr Director | 175000
 | A&A Headcount |  |  | 4 |  |  | 1 | Vice President | 237500
 |  |  |  |  |  |  |  | [NAME] | 312500 | 0
 | Total Headcount |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 1
ENAOUTLG | Outside Legal |  |  |  |  |  |  | Benefits & Taxes |  |  | 0.2
ENAOUTTX | Outside Tax
ENAINSUR | Insurance
ENASYSDV | System Development
ENACORIT | Controllable Infrastructure
ENACORRN | Corporate Rent
ENAOTHAL | Other Allocated Direct  Expenses |  |  |  |  |  | Other Expense Calculation
ENADEPR | Depreciation & Amortization
 |  |  |  |  |  |  | Based on information from ENW accounting.
Spreadsheet: 744434d1629240294-populate-value-using-vlookup-but-from-a-string-of-text-sample
Sheet: Ref

 | RPA ID | Emp ID | Name | Team Lead
 | [NAME] | 7503
 | elahabid | 7504
 | jayakujh | 7505
 | karayimu | 7506
 | niranjna | 7507
 | [NAME] | 7508
 | ramamgop | 7509
 | saudagaz | 7510
 | ssuchitr | 7511
 | tnmadan | 7512
 | venkatar | 7513 | [NAME]
 | wellasjo | 7514
Spreadsheet: 865645d1712678326-dynamic-look-up-test
Sheet: Sheet2

 | April | May | June | July | August | September | October | November | December | January | February | March
product num | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast | Forecast
123 | 10
124 | 20
125 | 30
126 | 40
127 | 50
128 | 60
129 | 70
130 | 80
131 | 90
132 | 100
Spreadsheet: 767575d1644524292-extracting-data-from-another-workbook-example
Sheet: Sheet1

 | WORKBOOK 1 |  |  |  |  |  | [NAME] 2
 |  | REVIEW 1 |  | REVIEW 2 |  |  | ID | Review | Status | Completed by
 | ID | Status | Completed by | Status | Completed by |  | 1 | Review 1 | Complete | Name 1
 | 1 | Complete | Name 1 |  |  |  | 2 | Review 1 | Not started | Name 2
 | 2 |  |  |  |  |  | 3 | Review 2 | Needs action | Name 3
 | 3 |  |  | Needs action | Name 3
 | I want this workbook to pull across the status of reviews if the ID matches, and the review aligns to the header. Example results are populated.
Spreadsheet: 599764d1543306864-matching-data-using-index-and-match-using-last-4-digits-book1
Sheet: Sheet1

1408 |  |  | Q | AAA 1408
1795 |  |  | W | DDD 1795
1671 |  |  | E | BBB 1671
1979 |  |  | R | GGG 1979
1210 |  |  | T | HHH 1210
1373 |  |  | Y | CCC 1373
1325 |  |  | U | III 1325
1317 |  |  | I | FFF 1317
1489 |  |  | O | EEE 1489
Spreadsheet: 181418d1348037260-i-need-to-show-keywrod-in-rows-against-single-url-guys-help-needed
Sheet: Sheet1

What I have
url | keywords
url1 | a
url1 | b
url1 | c
url1 | d
url1 | e
url1 | f
url2 | aa
url2 | bb
url2 | cc
url2 | dd
What is want
url1 | a | b | c | d | e | f
url2 | aa | bb | cc | dd
Spreadsheet: 869817d1716375869-required-multilevel-sequence-serial-numbers-book2
Sheet: Sheet1

 | C Index | C-Title | M-Index | M-Title | CM Index | CM Title |  | Helper 1 | Helper 2
 | C-1 | ABC | M-1.1 | AAA |  | ACD
 |  |  |  |  |  | DAA |  | CM-1.1
 |  |  |  |  |  | KJFF |  | CM-1.1
 |  |  | M-1.2 | BBB |  | SKSD |  | CM-1.2
 |  |  |  |  |  | AWR |  | CM-1.2
 |  |  |  |  |  | AD |  | CM-1.2
 |  |  |  |  |  | RE |  | CM-1.2
 |  |  | M-1.3 | CCC |  | ERE |  | CM-1.3
 |  |  |  |  |  | AF |  | CM-1.3
 | C-2 | XYZ | M-2.1 | DDD |  | EERE |  | CM-2.1
 |  |  |  |  |  | ADF |  | CM-2.1
 |  |  |  |  |  | ADFFE |  | CM-2.1
 |  |  |  |  |  | AVE |  | CM-2.1
 |  |  | [NAME] | EEE |  | ETER |  | CM-2.2
 |  |  |  |  |  | EREA |  | CM-2.2
 |  |  |  |  |  | AFA |  | CM-2.2
 |  |  |  |  |  | ADFE |  | CM-2.2
 |  |  |  |  |  | ADF |  | CM-2.2
 |  |  |  |  |  | E |  | CM-2.2
 |  |  | M-2.3 | FFF |  | ERE |  | CM-2.3
 |  |  |  |  |  | RE |  | CM-2.3
 |  |  |  |  |  | A |  | CM-2.3
 | V-3 |  | M-3.1 |  |  | b |  | VM-3.1
 |  |  |  |  |  | h |  | VM-3.1
Spreadsheet: 681602d1591656098-how-to-look-for-the-total-value-look-for-total
Sheet: Arkusz1

[NAME] | 100 | 5 | 5
[NAME] | 150 | 7.5 | 7.5
[NAME] | 120 | 6 | 7.2
[NAME] | 90 | 4.5 | 4.05
[NAME] | 140 | 7 | 9.8
[NAME] | 80 | 4 | 3.2
Kelly | 130 | 2 | 2.6
 |  | [NAME] | [NAME]
 |  | 0 | 0
 |  | 120 | 0.06
 |  | 0 | 0
 |  | 0 | 0
 |  | 80 | 0.04
 |  | 0 | 0
 | sums
 | 10% of 200
 | the same in a single array formula
Spreadsheet: 171978d1343936131-multipul-percentage-too-1-figure-lookup-sum-range-day92
Sheet: Sheet1

Input | Results |  |  | Table
33 |  |  | 0 | to | 150 | 0.099
120 |  |  | 150.01 | to | 300 | 0.079
250 |  |  | 300 | to | 500 | 0.069
400 |  |  | 500.01 | to | 1000 | 0.059
750 |  |  | 1000.01 | to | 5000 | 0.025
2500
Spreadsheet: 118072d1313422349-using-vlookup-on-filtered-data-dummy
Sheet: Sheet2

code | material | amount | yes | no | del | err | all selections
00002795 | anything | 940,00
00003262 | anything | 901,00
00003266 | anything | 753,00
00003267 | anything | 595,00
00003268 | anything | 349,00
00003269 | anything | 679,00
00003270 | anything | 595,00
00003271 | anything | 592,00
00003272 | anything | 595,00
00003273 | anything | 595,00
00003278 | anything | 595,00
00003279 | anything | 1.866,00
00003280 | anything | 1.705,00
00003282 | anything | 648,00
00003346 | anything | 962,00
00003347 | anything | 512,00
00003348 | anything | 3.501,00
00003353 | anything | 186,00
00004580 | anything | 382,00
00004942 | anything | 642,00
00005952.00 | anything | 471,00
00034317 | anything | 642,00
00034593.02 | anything | 632,00
00035439 | anything | 632,00
Spreadsheet: 173255d1344492475-conditional-formatting-rows-with-max-and-min-specs-example-data
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Specificaition
Sample | MEASURED VALUES |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | MIN | AIM | MAX
A | 0.032 | 0.0352 | 0.0356 | 0.0357 | 0.0357 |  | 0.0361 | 0.0362 | 0.0362 | 0.0362 | 0.036 |  | 0.0358 | 0.0356 | 0.0358 | 0.0354 | 0.0322 | 0.033 | 0.0341 | 0.037
B | 0.0335 | 0.036 | 0.0367 | 0.0368 | 0.037 |  | 0.0373 | 0.0373 | 0.0373 | 0.0375 | 0.0368 |  | 0.0368 | 0.0366 | 0.0367 | 0.0361 | 0.0332 | 0.0324 | 0.0339 | 0.0354
C | 0.0334 | 0.0351 | 0.0366 | 0.0364 | 0.0362 |  | 0.0365 | 0.0365 | 0.0365 | 0.0365 | 0.0363 |  | 0.0359 | 0.0358 | 0.0355 | 0.0354 | 0.0334 | 0.0335 | 0.0346 | 0.0365
D | 0.0339 | 0.0362 | 0.0371 | 0.0373 | 0.0373 |  | 0.0376 | 0.0378 | 0.0378 | 0.0377 | 0.0375 |  | 0.0369 | 0.0368 | 0.0367 | 0.0362 | 0.0339 | 0.033 | 0.0341 | 0.037
E | 0.0352 | 0.0377 | 0.0382 | 0.0383 | 0.0385 |  | 0.0388 | 0.0389 | 0.0389 | 0.0388 | 0.0387 |  | 0.0383 | 0.0382 | 0.0381 | 0.0377 | 0.0356 | 0.033 | 0.035 | 0.037
F | 0.0376 | 0.0405 | 0.0413 | 0.0418 | 0.042 | 0.042 | 0.0422 | 0.0423 | 0.0421 | 0.0421 | 0.042 | 0.0416 | 0.0413 | 0.0411 | 0.0411 | 0.0405 | 0.0372 | 0.0378 | 0.039 | 0.0418
G | 0.0386 | 0.0419 | 0.0425 | 0.0427 | 0.0428 |  | 0.0431 | 0.0432 | 0.0432 | 0.0431 | 0.043 |  | 0.0425 | 0.0424 | 0.0422 | 0.0417 | 0.0385 | 0.0393 | 0.0405 | 0.0428
Spreadsheet: 70612d1271332773-if-and-else-with-the-use-of-a-list-cello
Sheet: Sheet1

 | daily | weekly |  |  | product | house2
house1 | 20 | 120 |  |  | time frame | weekly
house2 | 25 | 150
[NAME] | 21 | 130 |  |  | >>> | 150
[NAME] | 22 | 140 |  |  | [NAME] | 150
 |  |  |  |  | index/match | 150