tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 193969d1352999488-conditional-formatting-excell-2010-book1
Sheet: Sheet1

 | Month 1 | Month 2 | Month 3 | Month 4
A | 100 | 100 | 200 | 100
b | 100 | 100 | 150 | 175
c | 100 | 150 | 170 | 180
d | 100 | 100 | 200 | 220
e | 100 | 100 | 180 | 150
 |  | Change | Change | Change
Spreadsheet: 287471d1388811341-copying-data-to-cells-timesheet
Sheet: Chris

 |  | [NAME]
Name |  | 2013-12-12 00:00:00 | 2013-12-13 00:00:00 | 2013-12-14 00:00:00 | 2013-12-15 00:00:00 | 2013-12-16 00:00:00 | 2013-12-17 00:00:00 | 2013-12-18 00:00:00 | 2013-12-19 00:00:00 | 2013-12-20 00:00:00 | 2013-12-21 00:00:00 | 2013-12-22 00:00:00 | 2013-12-23 00:00:00
[NAME]
Spreadsheet: 272431d1382382890-complex-bonus-calculation-bonus-calculation
Sheet: Sheet

Month | % | Customer A |  | Bonus | Explanations about desired results
 |  | Sales | Payment
1 | 0.06 | 20000 | 0 | 0 | In a first month there is no bonus, because the payment is zero.
2 | 0.03 | 0 | 3000 |  | Bonus is 180 USD because, 3000 USD has been paid in this month and this payment is for  the previous month's 20 000 USD sales. Multiplied with 6% (3000*6%=180)
3 | 0.03 | 4000 | 19000 |  | 17 000 USD has been left from first month and its percentage is 6%, thus 17000*6%=1020  + 4000 USD is sales amount for current month but its 2000 USD has been paid only, thus 2000*3%=60 17000*0.06+2000*0.03=1080
4 | 0.05 | 0 | 3000 |  | There 2000 USD sales amount from previous month. Buyer pays 1000 USD extra and it will not be calculated as bonus. 2000*0.03=60
5 | 0.06 | 0 | 0 | 0
6 | 0.06 | 0 | 0 | 0
7 | 0.04 | 6000 | 0 |  | There is 1000 USD extra payment from 4th month. Percentage level is 4% because sale has been made in current month. 1000*0.04=40
8 | 0.05 | 0 | 0 | 0
9 | 0.06 | 0 | 5000 |  | Remaining 5000 USD sales is paying in full amount. 5000*0.04=200
10 | 0 | 0 | 0 | 0
11 | 0 | 0 | 0 | 0
12 | 0 | 0 | 0 | 0
Spreadsheet: 189340d1351163680-lookup-value-problem-apft-example
Sheet: APFT

# | RANK | NAME | SEX | AGE | PU | SU | RUN | TOTAL | PASS/FAIL | CURRENT APFT | NEXT APFT |  | WEIGHT | BODY FAT %
 |  |  | MALE | 17 | 60 | 60 | 60 |  |  | 2012-06-12 00:00:00
 |  |  | FEMALE | 17 | 60 | 60 | 60
 |  |  |  | AVERAGE
 |  | LEGEND |  | COLOR
 |  | TODAY'S DATE
 |  | GREATER THAN 60 DAYS (CURRENT)
 |  | 60 DAYS OR LESS
 |  | 30 DAYS OR LESS AND PAST DUE
Spreadsheet: 728533d1618501025-how-to-make-values-in-one-column-follow-the-values-in-other-columns-link-value-to-client
Sheet: Sheet1

 |  | January |  |  |  | February |  |  |  |  | March
 |  | Client name | Comments | Premium |  | Client name | Comments | Premium |  |  | Client name | Comments | Premium
 |  | [NAME] | Ok | 10000 |  | [NAME] | Ok | 10000 |  |  | [NAME] | Ok | 10000
 |  | Client Can | Renew ahead | 20000 | New client | [NAME] | Renew ahead | 17000 |  |  | [NAME] | Renew ahead | 17000
 |  | Client Cree | Talk to repr. | 15000 |  | Client Can | Talk to repr. | 20000 |  |  | Client Can | Talk to repr. | 20000
 |  | [NAME] | Small bus. | 1000 |  | Client Cree | Small bus. | 15000 |  | New client | Client Cannot | Small bus. | 15000
 |  |  |  |  |  | [NAME] |  | 1000 |  |  | Client Cree |  | 15000
 |  |  |  |  |  |  |  |  |  |  | [NAME] |  | 1000
Spreadsheet: 765621d1643427373-index-match-if-obtain-value-by-process-of-elimination-using-greater-than-and-less-than-sample
Sheet: Sheet2

Grade: | Current Hourly Wage: |  | 31.4
WS218 | Current Annual Salary: |  | 65312 |  | [NAME] will be in Cell C3
Year 1 |  |  |  |  | [NAME], IF [NAME] is less  than SHEET 1 COLUMN F, if TRUE then multiply B3 time 2%, if FALSE then move on to column G, if [NAME] is less than the lookup value in column G is TRUE then multiply B3 times 3%, if column G is FALSE, then move on to column H, if [NAME] is greater than the lookup value in column G then multiply B3 times 2%.
Year 2
Year 3
Year 4
Year 5
Year 6 |  |  |  |  | The idea is to copy the formula down to C4 through C32.  The formula will automatically calculate and adjust the raise percentage through the years.  Basically, the longer you work the less of a raise an employee gets.
Year 7
Year 8
Year 9
Year 10 |  |  |  |  | Cell D3
 |  |  |  |  | In cell [NAME], I would like to be able to display what percentage is being used for that
Spreadsheet: 5f10cfb7-03f8-412f-a664-3777ffd50415
Sheet: Sheet1

analytica 2012 - Aussteller Liste | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
 | Suche über Produkt- und Dienstleistungsverzeichnis (20 [NAME]):
 | 2 Analytik 2.4 Spektroskope 2.4.5 [NAME] (IR)
Nr. | Firma | Land | Ort | PLZ | Halle/Stand
1 | ABB Automation GmbH Sales FTIR-NIR | Deutschland | Frankfurt am Main | 60488 | A2.108
2 | Agilent Technologies Sales & Services GmbH & Co. [NAME] | Deutschland | Waldbronn | 76337 | A2.105/206
3 | analyticon instruments gmbh | Deutschland | Rosbach | 61191 | A2.439
4 | Bruker Corporation | USA | Billerica | MA 01821 | A2.331/432
5 | Bruker Optik GmbH | Deutschland | Ettlingen | 76275 | A2.331/432
6 | Buck Scientific Inc. | USA | East Norwalk | CT 06855 | B2.423
7 | Büchi Labortechnik GmbH | Deutschland | Essen | 45127 | A2.405
8 | FOSS GmbH | Deutschland | [NAME] | 25462 | A1.505
9 | Hamamatsu Photonics Deutschland GmbH | Deutschland | Herrsching | 82211 | A2.415/514
10 | JSB BV | Niederlande | Eindhoven | 5653 [NAME] | A2.130
11 | LLA Instruments GmbH | Deutschland | Berlin | 12489 | A2.435
12 | NIR-Online GmbH | Deutschland | Walldorf | 69190 | A1.421
13 | PAS-Analytik GmbH | Deutschland | Hamburg | 22419 | B2.430/6
14 | Perten Instruments GmbH | Deutschland | Hamburg | 21079 | A2.224
15 | PHARMA TEST Apparatebau AG | Deutschland | Hainburg | 63512 | A1.506
16 | [NAME] | Deutschland | Waldbronn | 76337 | A2.217
17 | Sentronic GmbH | Deutschland | Dresden | 01217 | A2.423
18 | SOLITON GmbH | Deutschland | Gilching | 82205 | A1.402
19 | Thermo Scientific | Deutschland | Dreieich | 63303 | B1.101/202
20 | [NAME] GmbH | Deutschland | Rendsburg | 24768 | A1.129
Spreadsheet: 780020d1652260997-grouping-dates-by-month-of-year-to-calculate-maximum-average-and-minimum-without-pivot-book2
Sheet: Sheet1

Date | Criteria | Amount |  |  | Column1 | Month [NAME] | Month Average | Month Minimum
2022-01-01 00:00:00 | A | 100 |  |  | A | 200 | 150 | 100
2022-01-10 00:00:00 | B | 50 |  |  | B | 1000 | 517 | 50
2022-02-25 00:00:00 | A | 200
2022-02-10 00:00:00 | B | 1000
2022-02-18 00:00:00 | B | 500
 | C
2021-01-01 00:00:00 | D
 | C |  |  |  |  |  | Required answer
2020-05-01 00:00:00 | E
 | C
 | D
Spreadsheet: 862127d1709895062-i-need-to-make-the-summary-page-more-user-friendly-to-make-it-look-better-analysis-090324
Sheet: Emails

[NAME]
[EMAIL] | [NAME]
[EMAIL] | [NAME]
[EMAIL]
[EMAIL]
Fox Recruitment
[EMAIL]
[EMAIL]
Pro-Force
[EMAIL]
[EMAIL]
CDS
[EMAIL]
Piotr Gajecki <[EMAIL]>
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
Spreadsheet: 856588d1705781363-find-daily-employee-spend-amounts-employee-reimbursement-example
Sheet: raw data

Employee | Approved Amount | Vendor | Transaction Date | Expense Type
[NAME], [NAME] | 45.5 | [NAME] | 2023-07-08 00:00:00 | Restaurant meal
[NAME], [NAME] | 20 | [NAME] | 2023-07-09 00:00:00 | Taxi fare
[NAME], [NAME] | 120 | [NAME] | 2023-09-05 00:00:00 | Hotel accommodation
[NAME], [NAME] | 15.75 | Global Treasures Emporium | 2023-09-05 00:00:00 | Souvenir purchase
[NAME], [NAME] | 300 | SkyVoyage Airlines | 2023-11-03 00:00:00 | Airline ticket
[NAME], [NAME] | 4.5 | [NAME] | 2023-08-28 00:00:00 | Coffee from a local cafe
[NAME], [NAME] | 30 | MetroPass Solutions | 2023-08-28 00:00:00 | Public transportation pass
[NAME], [NAME] | 12 | ArtScape Tickets | 2023-08-28 00:00:00 | Museum entrance fee
[NAME], [NAME] | 8.25 | [NAME] | 2023-10-08 00:00:00 | Snacks from a convenience store
[NAME], [NAME] | 50 | ExploreX Tours | 2023-11-19 00:00:00 | Sightseeing tour
[NAME], [NAME] | 100 | CashExpress Services | 2023-11-19 00:00:00 | ATM withdrawal
[NAME], [NAME] | 75 | RoadRoamer Rentals | 2023-11-19 00:00:00 | Rental car fee
[NAME], [NAME] | 10.5 | CinéMagic Entertainment | 2023-11-19 00:00:00 | Movie ticket
[NAME], [NAME] | 15 | ConnectEase Telecom | 2023-10-20 00:00:00 | Mobile SIM card
[NAME], [NAME] | 35.8 | FreshHarvest Mart | 2023-07-30 00:00:00 | Groceries from a local market
[NAME], [NAME] | 25 | AeroPark Services | 2023-07-30 00:00:00 | Airport parking
[NAME], [NAME] | 20 | FreshFolds Laundries | 2023-08-22 00:00:00 | Laundry service
[NAME], [NAME] | 2.5 | AquaQuench Ventures | 2023-10-04 00:00:00 | Water bottle from a street vendor
[NAME], [NAME] | 22.75 | RailRide Express | 2023-10-04 00:00:00 | Train ticket
[NAME], [NAME] | 60 | SereneTouch Retreat | 2023-11-29 00:00:00 | Spa/massage
[NAME], [NAME] | 40 | FuelFlow Stations | 2023-12-11 00:00:00 | Gas for rental car
[NAME], [NAME] | 50 | SwiftCare Clinics | 2023-12-28 00:00:00 | Emergency medical expenses
Spreadsheet: 863466d1710945706-calculating-time-based-on-event-formula-help-tracking-time-on-events-example
Sheet: Sheet1

AGV Route (Number): | AGV Number: | Battery #1 in | Battery #2 in | Battery #1 out | Battery #2 out | Time stamp | Name
 | 13 | 229 | 227 | 536 | 528 | 09:45:00 | MonDAGV |  | Explanation:
 | 12 | 25 | AX28 | 451 | 425 | 10:05:00 | MonDAGV |  | AGV 13 had flat batteries. Battery #536 and #528 were removed to put in 229 and 227
 | 9 | 425 | 451 | 230 | 442 | 10:15:00 | MonDAGV |  | Some time later
 | 3 | 238 | 377 | 96 | 106 | 08:30:00 | MonDAGV |  | AGV 13 had flat batteries. Battery # 229 and #227 were removed
 | 1 | 73 | 444 | 427 | 174 | 07:22:00 | MonDAGV
 | 5 | 1055 | 551 | 45 | 107 | 10:20:00 | MonDAGV |  | I need a sum to tell me the different between the time battery 227 went in and when it was removed
 | 87 | 1060 | 354 | 1015 | 1012 | 09:45:00 | MonDAGV
 | 13 | 418 | 94 | 310 | 227 | 12:10:00 | MonDAGV |  | Some time later, 227 will go back in again, and be removed again - I'll need another time on this occasion and the next etc.
 | 30 | 83 | 657 | 520 | 523 | 12:22:00 | MonDAGV
 | 21 | 70 | 528 | 10 | 18 | 12:44:00 | MonDAGV
 | 1 | 427 | 174 | 73 | 444 | 13:44:00 | MonDAGV |  | I run a power query to gather all the relevant data for AGV and flat batteries. The 'Name' is the sheet it's pulled from
 | 5 | 227 | 154 | 258 | 296 | 14:55:00 | MonDAGV |  | but I think these will be sheet numbers from 1-31 for dates vs week day numbers
 | 5 | 124 | 142 | 227 | 136 | 16:32:00 | MonDAGV
 | 9 | 591 | 227 | 322 | 897 | 19:55:00 | MonDAGV
 |  |  | example:
 |  |  | Battery: | Time in: | Time out: | Length of service:
 |  |  | 227 | 09:45:00 | 12:10:00
 |  |  | 227 | 14:55:00 | 16:32:00
 |  |  | 227 | 19:55:00
Spreadsheet: 792478d1660917826-output-multiple-blocks-of-data-from-let-ef-sheet
Sheet: Sheet1

Col1 | Col2 | Col3 | Col4 | Col5 | Col6
A | 379 | aa | 915 | qq | 689 |  |  |  | aa | 915 | #N/A | #N/A
B | 536 | ss | 398 | ww | 682 |  |  | 536 | ss | 398 | #N/A | #N/A
C | 872 | dd | 847 | ee | 935 |  |  | 687 | ff | 618 | #N/A | #N/A
D | 687 | ff | 618 | rr | 169
 |  |  |  |  |  |  |  |  | aa | 915 | #N/A | #N/A
 |  |  |  |  |  |  |  | 536 | ss | 398 | #N/A | #N/A
 |  |  |  |  |  |  |  | 687 | ff | 618 | #N/A | #N/A
 |  | aa | 915 | qq | 689
 | 536 | ss | 398 | ww | 682
 | 687 | ff | 618 | ee | 935 |  |  |  | aa | 915 | #N/A | #N/A
 |  |  |  |  |  |  |  | 536 | ss | 398 | #N/A | #N/A
 |  | aa | 915 | qq | 689 |  |  | 687 | ff | 618 | #N/A | #N/A
 | 536 | ss | 398 | ww | 682
 | 687 | ff | 618 | ee | 935
 |  |  |  |  |  |  |  | 379 | aa | 915 | qq | 689
 |  |  |  |  |  |  |  | 536 | ss | 398 | ww | 682
 |  |  |  |  |  |  |  | 687 | ff | 618 | ee | 935
Spreadsheet: sally_beck__34326__Cashflow Forecast 12-18r
Sheet: Hdct & Wages

 |  |  | 2002 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2003
SALARIES | Dec '01 |  | Jan |  | Feb |  | Mar |  | Apr |  | May |  | Jun |  | Jul |  | Aug |  | Sep |  | Oct |  | Nov |  | Dec |  | Jan |  | Feb |  | Mar |  | Apr |  | May |  | Jun
Apollo | 255654.82
Hall
Pearce | 26755.42 |  |  |  |  |  |  |  |  |  |  |  |  |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0
Sweeney | 227610.14 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0
Perlman | 1501504.03
Rub
Webb | 373500.16
Forster | 261994.03
Piper | 27415.41
Pickering | 29300
Beck | 25000
Dayao | 395725.35
Sommers | 0
Total Salaries
Estimated Tax Rate | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231 |  | 0.231
Total
Millions - Outflow
Tax Expense
Rounded
HEADCOUNT | Dec '01 |  | Jan |  | Feb |  | Mar |  | Apr |  | May |  | Jun |  | Jul |  | Aug |  | Sep |  | Oct |  | Nov |  | Dec |  | Jan |  | Feb |  | Mar |  | Apr |  | May |  | Jun
Apollo | 0
Hall | 0
Pearce | 0 |  |  |  |  |  |  |  |  |  |  |  |  |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0
Sweeney | 0 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0 |  | 0 |  | 0 |  | 0 |  | 0 |  | 0
Perlman | 0
Rub | 0
Webb | 0
Forster | 0
Piper | 0
Pickering | 0
Beck | 0
Dayao | 0
Sommers | 0
Accounting | 0
Total Headcount
Spreadsheet: 707515d1607331307-using-a-list-to-reduce-worksheets-midshires-master
Sheet: TMu

 |  |  |  | ADJUSTED HANDICAP |  |  |  |  |  | OFFICIAL HANDICAP |  |  |  |  | HANDICAPPING ALTERATIONS
hole | par | S/I | SHOTS | CALC | points | PAR 3 | SI/1 | SI/2 | S1/3 | SI/1 | S1/2 | S1/3 | CALC | points | EXACT | catagory | BUFFER | css | Nett | adjustment
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | HANDICAP |  | ZONE |  | Differential
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | sss | css adj | "RO"
in
out |  |  |  |  |  | TOTAL
total
Spreadsheet: f7d12e85-5972-42d1-badc-f3de9e7f30cd
Sheet: Sheet1

PROJECT IMPLEMENTATION SUMMARY | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13
COUNTRY: INDIA
SUMMARY OF PARTICIPATION IN RCA PROJECTS FOR 2000
 | FELLOWSHIPS |  | EQUIPMENT | EXPERT ASSIGNMENTS |  | REGIONAL TRAINING EVENTS |  |  |  | OTHER INFORMATION
PROJECT NUMBER | No. Fellows placed overseas for project training | No. Fellows received from overseas for project training | Was Equipment supplied from the project? | No. Experts received under the project during the year | No. Experts sent overseas under the project during the year | No. of Regional Training events hosted during the year | No. of lectureres provided for the Regional Training | No. of Participants sent from your country for the Regional Training during the year | No. of participants received from overseas for Regional Training in this project in your country | No. of other Regional events hosted in your country for the project | No. of other National events hosted in your country for the project | Estimated value of "in kind" contribution to the project during the year (US$) | Was there any TCDC contribution to the project during the year?
22nd RCA National Representatives Meeting, Mumbai, India.
RAS/0/025 |  |  | NO |  | 5 |  |  |  |  |  |  | 32600 | NO
[NAME] |  |  | NO |  | 5 |  |  | 3 |  |  |  | 6000 | NO
RAS/4/019 |  |  | NO | 5 | 1 |  |  | 3 | 28 | 2 |  | 12400 | NO
RAS/5/034 |  |  | NO |  |  |  |  | 1 |  |  |  |  | NO
RAS/5/035 |  |  | NO |  |  |  |  | 1 |  |  |  |  | NO
RAS/6/027 |  |  | NO |  |  |  |  | 4 |  |  |  |  | NO
RAS/6/028 |  | 2 | NO |  | 1 | 1 |  | 12 | 23 |  |  | 11400 | NO
RAS/6/029 |  |  | NO | 2 |  |  |  |  |  |  |  |  | NO
RAS/7/008 |  |  | NO |  | 1 |  |  | 1 |  |  |  | 800 | NO
RAS/8/076 |  |  | NO | 1 | 1 |  |  | 2 |  |  |  | 800 | NO
RAS/8/080 |  |  | NO |  |  | 1 |  | 1 | 18 | 1 |  | 18000 | NO
RAS/8/083 |  |  | NO |  |  |  |  | 2 |  |  |  |  | NO
RAS/8/084 |  |  | NO |  |  |  |  | 3 |  |  |  |  | NO
RAS/8/085 |  |  | NO |  |  |  |  | 1 |  |  |  |  | NO
RAS/8/086 |  |  | NO |  | 2 |  |  | 3 |  |  |  | 6000 | NO
RAS/8/087 |  |  | NO |  |  | 1 |  |  | 7 |  |  | 10000 | NO
RAS/9/018 |  |  | NO |  | 1 |  |  | 9 |  |  |  | 1400 | NO
RAS/9/024 |  |  | NO |  |  |  |  |  | 12 | 1 |  | 10000 | NO
 |  | 2 |  | 8 | 17 | 3 | 0 | 46 | 88 | 4 | TOTAL | 109400
Spreadsheet: 872838d1719287315-put-together-uneven-data-from-various-sheet-tabs-book9
Sheet: FEB

 | Year & Month | Total Number of Available Rooms* | Total Number of Sold Rooms** | Total Room Revenue | Currency | Total Revenue
 | 2022-02-01 00:00:00 | 128 | 66 | 100503.3 | Usd | 119613.62
 | 2022-02-02 00:00:00 | 128 | 69 | 108712.43 | Usd | 129944.22
 | 2022-02-03 00:00:00 | 128 | 81 | 144285.98 | Usd | 172227.05
 | 2022-02-04 00:00:00 | 128 | 72 | 121112.39 | Usd | 145313.64
 | 2022-02-05 00:00:00 | 128 | 72 | 125246.71 | Usd | 152839.97
 | 2022-02-06 00:00:00 | 128 | 42 | 61754.14999999999 | Usd | 74874.7
Spreadsheet: 68604d1269194819-excel-2007-pivot-table-with-conditional-value-ranges-forum-4
Sheet: Sheet2

Question | Property | R1 | R2 | R3 | R4 | Column1 | [NAME] | Positive Responses | Percent Positive |  |  | Minimum Positive Response | 4
1 | Speed | 3 | 3 | 3 | 3 |  | 4 | 4 | 1 |  |  | Maximum Valid Response | 6
2 | Efficiency | 4 | 4 | 4 | 6 |  | 3 | 0 | 0 |  |  | % Positive Ansers
3 | [NAME] | 5 | 5 | 6 | 5 |  | 3 | 0 | 0 |  |  | Speed
4 | Effectiveness | 4 | 4 | 5 | 6 |  | 3 | 0 | 0 |  |  | Efficiency
5 | Effectiveness | 3 | 5 | 4 | 6 |  | 3 | 1 | 0.3333333333333333 |  |  | [NAME]
6 | Effectiveness | 5 | 5 | 5 | 3 |  | 4 | 1 | 0.25 |  |  | Effectiveness
7 | [NAME] | 0 | 5 | 6 | 2 |  | 3 | 2 | 0.6666666666666666
8 | [NAME] | 9 | 4 | 2 | 4 |  | 3 | 1 | 0.3333333333333333
9 | Speed | 7 | 4 | 3 | 5 |  | 3 | 1 | 0.3333333333333333
10 | Speed | 3 | 3 | 7 | 4 |  | 3 | 2 | 0.6666666666666666
11 | Speed | 3 | 4 | 6 | 5 |  | 3 | 1 | 0.3333333333333333
12 | Efficiency | 5 | 5 | 3 | 5 |  | 4 | 1 | 0.25
13 | Effectiveness | 4 | 6 | 4 | 5 |  | 3 | 0 | 0
14 | Speed | 5 | 5 | 4 | 6 |  | 3 | 0 | 0
15 | [NAME] | 4 | 2 | 5 | 5 |  | 4 | 1 | 0.25
16 | [NAME] | 3 | 1 | 4 | 6 |  | 3 | 2 | 0.6666666666666666
17 | Speed | 4 | 5 | 4 | 4 |  | 4 | 0 | 0
18 | Efficiency | 6 | 3 | 4 | 2 |  | 3 | 2 | 0.6666666666666666
19 | Efficiency | 3 | 6 | 2 | 3 |  | 3 | 3 | 1
20 | Efficiency | 6 | 5 | 5 | 6 |  | 2 | 0 | 0
Spreadsheet: 134999d1325750210-excel-lookup-dummy-skill-matrix
Sheet: Team

Sr. No. | Group | Skill Expertise | ABC | BCD | EFG | HIJ | KLM | NOP
1 | Development Tools | [NAME] | 5 | 5 | 4 | 4 | 5 | 4
2 |  | Abaqus | 3 | 5 | 3 |  |  | 2
3 | QA Tools | LMS Test Lab |  | 5 | 4 | 2
4 | New Added By Team Leader | CATIA V5 |  | 3 |  |  | 4
5 |  | LMS Virtual Lab |  | 5
6 | Added Skills by Team Members | Windows | 4 |  | 4 | 4 |  | 4
7 |  | Linux/Unix | 1 |  | 2 |  |  | 3
8 |  | HTML/XHTML 1.1/CSS 2.0 |  |  | 2 |  |  | 1
9 |  | C/C++ |  |  | 2 |  | 2 | 1
10 |  | Visual Basic |  |  | 2
11 |  | Adobe Photoshop CS4 |  |  |  |  | 2 | 2
 | EMP Name | ABC
 | [NAME]
 | Abaqus
 | LMS Test Lab
 | CATIA V5
 | LMS Virtual Lab
 | Windows
 | Linux/Unix
 | HTML/XHTML 1.1/CSS 2.0
 | C/C++
 | Visual Basic
 | Adobe Photoshop CS4
Spreadsheet: 0cd804cc-1fcf-4f6c-a88f-d36b69cc4927
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
 | 8731.0 Building Approvals, Australia
 | TABLE 85. Value of Building Approved, Chain Volume Measures, Original - Northern Territory
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
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total houses ;  New ; |  |  | Original | A590537T | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total other residential building ;  New ; |  |  | Original | A590538V | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total residential building ;  New ; |  |  | Original | A590539W | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total residential building ;  Total alterations/additions (incl. refurb and conversion) ; |  |  | Original | A590540F | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total residential building ;  Total (Type of Work) ; |  |  | Original | A590541J | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total non-residential building ;  Total (Type of Work) ; |  |  | Original | A590542K | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
Value of Approval ($M) ;  Chain Volume Measures ;  Northern Territory ;  Total building ;  Total (Type of Work) ; |  |  | Original | A590543L | 1985-09-01 00:00:00 | 2011-09-01 00:00:00 | 105 | $ Millions | FLOW | Quarter | 3
© Commonwealth of Australia  2011
Spreadsheet: 135882d1326292074-simple-line-graph-burgertacolinegraph
Sheet: Sheet1

City 1 | Burgers | Tacos
Point 1 | 31.62 | 0
Point 2 | 0 | 15.5
 | Burgers | Tacos
 | 0 |  | <<< Look at this formula
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 | 6
 | 7
 | 8
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 | 25
 | 26
 | 27
 | 28
 | 29
 | 30
 | 31
 | 32
Spreadsheet: 819789d1677690984-create-a-rolling-60-minute-window-to-assess-busiest-time-period-rolling60minsample
Sheet: Sheet1

Time | Occurences | Rolling 60 minute total?
0005 | 4
0005 | 5
0010 | 5
0010 | 4
0010 | 5
0010 | 2
0010 | 9
0020 | 1
0030 | 2
0045 | 1
0105 | 13
0105 | 13
0105 | 13
0210 | 1
0430 | 31
0510 | 31
0510 | 31
0510 | 26
0525 | 1
0530 | 30
0530 | 30
0530 | 31
0530 | 31
0530 | 26
0540 | 31
0540 | 21
0540 | 23
0540 | 16
0540 | 1
0550 | 25
0550 | 8
0550 | 31
0600 | 3
0600 | 29
0620 | 31
0620 | 21
0620 | 20
0625 | 1
0630 | 1
0630 | 7
0630 | 28
0630 | 30
0630 | 31
0630 | 31
0630 | 31
0630 | 28
0635 | 9
0640 | 30
0645 | 8
0645 | 8
Spreadsheet: 54444d1254416155-how-to-combine-occurences-by-date-701669_alexeipg
Sheet: Sheet1

Article | Date | Term Mentioned | Running Total
Article 1 | 2008-12-01 00:00:00 | 1 | 1
Article 2 | 2008-12-01 00:00:00 | 1 | 2
Article 3 | 2008-12-01 00:00:00 | 1 | 3
Article 4 | 2008-12-01 00:00:00 | 1 | 4
Article 5 | 2008-12-01 00:00:00 | 1 | 5
Article 6 | 2008-12-03 00:00:00 | 1 | 1
Article7 | 2008-12-05 00:00:00 | 1 | 1
Article 8 | 2008-12-09 00:00:00 | 1 | 1
Spreadsheet: 696150d1600673795-quick-help-required-with-an-avergae-if-fuction-tally-23
Sheet: sheet3

[NAME] |  |  |  |  | Price per Kilo Summary
Species | Presentation | Boxes | Total (Kg) |  | Species | Grade | Presenattion | Boxes | Lowest (Kg) Price | Highest (Kg) Price | [NAME] |  | avg
 |  |  |  |  |  |  |  |  |  |  |  |  | 3.05
 |  |  |  |  |  |  |  |  |  |  |  |  | 3.05
 |  |  |  |  |  |  |  |  |  |  |  |  | 1.65
 |  |  |  |  |  |  |  |  |  |  |  |  | 0.6
 |  |  |  |  |  |  |  |  |  |  |  |  | 0.63
 |  |  |  |  |  |  |  |  |  |  |  |  | 5.66
 |  |  |  |  |  |  |  |  |  |  |  |  | 3.03
 |  |  |  |  |  |  |  |  |  |  |  |  | 2.57
 |  |  |  |  |  |  |  |  |  |  |  |  | 1
 |  |  |  |  |  |  |  |  |  |  |  |  | 6.38
 |  |  |  |  |  |  |  |  |  |  |  |  | 2.63
 |  |  |  |  |  |  |  |  |  |  |  |  | 1.64
 |  |  |  |  |  |  |  |  |  |  |  |  | 1.8
 |  |  |  |  |  |  |  |  |  |  |  |  | 0.75
 |  |  |  |  |  |  |  |  |  |  |  |  | 4.05
 |  |  |  |  |  |  |  |  |  |  |  |  | 4.44
 |  |  |  |  |  |  |  |  |  |  |  |  | 3.81