tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: michelle_lokay__26556__imbalsumm0012
Sheet: Mojave

56696
Day | Scheduled | Measured
1 |  | 71514
2 |  | 74070
3 | 65632 | 66238
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
2000-11-30 00:00:00 |  |  | 84262
2000-12-03 00:00:00
Spreadsheet: 275437d1383514000-sum-cells-based-on-current-month-report-template
Sheet: Front Row

 | Daily | Customer Type |  | Transaction Type |  | Transaction Count
 | PPV | RESIDENTIAL |  | PURCHASE LP/PPV |  | 1
 | Weekly |  | Customer Type |  | Transaction Type |  | Transaction Count
 | PPV |  | RESIDENTIAL |  | PURCHASE LP/PPV |  | 261
 | PPV |  | SLINGSHOT |  | PURCHASE LP/PPV |  | 30
 | PPV |  | ZERO $ STB |  | PURCHASE LP/PPV |  | 1
 | MTD |  | Customer Type |  | Transaction Type |  | Transaction Count
 | PPV |  | RESIDENTIAL |  | PURCHASE LP/PPV |  | 465
 | PPV |  | SLINGSHOT |  | PURCHASE LP/PPV |  | 63
 | PPV |  | ZERO $ STB |  | PURCHASE LP/PPV |  | 5
 | YTD |  | Customer Type |  | Transaction Type |  | Transaction Count
 | PPV |  | RESIDENTIAL |  | PURCHASE LP/PPV |  | 2091
 | PPV |  | SLINGSHOT |  | PURCHASE LP/PPV |  | 376
 | PPV |  | ZERO $ STB |  | PURCHASE LP/PPV |  | 10
 | LTD |  | Customer Type |  | Transaction Type |  | Transaction Count
 | PPV |  | RESIDENTIAL |  | PURCHASE LP/PPV |  | 3335
 | PPV |  | SLINGSHOT |  | PURCHASE LP/PPV |  | 486
 | PPV |  | ZERO $ STB |  | PURCHASE LP/PPV |  | 10
Spreadsheet: 133152d1324233640-counting-the-matching-ones-letter-searching
Sheet: Sayfa1

 | number matching |  | orange
apple
newyork |  |  |  |  | I do searching by entering any letters in cell D1.And those that match become red.What I am tring to achieve is to find out the number  of matchings and display the results in col [NAME] it is clear.Thanks.
london
washington
orange
yellow
blue
green
black
white
Sunday
Monday
Wednesday
Friday
Saturday
spring
summer
winter
january
september
december
april
may
june
july
twenty
eleven
six
seven
nine
ten
Spreadsheet: 709284d1608231571-cpr-training-tracker-countifs-cpr-tracker-forums
Sheet: Employee Data

Emp Name | Emp User ID | Emp ID | Shift Pattern | Shift Pattern Desc
[NAME] A [NAME] | [NAME] |  | AAAA | FC Variable Sched
[NAME] | crowa |  | TEST
[NAME] | [NAME] |  | TEST
[NAME] | bradhawk |  | AAAA | FC Variable Sched
Bradley Holloway | bhollowa |  | TEST
[NAME] Mathis | mathimat |  | AAAA | FC Variable Sched
[NAME] | bchelsea |  | AAAA | FC Variable Sched
[NAME] | balivac |  | TEST
[NAME] | bowlsd |  | TEST
[NAME] | [NAME] |  | AAAA | FC Variable Sched
[NAME] | donfulto |  | TEST
Spreadsheet: 883213d1731736219-formula-to-show-inventory-changes-forum-support
Sheet: Project Costs

Project Cost -  Pricing Info
Project Name | Supply Name | Tool Name | Price Per Unit | Sq Centimeters Used | Cost per Sq cm | Tool Cost Per Use | Total Unit Cost Amount Used | Total Project Cost
ABC Project | Blank Canvas Zipper Pouch Bulk, Makeup bag |  |  | 1008
 | Cardstock pack  - Reds/Pinks |  |  | 30
 | Cardstock pack - Browns/tans |  |  | 851
 | Cardstock pack - foil |  |  | 1585
 | Cardstock pack - Greens |  |  | 5928
 | Cardstock pack - Primary Colours
 |  | Transfer Tape
 |  | 36pcs Vibrant Multicolour Fine Point Dual Tip Pens
 |  | Basic Perforation Blade Tip & Housing
 |  | Premium Fine Point Housing
 |  | Premium Fine Point Replacement Blade
 |  | Black Deep Cut Housing
 |  | Black Deep Cut Replacement Blade
DEF Project | Blank Canvas Zipper Pouch Bulk, Makeup bag |  |  | 252
 | Cardstock pack  - Reds/Pinks |  |  | 624
 | Cardstock pack - Browns/tans |  |  | 624
 | Cardstock pack - foil |  |  | 2496
 | Cardstock pack - Greens |  |  | 2496
 | Cardstock pack - Primary Colours |  |  | 624
 |  | Transfer Tape
 |  | 36pcs Vibrant Multicolour Fine Point Dual Tip Pens
 |  | Basic Perforation Blade Tip & Housing
 |  | Premium Fine Point Housing
 |  | Premium Fine Point Replacement Blade
 |  | Black Deep Cut Housing
 |  | Black Deep Cut Replacement Blade
Tea Lights | Cardstock pack - foil |  |  | 624
 | Cardstock pack - Primary Colours |  |  | 624
 | Cardstock pack - Greens |  |  | 624
 |  | Premium Fine Point Housing
 |  | Premium Fine Point Replacement Blade
Spreadsheet: 599652d1543237560-weighted-average-formula-out-of-10-excel
Sheet: Sheet1

 | 0.25 | 0.22 | 0.13 | 0.05 | 0.35 | 1
 |  |  |  |  |  | Weigted Average out of 10
Name | 2 | 2 | 3 | 3 | 8
Aaryan | 6 | 4 | 5 | 4 | 8
Noman | 1 | 7 | 9 | 5 | 3
Rizwan | 7 | 10 | 10 | 5 | 5
Sheryar | 9 | 10 | 9 | 2 | 6
Adil | 1 | 4 | 3 | 5 | 9
Shahrukh | 5 | 3 | 4 | 3 | 3
Aliza | 7 | 5 | 3 | 8 | 9
[NAME] | 3 | 7 | 7 | 5 | 1
Jaan | 6 | 7 | 7 | 1 | 5
Spreadsheet: 881571d1729680572-repeat-cell-contents-based-on-quantity-testb
Sheet: Costing

SKU | Vendor Code | Description | Life Cycle Stage | [NAME] | Parent Type | Room | Type | Range | H (CM) | W (CM) | D (CM) | WH Assembly Item | CBM | Vendor | DS | Currency | Exch Rate | [NAME] | Landed Cost | RRP | Sale Price
123 |  | ABC |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 100
456 |  | EFG |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 150 | 125
789 |  | HIJ |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 50
Spreadsheet: 167207d1341928277-matching-columns-credit6
Sheet: Sheet1

Customer A | Customer Payment Balance | Customers with Credit balance | Credit Balance | More Credits than Payment Balance?
100 | 100 | 100 | 150 | Yes
200 | 300 | 200 | 0 | No
300 | 200 | 300 | 300 | No
400 | 500 | 800 | 100 | No
500 | 150 | 1000 | 425 | Yes
600 | 200 | Show all customers from col [NAME] If they do not show up in Col C, make col D balance  0
700 | 300 | Customers with no credit do not populate. I would like them to automatically pull from A
800 | 150
900 | 250
1000 | 400
 |  |  |  | Need help with highlighted
What I would Ideally like
Customer A | Customer Payment Balance | Customers with Credit balance | Credit Balance | More Credits than Payment Balance? | Credit Balance | More Credits than Payment Balance?
100 | 100 | 100 | 150 | Yes | 150 | yes
200 | 300 | 200 | 0 | No | 0 | no
300 | 200 | 300 | 300 | No | 300 | yes
400 | 500 | 400 | 0 | No | 0 | no
500 | 150 | 500 | 0 | Yes | 0 | no
600 | 200 | 600 | 0 | No | 0 | no
700 | 300 | 700 | 0 | No | 0 | no
800 | 150 | 800 | 100 | No | 100 | no
900 | 250 | 900 | 0 | No | 0 | no
1000 | 400 | 1000 | 425 | Yes | 425 | yes
 |  | Red filled by new code given by poster
Spreadsheet: 142383d1329816636-how-to-select-maximum-values-based-on-age-in-a-cell-with-an-existing-drop-down-list-pensions-calcs-v2
Sheet: Sheet2

0
Spreadsheet: 807527d1669929288-formular-for-analyze-best-and-weak-students-grades-and-ranks-bvj-issa-r2-
Sheet: 5 BEST AND WEAK STUDENTS

E. FIVE BEST STUDENTS
NO | NAME | SEX M=1 &F=2 | SCHOOL | WARD | SUBJECTS |  |  |  |  |  |  |  |  |  |  |  |  |  | TOTAL | AVERAGE | GRADE
 |  |  |  |  | KISW |  | ENGL |  | HIS |  | SAY |  | M/JAM |  | URA |  | S/KAZI
 |  |  |  |  | A | D | A | D | A | D | A | D | A | D | A | D | A | D
F. FIVE WEAK STUDENTS
NO | NAME | SEX M=1 &F=2 | SCHOOL | WARD | SUBJECTS |  |  |  |  |  |  |  |  |  |  |  |  |  | TOTAL | AVERAGE | GRADE
 |  |  |  |  | KISW |  | ENGL |  | HIS |  | SAY |  | M/JAM |  | URA |  | S/KAZI
 |  |  |  |  | A | D | A | D | A | D | A | D | A | D | A | D | A | D
Spreadsheet: 96771d1296063180-count-base-on-the-day-of-the-week-copy-of-counting
Sheet: Sheet1

NAME | START | FINISH
A | 2011-01-01 00:00:00 | 2011-01-08 00:00:00
B | 2011-01-02 00:00:00 | 2011-01-09 00:00:00
C | 2011-01-03 00:00:00 | 2011-01-10 00:00:00
D | 2011-01-04 00:00:00 | 2011-01-11 00:00:00
E | 2011-01-05 00:00:00 | 2011-01-12 00:00:00
F | 2011-01-03 00:00:00 | 2011-01-10 00:00:00
G | 2011-01-04 00:00:00 | 2011-01-11 00:00:00
Spreadsheet: 1a1218cf-6f78-43be-8f3c-872c12a38ba2
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 21. Value of Dwelling Units Approved in New Residential Buildings, Original, Australia
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 ;  New ;  Total houses ; |  |  | Original | A418405W | 1970-07-01 00:00:00 | 2011-06-01 00:00:00 | 492 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Semi-detached, row or terrace house, townhouse with one storey and similar ; |  |  | Original | A415787K | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Semi-detached, row or terrace house, townhouse with two or more storeys ; |  |  | Original | A422928K | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Total semi-detached, row or terrace houses, townhouses and similar ; |  |  | Original | A416423R | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Flat, unit or apartment in a building of one or two storeys ; |  |  | Original | A423531F | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Flat, unit or apartment in a building of three storeys ; |  |  | Original | A424176T | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Flat, unit or apartment in a building of four or more storeys ; |  |  | Original | A424728C | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Total flats, units or apartments, excl. [NAME] flats and other/unknown ; |  |  | Original | A417065V | 1991-07-01 00:00:00 | 2011-06-01 00:00:00 | 240 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Total other residential building ; |  |  | Original | A419140V | 1970-07-01 00:00:00 | 2011-06-01 00:00:00 | 492 | $'000 | FLOW | Month | 1
Value of Approval ;  New ;  Total residential building ; |  |  | Original | A419826L | 1956-01-01 00:00:00 | 2011-06-01 00:00:00 | 666 | $'000 | FLOW | Month | 1
© Commonwealth of Australia  2011
Spreadsheet: 65354d1266012028-countif-but-only-for-cells-that-correspond-to-date-previous-to-today-book1
Sheet: Sheet1

 |  |  |  |  | 2010-02-07 00:00:00 | 2010-02-08 00:00:00 | 2010-02-09 00:00:00 | 2010-02-10 00:00:00 | 2010-02-11 00:00:00 | 2010-02-12 00:00:00 | 2010-02-13 00:00:00 | 2010-02-14 00:00:00 | 2010-02-15 00:00:00 | 2010-02-16 00:00:00 | 2010-02-17 00:00:00 | 2010-02-18 00:00:00 | 2010-02-19 00:00:00 | 2010-02-20 00:00:00 | 2010-02-21 00:00:00 | 2010-02-22 00:00:00 | 2010-02-23 00:00:00 | 2010-02-24 00:00:00 | 2010-02-25 00:00:00 | 2010-02-26 00:00:00 | 2010-02-27 00:00:00 | 2010-02-28 00:00:00 | 2010-03-01 00:00:00 | 2010-03-02 00:00:00 | 2010-03-03 00:00:00 | 2010-03-04 00:00:00 | 2010-03-05 00:00:00 | 2010-03-06 00:00:00 | 2010-03-07 00:00:00 | 2010-03-08 00:00:00 | 2010-03-09 00:00:00 | 2010-03-10 00:00:00 | 2010-03-11 00:00:00 | 2010-03-12 00:00:00 | 2010-03-13 00:00:00 | 2010-03-14 00:00:00 | 2010-03-15 00:00:00 | 2010-03-16 00:00:00 | 2010-03-17 00:00:00 | 2010-03-18 00:00:00 | 2010-03-19 00:00:00 | 2010-03-20 00:00:00
 |  |  |  |  | Sun | Mon | Tue | Wed | Thu | Fri | Sat | Sun | Mon | Tue | Wed | Thu | Fri | Sat | Sun | Mon | Tue | Wed | Thu | Fri | Sat | Sun | Mon | Tue | Wed | Thu | Fri | Sat | Sun | Mon | Tue | Wed | Thu | Fri | Sat | Sun | Mon | Tue | Wed | Thu | Fri | Sat
 |  |  |  |  |  |  |  |  | UNB | W | W |  |  |  |  | UNB | W | W |  |  |  | W | W | W | W |  |  |  |  | W | W | W |  |  |  | W | W | W | W |  |  |  |  | W | W | W
 |  |  |  |  | Answer from formula should be 1, excluding the other UNB on 2/18 because it is after the date I'm using in my post for the example (assume today is 2/12)
 |  |  |  |  | Once this basic formula is complete, there would be a need to include multiple conditions to be counted. I assume this would be accomplished by simply adding the formula results together, similar to using countif as normal: i.e. - =SUM(COUNTIF(F8:AU8,"UNB")+COUNTIF(F8:AU8,"MIL")+COUNTIF(F8:AU8,"DIF")+etc)). If that assumption is not correct, please point me in the right direction.
Spreadsheet: 1f977134-d1c3-4825-8e08-86087e4a477d
Sheet: Sheet1

AKKA/LAA | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
A.Čaka iela 97,
Rīga, LV-1011
Tālr. | 67506131
Fakss | 67315620
e-pasts [EMAIL]
PROGRAMMAS PAZIŅOJUMS
[NAME] maksātājorganizācija
Izpildītājs
Izpildījuma vieta |  |  |  | Izpildījuma datums
Kontaktpersona |  |  |  | Tālrunis
Bruto ienākumu summa |  |  |  | Autoratlīdzības summa | aizpilda AKKA/LAA
Nr. | Darba nosaukums | Komponists | Teksta autors | Aranžētājs | Horeogrāfs | Izpildītājs | Ilgums | Skanēšanas reizes
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
 | Z.v. |  | Programmas paziņojums sastādīts pareizi:
 |  |  |  |  |  | paraksts, uzvārds
Spreadsheet: sally_beck__34340__2002 Budget Edie Format
Sheet: East Power

 | East Power
 | 2002 Plan
 |  |  |  |  |  |  |  |  |  | Per HC | New HC | Adjust Comp
 |  | 2001-09-01 00:00:00 |  | 2001 | 2002 |  | % |  |  |  |  |  |  | 2002
 |  | YTD Actual |  | Forecast | Plan |  | of Total |  |  |  |  |  |  | Plan
ENACOMP | Compensation |  |  |  |  |  |  |  | Compensation | 0
 | Special Pays
 | Analysts & Associates
ENABENTX | Benefits & Payroll Taxes |  |  |  |  |  |  |  | Other
ENAEMPEX | Employee Expense
ENAT&EEX | Travel & Entertainment Expense |  |  |  |  |  |  |  | Total
ENAOUTSV | Outside Services
ENASUPP | Supplies Expense
ENAMKTEX | Marketing |  |  |  |  |  |  |  | [NAME] | 33600 | 2
ENACONTR | Charitable Contributions |  |  |  |  |  |  |  | [NAME] | 52800 | 2
ENARENT | Rent |  |  |  |  |  |  |  | Staff | 54000
ENATECH | Technology |  |  |  |  |  |  |  | Specialist | 63000 | 0
ENATRANS | Transportation |  |  |  |  |  |  |  | Sr. Specialist | 78000
ENAOTHEX | Other Expenses |  |  |  |  |  |  |  | Analyst | 66000
ENATAXES | Taxes Other than Income |  |  |  |  |  |  |  | Associate | 97200
ENATOTDR | Total Direct Expenses |  |  |  |  |  |  |  | Manager | 120000
 |  |  |  |  |  |  |  |  | Director | 156000
 | Headcount |  |  |  |  |  |  |  | Sr. Director | 180000
 |  |  |  |  |  |  |  |  | VP | 216000
 | Analyst & Associate Headcount |  |  |  |  |  |  |  | MD | 240000 | 2
 | Total Headcount |  |  |  |  |  |  |  |  |  |  |  |  | 1
 |  |  |  |  |  |  |  | Other Expense Calculation
 | Outside Services | 524067
 |  |  |  |  |  |  |  | Total Misc Exp | Old HC | Exp/Old HC | New HC | Exp/New HC
Spreadsheet: 848120d1698917923-using-formula-to-return-unique-values-works-but-returns-a-double-value-testsheets-3-h
Sheet: Partnerships

 | Partner |  | Budget |  | Actuals |  | Opmerkingen |  | Kwartaal
 | Value 1 |  | 10000 |  | 10000 |  | [NAME] ipsum dolor sit amet, consectetur adipiscing elit |  | Q4
 | Value 2 |  | 5000 |  | 5200 |  |  |  | Q2
 | Value 3 |  | 10000 |  | 10500 |  |  |  | Q1
 | Value 4 |  | 4000 |  | 4000 |  |  |  | Q3
 | Value 3 |  | 2500 |  | 2750
 | Value 2 |  | 500 |  | 500
 | Value 3 |  | 1500 |  | 1750
SUBTOTAAL |  |  | 10000 |  | 10000 |  |  | Q1 |  | undesired result
 | Value 2 |  | 5500 |  | 5700 |  |  | Q2
 | Value 3 |  | 14000 |  | 15000 |  |  | Q3
 | Value 4 |  | 4000 |  | 4000 |  |  | Q4
TOTAAL
Spreadsheet: 42152d1240716546-shifting-formula-sample
Sheet: Sheet1

NAME |  | hr25/sr25/ut50 |  |  | ER | CR | CD | DR | PE | HR | MA | OQ | SR | UT
Whepla* |  |  |  |  |  |  |  | 998 |  |  | 970 | 916 | 302 | 65
Anaiek* |  | 0.7700681818181818 |  |  |  | 698 | 751 | 649 |  | 301 | 927 | 866 | 660 | 854
...several hundred more rows of different data
 |  | HR cap | 550
 |  | SR cap | 800
 |  | UT cap | 1000
 |  | HR is 25% of the total, SR is 25%, and UT is 50%
 |  | The other columns are ignored in this particular formula. Only SR, HR and UT are used
 |  | [NAME] in C3 is the beginning standard, and correct for this row
 |  | The formula in C3 needs to be applied to all rows
 |  | If HR is missing, the new weights should be UT is 66% and SR is 33%
Spreadsheet: 327665d1403638149-concatenate-variable-ranges-of-character-strings-tasasupd_0529upd-ans2
Sheet: Sheet9

SERIES | ACCIDENT_ID | SEVERITY | KILLED | INJURED | DUPLICATE | PATTERN | PATTERN2 | UNIQUE | Pattern of Values | [NAME] ASSIGNED |  | COUNT
 | 1111 | PDO | 0 | 0 | DEL
 | 1111 | K | 1 | 0 | 0
 | 1111 | PDO | 0 | 0 | DEL
 | 1111 | PDO | 0 | 0 | DEL
 | 1112 | K | 1 | 4 | 0
 | 1112 | K | 1 | 4 | 0
 | 2222 | I | 0 | 1 | DEL
 | 2222 | K | 1 | 0 | 0
 | 2222 | I | 0 | 1 | DEL
 | 2222 | PDO | 0 | 0 | DEL
 |  |  | 0 | 0
Spreadsheet: 267208d1380012832-vlookup-function-0a215_a
Sheet: Stewart, Shane

[NAME], Shane
Umpire | Player | Team | Position | Votes | Team Margin | K | H | D | CP | UP | DE% | CLG | M | CM | M50 | HO | CLR | CC | ST | R50 | FF | FA | T | 0.01 | Bo | [NAME] | G | B | GA | G% | TG% | DT
Spreadsheet: cd5874f8-a8e4-4cb2-81d1-40aa98f3821d
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 | Unnamed: 12
 | CORDOBA - CABANA A PARTIR DE ENERO 2014
 | [NAME] | Lunes a Lunes | Sábados y Domingos | Lunes a Viernes | Lunes a Viernes | Lunes a Viernes | Sábados y Domingos | Sábados y Domingos | Lunes a Viernes | Lunes a Lunes | Sábados y Domingos | Lunes a Viernes
 | Terminal de Córdoba | 07:30:00 | 10:35:00 | 10.40 | 11:45:00 | 12:40:00 | 12:50:00 | 16:35:00 | 16:50:00 | 18:30:00 | 20:25:00 | 20:45:00
 | Villa Allende Monolito | 08:15:00 | 11:20:00 | 11:25:00 | 12:30:00 | 13:25:00 | [NAME] | 17:20:00 | 17:35:00 | 19:15:00 | 21:10:00 | 21:30:00
 | Villa Allende Municipalidad | [NAME] | 11:27:00 | 11:32:00 | 12:37:00 | 13:32:00 | 13:42:00 | 17:27:00 | 17:42:00 | 19:22:00 | 21:17:00 | 21:37:00
 | [NAME]. 16 | 08:35:00 | 11:40:00 | 11:45:00 | 12:50:00 | 13:45:00 | 13:55:00 | 17:40:00 | 17:55:00 | 19:35:00 | 21:30:00 | 21:50:00
 | Terminal de Unquillo. | 08:40:00 | 11:45:00 | 11:50:00 | 12:55:00 | 13:50:00 | 14:00:00 | 17:45:00 | 18:00:00 | 19:40:00 | [NAME] | 21:55:00
 | Cabana | 09:00:00 | 12:05:00 | 12.10 | 13:15:00 | [NAME] | 14:20:00 | 18:05:00 | 18:20:00 | 20:00:00 | 21:55:00 | 22:15:00
 | REGRESO | Lunes a Lunes | Lunes a Lunes | Lunes a Lunes | Lunes a Lunes | Lunes a Viernes | Lunes a Lunes | Lunes a Lunes | Lunes a Lunes | Lunes a Viernes
 | Cabana | 06:00:00 | 07:20:00 | 09:20:00 | 12:30:00 | 13:15:00 | 14:30:00 | 18:35:00 | 20:20:00 | 22:15:00
 | Villar |  |  |  |  |  |  |  |  | 22:25:00
 | Terminal de Unquillo. | 06:20:00 | 07:40:00 | 09:40:00 | 12:50:00 | [NAME] | 14:50:00 | 18:55:00 | 20:40:00
 | [NAME]. 16 | 06:25:00 | 07:45:00 | 09:45:00 | 12:55:00 |  | 14:55:00 | 19:00:00 | 20:45:00
 | Villa Allende Municipalidad | 06:38:00 | 07:58:00 | 09:58:00 | 13:08:00 |  | 15:08:00 | 19:13:00 | 20:58:00
 | Villa Allende Monolito | 06:45:00 |  |  | 13:15:00
 | Villa Allende La Herradura |  | 08:06:00 | 10:06:00 |  |  | [NAME] | 19:21:00
 | Aeropuerto |  | 08:13:00 | 10:13:00 |  |  | 15:27:00 | 19:28:00 | 21:13:00
 | Terminal de Córdoba | 07:35:00 | 08:55:00 | 10:50:00 | 14:00:00 |  | 15:55:00 | 20:05:00 | 21:50:00
 | Consultas, [NAME] e Información |  |  |  |  | [PHONE]
Spreadsheet: 0ca5217a-34b1-4185-816f-1092f1cdae84
Sheet: Introduction

 | This  spreadsheet accompanies the U.S. GAAP Financial Reporting Taxonomy v2014 DRAFT Release Notes (August 31, 2013):
 | Below is the link to the worksheet which lists the elements by change made.
 |  |  | Appendix | No. of Elements
 |  |  | Appendix 1: Data Type Changes | 0
 |  |  | Appendix 2: Balance Type Changes | 0
 |  |  | Appendix 3: Deprecated Items | 98
 |  |  | Appendix 4: Label Changes | 66
 |  |  | Appendix 5: Reference Changes | 15
 |  |  | Appendix 6: Definition Changes | 66
 |  |  | Appendix 7: New Elements | 301
 |  |  | Appendix 8: Deleted Elements | 706
Spreadsheet: 836466d1689377369-combining-formulas-help
Sheet: Project Commitments

 |  |  |  | Commercial Customers
 |  |  |  | Wholesale Customers
 |  |  |  | Total Commercial Capex
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Year to Date
 |  |  | Project Number | Work Order Number | Project Site Name | Program | January | February | March | April | May | June | July | August | September | October | November | December |  | Approved | Status | Projects Completed | Projects Inflight | Approved  (Open Projects) | Committed  (Open Projects) | Total Committed |  | Invested | Budget | [NAME]
 |  |  | A-012345 |  |  |  |  |  |  |  | 203853
 |  |  | A-012346
 |  |  | A-012347 |  |  |  |  |  | 7554
 |  |  | [NAME]
 |  |  | A-012349
 |  |  | A-012350 |  |  |  | 7554
 |  |  | A-012351
 |  |  | A-012352 |  |  |  | 7554
 |  |  | A-012353
 |  |  | A-012354
 |  |  | A-012355 |  |  |  |  |  |  |  |  | 580.39
 |  |  | A-012356
 |  |  | A-012357
Spreadsheet: 790525d1659764469-search-table-given-dates-and-numbers-as-criteria-help_please-v2
Sheet: Sheet1

VOLUME DISCOUNT PER ITEM TABLE BASED ON INVOICE DATE
VOLUME PER ITEM: |  |  | 5000 |  | CHANNEL: |  | EU
INVOICE DATE: |  |  | 2022-02-15 00:00:00 |  | VOLUME DISCOUNT: |  |  | <<<--- HELP
 |  |  |  |  | EXCEL 365 FORMULA: |  |  | <<<--- OK
WORKAROUND: INSTEAD VOL ONLY, RENAME VOL TO ≥VOL AND INSERTED A COLUMN <VOL
FOR NON-EXCEL 365, SORT BY VOL
≥VOL | <VOL | FR_DATE | TO_DATE | EU | DL | DR | TB | PL | RM
0 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0 | 0 | 0 | 0 | 0 | 0
2000 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.04 | 0 | 0 | 0 | 0 | 0
5000 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.08 | 0 | 0 | 0 | 0 | 0
10000 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.12 | 0 | 0 | 0.04 | 0.04 | 0
15000 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.16 | 0 | 0 | 0.08 | 0.08 | 0
20000 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.2 | 0 | 0 | 0.12 | 0.12 | 0
25000 |  | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.2 | 0 | 0 | 0.16 | 0.16 | 0
30000 | 9999999 | 2022-02-01 00:00:00 | 2022-12-31 00:00:00 | 0.2 | 0 | 0 | 0.2 | 0.2 | 0
0 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0 | 0 | 0 | 0 | 0 | 0
2000 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.02 | 0 | 0 | 0 | 0 | 0
5000 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.04 | 0 | 0 | 0 | 0 | 0
10000 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.06 | 0 | 0 | 0.02 | 0.02 | 0
15000 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.08 | 0 | 0 | 0.04 | 0.04 | 0
20000 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.1 | 0 | 0 | 0.06 | 0.06 | 0
25000 |  | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.1 | 0 | 0 | 0.08 | 0.08 | 0
30000 | 9999999 | 2022-01-01 00:00:00 | 2022-01-31 00:00:00 | 0.1 | 0 | 0 | 0.1 | 0.1 | 0
Spreadsheet: 150849d1334692874-combine-two-rows-after
Sheet: Sheet1

Cust # | Agent | Comment | Date | Total | Rating A | Rating B
10 | [NAME] | AAA | 2012-04-17 00:00:00 | 15 | 1 | 5
11 | [NAME] | ZZZ | 2012-04-18 00:00:00
12 | jill | CCC | 2012-04-15 00:00:00 | 25 | 5 | 4
45 | bob | BBB | 2012-04-20 00:00:00
Spreadsheet: 672222d1586796848-formula-add-degree-sign-min-sign-and-sec-sign-to-a-cell-degreemins
Sheet: Sheet1

 | Ket | 0 | 0 | 0 |  |  | Ket | 0°00’00”
 | Ven | 0 | 2 | 43 |  |  | Ven | 0°02’43”
 | Sun | 0 | 10 | 30 |  |  | Sun | 0°10’30” |  |  |  | ° | alt0176
 | [NAME] | 0 | 12 | 50 |  |  | [NAME] | 0°12’50”
 | Mar | 0 | 16 | 44 |  |  | Mar | 0°16’44” |  |  |  | ’ | [NAME]
 | Rah | 0 | 19 | 27 |  |  | Rah | 0°19’27”
 | Jup | 0 | 26 | 27 |  |  | Jup |  |  |  |  | ” | alt0148
 | Sat | 0 | 32 | 40 |  |  | Sat
 | Mer | 0 | 40 | 4 |  |  | Mer
 | Ven | 0 | 46 | 40 |  |  | Ven
 | Sun | 1 | 8 | 52 |  |  | Sun
 | [NAME] | 1 | 15 | 32 |  |  | [NAME]
 | Mar | 1 | 26 | 39 |  |  | Mar
 | Rah | 1 | 34 | 26 |  |  | Rah
 | Jup | 1 | 54 | 26 |  |  | Jup
 | Sat | 2 | 12 | 13 |  |  | Sat
 | Mer | 2 | 33 | 20 |  |  | Mer
 | Ket | 2 | 52 | 13 |  |  | Ket
 | Sun | 3 | 0 | 0 |  |  | Sun
 | [NAME] | 3 | 2 | 0 |  |  | [NAME]
 | Mar | 3 | 5 | 20 |  |  | Mar
 | Rah | 3 | 7 | 40 |  |  | Rah
 | Jup | 3 | 13 | 40 |  |  | Jup
 | Sat | 3 | 19 | 0 |  |  | Sat
 | Mer | 3 | 25 | 20 |  |  | Mer
 | Ket | 3 | 31 | 0 |  |  | Ket
 | Ven | 3 | 33 | 20 |  |  | Ven
 |  |  |  |  |  |  |  |  | I need help with a formula that will  copy from C2 add degree °sign
 |  |  |  |  |  |  |  |  | copy from D2 add min  ’sign and copy e2 add the sec ”
 |  |  |  |  |  |  |  |  | all these will appear in I2