tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 599731d1543282637-retail-inventory-calculating-multiple-items-in-a-sale-copy-of-retail-inventory-23102018-markp2010-
Sheet: Products

INVENTORY AND SALES MANAGER |  |  |  |  | Orders and Inventory |  | Report | Terms
INSTRUCTIONS
1. Enter Products below
2. Enter Order details in the Orders and Inventory worksheet
3. View the report in the Report worksheet.
ENTER PRODUCTS |  |  |  |  |  | FEATURES:
Product Name | Product Description | Product Category | Re-Order Point |  |  | Enter and manage up to 2000 different Products
P1 |  | Cream | 10 |  |  | Set custom re-order points for each product
P2 |  | Cream | 10 |  |  | Simple and Easy data entry
P3 |  | Cream | 10 |  |  | Know current inventory levels of each product
P4 |  | Cream | 10 |  |  | Identify the products to be re-ordered
P5 |  | Cream | 10 |  |  | Know if the sale orders can be fulfilled
P6 |  | Butter | 10 |  |  | Easily understand the sales and purchase patterns (monthly and cumulative)
P7 |  | Butter | 10 |  |  | Quickly see your top customers and suppliers
P8 |  | Cream | 10 |  |  | Identify your best performing products
P9 |  | Cream | 10 |  |  | Know how the different product categories contribute to sales
P10 |  | Cream | 10 |  |  | Easily retrieve and view your order details
Pack 1 | P1,P2,P3,P3
Pack 2 | P1,P5,P7,P8,P8,P10 |  |  |  |  | DATA VALIDATION
End of 2000 Products
Spreadsheet: 866500d1713432520-a-formula-to-select-the-highest-cell-in-a-column-that-then-shows-the-entire-row-walks
Sheet: 2017

 |  |  |  |  |  |  | 2017
 |  |  |  |  |  |  |  | Number  of Walks | Total Miles | Total Height in Feet | Total Hours Walked | Average Speed
 |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  |  | Will
 |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  |  | [NAME]
Spreadsheet: 876196d1722874291-placing-team-to-game-dates-learning-the-ropes-book-5-no-merged-cells-aligw
Sheet: Team-Course Schedule

Teams | 2025-05-27 00:00:00 | Week 1 | HCP | Place |  |  | HCP | Place |  |  | HCP | Place |  |  | HCP | Place |  |  | HCP | Place
 | 1
 | 1 | [NAME] slow |  |  | 10 | [NAME] |  |  | 9 | [NAME] |  |  | 8 | Shelly Early |  |  | 7 | [NAME]
 |  | VS | HCP |  |  | VS | HCP | Place |  | VS | HCP | Place |  | VS | HCP | Place |  | VS | HCP | Place
 | 6
 | 6 | [NAME] |  |  | 2 | Nate Late |  |  | 3 | Mac Long |  |  | 4 | [NAME] |  |  | 5 | [NAME]
 | Team-Course Schedule
Spreadsheet: 06d2afb7-1e07-4156-9765-c67a373a1ce1
Sheet: Girls

 | 2013 US Youth Soccer ODP Region II Championships & Showcase - Girls
 | Sportscore Two Soccer Complex  8800 E Riverside Blvd, Loves Park, Illinois
 | 96 GIRLS |  |  |  |  | 97 GIRLS |  |  |  |  |  | 98 GIRLS
 | Day/Date | Time | Fld # | Fld # |  | Day/Date | Time | Fld # | Fld # | Fld # |  | Day/Date | Time | Fld # | Fld # | Fld # | Fld # | Fld #
 | SS2 Flds |  | 201 | 202 |  | SS2 Flds |  | 205 | 206 | 209 |  | SS2 Flds |  | 203 | 204 | 207 | 208
 | 7/5 Fri PM | 4pm | MI-IL | WI-IA |  | 7/5 Fri PM | 4:15pm | MN-MI | IL-IN |  |  | 7/5 Fri PM | 4:30pm | IA-IN1 | [NAME] | KY-IL2 | IN2-DAK
 |  | 6pm | IN-OS | MN-MO |  |  | 6:15pm | KY-WI | MO-OS | KS-ON |  |  | 6:30pm | WI-OS2 | MI-MO | NE-ON2 | ON1-OS1
 | SS2 Flds |  | 218 | 219 |  | SS2 Flds |  | 210 | 211 | 213 |  | SS2 Flds |  | 216 | 217 | 220 | 221
 | 7/6 Sat AM | 8am | WI-IN | IL-OS |  | 7/6 Sat AM | 8:15am | IL-MI | IN-MN | OS-ON |  | 7/6 Sat AM | 8:30am | IL-IA | IN1-KY | IL2-MN | OS1-DAK
 |  | 10am | IA-MO | MI-MN |  |  | 10:15am | WI-MO | KS-KY |  |  |  | 10:30am | ON1-IN2 | NE-WI | ON2-MI | OS2-MO
 | SS2Flds |  | 201 | 202 |  | SS2 Flds |  | 205 | 206 | 209 |  | SS2 Flds |  | 203 | 204 | 207 | 208
 | 7/6 Sat PM | 4pm | IL-WI | IN-MI |  | 7/6 Sat PM | 4:15pm | ON-WI | IL-MN | MI-OS |  | 7/6 Sat PM | 4:30pm | IL-KY | IN1-MN | IA-IL2 | IN2-OS1
 |  | 6pm | MN-IA | MO-OS |  |  | 6:15pm | KY-IN | MO-KS |  |  |  | 6:30pm | DAK-ON1 | OS2-NE | MO-ON2 | WI-MI
 | SS2 Flds |  | 218 | 219 |  | SS2 Flds |  | 210 | 211 | 213 |  | SS2 Flds |  | 216 | 217 | 220 | 221 | 209
 | 7/7 Sun AM | 8am | OS-WI | IA-MI |  | 7/7 Sun AM | 8:15am | KS-ON | IN-MO | MN-KY |  | 7/7 Sun AM | 8:30am | Top 2 Pts | Match-up | Match-up | Match-up | Match-up
 |  | 10am | IL-MN | MO-IN |  |  | 10:15am | IL-OS | WI-MI |  |  |  | 10:30am | Match-up | Match-up | Match-up | Match-up
 |  |  | 2x 35 Min. Halves |  |  |  | 2x35 Min Halves |  |  |  |  |  | 2x35 Min Halves
 |  | IL | MI |  |  | Championship bracket for bold teams |  |  |  |  |  |  | Championship bracket for bold teams
 |  | IA | WI |  |  | IL | KY | MO | ON |  |  |  | A IL |  | B IA
 |  | IN | MO |  |  | IN | MI | OS |  |  |  |  | A IN |  | B IL2
 |  | MN | OS |  |  | MN | WI | KS |  |  |  |  | A KY |  | B MN
 |  |  |  |  |  | Pts. 3 for win, 1 for tie , 1  for goal up to 4/game |  |  |  |  |  |  | Pts. 3for win, 1 for tie , 1 for a goal up to 4/game
 |  |  | Advancement only applies for bolded teams entered in National ODP Championship series.   All others are Showcase matches. |  |  |  |  |  |  |  |  |  | A group plays B group
 |  |  |  |  |  |  |  |  |  |  |  |  | 2 highest point getters regardless of group play in championship
 |  |  |  |  |  |  |  |  |  |  |  |  | 1998 "B" Bracket Teams
 |  |  |  |  |  |  |  |  |  |  |  |  | IN2 | WI | MI
 |  |  |  |  |  |  |  |  |  |  |  |  | DAK | OS2 | MO
 |  |  |  |  |  |  |  |  |  |  |  |  | ON | NE | ON2
 |  |  |  |  |  |  |  |  |  |  |  |  | OS
Spreadsheet: 742776d1628024901-2-columns-2-drop-down-lists-make-certain-cells-in-2nd-drop-down-list-populate-sample-drop-down-list-with-dv
Sheet: Sheet1

Week # | Over 38 Hours? | Submitted Timesheet?
Week1 | Yes | Yes - Give me the money
Week2 | No | N/A - No Overtime
Week3 | Yes | Yes - Give me the money
Week4 | Yes | Yes - Give me the money
Week5 | No | N/A - No Overtime
Week6 | No | N/A - No Overtime
Week7
Week8
Week9
Week10
Week11
[NAME]
Week13
Week14
Week15
Week16
Week17
Week18
Week19
Week20
Week21
Week22
Week23
Week24
Week25
Week26
Week27
Week28
Week29
Week30
Spreadsheet: kimberly_watson__20556__imbalsumm0109
Sheet: SidR

 | [NAME]
 | POI 1190 - Keystone Plant Outlet
Day | Measured | Scheduled
1 | 58538 | 63848
2 | 58642 | 55697
3 | 58406 | 59792
4 | 59692 | 63944
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
2001-08-31 00:00:00 |  |  | 13515
2001-09-04 00:00:00
CBS Volume
 |  |  | 4742
Spreadsheet: richard_sanders__32083__attachments
Sheet: Portfolio 1 - NP15 Longs

[NAME]: | [NAME] of Four Portfolio Bid that Was Ultimately Scheduled at Silver Peak
 | Initial Bid
 | Price | Quantity | Price | Quantity | Price | Quantity | Price | Quantity | Unconstrained | Accepted
Hour Ending |  |  |  |  |  |  |  |  | MCP
0100 | 0 | 0 | 2500 | 0 |  |  |  |  | 20.6554 | 0
0200 | 0 | 0 | 2500 | 0 |  |  |  |  | 18.3717 | 0
0300 | 0 | 0 | 2500 | 0 |  |  |  |  | 17.504 | 0
0400 | 0 | 0 | 2500 | 0 |  |  |  |  | 14.0569 | 0
0500 | 0 | 0 | 2500 | 0 |  |  |  |  | 18.9964 | 0
0600 | 0 | 0 | 2500 | 0 |  |  |  |  | 24.4967 | 0
0700 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 19.9428 | 725
0800 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 25.8947 | 725
0900 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 26.9196 | 725
1000 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 27.5973 | 725
1100 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 28.3814 | 725
1200 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 28.1807 | 725
1300 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 27.999 | 725
1400 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 28.7672 | 725
1500 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 28.9763 | 725
1600 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 28.1041 | 725
1700 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 28.1997 | 725
1800 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 27.0583 | 725
1900 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 26.5752 | 725
2000 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 25.6897 | 725
2100 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 29.2826 | 725
2200 | 0 | 0 | 18.35 | 0 | 18.36 | 725 | 2500 | 725 | 26.4872 | 725
2300 | 0 | 0 | 2500 | 0 |  |  |  |  | 25.9942 | 0
2400 | 0 | 0 | 2500 | 0 |  |  |  |  | 24.4942 | 0
Spreadsheet: 525727d1498852648-frequency-of-unique-value-and-sum-of-unique-values-based-on-criteria-test_formula
Sheet: Sheet1

Name | ID | rate | onsite | boli | unique numer of rates per person that onsite=1 boli=1 and greater than 0 | subtotal unique number rates per person that boli=1 onsite=1 and greater than 0
[NAME] | 101 | 29.37 | 1 | 1 | {=SUM(--(FREQUENCY(IF([[ID ]]=[@[ID ]],[rate]),[rate])>0),0)}
[NAME] | 101 | 0 |  | 0
[NAME] | 101 | 37.41 | 0 | 1
[NAME] | 101 | 29.37 | 0 | 1
[NAME] | 101 | 37.41 | 1 | 1
[NAME] | 106 | 29.37 | 1 | 1
[NAME] | 106 | 45.15 | 1 | 1
[NAME] | 106 | 29.37 | 1 | 1
[NAME] | 106 | 45.15 | 1 | 1
[NAME] | 106 | 37.41 | 1 | 1
[NAME] | 106 | 28.19 | 1 | 1
[NAME] | 107 | 29.37 | 0 | 1
[NAME] | 107 | 29.37 | 1 | 1
[NAME] | 107 | 29.37 | 1 | 1
[NAME] | 107 | 29.37 | 0 | 1
[NAME] | 107 | 29.37 | 0 | 1
[NAME] | 107 | 29.37 | 0 | 1
Spreadsheet: 876630d1723360629-how-to-link-or-import-data-between-two-excel-workbooks-with-very-different-formats-daily-sheets
Sheet: 06.28.24

 | AM SHIFT REPORT
 |  |  |  | 2024-06-28 00:00:00
 | UNIT | Bed Capacity | Bud. Beds | Census | Census Pending | RN's | RN PD | Travel | RN OT | RN Sick | Tech | N.A. | Comments
 | 3RD FL | 13 | 7 | 5 | 0 | 2 | 0 | 0 | 0 | 0 | 1 | 0
 | 4TH FL | 38 | 22 | 24 | 0 | 5 | 0 | 3 | 0 | 0 | 2 | 0
 | 5TH FL | 34 | 20 | 22 | 1 | 5 | 2 | 1 | 0 | 0 | 1 | 0
 | ABC | 27 | 18 | 20 | 1 | 6 | 1 | 1 | 0 | 0 | 3 | 0
 | MNO | 12 | 6 | 6 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 0
 | Total MED
 | JKL | 26 | 4 | 4 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0
 | DEF | 10 | 4 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0
 | GHI | N/A | N/A | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 0
 | Total MAT
 | Total Holds AM | N/A | N/A | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 2 | 0
 | Total Holds MID |  |  | 0 | 0 | 4 | 1 | 0 | 0 | 0 | 1 | 0
 | Total House Census
 | PM SHIFT REPORT
 |  |  |  | 2024-06-28 00:00:00
 | UNIT | Bed Capacity | [NAME] | Census | Census Pending | RN's | RN PD | Travel | RN OT | RN Sick | Tech | N.A. | Comments
 | 3RD FL | 13 | 7 | 4 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0
 | 4TH FL | 38 | 22 | 22 | 0 | 4 | 0 | 0 | 0 | 1 | 1 | 0
 | 5TH FL | 34 | 20 | 22 | 0 | 4 | 1 | 2 | 0 | 0 | 1 | 0
 | ABC | 27 | 18 | 20 | 0 | 5 | 0 | 2 | 1 | 1 | 2 | 0
 | MNO | 12 | 6 | 5 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 0
 | Total MED
 | JKL | 26 | 4 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0
 | DEF | 10 | 4 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0
 | GHI | N/A | N/A | 1 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 0
 | Total MAT
 | Total Holds PM | N/A | N/A | 0 | 0 | 4 | 2 | 0 | 0 | 0 | 1 | 0
 | Total House Census
Spreadsheet: 701792d1603932150-formula-for-specific-cell-to-trigger-from-multiple-drop-downs-book2
Sheet: Sheet1

 | EMPLOYEE NAME | Title | Step | Path Position # | UC Path ID | DOS | Account | Pay Rate | Dist % | Mo/BW Total | Annual Sal | Dist Begin Date | Dist End Date | Comments | Grant end date | Vac | Sick lve | Appt End date | Visa Type | [NAME]
 |  | GSR | 1
Spreadsheet: 162784d1340060664-copy-of-managers-clients-info-from-master-list-database-example
Sheet: TFA

Date | Name | SSN | CAT | VASH | Amount | Payable To | Type | Reason | Comments | Case Manager | Amount Denied | Reason Denied
2012-06-01 00:00:00 | Smith, R. |  |  |  | 1009 | DNN Palmdale Land Co. | Rent | Security Deposit | asdfjkl; | [NAME]
2012-06-04 00:00:00 | Walls, B. |  |  |  | 1186 | [NAME], LLC | Rent | Security Deposit | asdfjkl;
2012-06-05 00:00:00 | Smith, C. |  |  |  | 1110 | 455 [NAME], LLC | Rent | Security Deposit | asdfjkl;
2012-06-06 00:00:00 | Smith, J. |  |  |  | 50 | asdfjkl; | Utilities | Utility Deposit | asdfjkl;
2012-06-07 00:00:00 | Walls, B. |  |  |  | 62 | asdfjkl; | Other | Emergency Supplies | asdfjkl;
2012-06-07 00:00:00 | Smith, E. |  |  |  | 1000 | asdfjkl; | Rent | Rent/Fee | asdfjkl;
2012-06-07 00:00:00 | Smith, K. |  |  |  | 972 | asdfjkl; | Rent | Security Deposit | asdfjkl;
Spreadsheet: 64367d1265234010-vlookup-returns-value-from-different-row-vlookup-mess
Sheet: Sheet1

it0000 |  | PRIVATE |  |  |  | it0000 | 101112
it0001 |  | DEPT OF COMMERCE/NOAA |  | 1305 E WEST HWY |  | it0001 | 100488 | 20910
it0002 |  | DEPT OF JUSTICE |  | 1331 PENNSYLVANIA AVE  NW |  | it0002 | 101494 | 20004
[NAME] |  | AVERSTAR  INC, G37 |  | 1593 SPRING HILL ROAD, SUitE 700 |  | [NAME] | 100363 | 22182
it0004 |  | RS INFORMATION SYSTEMS (RSIS) |  | 1651 OLD MEADOW RD  5TH FLR |  | it0004 | 105257 | 22102
it0005 |  | SPARTA INC |  | 23041 AVENIDA DE LA CARLOTA STE 325 |  | it0005 | 104271 | 92653-1545
it0006 |  | DIRECTORATE OF CONTRACTING |  | 30 N WOLFE AVE |  | it0006 | 100488 | 93524
it0007 |  | GSA |  | 301 7TH & D ST SW  RM 5060 |  | it0007 | 102401 | 20407
it0008 |  | DEPT OF HEALTH AND HUMAN SERVICES |  | 330 INDEPENDENCE AVE RM 443H SW |  | it0008 | 101485 | 20201-0002
it0009 |  | FOOD AND DRUG ADMIN |  | 3900 NCTR RD HFT 322 |  | it0009 | 102254 | 72079
it0010 |  | SECURitY & EXCHANGE COMMISSION |  | 450 5TH ST NW R10199 |  | it0010 | 105004 | 20544
it0011 |  | AMDAHL |  | 5335 WISCONSIN AVE NW |  | it0011 | 100100 | 20015
it0012 |  | DEPT OF HEALTH AND HUMAN SERVICES |  | 5600 FISHERS LN  RM 13A 19 |  | it0012 | 101476 | 20857
it0013 |  | FOOD AND DRUG ADMIN |  | 5630 FISHERS LN  FHSL BLDG RM2003 |  | it0013 | 101464 | 20857
it0014 |  | FEDERAL AVIATION ADMINISTRATION |  | 600 MARYLAND AVE  SW SUitE 308E |  | it0014 | 102211 | 20024
it0015 |  | NATIONAL INSTitUTE OF HEALTH |  | 6120 EXECUTIVE BLVD EPS/RM 638 |  | it0015 | 101479 | 20852
it0016 |  | DEPT OF HEALTH & HUMAN SERV |  | 7500 SECURitY BLVD |  | it0016 | 101467 | 21244
it0017 |  | INTERMETRICS  INC |  | 7918 JONES BRANCH DR  SUitE 710 |  | it0017 | 102589 | 22102
it0018 |  | GSA REGION 11 |  | 7TH & D ST SW |  | it0018 | 102402 | 20407
it0019 |  | TRANSPORTATION SECURitY ADMIN |  | 800 INDEPENDENCE AVE SW |  | it0019 | 102213 | 20591
it0020 |  | GROUP HEALTH INC |  | 88 W END AVE |  | it0020 | 102304 | 10023
it0021 |  | DEPT OF TRANSPORTATION - FAA |  | ACCOUNTING SECTION  ACT-32 |  | it0021 | 102217 | 8405
it0022 |  | NATIONAL INSTitUTE OF HEALTH |  | B1B32  31 CTR DR MSC 2045 |  | it0022 | 101475 | 20892
it0023 |  | NATIONAL INSTitUTE OF HEALTH |  | BLDG 31 RM BIB39 |  | it0023 | 101475 | 20892
it0024 |  | FEDERAL AVIATION ADMIN |  | CONTRACTS BRANCH  ACT 51 |  | it0024 | 102217 | 8405
it0025 |  | NATIONAL INSTitUTE OF HEALTH |  | NATIONAL LIB OF MEDICINE BLDG 38 |  | it0025 | 103544 | 20892
Spreadsheet: 48248d1247498440-count-letter-w-in-the-last-5-entries-countif-last-5
Sheet: Sheet1

 | 68 |  | 3
 | 69
 | 70
 | 71
 | 72 | W
 | 73 | L
 | 74 | W
 | 75
 | 76 | w
 | 77 | w
july | 78
 | 79 | w
 | 80 | w
 | 81 | w
 | 82 | w
 | 83 | w
 | 84
 | 85
 | 86
 | 87
 | 88
 | 89 | w
 | 90 | w
 | 91
 | 92 | w
 | 93
 | 94 | w
Spreadsheet: 792999d1661257601-formula-for-date-conversation-in-the-specific-format-daf-concatenated-days-aligw
Sheet: Sheet1

 | Date | Customer name |  |  | output required
 | 2022-08-01 00:00:00 | Dominos
 | 2022-08-02 00:00:00 | Kfc |  |  | Customer | Date visited
 | 2022-08-03 00:00:00 | [NAME]
 | 2022-08-04 00:00:00 | Burger king |  |  | Kfc
 | 2022-08-05 00:00:00 | la pinoz |  |  | [NAME]
 | 2022-08-06 00:00:00 | pizza king |  |  | Burger king
 | 2022-08-07 00:00:00 | Dominos |  |  | la pinoz
 | 2022-08-08 00:00:00 | Burger king |  |  | pizza king
 | 2022-08-09 00:00:00 | Kfc
 | 2022-08-10 00:00:00 | [NAME]
 | 2022-08-11 00:00:00 | Dominos
 | 2022-08-12 00:00:00 | Burger king
 | 2022-08-13 00:00:00 | pizza king
Spreadsheet: 837100d1689850671-indirect-a1-a5-and-a1-to-spill-a1-from-other-sheets-doesnt-work-how-could-i-do-it-example-132-aligw
Sheet: QUICK EXAMPLE

 | <- 1- This list changes depending on tab LISTS |  |  |  |  |  | <- 2-  I can drag this function but then its not dynamic anymore and I need it dynamic as it depends on the list size.
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | ANSW2
 |  |  |  |  |  |  |  |  |  | 3- The function that would be logical and dynamic is this one but doesn't work -> |  |  |  |  |  |  |  | ANSW3
 | <-   4-  This approach what I would like but is not a solution as I need to add more sheet in he future.
 |  | For example, next year, I will add sheet 5 and then the function stop work.
 |  | It also doesn't allow to have dynamic answers
 |  |  | For example If I want to have instead of A1 of everysheet, an index(match(xxx),match(xxx)) Then it won't really work.
Spreadsheet: 164104d1340650405-converting-each-line-to-4-line-to-preparing-data-to-make-a-discrete-choice-model-shiraz
Sheet: converted line 2

choice | dst | aco | amo | norm | ct | tt | tin | tout | nbrd | jcbd | icbd
0 | 2.76 | 0.06 | 0.09 | 0.77 | 5.89 | 29.45 | 7.59 | 21.86 | 1 | 1 | 1
1 | 2.76 | 0.06 | 0.09 | 0.77 | 5.89 | 29.45 | 7.59 | 21.86 | 1 | 1 | 1
0 | 2.76 | 0.06 | 0.09 | 0.77 | 5.89 | 29.45 | 7.59 | 21.86 | 1 | 1 | 1
0 | 2.76 | 0.06 | 0.09 | 0.77 | 5.89 | 29.45 | 7.59 | 21.86 | 1 | 1 | 1
Spreadsheet: 76317d1276814114-smarter-chart-example-forecast
Sheet: Dashboard

 |  | REVENUE FORECAST DASHBOARD
 |  | Sales Category |  |  |  | All
 |  | Month |  | All
 |  | Category |  |  | Optimistic |  |  | Expected |  |  | Pessimistic |  |  | Mean
 |  | Total
Spreadsheet: 152124d1335269463-count-c6-n6-minusing-if-a-ws-or-hs-are-in-those-cells-register-test-1
Sheet: Test

WEEK COMMENCING |  |  | 2012-04-16 00:00:00
Name | REFERENCE | MONDAY |  | TUESDAY |  | WEDNESDAY |  | THURDAY |  | FRIDAY |  | SATURDAY | SUNDAY | TOTAL SESSION      2 sessions for each half day max 14 but total days will be a max of 7 | TOTAL DAY  max of 7 (goes up in whole numbers) if attend 1/2 day, this is counted as 1, if attends both AM and PM this is counted as 1
 |  | AM | PM | AM | PM | AM | PM | AM | PM | AM | PM
BENNION RICHARD | <36559> | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 |  | 0 | 0 | 0 | 4 | 2
BERRYMAN SUSAN | <38223> | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 8 | 4
BIRCH DARREN JOHN | <37563> | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
[NAME] | <159898> | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1
BULL SONIA | <DP38141> | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 4 | 2
CABLE GLEN | <DP37946> | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
CALCUTT MATTHEW | <37953> | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
[NAME] | <56179> | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
JONES KATY | <DP38054> | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1
LONG SALLY | <DP38000> | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 4 | 2
NEILL COLIN | <38282> | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 8 | 4
ROAST GEMMA | <DP56125> | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1
SERATI-SHIRAZI JODY | <DP123487> | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
SMITH PAUL | <DP37229> | HS | HS | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
TIMMS DANIEL | <37351> | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 8 | 4
 |  |  |  |  |  |  |  |  |  | 0 | 0 | 0 | 0 | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
Total Sessions |  | 8 | 8 | 11 | 11 | 12 | 12 | 11 | 11 | 9 | 9 | 0 | 0 | 102 | 51
Number of Sessions |  | 7 | 7 | 11 | 11 | 12 | 12 | 11 | 11 | 9 | 9 | 0 | 0 | 100
Number of HS Sessions |  | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2
Number of WS  Sessions |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Total Sessions |  | 8 | 8 | 11 | 11 | 12 | 12 | 11 | 11 | 9 | 9 | 0 | 0 | 102 | 0
KEY:
0 | DOES NOT ATTEND SERVICE
1 | DOES ATTEND SERVICE
HS | Home Support - IS SUPPORTED AT HOME BY STAFF FROM DAY SERVICE
WS | [NAME], Supported by Staff out in the community,  NO support given at home or in DTS
Spreadsheet: 202720d1356710064-auto-update-data-provider
Sheet: Master

Providers | Days | Duration | Provider | Location | Yes/no | [NAME]
1 | Mon | 1 | 1 | a | Yes | 1
2 | [NAME] | 1.25 | 1.25 | b | No | 2
3 | Wed | 1.5 | 1.5 | c |  | 3
4 | Thurs | 1.75 | 1.75 | d |  | 4
5 | Fri | 2 | 2 | e |  | 5
6 | MW | 2.25 | 2.25 | f |  | 6
7 | TueThu | 2.5 | 2.5 | g |  | 7
8 | MWF | 2.75 | 2.75 | h |  | 8
9 | [NAME] | 3 | 3 | i |  | 9
10 | MTWTF | 3.25 | 3.25 | j |  | 10
11 |  | 3.5 | 3.5 | k |  | 11
12 |  | 3.75 | 3.75 | l |  | 12
13 |  | 4 | 4 | m |  | 13
14 |  | 4.25 | 4.25 | n |  | 14
15 |  | 4.5 | 4.5 | o |  | 15
16 |  | 4.75 | 4.75 | p |  | 16
17 |  | 5 | 5 | q |  | 17
18 |  | 5.25 | 5.25 | r |  | 18
19 |  | 5.5 | 5.5 | s |  | 19
20 |  | 5.75 | 5.75 | t |  | 20
21 |  | 6 | 6 | u |  | 21
22 |  | 6.25 | 6.25 | v |  | 22
23 |  | 6.5 | 6.5 | w |  | 23
24 |  | 6.75 | 6.75 | x |  | 24
25 |  | 7 | 7 | y |  | 25
26 |  | 7.25 | 7.25 | z |  | 26
 |  | 7.5 | 7.5
 |  | 7.75 | 7.75
 |  | 8 | 8
 |  | 8.25
 |  | 8.5
 |  | 8.75
 |  | 9
Spreadsheet: 02e4b555-05a6-40f8-a00e-8401a50136eb
Sheet: Table of Contents

CFTC Swaps Report
2013-02-13 00:00:00
Table of Contents
All Swaps
1. Gross Notional Outstanding by Cleared Status
2. Gross Notional Outstanding by Participant Type
3. Net Notional Outstanding by Cleared Status
4. Net Notional Outstanding by Participant Type
5. Transaction Ticket Volume by Cleared Status
6. Transaction Ticket Volume by Participant Type
7. Transaction Dollar Volume by Cleared Status
8. Transaction Dollar Volume by Participant Type
Swaps by Asset Class
Interest Rate Swaps
9a. Gross Notional Outstanding -  Product Type and Cleared Status
9b. Gross Notional Outstanding - Cleared - Supermajor Currency
9c. Gross Notional Outstanding - Cleared - Major Currency
9d. Gross Notional Outstanding - Cleared - Tenor
10a. Net Notional Outstanding - Product Type and Cleared Status
10b. Net Notional Outstanding - Cleared - Supermajor Currency
10c. Net Notional Outstanding - Cleared - Major Currency
10d. Net Notional Outstanding - Cleared - Tenor
11a. Transaction Ticket Volume - Product Type and Cleared Status
11b. Transaction Ticket Volume - Cleared - Supermajor Currency
11c. Transaction Ticket Volume - Cleared - Major Currency
11d. Transaction Ticket Volume - Cleared - Tenor
12a. Transaction Dollar Volume - Product Type and Cleared Status
12b. Transaction Dollar Volume - Cleared - Supermajor Currency
12c. Transaction Dollar Volume - Cleared - Major Currency
12d. Transaction Dollar Volume - Cleared - Tenor
Credit Default Swaps
13a. Gross Notional Outstanding - Product and Participant Type
13b. Gross Notional Outstanding - Product Type and Grade
14a. Net Notional Outstanding - Product and Participant Type
14b. Net Notional Outstanding - Product Type and Grade
15a. Transaction Ticket Volume - Product and Participant Type
15b. Transaction Ticket Volume - Product Type and Grade
16a. Transaction Dollar Volume - Product and Participant Type
16b. Transaction Dollar Volume - Product Type and Grade
Equity Swaps
17. Gross Notional Outstanding
18. Net Notional Outstanding
19. Transaction Ticket Volume
20. Transaction Dollar Volume
Other Commodity Swaps
21. Gross Notional Outstanding
22. Net Notional Outstanding
23. Transaction Ticket Volume
24. Transaction Dollar Volume