tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 875666d1722275660-sheet-references-how-to-solve-magicsheet-v2-template-started
Sheet: Feeds

 |  |  |  | 1 | 2 | 3 | 4
 |  |  |  | 1 | 2 | 3 | 4
 |  |  |  | 1 |  | 3 | 4
 |  |  |  | 1 |  | 3 | 4
 |  |  |  | 1 |  |  | 4
Spreadsheet: 869699d1716297197-pull-data-through-from-a-worksheet-which-worksheet-is-defined-by-the-value-in-a-cell-template-
Sheet: Load Sheet

Date | Customer | Site | Product | Del. Site | [NAME] | Quantity | Count | Pack Weight (g) | Total No. Packs | Weight (kg) | Total No. Pallets | Load No.
 | Tesco | A | Peas | A2B | [NAME] |  | 12 | 225 | 0 | 0 |  |  |  | Date:
 | Sainsburys | B | Carrots | B2C | [NAME] |  | 12 | 225 | 0 | 0 |  |  |  | 10624
 | Morrisons | C | Broccoli | C2D | [NAME] |  | 12 | 225 | 0 | 0
 | Asda | D | Cauliflower | D2E | [NAME] |  | 12 | 225 | 0 | 0
 | Lidl | E | Cabbage | E2F | [NAME] |  | 12 | 225 | 0 | 0
 | Aldi | F | Lettuce | F2G | [NAME] |  | 12 | 225 | 0 | 0
Spreadsheet: 822062d1679071412-count-the-number-of-instances-of-a-value-in-one-column-based-on-a-value-in-another-sample
Sheet: Summary

ID# | Assocaite Name | Supervisor | Department | Total Points | Level | Verbal Warning Date | Stop - VW | Written Warning Date | Stop - WW | Start - Final Written Warning Date | Stop - Final | Termination | Tardies | WLBD | Date
111111 |  |  |  |  |  | 2022-11-15 00:00:00
222222
333333
444444
555555
666666
777777
888888
999999 |  |  |  |  |  | 2022-11-02 00:00:00 |  | 2022-12-02 00:00:00 |  | 2023-02-02 00:00:00
111112
111113
111114
111115
111116
111117
111118
111119 |  |  |  |  |  | 2023-02-03 00:00:00 |  | 2023-02-04 00:00:00
111120
111121
111122
Spreadsheet: 811435d1672506104-cell-function-operation-inputted-from-another-cell-in-excel-excel_problem_funtionselection
Sheet: Sheet1

Column | B | C | D |  |  | Min row | 6
Operation | AVERAGE | MIN | MAX |  |  | [NAME] row | 17
 | Measurement X
 | Temp(C) | Temp Low(C) | Temp High(C)
Jan | -2.873 | -18.7 | 5.5
Feb | -1.879 | -15 | 4.2
Mar | -0.006 | -11.2 | 12
Apr | 3.443 | -8.5 | 14.7
May | 9.389 | -1.6 | 22
Jun | 17.08 | 6.3 | 31.8
Jul | 17.844 | 9.4 | 30
Aug | 18.943 | 7 | 29.8
Sep | 9.609 | 2.3 | 17.9
Oct | 7.941 | -2.4 | 14.8
Nov | 2.661 | -5.1 | 13.3
Dec | -0.7 | -16.5 | 4.7
YEAR
Average
Min
[NAME]
Spreadsheet: 270542d1381516175-create-list-based-on-criteria-and-is-unique-create-list-solution
Sheet: Sheet1

 | Data
 | CP | type | size | color | name | details | test |  | CP | type | size | color | name | details | test
1 | CP1 | car | small | red | [NAME] | liked it | no |  | CP1 | car | small | blue | [NAME] | liked it | no
2 | CP1 | car | small | red | [NAME] | liked it | no |  | CP1 | car | small | red | [NAME] | liked it | no
3 | CP1 | car | small | red | [NAME] | liked it | no |  | CP1 | van | large | purple | [NAME] | liked it | no
4 | CP1 | car | small | blue | [NAME] | liked it | no |  | CP1 | van | large | red | [NAME] | accident | yes
5 | CP1 | van | large | red | [NAME] | accident | yes |  | CP2 | truck | large | black | [NAME] | bumpy | no
6 | CP1 | van | large | red | [NAME] | accident | yes |  | CP2 | truck | midsize | black | [NAME] | bumpy | yes
7 | CP1 | car | small | blue | [NAME] | liked it | no |  | CP3 | van | small | grey | [NAME] | confortable | yes
8 | CP1 | van | large | purple | [NAME] | liked it | no
9 | CP1 | van | large | purple | [NAME] | liked it | no
10 | CP2 | truck | midsize | black | [NAME] | bumpy | yes
11 | CP2 | truck | midsize | black | [NAME] | bumpy | yes
12 | CP2 | truck | midsize | black | [NAME] | bumpy | yes
13 | CP2 | truck | large | black | [NAME] | bumpy | no
14 | CP2 | truck | large | black | [NAME] | bumpy | no
15 | CP2 | truck | large | black | [NAME] | bumpy | no
16 | CP3 | van | small | grey | [NAME] | confortable | yes
17 | CP3 | van | small | grey | [NAME] | confortable | yes
18 | CP3 | van | small | grey | [NAME] | confortable | yes
19 | CP3 | van | small | grey | [NAME] | confortable | yes
Spreadsheet: 779125d1651593974-what-affect-has-question-1-on-question-2-is-there-a-formula-survey-analysis
Sheet: Blad1

Question 1 | Question 2
3 | No
5 | No
2 | No
1 | No
2 | No
3 | No
4 | No
2 | No
2 | No
5 | Yes
2 | No
3 | No
5 | No
3 | No
1 | No
2 | No
3 | No
5 | Yes
4 | No
Spreadsheet: 723145d1615541809-count-duplicate-values-in-the-same-cell-and-in-a-range-example-1-2-
Sheet: Sheet1

 | INVOICE DATE | SITE | PLOT(S)
 | 2021-02-26 00:00:00 | Gipping [NAME] | 123, 124, 125, 126
 | 2021-03-04 00:00:00 | Gipping [NAME] | 108, 110
 | 2021-03-05 00:00:00 | Gipping [NAME] | 108, 987
 | 2021-03-02 00:00:00 | Gipping [NAME] | 108
 | 2021-02-03 00:00:00 | Gipping [NAME] | 109
 | 2021-02-01 00:00:00 | Gipping [NAME] | 123, 124
 | 2021-02-26 00:00:00 | Gipping [NAME] | 82, 83
 | 2021-02-25 00:00:00 | a | 110, 112
 | 2021-02-24 00:00:00 | a | 123, 124, 125, 126, 127
 | 2021-02-20 00:00:00 | a | 123, 124, 125
 | 2021-02-19 00:00:00 | a | 124, 125, 126
 | 2021-02-18 00:00:00 | a | 123
 | 2021-02-17 00:00:00 | a | 124
 | 2021-02-15 00:00:00 | a | 126, 127
 | 2021-02-16 00:00:00 | Gipping [NAME] | 127
Spreadsheet: 881920d1730160022-copying-p-and-l-data-forum-pnl
Sheet: Sheet1

Billing expense
 | Gatlinburg |  | 1000 |  |  | Gatlinburg | Kodak | LeConte | Newport | [NAME] | School | Sevierville | [NAME] | Veterans | Billing expense - Other
 | Kodak |  | 0 |  | Billing expense
 | LeConte |  | 0 |  | Computer Software
 | Newport |  | 0
 | [NAME] |  | 2500
 | School |  | 1100
 | Sevierville |  | 9500
 | [NAME] |  | 8500
 | Veterans |  | 0
 | Billing expense - Other |  | 0
Computer Software
 | Business Office |  | 1000
 | Gatlinburg |  | 300
 | LeConte |  | 0
 | [NAME] |  | 300
 | School |  | 115.14
 | Sevierville |  | 864.29
 | [NAME] |  | 450.67
 | Veterans |  | 0
 | Computer Software - Other |  | 0
Spreadsheet: 801484d1666218767-getting-cell-values-based-on-an-different-cells-dont-know-what-formula-to-use-northot-v2-nking00-
Sheet: Summary

 |  |  |  |  |  |  |  |  |  | Coverage Summary for
 | 30A |  |  |  | 30B |  |  |  | 30C |  |  |  | 30D |  |  |  | 30E |  |  |  | 30F |  |  |  | 30G |  |  |  | 30H
 |  |  |  |  |  |  |  |  |  |  |  |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]?
 | 30J |  |  |  | 30K |  |  |  | 95A |  |  |  | 95B |  |  |  | 95C |  |  |  | 95D |  |  |  | 95E |  |  |  | 95F
 | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]? |  | #[NAME]? | #[NAME]? | #[NAME]?
 | 95G |  |  |  | 95H |  |  |  | 95J |  |  |  | 95K |  |  |  | 95L |  |  |  | 95M |  |  |  | 95N |  |  |  | Floaters
 | [NAME] |  |  |  | SWD |  |  |  | SWG |  |  |  | Tech |  |  |  | [NAME]
Spreadsheet: 330397d1404738993-formula-using-multiple-if-criteria-2015-daily-room-credit-test
Sheet: 2015 DAILY ROOM CREDIT

DAILY ROOM CREDIT
NAME OF STAFF RESPONSIBLE |  |  |  |  |  | DATE:
OPENING |  |  | CLOSING |  |  | HOTEL:
 |  |  |  |  |  | RESORT:
ROOM | CREDIT |  |  | AMOUNT PAID |  | PREVIOUS SALES |  | FINAL CREDIT
# NBR | START | END | TODAY | CASH | CREDIT CARD | CASH | CREDIT CARD | TODAY
A | B | C | D (C-B) | E | F | G (E-D) | H (F-D) | I = D if E or F = 0
100
101
102 | 50 | 100 |  | 50 | 50
103
104
105
106
107 |  | 75
108 |  | 12
109
110/111
200 | 23.5 | 263.5 |  | 263.5
201
202 | 8 | 8 |  | 8
203 | 15 | 15 |  |  | 15
204
205
206 | 5 | 5 |  |  | 5
207 | 5 | 5 |  |  | 5
208 | 5 | 8 |  | 8
209
210/211
300
301
302
303 | 43 | 43 |  |  | 43
304 | 3 | 3 |  | 3
305
306 | 65 | 65 |  |  | 65
307 | 4 | 4 |  | 4
308 | 201 | 201 |  |  | 201
309
310/311
400 | 23 | 39
401 | 5 | 5 |  | 5
402
403 | 12 | 12 |  | 12
404 | 23 | 23 |  | 23
405
406 | 56 | 1206 |  |  | 1206
407 | 16 | 16 |  | 16
408
TOTAL
ONLY FILL IN AREAS FILLED WITH THIS BACKGROUND COLOUR
Spreadsheet: 740061d1626170693-assign-unique-project-code-project-id-challenge
Sheet: Sheet1

Company Name | Original ID | ID
ABC
ABCD
ACBDE
ABCDE |  |  |  |  |  |  |  |  |  | Requirements
dfsdsdf
sdfsdf |  |  |  |  |  |  |  |  |  | ID should equal first 5 characters of company name | Represented by 'Original ID' which is the value it would be if no dupes
sdfsdf |  |  |  |  |  |  |  |  |  | Where Company name < 5 characters, add trailing zeros to make up to 5 characters
sdfsdf
sdfsdf |  |  |  |  |  |  |  |  |  | If that ID has been taken already, then;
sdfdfsf |  |  |  |  |  |  |  |  |  | if last digit is not a number then replace with a "0"
ddddd |  |  |  |  |  |  |  |  |  | If last 2 digits = 99 then replace with '000'
sss99 |  |  |  |  |  |  |  |  |  | IF last digits is a "9" replace with "00"
ddddd99 |  |  |  |  |  |  |  |  |  | If last digit is any other number add one (eg if 4 replace it with a 5)
sd99
sdfsdf
gg
gs
sdfdsfsfsdf
Spreadsheet: 206598d1358237559-how-to-create-a-functional-drop-down-menu-to-update-expiry-dates-timestamp-plus-adding-months-1
Sheet: New Members

2013-01-15 00:00:00 |  | This is what I see! Don't you see the same?
 |  |  |  |  |  |  |  | 2013-01-21 18:04:18
Member ID | First Name | Last Name | Membership Type | Start Date | [NAME]
1 | [NAME] | Kimuyu | 1 Week | 2013-01-14 18:04:18 | 2013-01-20 18:04:18 |  |  | 1 Week
2 | Rhys | McDonald |  |  |  |  |  | 1 Month | 1
3 | [NAME] | Sharp | 6 Months | 2013-01-15 09:44:22 | 2013-07-02 09:44:22 |  |  | 3 Months | 3
4 | Adam | Simnott |  |  |  |  |  | 6 Months | 6
5 | Mark | Finch | 3 Months | 2013-01-15 09:46:15 | 2013-04-09 09:46:15 |  |  | 12 Months | 12
6 | [NAME] | [NAME] | 12 Months | 2013-01-14 18:05:01 | 2013-12-16 18:05:01
7 | [NAME] | [NAME]
8 | Vishal | [NAME]
9 | [NAME] | Edwards
10 | [NAME] | Bradley | 1 Month | 2013-01-15 08:40:41 | 2013-02-12 08:40:41
11 | [NAME] | Knight
12 | [NAME] | Palmer
13 | Kristen | Duffin | 3 Months | 2013-01-15 08:40:47 | 2013-04-09 08:40:47
14 | [NAME] | Burrows
15 | [NAME] | Watson
16 | [NAME] | [NAME]
17 | [NAME] | Illson
18 | [NAME] | Murphy
19 | [NAME] | Whitehead
20 | [NAME] | Bone
21 | [NAME] | Lampard
22 | [NAME] | Craven
23 | [NAME] | [NAME]
24 | Aby | [NAME]
25 | Micheal | Beeby
26 | [NAME] | [NAME]
27 | [NAME] | Wroughton
28 | Peri | Theodosiou
29 | [NAME] | Coulsons
30 | Shaun | Guthrit
31 | Mark | Bailey
32 | [NAME] | Betts
33 | [NAME] | [NAME]
34 | [NAME] | [NAME]
35 | [NAME] | Thorpe
36 | [NAME] | Bhamra
37 | Arran | Coffey
38 | [NAME] | Smith
39 | George | draper
40 | [NAME] | Wilson
41 | Adrian | Mulligan
42 | [NAME] | [NAME]
43 | Brett | Mitchell
44 | [NAME] | Gibbons
45 | Callum | Smith
46 | Callum | [NAME]
47 | [NAME] | [NAME]
48 | [NAME] | Griffiths
49 | [NAME] | McAdam
50 | [NAME] | Would
51 | Jon | [NAME]
52 | [NAME] | Orridge
53 | Adam | [NAME]
54 | Niall | Gibbons
55 | [NAME] | [NAME]
56 | [NAME] | Mclocklin
57 | [NAME] | Ward
58 | [NAME] | Thorpe
59 | [NAME] | Durner
Spreadsheet: 288242d1389128378-staff-scheduler-schedule
Sheet: Sheet3

 | Interval | 2014-01-01 00:00:00 |  | 2014-01-02 00:00:00 |  | 2014-01-03 00:00:00 |  | 2014-01-04 00:00:00 |  | 2014-01-05 00:00:00 |  | 2014-01-06 00:00:00 |  | 2014-01-07 00:00:00 |  | 2014-01-08 00:00:00 |  | 2014-01-09 00:00:00 |  | 2014-01-10 00:00:00 |  | 2014-01-11 00:00:00 |  | 2014-01-12 00:00:00 |  | 2014-01-13 00:00:00 |  | 2014-01-14 00:00:00 |  | 2014-01-15 00:00:00 |  | 2014-01-16 00:00:00 |  | 2014-01-17 00:00:00 |  | 2014-01-18 00:00:00 |  | 2014-01-19 00:00:00 |  | 2014-01-20 00:00:00 |  | 2014-01-21 00:00:00 |  | 2014-01-22 00:00:00 |  | 2014-01-23 00:00:00 |  | 2014-01-24 00:00:00 |  | 2014-01-25 00:00:00 |  | 2014-01-26 00:00:00 |  | 2014-01-27 00:00:00 |  | 2014-01-28 00:00:00 |  | 2014-01-29 00:00:00 |  | 2014-01-30 00:00:00 |  | 2014-01-31 00:00:00
 | 00:00:00
 | 00:30:00
 | 01:00:00
 | 01:30:00
 | 02:00:00
 | 02:30:00
 | 03:00:00
 | 03:30:00
 | 04:00:00
 | 04:30:00
 | 05:00:00
 | 05:30:00
 | 06:00:00
 | 06:30:00
 | 07:00:00
 | 07:30:00
 | 08:00:00
 | 08:30:00
 | 09:00:00
 | 09:30:00
 | 10:00:00
 | 10:30:00
 | 11:00:00
 | 11:30:00
 | 12:00:00
 | 12:30:00
 | 13:00:00
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 | 23:00:00
 | 23:30:00
Spreadsheet: 77a13a74-451c-4752-81a2-cd6a3ebe6bbb
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SNOWSHOE | T1 | SKATE | T2 | SKI | POSITION | TOTAL TIME
8903 | 21946 | Reinhold | Wolter | GER | 270 | 00:25:39 | 00:00:48 | 00:54:35 | 00:03:16 | 00:30:10 | 1 | 01:54:29
Spreadsheet: 783289d1654708157-filter-instead-of-index-and-small-sample
Sheet: FilteredResult

[NAME] |  | DATE | TIME | COURSE | CLASSROM |  |  |  |  | DATE | TIME | COURSE | CLASSROM
Name1 |  |  | 12:00:00 | Literature | ? |  |  |  |  |  |  |  | 10A
 |  | 2020-11-05 00:00:00 | 12:00:00 | German | ? |  |  |  |  |  |  |  | 11B
 |  | 2020-11-11 00:00:00 | 12:00:00 | Chemistry | ? |  |  |  |  |  |  |  | 10A
 |  | 2020-11-12 00:00:00 | 12:00:00 | English |  |  |  |  |  |  |  |  | 10B
 |  | 2020-11-25 00:00:00 | 12:00:00 | Physics |  |  |  |  |  |  |  |  | 10A
 |  | 2020-11-26 00:00:00 | 12:00:00 | History |  |  |  |  |  |  |  |  | 10B
 |  | 2020-12-02 00:00:00 | 12:00:00 | Geometry |  |  |  |  |  |  |  |  | 10C
Spreadsheet: 19b411f6-6054-4e2b-98c2-e2e17b818223
Sheet: Foreign

Foreign Sales Data
Dollars in millions
The Company's operations outside of the United States are principally in Canada, Europe, Mexico and China.
The sales information below is compiled based on the areas we have operations, primarily manufacturing locations.
 | Continuing Operations |  |  |  |  |  |  | 2005-2011 |  |  | Historical Data, As Originally Reported |  |  |  |  |  |  |  |  |  |  | 1996-2006
Year ended Dec. 31 | 2011 | 2010 | 2009 | 2008 | 2007 | 2006 | 2005 | CAGR |  | Year ended Dec. 31 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 | 1998 | 1997 | 1996 | CAGR
External Sales |  |  |  |  |  |  |  |  |  | External Sales
United States | 2589.1 | 2426.7 | 2289.1 | 3025.4 |  |  |  |  |  | United States | 4361 | 4163 | 4029.3 | 3468 | 3489.7 | 3421.1 | 3675.6 | 3345.8 | 3025.9 | 2636.6 | 2304.8
% U.S. |  |  |  |  |  |  |  |  |  | % U.S.
Canada and Mexico | 266.8 |  |  | 323.1 |  |  |  |  |  | Canada and Mexico |  |  |  | 559 | 477.6 |  | 385 | 283.9 | 234.2 | 199.1 | 127.1
Europe | 373.1 | 302.3 | 278.1 | 409 | 402 | 353.7 | 373.9 |  |  | Europe | 354 | 374 | 403.2 | 315 | 268.2 | 237 | 190.5 | 139.2 | 110.3 | 73.6 | 34.3
China | 331.3 | 323.5 | 233.1 | 267.2 | 224 | 157.3 | 94.6 |  |  | Other Foreign | 210 |  | 86.3 | 46 | 36.3 | 28.5 | 25.2 | 9.8
Other Foreign | 75.7 | 58.3 | 42.9 | 51.4 | 62.1 | 52.8 | 39.2 |  |  | Subtotal - Foreign
Subtotal - Foreign |  |  |  |  |  |  |  |  |  | % Foreign
% Foreign |  |  |  |  |  |  |  |  |  | Total
Total |  |  |  |  |  |  |  |  |  | New Countries Entered
New Countries Entered |  |  |  |  |  |  |  |  |  |  | India | South | Russia | Korea |  |  | Austria | Brazil | China | Italy | Germany
 |  |  |  |  |  | India | South Africa |  |  |  |  | Africa | Hungary |  |  |  | Croatia | Australia | Denmark | Switzerland | Mexico
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Spain |  |  | U.K.
 |  |  |  |  |  |  |  |  |  | Long-Lived Assets
 |  |  |  |  |  |  |  |  |  | United States | 1727.3 | 1694 | 1553.9 | 1552 | 1591.1 | 1591.5 | 1593.3 | 1421.4 | 1183.8 | 989.2 | 824.7
 |  |  |  |  |  |  |  |  |  | Foreign |  |  |  | 518 | 422 |  | 374.6 | 299.9 | 214.4 | 172.5 | 124.9
 |  |  |  |  |  |  |  |  |  | % Foreign
 |  |  |  |  |  |  |  |  |  | Total | 2371.2 | 2289 | 2132.4
Spreadsheet: michelle_lokay__26569__imbalsumm0012
Sheet: EOG

 | 500249 |  | 500260 |  | 500646 |  | 500598
 | Pronghorn |  | Pitchfork Ranch |  | Tristi Draw
Day | Measured | Scheduled | Measured | Scheduled | Measured | Scheduled | Measured | Scheduled
1 | 21055 | 19223 | 10745 | 10000
2 | 21202 | 19584 | 10722 | 10000
3 | 17314 | 17788 | 10773 | 10000
4 | 27334 | 19584 | 10003 | 10000
5 | 30871 | 33371 | 10556 | 10500
6 | 31042 | 29250 | 9009 | 10500
7 | 31704 | 34250 | 9973 | 10500
8 | 31619 | 34219 | 9894 | 10000
9 | 31577 | 30678 | 11348 | 8750
10 | 31492 | 30632 | 11398 | 8750 | 671
11 | 31398 | 30267 | 11008 | 8750
12 | 31349 | 32989 | 10713 | 11802 | 1
13 | 31276 | 33000 | 9316 | 11783 | 69
14 | 31176 | 33688 | 10651 | 12500
15 | 31266 | 33750 | 9937 | 12500
16 | 31180 | 33750 | 8772 | 11000
17 | 31204 | 33750 | 10588 | 11000
18 | 31116 | 33750 | 10759 | 11000
19 | 31031 | 27160 | 10512 | 8500
20
21
22
23
24
25
26
27
28
29
30
31
2000-11-30 00:00:00 |  |  |  |  |  |  |  |  | -532429.6
2000-12-19 00:00:00
 |  |  | 516.78
 |  |  | 212.08
 |  |  | 58.33
 |  |  | 25
Spreadsheet: 835368d1688542878-count-and-rank-from-data-with-category-example-hd
Sheet: Sheet1

 | Group | Transport |  |  | Count |  |  |  | Rank |  |  |  |  | Count |  |  |  | Rank
 | Children | Boat |  |  | Group | Transport | Count |  | Group | Transport | Count | Rank |  | Group | Transport | Count |  | Group | Transport | Count | Rank
 | Adult | Car |  |  | Children | Boat | 1 |  | Children | Bus | 2 | 1 | Adult |  | Car | 1 |  |  | Boat | 3 | 1
 | Teen | Bike |  |  |  | Car |  |  |  | Boat | 1 | 2 | Adult |  | Bus | 1 |  |  | Taxi | 2 | 2
 | Adult | Bus |  |  |  | Bike | 1 |  |  | Bike | 1 | 2 | Adult |  | Taxi | 2 |  |  | Car | 1 | 3
 | Adult | Taxi |  |  |  | Bus | 2 |  |  | Plane | 1 | 2 | Adult |  | Boat | 3 |  |  | Bus | 1 | 3
 | Teen | Boat |  |  |  | Plane | 1 |  |  | Car |  |  | h | Children | Boat | 1 |  | Children | Bus | 2 | 1
 | Teen | Taxi |  |  |  | Taxi |  |  |  | Taxi |  |  | h |  | Bike | 1 |  |  | Boat | 1 | 2
 | Children | Bike |  |  | Teen | Boat | 2 |  | Teen | Car | 3 | 1 | h |  | Plane | 1 |  |  | Bike | 1 | 2
 | Teen | Car |  |  |  | Car | 3 |  |  | Boat | 2 | 2 | h |  | Bus | 2 |  |  | Plane | 1 | 2
 | Adult | Boat |  |  |  | Bike | 1 |  |  | Bike | 1 | 3 | t | Teen | Bike | 1 |  | Teen | Car | 3 | 1
 | Children | Plane |  |  |  | Bus |  |  |  | Taxi | 1 | 3 | t |  | Boat | 2 |  |  | Boat | 2 | 2
 | Children | Bus |  |  |  | Plane |  |  |  | Bus |  |  | t |  | Taxi | 1 |  |  | Bike | 1 | 3
 | Adult | Boat |  |  |  | Taxi | 1 |  |  | Plane |  |  | t |  | Car | 3 |  |  | Taxi | 1 | 3
 | Adult | Taxi |  |  | Adult | Boat | 3 |  | Adult | Boat | 3 | 1
 | Teen | Boat |  |  |  | Car | 1 |  |  | Taxi | 2 | 2
 | Teen | Car |  |  |  | Bike |  |  |  | Car | 1 | 3
 | Children | Bus |  |  |  | Bus | 1 |  |  | Bus | 1 | 3
 | Teen | Car |  |  |  | Plane |  |  |  | Bike
 | Adult | Boat |  |  |  | Taxi | 2 |  |  | Plane
Spreadsheet: 07e5185f-0c87-4343-8f7e-bed4f3ba4ae4
Sheet: Env & Cul

 |  | 2011/12 Council Plan Measure schedule for Environment & Culture
Service Area | CBP Measure Template Received | Existing or New CP Measure | Directorate | Portfolio | Strategic Outcome | SCS Sub Outcome | Directorate Actions to Sub Outcomes | Measure Title and Description | Data Frequency | KPI or Initiative | 2010/11 Result (Q3) | 2010/11 Target | 2011/12 Target | Directorate comment
 |  | New | Environment & Culture | Leisure, Sports & Culture | Succeed Economically | Increasing employment and economic activity within the city. Ensuring that people have the education and skills to make the most of job opportunities | Continue to work towards a world class library of Birmingham and to work to maximise the contribution of our cultural assets to the promotion of Birmingham. NOTE: This is an objective of the Leader’s Prospectus | Library of Birmingham capital project on target and to budget | Quarterly | Initiative | n/a | n/a | Library of Birmingham capital project on target and to budget | Measure has been approved by Cabinet Member Priority covered in budget proposal
 |  | Existing | Environment & Culture | Transport, Environment & Regeneration | Stay Safe, Clean & Green | Securing cleaner, greener, sustainable neighbourhoods empowering citizens to make their neighbouirhoods better places to live. | Minimise residual household waste and municipal waste that is land filled | Reduce residual household waste | Quarterly | KPI | tbc | tbc | 690k per household | Measure has been approved by Cabinet  Member Priority covered in budget proposal
 |  | Existing | Environment & Culture | Transport, Environment & Regeneration | Stay Safe, Clean & Green | Securing cleaner, greener, sustainable neighbourhoods empowering citizens to make their neighbouirhoods better places to live. | Minimise residual household waste and municipal waste that is land filled | % household waste which is reused, recycled and composted | Quarterly | KPI | tbc | tbc | 0.34 | Measure has been approved by Cabinet  Member Priority covered in budget proposal
 |  | Existing | Environment & Culture | Transport, Environment & Regeneration | Stay Safe, Clean & Green | Securing cleaner, greener, sustainable neighbourhoods empowering citizens to make their neighbouirhoods better places to live. | Minimise residual household waste and municipal waste that is land filled | % municipal waste sent to landfill | Quarterly | KPI | tbc | tbc | 0.1 | Measure has been approved by Cabinet  Member Priority covered in budget proposal
 |  | Existing | Environment & Culture | Leisure, Sports & Culture | Be Healthy | Securing cleaner, greener, sustainable neighbourhoods empowering citizens to make their neighbouirhoods better places to live. |  | Adults participation in Sport | Annual | KPI |  |  | 0.2012
Spreadsheet: 829359d1684165316-formula-to-return-name-match-help-match-sample-etaf
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  | Initial |  |  |  |  |  | [NAME] Here | G,M,T | [NAME]
 |  |  |  |  |  |  |  |  |  | H |  |  |  |  |  | [NAME] | H,J | [NAME]
 |  |  |  |  |  |  |  |  |  | S |  |  |  |  |  | [NAME] | F,K,L,S | [NAME]
 |  |  |  |  |  |  |  |  |  | A |  |  |  |  |  | Mrs. [NAME] | I,R,U,V,W,X,Y,Z | Test Person
 |  |  |  |  |  |  |  |  |  | T |  |  |  |  |  | [NAME] | C,D,O,P,Q | Mr. [NAME]
 |  |  |  |  |  |  |  |  |  | R |  |  |  |  |  | Test Person | A,B,E,N | Mrs. [NAME]
 |  |  |  |  |  |  |  |  |  | C |  |  |  |  |  | Mr. [NAME]
 |  |  |  |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  |  |  | A
 |  |  |  |  |  |  |  |  |  | L
 |  |  |  |  |  |  |  |  |  | M
 |  |  |  |  |  |  |  |  |  | W
 |  |  |  |  |  |  |  |  |  | J
 |  |  |  |  |  |  |  |  |  | H
 |  |  |  |  |  |  |  |  |  | S
 |  |  |  |  |  |  |  |  |  | S
 |  |  |  |  |  |  |  |  |  | S
 |  |  |  |  |  |  |  |  |  | W
 |  |  |  |  |  |  |  |  |  | H
Spreadsheet: 748562d1632217597-populate-dynamic-calendar-with-tasks-based-on-task-frequency-tasks-calendar-ans
Sheet: Calendar

 |  |  |  |  |  |  |  |  |  | Month | 9
 | Sunday | Monday |  | Wednesday | Thursday | Friday | Saturday |  |  | Year | 2021
 |  | Task | Task | Task | Task | Task
1
2
3
4
5
6
7
 |  | Task | Task | Task | Task | Task
1
2
3
4
5
6
7
 |  | Task | Task | Task | Task | Task
1
2
3
4
5
6
7
 |  | Task | Task | Task | Task | Task
1
2
3
4
5
6
7
 |  | Task | Task | Task | Task | Task
1
2
3
4
5
6
7
 |  | Details
1
2
3
4
5
6
7
Spreadsheet: 215681d1361455376-lookup-all-cells-with-a-certain-value-then-take-a-value-based-on-two-other-variables-example-to-explain
Sheet: Sheet1

Category (D) | Value (A) | Required Value (B) | Best Method to achieve req. value [C)
Wood | 90 | 95 | Need this to be calculated
Category (D) | Increase (E) | Minimum value of (A) required to use this increase (F) | Method [C)
Wood | 5 | 90 | Method 1
Wood | 76 | 86 | Method 2
Wood | 4 | 91 | Method 3
Not-Wood | 5 | 90 | Method 4