tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 867404d1714233026-weekend-rota-planning-generate-values-based-on-criteria-date-shift-pattern-weekend-rota-planing
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Apple | [NAME] | Pear | Grape | Plum
 |  |  |  | 2023-04-26 00:00:00 |  |  |  |  |  |  |  |  |  | 2024-04-26 00:00:00 | 1 | 0 | 0 | 1 | 1
 |  |  | Name | FRIDAY |  | SATURDAY |  | SUNDAY |  | MONDAY |  |  |  | 2024-04-27 00:00:00 | 1 | 1 | 1 | 0 | 1
 |  |  | Apple | 06:00:00 | 18:00:00 | 06:00:00 | 18:00:00 | 06:00:00 | 18:00:00 |  |  |  |  | 2024-04-28 00:00:00 | 1 | 0 | 1 | 0 | 1
 |  |  | [NAME] |  |  | 06:00:00 | 18:00:00 |  |  | 06:00:00 | 18:00:00 |  |  | 2024-04-29 00:00:00 | 0 | 1 | 0 | 0 | 1
 |  |  | Pear |  |  | 06:00:00 | 18:00:00 | 06:00:00 | 18:00:00
 |  |  | Grape | 06:00:00 | 18:00:00
 |  |  | Plum | 06:00:00 | 18:00:00 | 06:00:00 | 18:00:00 | 06:00:00 | 18:00:00 | 06:00:00 | 18:00:00
Spreadsheet: louise_kitchen__23837__2QYTD Orig w notes
Sheet: West Power

West Power
Mid Year 2001
Originator |  | Commodity |  | Team |  | Total |  | %Total
[NAME] |  | Power |  | West
Wehn |  | Power |  | West |  | 16000000
[NAME] |  | Power |  | West
[NAME] | * | Power |  | West
Thome | * | Power |  | West |  | 10000000
Calger |  | Power |  | West
Choi |  | Power |  | West |  | 8663463
Krebs |  | Power |  | West |  | 9742219
Rosman |  | Power |  | West |  | 7094465
Malowney |  | Power |  | West |  | 2105422
[NAME] |  | Power |  | West |  | 2369844
Wolfe |  | Power |  | West |  | 5430414
[NAME] |  | Power |  | West |  | 1914254
Rawson |  | Power |  | West |  | 3565507
Scholtes |  | Power |  | West |  | 1681166
Cocke |  | Power |  | West |  | 750594
Ward |  | Power |  | West |  | 1757
Etringer |  | Power |  | West |  | 4000000
McDonald |  | Power |  | West
Page |  | Power |  | West |  | 4000000
Slaughter | * | Power |  | West |  | 4000000
Buerkle | * | Power |  | West |  | 2000000
Dyer |  | Power |  | West
Total
*includes $5M to be recognized 3Q for Fountain Valley (PSCO)
Spreadsheet: 56857d1256996347-lookup-example
Sheet: 250

TRACE NUMBER | LENGTH | TRACE INSTALLED | 100% COMPLETE
250-C-4002-01-HT01 | 20 | 2009-10-31 00:00:00 |  | I WANT CELL D6 TO HAVE THE SAME VALUE AS B6 WHEN C6 IS NOT BLANK
250-C-4002-01-HT03 | 15 | 2009-10-28 00:00:00
250-C-4002-01-HT02A | 30 | 2009-09-27 00:00:00
250-C-4002-01-HT02B | 45 | 2009-08-08 00:00:00
250-C-4003-01-HT01 | 69 | 2009-10-03 00:00:00
Spreadsheet: 865676d1712702397-averages-from-a-table-based-on-a-day-of-the-week-and-beginning-ending-time-average-days-times-sample-01
Sheet: Sheet1

FRIDAY
START TIME | END TIME | AVERAGE TRANSACTIONS | AVERAGE AMOUNTS
00:00:00 | 00:59:59
01:00:00 | 01:59:59
02:00:00 | 02:59:59
03:00:00 | 03:59:59
04:00:00 | 04:59:59
05:00:00 | 05:59:59
06:00:00 | 06:59:59
07:00:00 | 07:59:59
08:00:00 | 08:59:59
09:00:00 | 09:59:59
10:00:00 | 10:59:59
11:00:00 | 11:59:59
12:00:00 | 12:59:59
13:00:00 | 13:59:59
14:00:00 | 14:59:59
15:00:00 | 15:59:59
16:00:00 | 16:59:59
17:00:00 | 17:59:59
18:00:00 | 18:59:59
19:00:00 | 19:59:59
20:00:00 | 20:59:59
21:00:00 | 21:59:59
22:00:00 | 22:59:59
23:00:00 | 23:59:59
Spreadsheet: 774339d1648406187-sumifs-with-sums-from-mulitple-columns-based-on-its-names-file
Sheet: Arkusz1

customer | product | sub-product | volume Jan | revenue Jan | costs Jan | volume Feb | revenue Feb | costs Feb | volume  March | revenue  March | costs  March | volume April | revenue April | costs April | SUM VOLUME
www | [NAME] | wer | 180 | 65 | 23 | 230 | 155 | 202 | 200 | 123 | 56 | 163 | 89 | 153
eee | [NAME] | sdf | 80 | 35 | 21 | 16 | 90 | 149 | 131 | 2 | 59 | 199 | 112 | 205
rrr | wsx | xcv | 77 | 207 | 199 | 69 | 67 | 55 | 105 | 219 | 109 | 84 | 33 | 49
ttt | [NAME] | wer | 227 | 118 | 138 | 44 | 231 | 14 | 116 | 45 | 37 | 78 | 113 | 142
eee | wsx | sdf | 137 | 93 | 100 | 191 | 231 | 4 | 49 | 143 | 68 | 16 | 156 | 22
rrr | [NAME] | xcv | 82 | 223 | 231 | 170 | 207 | 98 | 24 | 77 | 112 | 116 | 222 | 2
ttt | wsx | wer | 45 | 14 | 85 | 16 | 175 | 35 | 8 | 175 | 87 | 179 | 147 | 133
www | [NAME] | sdf | 7 | 217 | 194 | 101 | 74 | 88 | 50 | 93 | 125 | 98 | 80 | 4
www | [NAME] | wer | 135 | 40 | 216 | 114 | 102 | 14 | 126 | 155 | 64 | 206 | 38 | 48
eee | [NAME] | sdf | 79 | 126 | 172 | 194 | 123 | 11 | 36 | 211 | 15 | 153 | 46 | 84
rrr | wsx | xcv | 126 | 94 | 231 | 35 | 218 | 85 | 182 | 141 | 129 | 152 | 81 | 36
ttt | [NAME] | wer | 53 | 59 | 233 | 194 | 120 | 25 | 78 | 191 | 226 | 52 | 82 | 87
eee | wsx | sdf | 225 | 44 | 132 | 96 | 99 | 171 | 216 | 171 | 125 | 36 | 213 | 171
rrr | [NAME] | xcv | 197 | 223 | 82 | 133 | 18 | 169 | 211 | 223 | 34 | 73 | 107 | 153
ttt | wsx | wer | 200 | 80 | 125 | 74 | 176 | 93 | 21 | 120 | 4 | 168 | 43 | 109
www | [NAME] | sdf | 213 | 196 | 190 | 43 | 168 | 11 | 204 | 130 | 171 | 162 | 77 | 213
www | [NAME] | wer | 38 | 113 | 73 | 181 | 161 | 164 | 183 | 117 | 171 | 14 | 18 | 112
eee | [NAME] | sdf | 133 | 168 | 83 | 114 | 23 | 215 | 230 | 200 | 225 | 204 | 49 | 123
rrr | wsx | xcv | 23 | 22 | 47 | 41 | 133 | 226 | 95 | 67 | 76 | 124 | 110 | 173
ttt | [NAME] | wer | 119 | 142 | 126 | 189 | 105 | 225 | 130 | 26 | 216 | 9 | 123 | 203
eee | wsx | sdf | 134 | 88 | 150 | 38 | 223 | 188 | 102 | 0 | 199 | 69 | 159 | 25
Spreadsheet: 159788d1338843035-excel-2007-i-need-a-formula-to-calculate-six-months-at-a-time-from-separate-sheet-tabs-hr-calendar-with-formulas
Sheet: Apr

 | SUNDAY | MONDAY | TUESDAY | WEDNESDAY | THURSDAY | FRIDAY | SATURDAY |  | 1. Absent - EX  2. Absent - UN  3. Bereavement  4. Discipline  5. FMLA  6. Tardy
 |  |  | Franklin 6 |  | Franklin 6
 |  |  |  | Franklin 6
 |  |  | NOTES:
 |  |  | Type in Employee's Last Name and the Corresponding Number
Spreadsheet: 3f19212a-df88-453d-a8e0-b6cbade30045
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3
 |  | How To Use the Team Generation Rate Calculator
 | 1 | The TGR Calculator is designed to be a quick and easy way of generating TGR's for an Area.  The calculator expresses the TGR in two ways, [NAME] per 1000 population ,  and Population needed to generate a single team.
 | 2 | TGR's are based on the actual number of the local population of an area which is within  that age group, these are called Active Age Groups.  The Calaculator will provide TGR's per age group.  All you need to do is input the following information;
 |  | a. | Census Population totals for each your Local Authority Area.
 |  | b. | Number of Teams within each Age Group for each sport.
 |  | The calculator has been designed to minimise the amount of information you have to input. The cells that need to be filled in with data, are all highlighted in Yellow.  Once these cells have been filled in, the caluator will automatically generate the other figures.
 | 4 | First step is to fill in the census population totals for your Area.  This information can be accessed form the Office of National Statistics Web site.  http://www.statistics.gov.uk/.   From the Census 2001 section you will be able to find your areas population breakdown form the Local Authority profiles.  [NAME] these figures into the yellow cells on the 'Census Population' sheet of this calculator.
 | 5 | The Calculator will automatically calculate how much of the areas population are in each of  the Active Age Groups.  These are shown in the 'Active Age Group' sheet.  Note,  these figures will be automatically generated, and so you do not need to input any data in this sheet.
 | 6 | The second stage is to input the number of teams by sport and by age group. These need to be filled in on the 'TGR Calculator' sheet.   Please note, that if there are no teams in an age group, please put '0'.      The calculator will then generate the Team Geneartion rates for each age group and sport for you area.
 | 7 | When you have completed this TGR calculator, please send a copy of this file to Sport England.  These figures will help in compiling a list of comparable TRG's from all over the country.  This list will be published on Sport Engalnd's website.
Spreadsheet: 157752d1337866458-calculating-lap-time-splits-example
Sheet: Sheet1

 | Run Time | Bike Time | Split 1 | 2nd Run Time | [NAME]
Run Pos | Min:Sec | Min:Sec | Min:Sec | Min:Sec | Min:Sec
1 | 13.26 | 37.31 | ??.?? | 52.24 | ??.??
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Spreadsheet: 732774d1621237100-how-to-apply-if-on-linest-argument-linest_array
Sheet: Sheet1

Area | Area
ha | $US/ha
10 | 5000 |  | =PRODUCT(IF(ISNUMBER(S3:S30);S3:S30);IF(ISNUMBER(T3:T30);T3:T30))
50 | 20000
 |  |  | =LINEST(IF(ISNUMBER(S3:S4);S3:S4);IF(ISNUMBER(T3:T4);T3:T4);TRUE;TRUE)
 |  |  |  | -3.333333333333336
 |  |  | 0 | 0
 |  |  | 1 | 0
 |  |  | 0 | 0
 |  |  | 800 | 0
 |  |  | =LINEST(S3:S4;T3:T4;TRUE;TRUE)
 |  |  |  | -3.333333333333336
 |  |  | 0 | 0
 |  |  | 1 | 0
 |  |  | #[NAME]! | 0
 |  |  | 800 | 0
 |  |  | =LINEST(IF(ISNUMBER(S3:S30);S3:S30);IF(ISNUMBER(T3:T30);T3:T30);TRUE;TRUE)
 |  |  |  | #[NAME]!
 |  |  | #[NAME]! | #[NAME]!
 |  |  | #[NAME]! | #[NAME]!
 |  |  | #[NAME]! | #[NAME]!
 |  |  | #[NAME]! | #[NAME]!
Spreadsheet: 872066d1718428440-athletic-spread-sheet-formulas-athletics-spreadsheet-v13-1-aligw
Sheet: Overall

 |  |  |  |  | OVERALL POINTS
TIBROGARGAN | BOYS | [NAME] | 9YRS | 10YRS | 11YRS | 12YRS | TOTAL |  | SENIORS |  |  | JUNIORS
 |  |  |  |  |  |  |  |  | TIBROGARGAN |  |  | TIBROGARGAN
 | GIRLS | [NAME] | 9YRS | 10YRS | 11YRS | 12YRS | TOTAL |  | COOCHIN |  |  | COOCHIN
 |  |  |  |  |  |  |  |  | COONOWRIN |  |  | COONOWRIN
COOCHIN | BOYS | [NAME] | 9YRS | 10YRS | 11YRS | 12YRS | TOTAL
 | GIRLS | [NAME] | 9YRS | 10YRS | 11YRS | 12YRS | TOTAL
COONOWRIN | BOYS | [NAME] | 9YRS | 10YRS | 11YRS | 12YRS | TOTAL
 | GIRLS | [NAME] | 9YRS | 10YRS | 11YRS | 12YRS | TOTAL
Spreadsheet: 101336d1299494909-excel-2007-cross-referencing-tables-testb
Sheet: Sheet1

 | Product 1 | Product 2 | Product 3 | Product 4 | Product 5 | Product 6 | Product 7 | Product 8 | Product 9 | Product 10 | Product 11 | Product 12
Customer 1 | 2 | 2 | 1 | 2 | 1 | 2 | 4 | 3 | 2 | 1 | 2 | 2
Customer 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1
Customer 3 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0
Customer 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
Customer 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Customer 6 | 0 | 0 | 1 | 0 | 1 | 2 | 2 | 2 | 1 | 0 | 1 | 0
Customer 7 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 2 | 1
Customer 8 | 0 | 1 | 1 | 2 | 2 | 3 | 2 | 1 | 1 | 0 | 2 | 1
Customer 9 | 2 | 2 | 2 | 1 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1
Customer 10 | 1 | 2 | 1 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 2 | 2
Customer 11 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 1 | 0
Customer 12 | 2 | 2 | 1 | 1 | 1 | 2 | 3 | 3 | 2 | 1 | 2 | 2
Customer 13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Customer 14 | 1 | 1 | 2 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 1 | 0
Spreadsheet: michelle_lokay__26574__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 | 30984 | 32750 | 10962 | 12000
21 | 38918 | 42749 | 10803 | 12000 | 10737 | 10000
22 | 39201 | 36960 | 10732 | 12000 | 13149 | 10000
23 | 39181 | 37311 | 10339 | 12000 | 13715 | 10000
24 | 39009 | 39743 | 10280 | 12000 | 13618 | 10000
25 | 38731 | 39802 | 10415 | 12000 | 13438 | 10000 | 3235
26 | 37876 | 39802 | 9718 | 12000 | 13282 | 10000 | 5213
27 | 38050 | 39802 | 8966 | 12000 | 12337 | 10000 | 4315
28 | 38395 | 38802 | 10047 | 12000 | 11700 | 10000 | 3911
29 | 38295 | 33722 | 10525 | 12000 | 12294 | 10000 | 4411
30 | 38033 | 34704 | 10065 | 12000 | 12387 | 10000 | 5763
31 | 37731 | 38802 | 10151 | 12000 | 12431 | 10000 | 3927
2000-11-30 00:00:00 |  |  |  |  |  |  |  |  | -532429.6
2000-12-31 00:00:00
 |  |  | 516.78
 |  |  | 212.08
 |  |  | 58.33
 |  |  | 25
Spreadsheet: 881226d1729178834-median-score-formula-using-table-name-instead-of-range-median-scores-test-3
Sheet: Sheet1

Year | Scores 1 | Scores 2
2022-2023 | 97 | 110 |  |  |  |  |  |  | 2022-2023
2022-2023 | 102 | 111 |  |  |  |  |  |  | 2023-2024
2022-2023 | 120 | 112 |  |  | Year | Score 1 | Score 2 |  | 2024-2025
2022-2023 | 111 | 111 |  | Median Score | 2022-2023
2022-2023 | 115 | 126
2022-2023 | 89 | 128
2022-2023 | 114 | 123
2022-2023 | 107 | 126
2022-2023 | 99 | 125
2022-2023 | 100 | 122
2022-2023 | 86 | 129
2022-2023 | 118 | 113
2022-2023 | 114 | 124
2022-2023 | 131 | 119
2022-2023 | 109 | 114
2022-2023 | 120 | 124
2023-2024 | 113 | 100
2023-2024 | 123 | 125
2023-2024 | 99 | 123
2023-2024 | 112 | 110
2023-2024 | 111 | 137
2023-2024 | 116 | 115
2023-2024 | 114 | 115
2023-2024 | 101 | 129
2023-2024 | 115 | 107
2023-2024 | 113 | 119
2023-2024 | 102 | 121
2023-2024 | 131 | 120
2023-2024 | 108 | 127
2023-2024 | 125 | 121
2023-2024 | 100 | 117
2023-2024 | 114 | 113
2024-2025 | 106 | 133
2024-2025 | 117 | 99
2024-2025 | 101 | 123
2024-2025 | 112 | 128
2024-2025 | 117 | 114
2024-2025 | 111 | 119
2024-2025 | 121 | 134
2024-2025 | 101 | 110
2024-2025 | 105 | 128
2024-2025 | 67 | 127
Spreadsheet: 691439d1597688846-help-to-sum-duplicates-excel-problem
Sheet: Blad1

 | total sales | sold by telephone | sold IRL |  |  |  | total sales | sold by telephone | sold IRL
[NAME] | 5 | 3 | 2 |  |  | [NAME] | 7 | 4 | 3
[NAME] | 1 | 1 | 0 |  |  | [NAME] | 6 | 3 | 3
[NAME] | 2 | 1 | 1 |  |  | Bo Ek | 5 | 3 | 2
Bo Ek | 5 | 3 | 2 |  |  | [NAME] | 5 | 2 | 3
[NAME] | 2 | 1 | 1 |  |  | [NAME] | 5 | 2 | 3
[NAME] | 3 | 1 | 2
[NAME] | 5 | 2 | 3
[NAME] | 5 | 2 | 3
Spreadsheet: 841304d1693493579-match-date-on-two-different-pages-and-paste-data-in-columns-ef-file
Sheet: 12-8 Night

 | CR1 | Priority | Headcount | QI
1 | Alinity RV | 16 | 0.25 | [NAME]
2 | Alinity RV | 15 | 0.25 | Lilia
3 | Alinity RV | 14 | 0.25 | Emil
4 | Alinity RV | 13 | 0.25 | Romona
5 | Alinity RV | 12 | 0.25
12 | [NAME] | 18 | 0.25
13 | [NAME] | 19 | 0.25
9 | Architect RV | 11 | 0.25
15 | [NAME] | 20 | 0.5
17 | Architect RV | 10 | 0.25
31 | Architect RV | 9 | 0.25
8 | Architect RV | 17 | 0.25
10 | Architect RV | 7 | 0.25
11 | [NAME]
18 | Architect RV | 8 | 0.25
19 | Architect RV | 6 | 0.25
20 | [NAME] | 5 | 0.5
21 | Architect RV | 4 | 0.25
22 | Architect RV | 3 | 0.25
23 | Architect RV | 2 | 0.25
7 | Architect SC | 1 | 0.25
Total
 | CR2 | Priority
73 | 8ul | 5 | 0.25
74 | Side Cassette | 1 | 0.25
78 | PP1 | 2 | 0.25
79 | E/O Piston | 3
77 | Base Cassette OQ
87 | [NAME] | 6
53 | Architect RV | 7 | 0.2
61 | [NAME] | 10 | 0.5
66 | [NAME] | 9 | 0.5
83
84
86 | [NAME] | 8 | 0.25
62 | NP227 | 16 | 0.25
63 | NP104 | 15 | 0.25
67 | [NAME] | 14 | 0.25
88 | [NAME] | 11 | 0.25
106
107
108
109
Total
Grand Total
Spreadsheet: 889694d1740599404-repeat-formula-but-of-different-range-size-and-return-as-dynamic-array-repeat-formula-and-return-as-array
Sheet: Sheet1

 | Original Data
 |  | Region | Type | 2025-01-01 00:00:00 | 2025-02-01 00:00:00 | 2025-03-01 00:00:00 | 2025-04-01 00:00:00 | 2025-05-01 00:00:00
 |  | North | A | 19 | 9 | 20 | 9 | 6
 |  | North | B | 5 | 1 | 2 | 17 | 13
 |  | North | C | 20 | 10 | 11 | 17 | 14
 |  | South | A | 12 | 5 | 4 | 13 | 17
 |  | South | B | 12 | 20 | 4 | 9 | 14
 |  | South | C | 19 | 11 | 13 | 9 | 13
 | [NAME] |  | Type | -4 | -3 | -2 | -1 | 0
 |  |  | A | 0.05 | 0.05 | 0.1 | 0.1 | 0.05
 |  |  | B | 0.15 | 0.1 | 0.1 | 0.1 | 0.15
 |  |  | C | 0.15 | 0.1 | 0.2 | 0.05 | 0.1
 | Desired Result in dynamic array
 |  | Region | Type | 2025-01-01 00:00:00 | 2025-02-01 00:00:00 | 2025-03-01 00:00:00 | 2025-04-01 00:00:00 | 2025-05-01 00:00:00
 |  | North | A
 |  | North | B
 |  | North | C
 |  | South | A
 |  | South | B
 |  | South | C
Spreadsheet: 818529d1676900698-how-to-return-multiple-text-values-in-1-cell-s666-pq-return-multiple-text-values-in-1-cell
Sheet: Data

Type of card | Used
iDeal | x |  | Used | Type of card
[NAME] | x |  | x | iDeal + [NAME]
Maestro | x
VISA | x
MasterCard | x
ApplePay | x
[NAME] | x
 | if you change Used right click on green table and choose [NAME]
Spreadsheet: 7e5cf299-7546-4461-a728-4b0ae22f83a2
Sheet: Sheet1

Bevölkerung des Freistaates Sachsen nach ausgewählten Altersgruppen | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
[NAME]
Alter von ... bis                     unter ... Jahren | 2011 | 2015 | 2020 | 2025
1 000
unter 20 | 9228 | 9767 | 9503 | 8857
20 - 65 | 40408 | 37433 | 33602 | 30352
65 und mehr | 17246 | 17379 | 18326 | 19030
Insgesamt | 66882 | 64579 | 61431 | 58239
%
unter 20 | 13.79743428725217 | 15.12411155329132 | 15.4693884195276 | 15.20802211576435
20 - 65 | 60.41685356299153 | 57.96466343548212 | 54.69876772313653 | 52.11627946908429
65 und mehr | 25.78571214975629 | 26.91122501122656 | 29.83184385733587 | 32.67569841515136
Insgesamt | 100 | 100 | 100 | 100
Abhängigkeitsquotient
Jugendquotient | 22.83706196792714 | 26.09195095236823 | 28.28105469912505 | 29.18094359515024
Altenquotient | 42.67966739259553 | 46.42694948307643 | 54.53842033212308 | 62.69768054823406
Gesamtquotient | 65.51672936052267 | 72.51890043544466 | 82.81947503124813 | 91.87862414338429
Gebietsstand: | 1. Januar 2012
Quelle: | 2011 Bevölkerungsfortschreibung auf Basis der [NAME] vom 03. Oktober 1990
 | 2012 - 2025 Bevölkerungsprognose
Bevölkerung jeweils am 31. Dezember
Prognoseergebnisse werden bei der Veröffentlichung immer auf volle [NAME] gerundet. [NAME] basieren [NAME] ungerundeten Werten. Beim [NAME] der [NAME] werden Ihnen die ungerundeten [NAME] zur Verfügung gestellt, damit [NAME] eigenen Berechnungen genauer durchführen können. Die Darstellung der Ergebnisse sollte dann aber wieder gerundet erfolgen.
Spreadsheet: 774026d1648164441-split-ties-with-elaborate-index-match-large-equation-p3anut
Sheet: Sheet1

Scout Names | Total | Date
a | 1 | 2022-01-01 00:00:00
b | 2 | 2022-01-01 00:00:00
c | 2 | 2022-01-01 00:00:00
d | 3 | 2022-01-01 00:00:00
e | 4 | 2021-01-01 00:00:00
LARGE values | Expected | P3anut1 | P3anut2 | Nick
1 | d
2 | b
3 | c
4 | a
5 | n/a
Spreadsheet: 807772d1670038400-list-unique-numbers-in-multiple-ranges-sample
Sheet: Sheet1

 |  |  | 2022-11-12 00:00:00 | 2022-11-13 00:00:00 | 2022-11-14 00:00:00 | 2022-11-15 00:00:00 | 2022-11-16 00:00:00 | 2022-11-17 00:00:00 | 2022-11-18 00:00:00
Lead |  |  | SAT | SUN | MON | TUE | WED | THU | FRI
 |  |  | 1500 | 1500 |  |  |  |  | 1500
Supervisors |  |  | SAT | SUN | MON | TUE | WED | THU | FRI
 |  |  |  | 1600 | 1600 | 1600 | 1600
 |  |  | 1600 |  |  |  | 1600 | 1600 | 1600
 |  |  |  |  | 1600 | 1600 | 1600 | 1600
 |  |  | 1600 | 1600 |  |  |  | 1600 | 1600
Dual Rates |  |  | SAT | SUN | MON | TUE | WED | THU | FRI
 |  |  | 1645 | 1645 | 1645 | 1645 |  |  | 1645
 |  |  |  |  | 1645-F | 1645-F | 1645 | 1645 | 1645
 |  |  | 1645 |  |  | 1645 | 1645-F | 1645 | 1645
 |  |  | 1645 | 1645 | 1645 | 1645-F |  |  | 1645
 |  |  | 1500 | 1500-F |  |  | 1645 | 1645 | 1645
Full Time |  |  | SAT | SUN | MON | TUE | WED | THU | FRI
 |  |  | 1645 | 1645 | 1645 | 1645 | 1645
Part Time |  |  | SAT | SUN | MON | TUE | WED | THU | FRI
 |  |  | 1500 | 1500 |  |  | 1645 | 1645
 |  |  |  | 1500 |  |  | 1645 | 1645
 |  |  |  |  |  |  | 1645 | 1645 | 1645
 |  |  |  |  |  |  | 1645 | 1900 | 2100
 |  |  | 1500 | 1645 | 1645 | 1645
 |  |  |  | 1500 | 1645 | 1645
 |  |  |  |  | 1645 | 1645
 |  |  |  |  | 1645 | 1645 | 1645
Spreadsheet: 872588d1718964111-dashboard-with-tables-linking-to-specific-person-hr-dashboard-anon
Sheet: Data

Absences
 |  |  | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | [NAME] | All Staff
 |  | January | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 |  |  |  | January
 |  | February | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 |  |  |  | February
 |  | March | 0 | 0 | 2 | 0 | 0 | 1 | 1 | 1 | 1 | 0 |  |  |  | March
 |  | April | 1 | 0 | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 1 |  |  |  | April
 |  | May | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 |  |  |  | May
 |  | June | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 |  |  |  | June
 |  | July | 5 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 2 |  |  |  | July
 |  | August | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 |  |  |  | August
 |  | September | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 |  |  |  | September
 |  | October | 2 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 |  |  |  | October
 |  | November | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 |  |  |  | November
 |  | December | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |  |  |  | December
 |  | Total |  |  |  |  |  |  |  |  |  |  |  |  |  | Total
Spreadsheet: 700028d1602908632-formula-to-extract-data-based-on-month-and-year-extract-profits
Sheet: BR1

BR1 | 2019-10-01 00:00:00 | 2019-11-30 00:00:00 | 2019-12-31 00:00:00 | 2020-01-31 00:00:00 | 2020-02-29 00:00:00 | 2020-03-31 00:00:00 | 2020-04-30 00:00:00 | 2020-05-31 00:00:00 | 2020-06-30 00:00:00 | 2020-07-31 00:00:00 | 2020-08-31 00:00:00 | 2020-09-30 00:00:00
Net Profit Achieved Month-Dept1 | 1372 | 24256 | -2214 | 16883 | 5766 | 72022 | 85015 | 60125 | -22145 | 45125 | 30185
Net Profit Achieved Month-Dept2 | 20762.74933333333 | 25353.09333333333 | 29764.506 | 16542.99333333334 | 20720.564 | 1593.458 | 6826.338266666667 | 3313.036628571427 | -200.2650095238427 | -3713.56664761904 | -7226.868285714333
Net Profit Achieved Month-Dept3 | 15442.94033333333 | 17228.84733333333 | 16793.18266666667 | 21141.468 | 16698.47933333333 | 16818.52233333333 | 18317.4158 | 18592.70412380953 | 18867.99244761907 | 19143.2807714286 | 19418.56909523806
Net Profit Achieved Month-Dept4 | 24686.335 | 27093.99566666667 | 22422.78966666667 | 18538.71766666667 | 15402.05133333333 | 24938.53266666667 | 18410.512 | 17333.40009523813 | 16256.2881904762 | 15179.17628571433 | 14102.0643809524
Spreadsheet: 78a0a9b5-d6df-4787-a310-82747e30055b
Sheet: Sheet1

Chicago Season Schedule | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7
Date | Game Number | Visiting Team | Visiting Score | Home Team | Home Score | Game Time/Status | Venue
2014-04-25 | 1 | Chicago | 4 | Rochester | 3 | Final OT | Blue Cross [NAME], NY
2014-04-26 | 2 | Chicago | 2 | Rochester | 3 | Final | Blue Cross [NAME], NY
2014-05-01 | 3 | Rochester | 0 | Chicago | 4 | Final | Allstate [NAME], IL
2014-05-02 | 4 | Rochester | 7 | Chicago | 2 | Final | Allstate [NAME], IL
2014-05-04 | 5 | Rochester | 2 | Chicago | 4 | Final | Allstate [NAME], IL
2014-05-09 | 1 | Toronto | 5 | Chicago | 2 | Final | Allstate [NAME], IL
2014-05-10 | 2 | Toronto | 4 | Chicago | 2 | Final | Allstate [NAME], IL
2014-05-14 | 3 | Chicago | 3 | Toronto | 4 | Final OT | Ricoh Coliseum Toronto, ON
2014-05-16 | 4 | Chicago | 0 | Toronto | 4 | Final | Ricoh Coliseum Toronto, ON
Spreadsheet: 491941d1480706694-conditional-formatting-on-or-off-excelforum
Sheet: 9

Client | Notes | Controls | Tech | Initials
A | Positive Serology | Negative | A S
S | Expired | Positive | A D
F | Client Cancelled |  | A F
D |  |  | A G
G |  |  | A H
H
J