tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 14011923-c598-453d-9353-8538096af358
Sheet: Sheet1

Bevölkerung des Freistaates Sachsen nach ausgewählten Altersgruppen | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
[NAME] Mittweida - Variante 1
Alter von ... bis                     unter ... Jahren | 2011 | 2015 | 2020 | 2025
1 000
unter 20 | 17595 | 17576 | 16731 | 15351
20 - 25 | 6053 | 3345 | 3765 | 3923
25 - 35 | 13217 | 12169 | 8877 | 6779
35 - 55 | 34944 | 31641 | 27432 | 24633
55 - 67 | 21113 | 23247 | 22916 | 21447
67 und mehr | 29006 | 28266 | 30168 | 31495
Insgesamt | 121928 | 116244 | 109889 | 103628
%
unter 20 | 14.43064759530215 | 15.11992016792265 | 15.22536377617414 | 14.8135639016482
20 - 25 | 4.964405222754412 | 2.877567874470941 | 3.426184604464505 | 3.78565638630486
25 - 35 | 10.84000393674956 | 10.46849729878531 | 8.078151589331052 | 6.541668274983595
35 - 55 | 28.65953677580211 | 27.21946939196862 | 24.96337213005851 | 23.77060253985409
55 - 67 | 17.31595695820484 | 19.99845153298235 | 20.85377062308329 | 20.69614389933222
67 und mehr | 23.78944951118693 | 24.31609373387014 | 27.4531572768885 | 30.39236499787702
Insgesamt | 100 | 100 | 100 | 100
Gebietsstand: | 31. [NAME] 2008
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: 727228d1617790457-conditional-formatting-error-book1gk
Sheet: Sheet1

 | Product | Company | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote | Price per kg | Unit | Date of quote
 | [NAME] |  |  |  | 2021-04-17 00:00:00 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.1 | 100 Kg | 2020-11-11 00:00:00
 | Sunflower Oil |  |  |  | 2021-05-17 00:00:00 |  |  |  |  |  |  |  |  |  |  |  |  | 1.4 | 13 x 20L drum | 2021-02-10 00:00:00
 | Sunflower Oil (refined, deodorised & winterised) |  |  |  | 2021-06-17 00:00:00 |  |  |  |  |  |  |  |  |  |  |  |  | 1.35 | 48 x 20 L bottle in a box. £ per 20L | 2021-02-11 00:00:00 |  |  |  |  |  |  |  |  |  |  |  |  | 1.3 | 920 Kg IBC | 2021-02-11 00:00:00
 | Sunflower Seed Oil (Helianthus Annuus) REFINED |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.63 | 25Kg REPACKS | 2021-02-10 00:00:00 |  |  |  |  |  |  |  |  |  | 1.88 | 200 Kg drums | 2021-02-10 00:00:00
 | [NAME] (Cosmetic blend) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.64 | 25kG Poly multiples | 2021-02-10 00:00:00 |  |  |  |  |  |  |  |  |  | 1.89 | 190kg drum | 2021-02-10 00:00:00
 | [NAME] (Prunus Amygdalus Dulcis) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.05 | 200 Kg | 2021-02-11 00:00:00
 | [NAME] BP73 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3.04 | 25kG Poly multiples | 2021-02-10 00:00:00 |  |  |  |  |  |  |  |  |  | 2.29 | 190kg drum | 2021-02-10 00:00:00
 | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6.13 | 25kG Poly multiples | 2021-02-10 00:00:00 |  |  |  |  |  |  |  |  |  | 5.38 | 190kg drum | 2021-02-10 00:00:00
 | [NAME] |  |  |  |  |  |  |  | 18.75 | 5 Kg | 2020-12-04 00:00:00 |  |  |  |  |  |  |  |  |  | 18 | 25Kg | 2020-12-04 00:00:00
 | Tea Tree Oil Chinese (prime A grade) |  | 31.5 | 1 Kg | 2020-10-12 00:00:00 |  |  |  | 28.5 | 5 Kg | 2020-12-04 00:00:00 |  |  |  |  |  |  |  |  |  | 27.75 | 25Kg | 2020-12-04 00:00:00
 | Tetrasodium EDTA (Primesurf EDTA Na4 [NAME]) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.9 | 25Kg | 2021-03-10 00:00:00
 | Tetrasodium EDTA (Primesurf EDTA Na4 [NAME]) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4.1 | 125Kg | 2021-03-10 00:00:00
 | Triethanolamine TEA 90% (Tela 9990) |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2.15 | 200 Kg drum | 2020-12-09 00:00:00
Spreadsheet: 67923d1268417342-collapse-data-to-fill-in-holes-sample-data
Sheet: before

ID Number | Grade | M-F score | M-F % | R-F score | R-F % | M-W score | M-W % | R-W score | R-W %
260010001361 | 5 |  |  | 182 | 5 |  |  | 200 | 22
260010001361 | 5 | 197 | 14 |  |  | 202 | 17
260010014889 | 5 |  |  | 212 | 64
260010014889 | 5 | 205 | 31
260010015775 | 5 |  |  | 193 | 15 | 212 | 40
260010015775 | 5 | 204 | 29 |  |  |  |  | 190 | 8
260010019965 | 4 |  |  | 212 | 64 | 217 | 53
260010019965 | 4 | 213 | 55 |  |  |  |  | 211 | 52
260010020440 | 4 |  |  | 219 | 83
260010020440 | 4 | 223 | 80
260010025397 | 4 |  |  | 187 | 17 | 190 | 9
260010025397 | 4 | 192 | 18 |  |  | 190 | 9
260010026892 | 4 |  |  | 204 | 60 | 223 | 89
260010026892 | 4 | 215 | 84
260010027331 | 4 |  |  | 200 | 29 |  |  | 201 | 24
260010027331 | 4 |  |  | 200 | 29 | 201 | 15
260010027331 | 4 | 198 | 16 |  |  | 201 | 15
260010027891 | 4 |  |  | 214 | 86 | 211 | 62
260010027891 | 4 | 209 | 70
260010028271 | 4 |  |  | 183 | 11 | 205 | 42
260010028271 | 4 | 192 | 18
260010028652 | 4 |  |  | 210 | 77 | 207 | 49
260010028652 | 4 | 193 | 21
260010030543 | 4 |  |  | 180 | 8 | 201 | 30
260010030543 | 4 | 192 | 18
260010030709 | 2 |  |  | 174 | 10 |  |  | 182 | 16
260010030709 | 2 | 180 | 16
260010031182 | 3 |  |  | 186 | 35 |  |  | 188 | 27
260010031182 | 3 | 191 | 46 |  |  |  |  | 188 | 27
260010032275 | 4 |  |  | 198 | 41
260010032275 | 4 | 202 | 46
260010035265 | 4 |  |  | 198 | 41 | 219 | 82
260010035265 | 4 | 205 | 57
260010036540 | 2 |  |  | 189 | 76 |  |  | 185 | 47
260010036540 | 2 |  |  | 189 | 76 | 195 | 78
260010036540 | 2 | 190 | 84
260010036540 | 2 |  |  |  |  | 195 | 78
Spreadsheet: 817159d1676029868-finding-and-returning-the-text-of-the-cell-to-the-right-of-a-value-in-a-dynamic-array-excelquestion1
Sheet: Sheet1

1 | A |  |  | 4 | G
 |  |  |  |  |  |  |  |  |  | 3 | F
 |  |  |  |  |  | 7 | T
 |  |  | 2 | B
 |  |  |  |  |  |  |  | 6 | L
 |  | 5 | Q
What letter is next to # x?
1
2
3
4
5
6
7
Spreadsheet: 695332d1600158877-averageif-on-separate-values-without-0-book9
Sheet: Sheet1

 |  |  | PLANT 1 |  |  |  | PLANT 2 |  |  |  | PLANT 3 |  |  |  | TOTAL
 |  | SEASON | Avail | ADR BAR |  | SEASON | Avail | ADR BAR |  | SEASON | Avail | ADR BAR |  | SEASON | Avail | ADR BAR
 |  | L | 0 | 0 |  | L | 3 | 3000 |  | L | 0 |  |  | L |  |  | average without 0
 |  | H | 72 | 8700 |  | H | 56 | 5000 |  | H | 67 | 4500 |  | H |  |  | average without 1
 |  | P | 34 | 9000 |  | P | 78 | 8000 |  | P | 100 | 5500 |  | P |  |  | average without 2
Spreadsheet: 525515d1498752833-list-to-matrix-list-to-matrix
Sheet: Sheet1

Job Number | Employee | Occurances |  |  | Job Number | Employee 1 | 1-Count | Employee 2 | 2-Count | Employee 3 | 3-Count | Employee 4 | 4-Count | Employee 5 | 5-count
1 | [NAME] | 3 |  |  | 1
1 | [NAME] | 4 |  |  | 2
1 | [NAME] | 4 |  |  | 3
2 | [NAME] | 3 |  |  | 4
2 | [NAME] | 4 |  |  | 5
2 | [NAME] | 9
2 | [NAME] | 5
3 | [NAME] | 4
3 | [NAME] | 3
3 | [NAME] | 1
3 | [NAME] | 2
3 | [NAME] | 8
4 | [NAME] | 4
4 | [NAME] | 6
4 | [NAME] | 9
4 | [NAME] | 1
5 | [NAME] | 2
5 | [NAME] | 4
5 | [NAME] | 12
Spreadsheet: 083991a7-7953-44a2-a220-c5c82e928d50
Sheet: Sheet1

Victims | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Age Category
by Offense Category, 2011
Offense Category | Total Victims1 | Age Category
 |  | Adult | Juvenile2 | Unknown
Total | 4305708 | 3901783 | 312119 | 91806
Crimes Against Persons | 1321523 | 1070432 | 228959 | 22132
[NAME] | 1226300 | 1029303 | 176071 | 20926
Homicide Offenses | 3792 | 3365 | 372 | 55
Kidnapping/Abduction | 15310 | 11405 | 3671 | 234
Sex Offenses, Forcible | 69356 | 26140 | 42365 | 851
Sex Offenses, Nonforcible | 6765 | 219 | 6480 | 66
Crimes Against Property | 2984185 | 2831351 | 83160 | 69674
[NAME] | 11869 | 9977 | 478 | 1414
Bribery | 234 | 185 | 14 | 35
Burglary/Breaking & Entering | 543854 | 524687 | 8039 | 11128
Counterfeiting/Forgery | 38106 | 35642 | 310 | 2154
Destruction/Damage/Vandalism | 674702 | 648395 | 10012 | 16295
Embezzlement | 3455 | 3276 | 42 | 137
Extortion/Blackmail | 1234 | 1120 | 92 | 22
Fraud Offenses | 200512 | 192400 | 2608 | 5504
Larceny/Theft Offenses | 1249040 | 1171254 | 51999 | 25787
Motor Vehicle Theft | 152373 | 148340 | 907 | 3126
Robbery | 82243 | 73767 | 7767 | 709
[NAME] Offenses | 26563 | 22308 | 892 | 3363
1This table includes only individual (person) victims and does not include business, financial institution, government, religious organization, and other victims.  Victims are counted once for each offense type to which they are connected.
2For this table, a Juvenile is a victim under the age of 18.
Spreadsheet: 873229d1719674090-copy-information-from-cells-if-marked-x-in-another-column-example
Sheet: Sheet1

titles | price | cancel? | price2
New York Times | 70 |  |  |  |  | Total budget for subscriptions | 1500
New Yorker | 100 | x | 100 |  |  | amount saved | (sum of prices in column D)
the Herald | 60 | x | 60
Vogue | 90
national Geographic | 50 | x | 50
Spreadsheet: 775923d1649383236-finding-highest-rated-department-by-the-sum-of-total-sales-and-employee-id-excel-training-help-different-tabs
Sheet: Presentation

 |  |  | Employee ID | Department | 2016-01-01 00:00:00 | 2016-02-01 00:00:00 | 2016-03-01 00:00:00 | Total Sales | Helper | Row Labels | Count of Jan-16
Emoloyee ID | Department | Department from different tab | 1006 | Development | 1 | 9 | 3 |  |  | Development | 2
1006 |  |  | 1007 | Finance | 2 | 7 | 5 |  |  | Finance | 2
1007 |  |  | 1009 | Finance | 6 | 1 | 4 |  |  | MD | 2
1009 |  |  | 1100 | Finance | 54 | 67 | 7 |  |  | Support | 5
1100 |  |  | 3900 | Support | 5 | 2 | 1 |  |  | Grand Total | 11
3900 |  |  | 4500 | Support | 41 | 45 | 7
4500 |  |  | 133 | Support | 66 | 77 | 21
133 |  |  | 133 | Support | 44 | 33 | 88
133 |  |  | 133 | Support | 8 | 7 | 5
133 |  |  | 1007 | Support | 2 | 7 | 5
1007 |  |  | 1007 | Support | 55 | 87 | 5
1007 |  |  | 99 | MD | 5 | 56 | 5
99 |  |  | 100 | Support | 2 | 2 | 56
100 |  |  | 100 | Support | 1 | 56 | 5
100 |  |  | 1009 | Finance | 3 | 6 | 5
1009 |  |  | 1009 | Development | 2 | 5 | 1
1009 |  |  | 1009 | Development | 500 | 700 | 700
1009 |  |  | 3900 | MD | 77 | 23 | 29
3900 |  |  | 3900 | MD | 55 | 33 | 44
3900 |  |  | 3900 | Development | 99 | 66 | 99
3900 |  |  | 3900 | Development | 7 | 8 | 9
3900 |  |  | 1100 | Finance | 54 | 67 | 7
1100 |  |  | 1006 | Development | 76 | 8 | 78
 |  |  | 1006 | Finance | 34 | 44 | 65
 |  |  | 1006 | Finance | 22 | 28 | 7
 |  |  | 1006 | MD | 9 | 110 | 21
 |  |  | 1006 | MD | 45 | 34 | 8
 |  |  | 1007 | MD | 78 | 78 | 8
 |  |  | 1100 | Finance | 54 | 67 | 7
 |  |  | 1100 | Finance | 54 | 67 | 7
 |  |  | 1100 | MD | 98 | 106 | 99
 |  |  | 1100 | MD | 3 | 2 | 3
 |  |  | 1100 | Development | 101 | 101 | 101
 |  |  | 1100 | Development | 6 | 4 | 3
 | Hi all,
In G13 I am trying to get the department by Employee Id with the highest number of sales based on column J, so for example for B3 the result shoud be MD.
Tried index and match with [NAME] but gives the wrong answer as I am looking for the total amount of sales for a department based on the iD.
Much , much appreciated your help!
Spreadsheet: 824205d1680370060-circular-reference-circular-reference
Sheet: Sheet1

Useful Asset Life, Years |  |  | 10
Double Declining Balance Depreciation |  |  | DDB |  |  |  | METHOD 2
METHOD 1
Year | Asset Cost | Depreciation |  | Dep. Of $1 | Reverse Ticker |  | Year 1 | Year 2 | Depreciation
1 | 500
 | 200
Spreadsheet: 137078d1326942848-averaging-totals-in-excel-for-fuel-mileage-sheet-fuel-mileage-1-unit-6363-stock-ecm
Sheet: MileageCalculator

[NAME] for Unit 6363
Refuel Date | [NAME] | [NAME] | Gallons | $Cost | MPG | $Cost per Mile
2011-11-25 00:00:00 | 112026 |  | (fuel added) |  | (mileage)
2011-11-28 00:00:00 | 113232 | 1206 | 190.645 | 749.04 | 6.325893676728999 | 0.621094527363184
2011-11-29 00:00:00 | 113575 | 343 | 61.522 | 241.72 | 5.575241377068366 | 0.7047230320699709
2011-12-02 00:00:00 | 114913 | 1338 | 240.35 |  | 5.566881630954858
2011-12-06 00:00:00 | 116122 | 1209 | 185.594 | 701.36 | 6.514219209672727 | 0.5801157981803143
2011-12-07 00:00:00 | 116544 | 422 | 74.9 | 284.55 | 5.634178905206942 | 0.6742890995260664
2011-12-10 00:00:00 | 118005 | 1461 | 265 |  | 5.513207547169811
2011-12-13 00:00:00 | 119218 | 1213 | 189.708 | 716.91 | 6.394037151833344 | 0.5910222588623247
2011-12-14 00:00:00 | 119512 | 294 | 49.33 | 191.35 | 5.959862152848165 | 0.6508503401360544
2011-12-16 00:00:00 | 119769 | 257 | 51.541 | 199.93 | 4.986321569236142 | 0.7779377431906616
 |  | 7743 | 1308.59 | 3084.86 | 5.829982580079928 | 0.6571475427612252 | 5.91 mpg
Spreadsheet: 702762d1604514663-conditional-formatting-highlight-date-that-has-text-sample
Sheet: Sheet1

# | Name | Exp | Notes on conditional formatting
1675-0519 | Name 10 | n/a | don't want red
1648-0119 | Name 12 | 2021-06-01 00:00:00 | don't want red
2021-0221 | Name 1 | 2020-10-15 00:00:00 | should be red
1526-0316 | Name 78 | 10/15/2020-test message | should be red
1991-0720 | Name 0865 | 2020-11-01 00:00:00 | should be red
2034-0721 | Name 293 | 5/1/2021-test message 1; 10/15/2020-test message 2 | should be red
Spreadsheet: 152124d1335269463-count-c6-n6-minusing-if-a-ws-or-hs-are-in-those-cells-register-test-1
Sheet: 2

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
 |  | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 |  | 0 | 0 | 8 | 4
 |  | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 6 | 3
 |  | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 6 | 4
 |  | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 6 | 3
 |  | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 8 | 4
 |  | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 | 1
 |  | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 4 | 3
 |  | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 4 | 2
 |  | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
 |  | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 8 | 4
 |  | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 6 | 3
 |  | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 6 | 3
 |  | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2
 |  | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 10 | 5
 |  | HS | HS | 0 | 0 | HS | HS | HS | HS | 1 | 1 | 0 | 0 | 6 | 4
 |  | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 | 1
 |  |  |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
Total Sessions |  | 9 | 10 | 9 | 9 | 9 | 10 | 13 | 13 | 7 | 7 | 0 | 0 | 96 | 51
Number of Sessions |  | 8 | 10 | 9 | 9 | 9 | 9 | 12 | 12 | 7 | 7 | 0 | 0 | 92
Number of HS Sessions |  | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 4
Number of WS  Sessions |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Total Sessions |  | 9 | 10 | 9 | 9 | 9 | 10 | 13 | 13 | 7 | 7 | 0 | 0 | 96 | 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: 825818d1681552768-correction-of-the-indirect-timetable-formula-2023-draft-dailykode-
Sheet: APRIL

 |  | DATE | 2023-04-01 00:00:00
GR. 1 | Nr. [NAME]. | ID | Name |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | NORM HOURS | WORK HOURS | SCREEN HOURS | WEEK HOURS | NIGHT HOURS | CO | CM
 | 1 | 111 | Jhon |  |  |  |  |  | N |  |  |  | N |  |  |  |  |  | H |  |  |  |  |  |  | H |  |  |  |  |  |  | H
 | 2 | 112 | [NAME]
 | 3 | 113 | Adalyn
 | 4 | 114 | [NAME]
 | 5 | 115 | Beverly
Spreadsheet: 98311d1297268830-excel-2007-running-count-by-date-excel-question
Sheet: Sheet1

First formula I have is a simple counting formula. It is "=rows(a$1:a2)-1" , it counts one to many.
What I need, or would like to have is something that counts the individual occurances by date, then totals all those occurances for that date and in total. For example:
 |  | daily count | daily total | overall total
task A
2011-01-31 10:52:00 |  | 1
2011-01-31 10:52:00 |  | 2
2011-01-31 10:52:00 |  | 3
2011-01-31 15:45:00 |  | 4
2011-01-31 15:49:00 |  | 5
2011-01-31 16:02:00 |  | 6
2011-01-31 16:34:00 |  | 7
2011-01-31 16:35:00 |  | 8 | 8
2011-02-01 09:47:00 |  | 1
2011-02-01 09:48:00 |  | 2
2011-02-01 09:49:00 |  | 3
2011-02-01 14:32:00 |  | 4 | 12
2011-02-04 13:13:00 |  | 1
2011-02-04 13:14:00 |  | 2
2011-02-04 13:18:00 |  | 3
2011-02-04 13:18:00 |  | 4
2011-02-07 13:51:00 |  | 5
2011-02-07 13:51:00 |  | 6
2011-02-07 15:09:00 |  | 7
2011-02-07 15:11:00 |  | 8 | 20
task b |  | daily count | daily total
2011-01-31 10:52:00 |  | 1
2011-01-31 10:52:00 |  | 2
2011-01-31 10:52:00 |  | 3
2011-01-31 15:45:00 |  | 4
2011-01-31 15:49:00 |  | 5
2011-01-31 16:02:00 |  | 6
2011-01-31 16:34:00 |  | 7
2011-01-31 16:35:00 |  | 8 | 8
2011-02-01 09:47:00 |  | 1
2011-02-01 09:48:00 |  | 2
2011-02-01 09:49:00 |  | 3
2011-02-01 14:32:00 |  | 4 | 12
2011-02-04 13:13:00 |  | 1
2011-02-04 13:14:00 |  | 2
2011-02-04 13:18:00 |  | 3
2011-02-04 13:18:00 |  | 4
2011-02-07 13:51:00 |  | 5
2011-02-07 13:51:00 |  | 6
2011-02-07 15:09:00 |  | 7
2011-02-07 15:11:00 |  | 8 | 20
 |  |  |  | 40
Spreadsheet: 6263c4bb-6cb5-46d8-a66c-471cd878254d
Sheet: SW015

SW | SUV | PS# | Ln | Item | Description | UOM | $ | Cat | Cat Desc
SW015 | McCalls | 2851 | 1 |  |  |  | 43 |  | [NAME]
SW015 | McCalls | 2851 | 2 |  |  |  | 43 |  | [NAME]
SW015 | McCalls | 2851 | 3 |  |  |  | 59 |  | [NAME]
SW015 | McCalls | 2851 | 4 |  |  |  | 28 |  | Hospital Underpads
SW015 | McCalls | 2851 | 5 |  |  |  | 30 |  | Hospital Underpads
SW015 | McCalls | 2851 | 6 |  |  |  | 35 |  | Hospital Underpads
SW015 | McCalls | 2851 | 7 |  |  |  | 31 |  | Disposable Personal Wipes
SW015 | McCalls | 2851 | 8 |  |  |  | 30 |  | Freight Fee
SW015 | New View | 2854 | 7 |  |  |  | 29.36 |  | Emergency Medical Services First Aid Kits
SW015 | New View | 2854 | 8 |  |  |  | 0.01 |  | Freight Fee
SW015 | New View | 2854 | 9 |  |  |  | 0.01 |  | Emergency Medical Services First Aid Kits
SW015 | New View | 2854 | 10 | 1000029874 | FIRST AID: small utility kit-bandage, ointment, gauze, tape, spray, aspirin, gloves. | EA | 24.63 |  | Emergency Medical Services First Aid Kits
SW015 | New View | 2854 | 11 | 1000029875 | FIRST AID: medium wall mounted-bandages, ointment, gauze, tape, spray, aspirin, gloves. | EA | 123.36 |  | Emergency Medical Services First Aid Kits
SW015 | McCalls | 3124 | 1 |  |  |  | 30 |  | Feminine Hygiene Products
SW015 | McCalls | 3124 | 2 |  |  |  | 20 |  | Feminine Hygiene Products
SW015 | McCalls | 3124 | 3 |  |  |  | 60 |  | Feminine Hygiene Products
SW015 | McCalls | 3124 | 4 |  |  |  | 63 |  | Feminine Hygiene Products
SW015 | McCalls | 3124 | 5 |  |  |  | 31 |  | Disposable Personal Wipes
SW015 | SCI | 3542 | 1 |  |  |  | 146 |  | Disposable Personal Wipes
SW015 | SCI | 3542 | 2 |  |  |  | 183 |  | Disposable Personal Wipes
SW015 | SCI | 3542 | 3 |  |  |  | 220 |  | Disposable Personal Wipes
SW015 | SCI | 3542 | 4 |  |  |  | 248.4 |  | Disposable Personal Wipes
SW015 | SCI | 3542 | 5 |  |  |  | 353 |  | [NAME]
SW015 | SCI | 3542 | 6 |  |  |  | 3.56 |  | Toothbrushes
SW015 | SCI | 3542 | 7 |  |  |  | 33.15 |  | Disposable Personal Wipes
SW015 | SCI | 3542 | 8 |  |  |  | 153.88 |  | Shampoos
Spreadsheet: 718961d1613437050-what-recipe-can-be-made-from-available-stock-recipe-4-
Sheet: Sheet1

 |  | Recipe |  |  |  | Available Stock
 | Recipe name | Ingredients | Kilogram |  |  | Ingredients | Kilogram
 | [NAME] | Carrot | 2000 |  |  | Carrot | 2000
 |  | Spice | 25 |  |  | Spice | 25 |  | "What can be made from this stock?"
 |  | Salt | 50 |  |  | Salt | 50
 |  | Onion | 150 |  |  | Onion | 150
 |  | capsicum | 200 |  |  | capsicum | 200
 |  | water | 3550 |  |  | water | 3550
 |  | culture | 20 |  |  | culture | 20
 |  | tea | 40 |  |  | tea | 40
 |  | total |  |  |  | total
 | Recipe name | Ingredients | Kilogram
 | [NAME] | Carrot | 3000
 |  | Spice | 25
 |  | Salt | 50
 |  | Onion | 150
 |  | capsicum | 200
 |  | water | 3550
 |  | culture | 20
 |  | tea | 40
 |  | total
Spreadsheet: 275055d1383319671-daily-tracking-weekkeys
Sheet: week4

DUPLEXES, TRIPLEXES, 4-PLEXES & TOWNHOMES
# | Address | CITY | Unit | Rent | Tenant | Lease Start | Lease Ends | TAA | Owner | Monday | [NAME] | Wednesday | Thursday | Friday | Saturday | Weekly | Monthly
612 | [NAME] | K |  |  |  |  |  |  |  | 11
614 | [NAME] | K |  |  |  |  |  |  |  | 1
625 | Brook | K | B
625 | Brook | K | C
1220 | [NAME] | CC
805 | Sissom | K | 1
1609 | Poage | K | B
1611 | Poage | K
512 | Blake | K
103 | White Wing | CC | A
722 | Sutton | K | A
301 | North Dr | CC | B
917 | [NAME] | CC | B
917 | [NAME] | CC | C
917 | [NAME] | CC | D
211 | Erby | CC | D
1904 | [NAME] | K | D
1906 | [NAME] | K | C
1102 | Eastside Dr | K | A
1006 | Eastside Dr | K | B
1006 | Eastside Dr | K | D
133 | [NAME] | CC | B
5808 | Greengate | K | A
3403 | Toledo | K | B
3403 | Toledo | K | C
3008 | Chaucer | K | A
3008 | Chaucer | K | B
4505 | Westcliff | K | C
3802 | Charolais | K | C
3414 | [NAME] | K | C
1103 | Covey | K | A
3207 | Toledo | K | A
1007 | Circle M | K | B
1007 | Circle M | K | C
1218 | Royal Crest | K
3402 | [NAME] | K | D
3408 | [NAME] | K | C
4404 | [NAME] | K | B
4410 | [NAME] | K | B
3802 | [NAME] | K | A
3802 | [NAME] | K | B
3301 | Toledo | K | C
2404 | Skylark | K
1408 | Dugger Circle | K | B
3406 | Toledo | K | A
3407 | [NAME] | K | A
927 | [NAME] | K
2911 | Cantabrian | K | D
4408 | [NAME] Dr | K | A
3408 | [NAME] | K | A
3408 | [NAME] | K | D
4300 | [NAME] | K | D
2600 | Edfield | K | B
1312 | Saddle | K
BR = # [NAME] |  |  |  |  |  |  |  |  |  |  |  |  | W/D = Washer/Dryer Connection
BA = # Bathrooms |  |  |  |  |  |  |  |  |  |  |  |  | Pets = Y - Pets Allowed with Pet Deposit, N - Pets Not Allowed
GAR = Garage, CP = Carport |  |  |  |  |  |  |  |  |  |  |  |  | HUD = Y- HUD Accepted, N - HUD Not accepted
UTIL = Utilities Paid (W = Water, N = None) |  |  |  |  |  |  |  |  |  |  |  |  | MW = Y - Military Deposit Waiver Accepted
CH = Central Heat |  |  |  |  |  |  |  |  |  |  |  |  | CA = Central Air
Spreadsheet: 221356d1363507782-lookup-with-condition-formula-choose-the-yes-only
Sheet: Sheet1

 |  | Company A | [NAME] | F | Yes
 |  | Company A | [NAME] | M
 |  | Company A | Lous | M |  |  |  | Result
 |  | Company A | [NAME] | M |  | Company A | [NAME] | F
 |  | Company B | [NAME] | M |  | Company B | [NAME]
 |  | Company B | [NAME] | M |  | Company C | Rem | M
 |  | Company B | [NAME] | F
 |  | Company B | Cicelia | F
 |  | Company C | Rem | M | Yes
 |  | Company C | [NAME] | F
 |  | Company C | Evie | F
 |  | Company C | Jass | F
 |  | Company C | [NAME] | M
 |  | Company C | [NAME] | M