tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 679260d1590295601-display-unique-customer-formula-box-data-excel-forum-2-
Sheet: Sample data set

 | Desired result
 | (manual) | Sample Data Set
 |  | All Files/1. [NAME]'s loans with [NAME].  [NAME]
 |  | All Files/1. [NAME]'s loans with [NAME].  Approved Loans/Todd & Tina Smith loan file/
 |  | All Files/1. [NAME]'s loans with [NAME].  Approved Loans/Todd & Tina Smith loan file/1. Submission/
 |  | All Files/1. [NAME]'s loans with [NAME].  Approved Loans/Todd & Tina Smith loan file/1. Submission/Credit Report.pdf
 |  | All Files/1. [NAME]'s loans with [NAME].  Approved Loans/Todd & Tina Smith loan file/1. Submission/ID Todd.pdf
 |  | All Files/1. [NAME]'s loans with MyHang/2.  In Process Loans/Robert & Mary Levander loan file/
 |  | All Files/1. [NAME]'s loans with MyHang/2.  In Process Loans/Robert & Mary Levander loan file/5. Funding/
 |  | All Files/1. [NAME]'s loans with MyHang/2.  In Process Loans/Robert & Mary Levander loan file/1. Submission/
 |  | All Files/1. [NAME]'s loans with MyHang/2.  In Process Loans/Robert & Mary Levander loan file/1. Submission/1008.pdf
 |  | All Files/1. [NAME]'s loans with [NAME].  Approved Loans/Alice & Frank Jones loan file/
 |  | All Files/1. [NAME]'s loans with [NAME].  Approved Loans/Alice & Frank Jones loan file/1. Submission/
 |  | All Files/1. [NAME]'s loans with MyHang/2.  In Process Loans/New folder (2)/
 |  | …and so on
 |  | Goal
 |  | I want to identify one record for each customer, and the file name that ends with "loan file/" seems to be the easiest identifier.
 |  | I don't want to list the sub-folders/files.
 |  | I believe if I had a formula that looked for a string that ended in "loan file/" I could achieve my goal.
 |  | In words, I'd want this formula to say… look for unique records that end in "loan file/" and have nothing after that string.
 |  | Thanks for any help!!
Spreadsheet: 220807d1363270839-vlookup-but-with-3-possible-col_index_num-to-choose-book2_edit
Sheet: Sheet1

TMX SITE ID | SITE NAME | TELCO | TELCO ID
 | LPT 1 | DARIOS
 | LPT 2 | CELESTICA
 | LPT 2 | DARIOS
 | LPT 3 | CELESTICA
 | LPT 3 | MAXIM
 | LPT 4 | MAXIM
 | LPT 5 | CELESTICA
 | LPT 7 | MAXIM
 | LPT 6 | MAXIM
 | LPT 6 | DARIOS
 | LPT 6 | CELESTICA
Spreadsheet: 686979d1594900260-find-a-text-string-and-return-that-cells-contents-plus-adjacent-cell-contents-suunto-search-example-2
Sheet: Jan 2013

 | Order | Order Number | Name | Order Date | Posted | Product
 | 1 | 2734 | Customer 1 | 2013-01-01 00:00:00 | 2013-07-01 00:00:00 | Scubapro Nova 230
 | 2 | 2736 | Customer 2 | 2013-02-01 00:00:00 |  | Faber 7ltr 300
 | 3 | 2737 | Customer 3 | 2013-02-01 00:00:00 | 2013-04-01 00:00:00 | Scubapro Jet sport
 | 4 | 2738 | Customer 4 | 2013-02-01 00:00:00 | 2013-03-01 00:00:00 | Suunto Vyper & Battery kit
 | 5 | 2739 | Customer 5 | 02//01/13 | 2013-03-01 00:00:00 | Waterproof 5/7
 | 6 | 2740 | Customer 6 | 2013-02-01 00:00:00 | 2013-03-01 00:00:00 | AQ gift voucher
 | 7 | 2743 | Customer 7 | 2013-03-01 00:00:00 | 2013-04-01 00:00:00 | Scubapro Jet sport
 | 8 | 2744 | Customer 8 | 2013-03-01 00:00:00 | 2013-04-01 00:00:00 | Suunto D4i
Spreadsheet: 854861d1704617720-extract-middle-companys-names-from-text-extract-middle-companys-names-from-text_1
Sheet: Sheet1

 | Company's | Results Must be with formula
 | [PHONE] ბარამბო და კომპანია შპს  400052287
 | [PHONE] ბი ემ ეს შპს  202196426 | ბი ემ ეს შპს
 | [PHONE] ბიდი კომპანი შპს  205295296 | ბიდი კომპანი შპს
 | [PHONE] გარანტია ლუქსი შპს 206334439 | გარანტია ლუქსი შპს
 | [PHONE] კომპანია ორბიტა შპს 202230790 | კომპანია ორბიტა შპს
 | [PHONE] მეგაკო თრეიდი შპს 404953528 | [NAME]
 | [PHONE] [NAME] 204875108 | [NAME]
 | [PHONE] მზიური შპს 205025079 | [NAME]
 | [PHONE] სოფთ [NAME]  400013873 | სოფთ გრუპ შპს
 | [PHONE] ქართული სადისტრიბუციომარკეტინგული კომპანის შპს 202282369 | ქართული სადისტრიბუციო-მარკეტინგული კომპანის შპს
 | [PHONE] შარმ ტრეიდინგი შპს 211397004 | შარმ ტრეიდინგი შპს
 | [PHONE] შევარდენი შპს  202263255 | შევარდენი შპს
 | [PHONE] სერა შპს 205278689 | სერა შპს
 | [PHONE] დიპლომატ ჯორჯია შპს 204557121 | დიპლომატ ჯორჯია შპს
 | [PHONE] ვიჯი შპს 406024127 | ვიჯი შპს
Spreadsheet: 600094d1543461222-enter-data-based-on-2-different-cells-2-columns-different-sheets-grading-excel-form
Sheet: T4 Adv Post

First name | Surname | ID number | Institution | Department | Email address | Course total
[NAME] ([NAME]) | [NAME] |  |  |  | [EMAIL] | 76
Qiran ([NAME]) | [NAME] |  |  |  | [EMAIL] | 45
Muxin | [NAME] |  |  |  | [EMAIL] | -
[NAME] ([NAME]) | [NAME] |  |  |  | [EMAIL] | -
Yiming ([NAME]) | [NAME] |  |  |  | [EMAIL] | -
[NAME] ([NAME]) | Fang |  |  |  | [EMAIL] | -
Qianyun (Fay) | Fang |  |  |  | [EMAIL] | 89
Yichao | Fu |  |  |  | [EMAIL] | 76
Junjie (Riol) | He |  |  |  | [EMAIL] | -
Jiaqing (Agnes) | Kang |  |  |  | [EMAIL] | 83
Yuetong (Isabel) | [NAME] |  |  |  | [EMAIL] | 73
[NAME]) | [NAME] |  |  |  | [NAME] | -
[NAME] (Klader) | [NAME] |  |  |  | [EMAIL] | -
Ruimin (Vic) | [NAME] |  |  |  | [EMAIL] | -
[NAME]) | [NAME] |  |  |  | [EMAIL] | -
[NAME]Seven ） | Qi |  |  |  | [EMAIL] | -
Junqi (Voang) | [NAME] |  |  |  | [EMAIL] | -
[NAME]） | Xiao |  |  |  | [EMAIL] | -
[NAME] (Leo) | [NAME] |  |  |  | [EMAIL] | -
Chenyi (Freddie) | Zhang |  |  |  | [EMAIL] | 78
Linfeng (Wayne) | Zhang |  |  |  | [EMAIL] | -
[NAME] (Vlad) | [NAME] |  |  |  | [EMAIL] | -
Xinwei (Will) | [NAME] |  |  |  | [EMAIL] | -
Hui ([NAME]) | Zhu |  |  |  | [EMAIL] | -
Spreadsheet: 722159d1615067633-how-to-get-a-percentage-of-multiple-samples-in-different-sized-groups-example-problem_1
Sheet: Sheet1

Groups | BL |  | isotopeLabel | compound |  | Groups | BL
 | 4332.102601 |  | C12 PARENT | 1-Methyladenosine |  | %C12
 | 247.6190562 |  | C13-label-1 | 1-Methyladenosine |  | %C13-1
 | 282.3730929 |  | C13-label-1 | 2-Aminoadipate |  | %C13-2
 | 86606.42235 |  | C12 PARENT | 2-Dehydro-D-gluconate |  | %C12
 | 5594.673016 |  | C13-label-1 | 2-Dehydro-D-gluconate |  | %C13-1
 | 374.1293339 |  | C13-label-2 | 2-Dehydro-D-gluconate |  | %C13-2
 | 736.8170807 |  | C13-label-3 | 2-Dehydro-D-gluconate |  | %C13-3
 | 286.0335553 |  | C13-label-4 | 2-Dehydro-D-gluconate |  | %C13-4
 | 650.6829134 |  | C13-label-5 | 2-Dehydro-D-gluconate |  | %C13-5
 | 7480.363114 |  | C13-label-6 | 2-Dehydro-D-gluconate |  | %C13-6
 | 101338.6897 |  | C12 PARENT | 2-Hydroxy-2-methylsuccinate |  | %C12
 | 4671.571551 |  | C13-label-1 | 2-Hydroxy-2-methylsuccinate |  | %C13-1
 | 365.3277504 |  | C13-label-2 | 2-Hydroxy-2-methylsuccinate |  | %C13-2
 | 271.3250412 |  | C13-label-3 | 2-Hydroxy-2-methylsuccinate |  | %C13-3
 | 101342.9589 |  | C12 PARENT | 2-hydroxyglutaric acid |  | %C12
 | 4678.652203 |  | C13-label-1 | 2-hydroxyglutaric acid |  | %C13-1
 | 365.3277504 |  | C13-label-2 | 2-hydroxyglutaric acid |  | %C13-2
 | 271.3250412 |  | C13-label-3 | 2-hydroxyglutaric acid |  | %C13-3
 | 50318.35344 |  | C12 PARENT | 3-Phosphoglycerate |  | %C12
 | 1489.110475 |  | C13-label-1 | 3-Phosphoglycerate |  | %C13-1
 | For example, I am taking J2, and then dividing it by Sum(J2:J4). I am trying to figure out a formula that will know to only do it for each group. The new group starts at the green highlight.
Spreadsheet: d86ca124-70fd-43d9-acb4-70e4d0179d55
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
5228 | 21956 | [NAME] | [NAME] | RSA | 41 | 00:11:01 | [NAME] | 00:34:12 | 00:00:59 | 00:21:24 | 1 | 01:08:29
5228 | 16036 | [NAME] | [NAME] | ZIM | 42 | 00:12:36 | 00:00:49 | 00:36:27 | 00:00:52 | 00:24:01 | 2 | 01:14:45
5228 | 34723 | Carmen | Cresswell | RSA | 0 | 00:14:57 | 00:01:13 | 00:40:50 | 00:03:43 | 00:31:43 | 3 | 01:32:27
Spreadsheet: 770768d1646244688-how-to-add-a-previous-value-and-current-value-entered-in-the-same-cell-inventory-tracker
Sheet: Inventory List

 | INVENTORY LIST
 | TOTAL INVENTORY VALUE: | INVENTORY ITEMS: |  | INVENTORY PICK LIST | BIN LOOKUP
 | SKU | ITEMS | [NAME] | TONS | [NAME] | UNIT | QTY | PICK QTY | CHECK OUT | [NAME] | CHECK IN | Final QTY | REORDER QTY | COST | INVENTORY VALUE | REORDER | Last Order Date
 | xxxxxxx | xxx |  | x |  |  | 11 | 3 |  | 4 |  |  | 0 | 7
 | xxxxxxx | xxx |  | x |  |  | 16 | 2 |  | 5 |  |  | 20 | 5
Spreadsheet: 25901928-ca61-45c6-a1bf-387b463ea0cc
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
 | Number of people in household…
 | 0 | ...aged 0-5 yrs |  |  | [NAME] |  | [NAME]
 | 2 | ...aged 6-13 yrs |  | [NAME] | A |  | B
 | 2 | ...aged 14-64 yrs |  | Fuel (electric, gas, or propane) | electric |  | gas
 | 0 | ...aged 65- yrs |  | Tank size | 40 | gallons | 40 | gallons
 | 4 | Total household members |  | Power vented? | False |  | True
 |  |  |  | Recovery efficiency (GAMA) | 1 | % | 0.76 | %
 | Other home characteristics (TRUE or FALSE) |  |  | Energy Factor (GAMA) | 0.92 |  | 0.62
 | True | Clothes washer present in home? |  | Input rating (GAMA) | 4.5 | kWh | 40 | MBTUh
 | 0 | Is clothes washer Energy Star? |  | Demand control credit? | False |  | False
 | 0 | Dishwasher present in home?
 |  | Is dishwasher [NAME]?
 | 0 | Adult at home during day? |  | Results
 | True | Residents pay hot water energy bill? |  | Daily hot water use | 50.80309999999999 | gallons/day | 50.80309999999999 | gallons/day
 | 0 | Multifamily residence with only seniors? |  | Annual fuel use | 3834.454526124786 | kWh | 198.7321514234101 | therms
 | Fuel Prices |  |  | Annual operating cost | 306.7563620899829 |  | 143.0871490248553
 | 70 | Natural Gas (cents/therm) |  | Life-cycle operating cost* | 3542.913976836911 |  | 1703.260020849807
 | 8 | Electricity (cents/kWh)
 | True | Propane ($/gallon) |  | Difference (A minus B) in …
 | 2.5 | Demand control credit (electric) ($/month) |  | ...annual operating cost | 163.6692130651277
 |  |  |  | …life-cycle operating cost* | 1839.653955987105
 | Temperatures (°F)
 | 130 | Water heater thermostat setpoint |  | *discounted to the present
 | 55 | Cold water inlet temperature
 | 60 | Air temperature around water heater |  | Based on Lawrence Berkeley National Laboratory |  |  | Key
 | 45 | Average annual outdoor air temperature |  | analytical model.  See: |  |  | Input cells
 |  |  |  | http://homeenergysaver.lbl.gov/hes/aboutwhm.html |  |  | Results cells
 | Life-cycle Parameters
 | 0.03 | Discount rate |  | Spreadsheet developed by [NAME], Energy Center of Wisconsin,
 | 15 | Life of water heater (years) |  | December, 2003.  (Page down for additional information.)
 | Intermediate calculations
 | 5.438 | hot water use by standard dishwasher |  | Fuel code | 2 |  | True
 | 14.2226 | hot water use by standard clothes washer |  | Tank UA | 3.560566760171863 |  | 7.986562456012738
 |  |  |  | Annual operating hours | 852.1010058055081 |  | 496.8303785585252
 |  |  |  | Annual power vent electricity @ 100 watts | False |  | 49.68303785585252
 |  |  |  | Annual base operating cost | 306.7563620899829 |  | 139.1125059963871
 |  |  |  | Annual electricity for power vent | False |  | 3.974643028468201
 |  |  |  | Annual demand control credit | False |  | False
Spreadsheet: 135801d1326237223-if-function-with-multiple-criteria-bonus0110
Sheet: Sheet1

 | Percent | Bonus
 | 0 | 100 | >>>>>>> | from 0% to 33% $100
 | 0.34 | 150 | >>>>>>> | from 34% to 39% $150
 | 0.4 | 200 | >>>>>>> | from 40% to 49% $200
 | 0.5 | 250 | >>>>>>> | from 50% to 100% $200
Percentage | Bonus Earned
0.6
Spreadsheet: 112332d1308490758-average-of-each-25-of-column-example
Sheet: Blad1

 |  | 1 |  | First 25% | 2ND 25% | 3RD 25% | Last 25%
 |  | 6 |  |  |  |  | ????
 |  | 8
 |  | 9
 |  | 78
 |  | 12
 |  | 55
 |  | 2
 |  | 7
 |  | 17
 |  | 18
 |  | 22
 |  | 26
 |  | 27
 |  | 29
 |  | 26
 |  | 38
 |  | 14
 |  | 11
 |  | 2
Spreadsheet: 821813d1678905439-copying-only-certain-items-to-separate-sheet-based-on-if-formula-new-master
Sheet: Attractions

Time | Party Name | Party Room | Host | Items | Quanity | Attraction Time
09:01:00 | Test Party | 3 | [NAME] | Go Karts | 100 | 11:00:00
09:01:00 | Test Party | 3 | [NAME] | Laser Tag | 10 | 11:15:00 |  | Use the lists on [NAME] to filter.
09:01:00 | Test Party | 3 | [NAME] | Roller Coaster | 10 | 11:30:00
11:30:00 | Alexis 9th bday | 3 | Alaina | [NAME] | 10 | 12:45:00
11:30:00 | Alexis 9th bday | 3 | Alaina | Inflatapark | 10 | 13:15:00
11:30:00 | Alexis 9th bday | 3 | Alaina | Laser Tag | 10 | 14:00:00
11:30:00 | Cecilia 8th Bday | 1 | Tristian | Laser Tag | 14 | 12:45:00
11:30:00 | Cecilia 8th Bday | 1 | Tristian | Inflatapark | 14 | 13:15:00
13:00:00 | [NAME] | 1 | Tristian | Laser Tag | 10 | 14:15:00
13:00:00 | [NAME] | 1 | Tristian | Bumper Cars | 10 | 14:45:00
13:00:00 | Laila 10th bday | 3 | Alaina | Go Karts | 10 | 14:15:00
13:30:00 | Ilyas Bday | 6 | Michelle | Go Karts | 10 | 14:45:00
13:30:00 | Ilyas Bday | 6 | Michelle | Laser Tag | 10 | 15:15:00
13:30:00 | Ilyas Bday | 6 | Michelle | [NAME] | 10 | 15:30:00
13:30:00 | Archies 3rd Bday | 4 | Pranya | No Set Attractions |  | 13:30:00
14:30:00 | Ebube 10th Birthday | 2 | Ilaya/Pranya | Go Karts | 12 | 15:45:00
14:30:00 | Ebube 10th Birthday | 2 | Ilaya/Pranya | Go Karts | 13 | 16:00:00
14:30:00 | Ebube 10th Birthday | 2 | Ilaya/Pranya | Roller Coaster | 12 | 16:15:00
14:30:00 | Ebube 10th Birthday | 2 | Ilaya/Pranya | Roller Coaster | 13 | 16:30:00
14:30:00 | Ebube 10th Birthday | 2 | Ilaya/Pranya | Laser Tag | 25 | 16:45:00
14:30:00 | Eli 7th Bday | 1 | Tristian | Laser Tag | 10 | 15:45:00
14:30:00 | Eli 7th Bday | 1 | Tristian | Inflatapark | 10 | 16:15:00
15:00:00 | Milanni 10th Bday | 4 | [NAME] | Go Karts | 10 | 16:15:00
15:00:00 | Milanni 10th Bday | 4 | [NAME] | Laser Tag | 10 | 16:30:00
15:00:00 | Selicity 16th Bday | 5 | Brooke | No Set Attractions |  | 15:00:00
16:00:00 | WNY Boys Soccer Team | 2 | Ilaya/Pranya | No Set Attractions |  | 16:00:00
16:00:00 | Constances bday | 1 | [NAME] | Go Karts | 10 | 17:00:00
16:00:00 | Constances bday | 1 | [NAME] | [NAME] | 10 | 17:30:00
16:00:00 | Antwain 10th bday | 3 | Tre | Laser Tag | 10 | 17:00:00
16:00:00 | Antwain 10th bday | 3 | Tre | Go Karts | 10 | 17:30:00
16:00:00 | Antwain 10th bday | 3 | Tre | [NAME] | 10 | 18:00:00
16:30:00 | Charan 9th bday | 6 | Michelle | Go Karts | 10 | 17:45:00
16:30:00 | Miah 14th Bday | 5 | Brooke | Roller Coaster | 10 | 17:45:00
16:30:00 | Miah 14th Bday | 5 | Brooke | Drop Tower | 10 | 18:15:00
17:30:00 | [NAME] | 1 | [NAME] | Go Karts | 10 | 18:30:00
17:30:00 | [NAME] | 1 | [NAME] | Laser Tag | 10 | 19:00:00
17:30:00 | Katies 11th bday | 3 | Tre | Laser Tag | 10 | 18:30:00
17:30:00 | Katies 11th bday | 3 | Tre | Go Karts | 10 | 19:00:00
18:00:00 | KJ 8th Bday | 4 | [NAME] | Laser Tag | 10 | 19:15:00
18:00:00 | KJ 8th Bday | 4 | [NAME] | Go Karts | 10 | 19:45:00
18:00:00 | KJ 8th Bday | 4 | the | Roller Coaster | 10 | 20:00:00
Spreadsheet: 829131d1683948635-help-with-daily-schedule-with-auto-days-off-example-tennfox-
Sheet: Tuesday

 | Primary | Trainee |  |  |  |  | Off
211
212
213
214
314
315
316
Spreadsheet: errol_mclaughlin_jr__10841__Gas stub period testing sample
Sheet: Sheet1

Deal Number
VG7039.1
VE4647.1
VF8079.1
VN0269.1
VQ2686.1
VS3468.1
VS3551.1
VY6145.1
Y32917.1
Y37195.1
Y51726.1
Sitara_Deal_Id
827308
862053
865594
887103
888501
911074
920032
1015257
1048646
1066288
Spreadsheet: b584c2d9-ee7d-4c54-99e1-d60e8c2f02cf
Sheet: Sheet1

Key Performance Indicators
The data in this spreadsheet shows overall results for KPIs 1-6 and organised sport from the Active People Survey for APS 4 (October 2009 - October 2010)
compared with [NAME] (October 2008-October 2009) and [NAME] (October 2007-October 2008).
KPI 1 Participation is defined as taking part on at least 3 days a week in moderate intensity sport and active recreation (at least 12 days in the last 4 weeks) for at least 30 minutes continuously in any one session. Participation includes recreational walking and cycling. Note: This is different to both the "One MIllion" sports participation and NI8 indicators.
KPI 2 Volunteering is defined as ‘Volunteering to support sport for at least one hour a week’.
KPI 3 Club membership is defined as ‘being a member of a club particularly so that you can participate in sport or recreational activity in the last 4 weeks’.
KPI 4 Receiving tuition is defined as ‘having received tuition from an instructor or coach to improve your performance in any sport or recreational activity in the last 12 months’.
KPI 5 Organised Competition is defined as ‘having taken part in any organised competition in any sport or recreational activity in the last 12 months’.
KPI 6 Satisfaction is the percentage of adults who are very or fairly satisfied with sports provision in their local area.
Organised sport is defined as the percentage of adults who have done at least one of the following: received tuition in the last 12 months,
taken part in organised competition in the last 12 months, or been a member of a club to play sport.
Indication of statistically significant change between two results
Please note that this spreadsheet highlights whether changes from Active People Survey 2 to the latest rolling 12 month period are statistically significant.
A statistically significant change is indicated by 'increase' or 'decrease' and this means that we are 95% certain that there has been a real change (increase or decrease).
Where there has been no statistically significant change this is indicated by ‘No change’.
For more information on measuring statistically significant change within [NAME], see the briefing note on Sport England’s website:
http://www.sportengland.org/research/active_people_survey/active_people_survey_2/idoc.ashx?docid=c2da16fe-f44b-4715-a798-5cd4f62fc422&version=3
The 'Base' refers to the sample size, i.e. the number of respondents
Where estimates are available, ONS population data (mid 2007 estimates for APS 2 data, mid 2008 estimates for APS 3 data, and mid 2009 estimates for APS 4 data)
has been used to provide population numbers, denoted by (n).
Spreadsheet: chris_germany__1924__Tallahasse Swing Cash Flow
Sheet: Est Cash Flow

Projected prepayments for next 60 Days for City of Tallahassee.
Date | Volume | Price [NAME] | Price | Total |  | Prepayments | Balance
2002-02-08 00:00:00 |  |  |  |  |  | 9500
2002-02-09 00:00:00 | 2000 | FGT Z3 GD + .05 | 2.2 |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 30800
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 17000
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
 |  | FGT Z3 GD + .05 |  |  |  | 0
Spreadsheet: 57784d1258001654-apply-names-model-example
Sheet: PROJECTED $ AND FTE (CALC)

Projected $ and FTE - Data Entry in Yellow - Projection Calcs in Blue
 | Projected Requirement $'000 | Projected Budget $'000 | [NAME] $'000
Total Lodgement Driven Revenue
Total Trial Driven Revenue
Fixed Revenue | 1
Total Revenue
Total Judicial Remuneration
Total Salaries
Total Staff Driven Expenses
Total Trial Driven Expenses
Total Indirect Expenses | 1
Total Corporate Expenses | 1
Total Expenses
Total Net Result
 | Projected Requirement AFTE | Projected Budget AFTE | [NAME]
Judiciary
Direct Staff
Client Services Officers
Registry Clerks
Total Direct Staff
Indirect Staff
Deputy [NAME], [NAME] | 1
Senior Client Services Officer | 1
Supervisor Registry Services | 1
Total Indirect Staff
Total Staff
Spreadsheet: louise_kitchen__22511__StaffNoAdd
Sheet: Sheet1

 | Alternative A:
 | Tech Services Staffing:  2001 vs. 2002
 |  | 2001 |  |  |  | 2002
 | 106262 | 107081 | 107459 |  | 106262 | 107081 | 107459 | Comments
1 |  | Virgo |  |  |  | Virgo
2 |  | [NAME] |  |  |  | [NAME]
3 |  | Golden |  |  |  | Golden
4 |  | [NAME] |  |  |  | [NAME]
5 |  | [NAME] |  |  |  | [NAME]
6 |  | [NAME] |  |  |  | [NAME]
7 |  | [NAME] |  |  |  | [NAME]
8 |  | Rose |  |  |  | Rose
9 |  | D.Williams |  |  |  | D.Williams
10 |  | S. Morris |  |  |  | S. Morris
11 | Mays |  |  |  | Mays
12 | [NAME] |  |  |  | [NAME]
13 | Gray |  |  |  | Gray
14 | Hammond |  |  |  | Hammond
15 | Mullen |  |  |  | Mullen
16 | Soderquist |  |  |  | Soderquist
17 | [NAME] |  |  |  | [NAME]
18 | [NAME] |  |  |  | [NAME]
19 | Deas |  |  |  | Deas
20 | Rimbau |  |  |  |  | Rimbau |  | Moved from 106262 to 107081 at Mid Year
21 | Gorden |  |  |  |  | Gorden |  | Moved from 106262 to 107081 at Mid Year
22 | [NAME] |  |  |  | Kras. Replmt. |  |  | [NAME], Aboudaher Starts 9/15/01
23 |  |  | [NAME] |  |  |  | [NAME] | RC 17459 Supports [NAME]
24 |  |  | Wilson |  |  |  | Wilson
25
26
Total | 12 | 10 | 2 |  | 10 | 12 | 2
Group Total |  |  | 24 |  |  |  | 24
 | Houston
 | Portland