tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 34634178-85f9-406a-a696-d419205d4317
Sheet: Trail Benefit Analysis

 | Trail Use Based on a 1.5 mile residential draw potential
 |  | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11
 |  | Population | Percentage of Adults | Total Adult Popoulation | Total Number of Commuters | Number of existing bicycle commuters | Number of new bicycle commuters | Number of existing pedestrain commuters | Total Daily adult cyclists | New daily adult cyclists | Annual Health Benefit | Annual Recreation/ commuter Benefit
 | Population within 400 meters | 3022 | 87.4
 | Population within 401- 800 meters | 4334 | 87.4
 | Population between 801-1600 meters | 6658 | 87.4
 | Population between 1601-2400 meters | 2450 | 87.4 |  |  |  | 0 |  |  | 0
 | Totals
 | 1. Population is from 2010 census overlayed within the City's GIS mapping System to provide population within 1.5 miles of the project site
 | 2. Percentage of adults in the population is from the 2010 census data.
 | 3. Total Adult population within 1.5miles of the project site
 | 4. Number of Commuters estimated at 50% of adults from National averages provided by NCHRP Report 552 page 38
 | 5. Number of existing Bicycle Communters is 5% of the total number of commuters within a 1.5 miles radius of the trail. 5% bicycle commute share is from the 2000 census data - City of Arcata
 | 6. Per the NCHRP Report 552, pg 39, the number of new bicycle commuters are estimated to be 1.93, 1.11 and 0.39 times the current values for residents at 400, 800 and 1600 meters respectively.
 | 7. Number of existing pedestrian commuters is calculated as 17% of the total commute population based on commute share from 2000 census data
 | 8. Total daily adult cyclists is calculated at the moderate rate of (.4 +1.2 x the commute share of 5% x the total adult population)as outlined in the NCHRP Report 552 page 38
 | 9. New daily adult cyclists is calculated to be 1.93, 1.11 and 0.39 times the current values for residents living within 400m, 800m and 1600m respecitively. NCHRP Report 552, pg. 39
 | 10. Annual Health Benefit is calculated as the number of new bicyclists x $128 (the median value per capita costs savings from physical activty of 10 studies per NCHRP Report 552 Appendix E)
 | 11. Annual Recreational/Commuter Benefit is the number of new cyclists (both recreational and commuter) x $10 per day of value x 365 days for recreational use and 260 days for commuter use.
Spreadsheet: 160365d1339067114-excel-2007-text-boxes-and-pictures-will-not-print-tried-lots-of-things-to-no-avail-copy-of-recipe-sheet-v5
Sheet: Warehouse Sheet

 | W  A  R  E  H  O  U  S  E      C  O  P  Y      O  N  L  Y
 | MATERIALS SHEET |  |  |  |  |  |  | Leaving the Warehouse on | Date
 |  |  |  |  |  |  |  | Going by
 |  |  |  |  |  |  |  | Issued | By | Date
 | Job No |  |  |  |  | Customer
 | Area |  |  |  |  | Site Details
 | Coverage/m²
 | Depth |  |  |  |  | Type of Job
 | Mix Code
 | AGGREGATE PER BATCH
 | Size | Type |  | Supplier |  | Kg in mix | [NAME] | No of Bags per mix | Total Tonnage | Total No. of [NAME]
 | SPRINKLE |  |  |  |  |  |  | LID COLOUR
 |  |  |  |  |  |  |  | IMPORTANT NOTES
 |  |  | Total No of Batches |  | Total [NAME]
 |  |  | I
 |  |  | P
 |  |  | Total |  |  |  |  | [NAME] | [NAME] in Bags | Seperate Tubs
 |  |  | Additive
 |  |  | Total
 |  |  | [NAME]
 | Job No
 | Mix Code
 | Total No. Of Batches
 |  | BATCHING RECORD |  |  |  |  |  | BATCHING RECORD
 | Batch No. |  |  |  |  |  |  | Batch No.
 | No of Batches |  |  |  |  |  |  | No of Batches
 | Date |  |  |  |  |  |  | Date
 | Batched By |  |  |  |  |  |  | Batched By
 |  |  | I | P |  |  |  |  | I | P
 | Wt per Batch |  | g | g |  |  |  | Wt per Batch | g | g
 | [NAME] |  | 2  /  5  /  10  ltr | 2  /  5  /  10  ltr |  |  |  | [NAME] | 2  /  5  /  10  ltr | 2  /  5  /  10  ltr
 | Drum No |  |  |  |  |  |  | Drum No
 | Were both I & P in same tub? |  |  | Yes  /  No |  |  |  | Were both I & P in same tub? |  | Yes  /  No
 | Catalyst added? |  | Yes  (        ml)  /  No |  |  |  |  | Catalyst added? | Yes  (        ml)  /  No
 |  | BATCHING RECORD |  |  |  |  |  | BATCHING RECORD
 | Batch No. |  |  |  |  |  |  | Batch No.
 | No of Batches |  |  |  |  |  |  | No of Batches
 | Date |  |  |  |  |  |  | Date
 | Batched By |  |  |  |  |  |  | Batched By
 |  |  | I | P |  |  |  |  | I | P
 | Wt per Batch |  | g | g |  |  |  | Wt per Batch | g | g
 | [NAME] |  | 2  /  5  /  10  ltr | 2  /  5  /  10  ltr |  |  |  | [NAME] | 2  /  5  /  10  ltr | 2  /  5  /  10  ltr
 | Drum No |  |  |  |  |  |  | Drum No
 | Were both I & P in same tub? |  |  | Yes  /  No |  |  |  | Were both I & P in same tub? |  | Yes  /  No
 | Catalyst added? |  | Yes  (        ml)  /  No |  |  |  |  | Catalyst added? | Yes  (        ml)  /  No
Spreadsheet: 70163d1270854462-is-it-possible-to-have-excel-do-an-automated-break-schedule-for-work-newbreakschedule
Sheet: Breaker2

 |  | Breaker:
 |  | Shift : | 11:00:00 | 21:00:00
Name of Breakee | Type | Break Start |  | Break finsihed | Floor
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Spreadsheet: 482613d1475150850-lookup-function-with-unusual-condition-copy-of-schachdatenbank-tullock-1
Sheet: 0-1 flip

 | W1 | 100 | P (white win)
 | [NAME] | 100 | P (black win)
 | q | 0.5514124293785311 | P (draw)
 | lambda | 1.5 | Pw+Pd
 | D1 | 50
 | D2 | 50
 | x1 (Nash)
 | x2 (Nash)
 | Key
 | expected payoff of P1 |  |  | expected payoff of P2
 | value win for P1 |  |  | value win for P2 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | P1 | P2
 | x* of P1 |  |  | x* of P2
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 5 | 6
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | exp. Payoff
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | value win | - | -
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | P1 is white
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | exp. Payoff
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | value win
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | x*
 |  |  |  |  |  |  |  |  |  |  |  | P1 is black
 |  |  |  |  |  |  |  |  |  |  |  | exp. Payoff
 |  |  |  |  |  |  |  |  |  |  |  | value win
 |  |  |  |  |  |  |  |  |  |  |  | x*
 |  |  |  | P1 is white
 |  |  |  | exp. Payoff
 |  |  |  | value win
 |  |  |  | x*
 | P1 is black
 | exp. Payoff
 | value win
 | x*
Spreadsheet: 668967d1585147956-calculating-coverage-in-months-example
Sheet: Zagreb Info

Zagreb SKU | Product Cote | Description | Market | Package Size | Technology | IB | INN | Mos | Inventory | 03.2020 | 04.2020 | 05.2020 | 06.2020 | 07.2020 | 08.2020 | 09.2020 | 10.2020 | 11.2020 | 12.2020
1 | 1 | X | X | 5 |  |  |  | 3.05339 | 2631 | 1466 | 630 | 472 | 1180 | 540 | 1370 | 839 | 1246 | 1345 | 1032
2 | 2 | X | X | 5 |  |  |  | 10 | 21450 | 1282 | 651 | 15 | 2526 | 866 | 2038 | 2780 | 3201 | 2625 | 1575
3 | 3 | X | X | 5 |  |  |  | 1.427 | 1800 | 1372 | 1000 | 750 | 1409 | 1091 | 2622 | 3231 | 4173 | 3728 | 3150
Spreadsheet: 885188d1734617001-tracker-to-be-populated-the-data-based-on-frequency-count-frequency-tracker
Sheet: Sheet1

 |  | Frequency | Frequency Count | Start Month | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
 |  | HY | 6 | Apr
 |  | HY | 6 | Jan
 |  | Q | 3 | JUN
 |  | M | 1 | Jan
 |  | Y | 12 | Jan
 |  | Expected Result
 |  | Frequency | Frequency Count | Start Month | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
 |  | HY | 6 | Apr
 |  | HY | 6 | Jan
 |  | Q | 3 | Jun
 |  | M | 1 | Jan
 |  | Y | 12 | Jan
Spreadsheet: 133319d1324331890-comparing-two-worksheets-tigeravatar-example-for-bertulfio
Sheet: Sheet3

Address | [NAME] | Organization
Address 01 |  | Organization 01
Address 02 | [NAME] 02
Address 03 |  | Organization 03
Address 04 |  | Organization 04
Address 05 | [NAME] 05
Address 06 | [NAME] 06 | Organization 06
Address 07 |  | Organization 07
Address 08 | [NAME] 08
Address 09 | [NAME] 09
Address 10 | [NAME] 10
Address 11 | [NAME] 11
Address 12 | [NAME] 12 | Organization 12
Address 13 |  | Organization 13
Address 14 | [NAME] 14 | Organization 14
Address 15 | [NAME] 15
Address 16 | [NAME] 16 | Organization 16
Address 17 | [NAME] 17 | Organization 17
Address 18 | [NAME] 18
Address 19 | [NAME] 19
Address 20 | [NAME] 20
Spreadsheet: tracy_geaccone__40573__EA Alloc to Other BUs - Support
Sheet: PR

Public Relations
Analysis of I/C Billings
 |  | 2001 Forecast |  |  |  |  |  | 2002 Plan
 |  | $ |  | % |  | HC |  | $ |  | % |  | HC
Total Direct Expense |  | 2235120 |  | 1 |  | 10 |  | 2368744 |  |  |  | 10
Allocation to other business units
EGM |  | 302800 |  |  |  |  |  | 473749
EIM |  | 302800 |  |  |  |  |  | 473749
ENW |  | 100933 |  |  |  |  |  | 473749
EBS |  | 0 |  | 0 |  |  |  | 118437
EEOS |  | 0 |  |  |  |  |  | 118437
Total
Net to ENA
Note
2002 Plan Direct Expense and allocations to business units include Bonus Accrual.
Spreadsheet: 789863d1659418068-can-i-auto-populate-a-field-based-on-a-date-when-the-if-function-doesnt-recognize-dates-payments-aligw
Sheet: Sheet1

Payments | Amt | Due Date | Pd | Late Fee
Month 1 |  | 2022-08-01 00:00:00 | False
Month 2 |  |  | False
Month 3 |  |  | False
Month 4 |  |  | False
Spreadsheet: 117847d1313159475-how-to-randomize-text-without-a-list-or-column-row-test
Sheet: Sheet1

[NAME] | 1
D | 2
[NAME] | 3
[NAME] | 104
r | 205
A | 306
[NAME] | 1407
[NAME] | 2508
[NAME] | 3609
[NAME] | 10000
Spreadsheet: 291422d1390291516-filling-down-formulas-simple-example
Sheet: Raw data

Name | Hours worked | Hourly rate
[NAME] | 27 | 20
[NAME] | 22 | 20
[NAME] | 19 | 20
[NAME] | 18 | 20
[NAME] | 30 | 20
Terrance | 29 | 20
[NAME] | 19 | 25
[NAME] | 27 | 25
[NAME] | 26 | 25
Philomena | 18 | 25
[NAME] | 20 | 25
[NAME] | 30 | 25
[NAME] | 24 | 25
[NAME] | 29 | 25
Christine | 15 | 25
Charlotte | 21 | 29
[NAME] | 28 | 29
[NAME] | 25 | 29
Martin | 18 | 29
[NAME] | 21 | 29
Spreadsheet: c8be0302-a9fc-45cb-b044-53a2de2073eb
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | RUN | T1 | BIKE | T2 | SKI | POSITION | TOTAL TIME
8768 | 46146 | Stefania | Valsecchi | ITA | 123 | 00:21:22 | [NAME] | 00:30:09 | 00:01:20 | 00:21:04 | 1 | 01:14:51
8768 | 55935 | Nataliya | Sila-Novitskaya | RUS | 126 | [NAME] | 00:00:28 | 00:34:10 | 00:01:12 | 00:21:08 | 2 | 01:17:38
8768 | 69394 | [NAME] | Degiovanni | ITA | 122 | 00:19:47 | 00:00:41 | 00:35:29 | 00:01:54 | 00:21:21 | 3 | 01:19:14
8768 | 55726 | [NAME] | Sala | ITA | 125 | 00:21:42 | 00:00:31 | 00:39:46 | 00:01:35 | 00:19:23 | 4 | [NAME]
8768 | 25349 | Cristina | Beretta | ITA | 124 | 00:24:12 | 00:00:40 | 00:45:40 | 00:02:29 | 00:30:54 | 5 | 01:43:58
Spreadsheet: 108063d1305158260-formula-for-finding-a-less-than-max-stdev-day92
Sheet: Sheet1

 | My formula |  |  | Without the 2's included
8 |  |  |  | 8
8.22 |  |  |  | 8.22
14.23 |  |  |  | 14.23
2 |  |  |  | 8.02
2 |  |  |  | 11.23
8.02 |  |  |  | 22.72
11.23 |  |  |  | 12.24
22.72 |  |  |  | 11.67
12.24 |  |  |  | 8.98
11.67 |  |  |  | 9.25
2 |  |  |  | 13.23
8.98 |  |  |  | 28.6
9.25 |  |  |  | 12.65
2 |  |  |  | 10.23
13.23 |  |  |  | 9.5
28.6 |  |  |  | 9.63
2 |  |  |  | 14.55
12.65 |  |  |  | 8.36
10.23
2
9.5
9.63
14.55
2
2
8.36
Spreadsheet: michelle_lokay__26654__SOCAL_PERMIAN
Sheet: Summary

 | EffDt | 2001-06-15 00:00:00 |  |  |  | SOCAL - PERMIAN SPREAD OPTION VALUE
 | INPUTS
 | Socal | Permian | Strike | Ann.IntRt | Vol.A | Vol.B | Correlation | ExpDt | OptType |  | Spread | Option Price
 |  |  | 0 | 0.06 |  |  | 0.5 | 2001-10-01 00:00:00 | 1
 |  |  |  |  |  |  |  | 2002-01-01 00:00:00
 |  |  |  |  |  |  |  | 2002-04-01 00:00:00
 |  |  |  |  |  |  |  | 2002-06-01 00:00:00
Spreadsheet: ac9e9b73-c9d8-42fc-abc0-e81695f6dc3f
Sheet: Sheet1

Campus | Last Name | First Name | [NAME] | Phone Number | Fax Number | Street | Street2 | City | State | Zip
Appalachian State University | Everts | [NAME] | [EMAIL] | [PHONE] | [PHONE] | Academy Drive |  | Boone | NC | 28608
East Carolina University | Ballard | Dr. [NAME] | [EMAIL] | [PHONE] |  | East Fifth Street |  | Greenville | NC | 27858
Elizabeth City State University | Becton | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 1704 Weeksville Road |  | Elizabeth City | NC | 27909
Fayetteville State University | [NAME] | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 1200 Murchison Road |  | Fayetteville | NC | 28301
NC Agricultural and Technical State University | Martin | Harold | [EMAIL] | [PHONE] | [PHONE] | 1601 East Market Street |  | Greensboro | NC | 27411
North Carolina Central University | Saunders-White | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 1801 Fayetteville Street |  | [NAME] | NC | 27707
NC State University | Woodson | [NAME] | [EMAIL] | [PHONE] | [PHONE] |  |  | Raleigh | NC | 27695
UNC Asheville | Orr | Doug | [EMAIL] | [PHONE] | [PHONE] | 1 University Heights |  | Asheville | NC | 28804
UNC-Chapel Hill | Folt | Carol | [EMAIL] | [PHONE] | [PHONE] |  |  | Chapel Hill | NC | 27599
UNC Charlotte | Dubois | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 9201 University City Boulevard |  | Charlotte | NC | 28223
UNC Greensboro | [NAME] | [NAME] | [EMAIL] | [PHONE] | [PHONE] | Post Office Box 26170 |  | Greensboro | NC | 27402
UNC Pembroke | [NAME] | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 1 University Drive |  | Pembroke | NC | 28372
[NAME] | [NAME] | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 601 South College Road |  | [NAME] | NC | 28403
UNC School of the Arts | Bierman | M. | [EMAIL] | [PHONE] | [PHONE] | 1533 South Main St. |  | Winston-Salem | NC | 27127
Western Carolina University | Belcher | [NAME] | [EMAIL] | [PHONE] | [PHONE] |  |  | Cullowhee | NC | 28723
Winston-Salem State University | Reaves | [NAME] | [EMAIL] | [PHONE] | [PHONE] | 601 [NAME], Jr. Drive |  | Winston-Salem | NC | 27110
North Carolina School of Science and Mathematics | [NAME] | J. | [EMAIL] | [PHONE] | [PHONE] | 1219 Broad Street |  | [NAME] | NC | 27705
Spreadsheet: 30538d1226056051-multiple-if-statements-insurance-bonus-calculator
Sheet: Sheet1

 |  | Insurance Bonus Calculator Example
 |  | Conversion Targets | Applications | Insurance Sales | Conversion Achieved | Bonus
 |  | 0.35 | 6 | 4 | 0.6666666666666666 | 40
 |  | 0.35 | 13 | 6 | 0.4615384615384616 | 0
 |  | 0.35 | 11 | 7 | 0.6363636363636364 | 70
 |  | Conversion Bands | Payment for each target
 |  | 35% - 44.9% | 3
 |  | 45% - 54.9% | 7
 |  | 55%+ | 10
Spreadsheet: 107781d1304941243-top-10-formula-book3
Sheet: Sheet1

Client | Division | Territory | Revenue
J Smith | Energy | Europe | 20000
T Jones | Energy | Japan | 40000
 | Energy Total |  | 60000
J Smith | Marine | Japan | 50000
T Jones | Marine | USA | 150000
 | Marine Total |  | 200000
B [NAME] | Mining | Europe | 50000
J Smith | Mining | USA | 10000
 | Mining Total |  | 60000
 | Grand Total |  | 320000
Spreadsheet: 758092d1638639254-return-value-based-on-more-or-less-than-0-sample-workbook_12042021
Sheet: Expected Output

Company | Account | AU | Sub Acct | CAAS | Currency | Amount |  |  | Company | Account | AU | Sub Acct | CAAS | Currency | Amount
00000 | 4033531 | 0011483 | 0000000 | [PHONE]-0011483-0000000 | USD | -100 |  |  | 00000 | 4033531 | 0011483 | 0000000 | [PHONE]-0011483-0000000 | USD | -100
00000 | 4033531 | 0011483 | 0000000 | [PHONE]-0011483-0000000 | USD | -1000 |  |  | 02047 | 4033531 | 0211742 | 0000000 | [PHONE]-0211742-0000000 | USD | -1000
00323 | 4033531 | 0042255 | 0000000 | [PHONE]-0042255-0000000 | USD | -1500 |  |  | 00323 | 4033531 | 0042255 | 0000000 | [PHONE]-0042255-0000000 | USD | -1500
00894 | 4033531 | 0027238 | 0000000 | [PHONE]-0027238-0000000 | USD | -800 |  |  | 00894 | 4033531 | 0027238 | 0000000 | [PHONE]-0027238-0000000 | USD | -800
00894 | 4033531 | 0218848 | 0000000 | [PHONE]-0218848-0000000 | USD | 500 |  |  | 00894 | 4033531 | 0218848 | 0000000 | [PHONE]-0218848-0000000 | USD | 500
00000 | 4033531 | 0103852 | 0000000 | [PHONE]-0103852-0000000 | USD | -1200 |  |  | 00000 | 4033531 | 0103852 | 0000000 | [PHONE]-0103852-0000000 | USD | -1200
00000 | 4033531 | 0103852 | 0000000 | [PHONE]-0103852-0000000 | USD | -1300 |  |  | 00000 | 4033531 | 0228023 | 0000000 | [PHONE]-0228023-0000000 | USD | -1300
00000 | 4033531 | 0233107 | 0000000 | [PHONE]-0233107-0000000 | USD | -900 |  |  | 00000 | 4033531 | 0233107 | 0000000 | [PHONE]-0233107-0000000 | USD | -900
00014 | 4033531 | 0053571 | 0000000 | [PHONE]-0053571-0000000 | USD | 780 |  |  | 00014 | 4033531 | 0053571 | 0000000 | [PHONE]-0053571-0000000 | USD | 780
02047 | 4032509 | 0211742 | 0000000 | [PHONE]-0211742-0000000 | USD | 845 |  |  | 02047 | 4032509 | 0211742 | 0000000 | [PHONE]-0211742-0000000 | USD | 845
00323 | 4032509 | 0211742 | 0000000 | [PHONE]-0211742-0000000 | USD | 652 |  |  | 00323 | 4032509 | 0042255 | 0000000 | [PHONE]-0042255-0000000 | USD | 652
Spreadsheet: richard_shapiro__32169__beckyandmelinda
Sheet: Assumptions

+Input!C3
2000 Plan Assumptions
D/C | DIRECT EXPENSES |  | Assumptions | Questions | Answers
 |  |  | Included 2 interns for June-Aug and headcount of 41, added Global Liquids salary only
052 |  |  | Based on estimated year-end; added add'l $7k for additional headcount expected
058
062 |  |  | Based on estimated year-end
175 |  |  | Based upon 26 phones @$120 and 29 pagers @ $35
061 |  |  | Based on estimated year-end, $65kUS, 25k London, $3k based on additions; US based on estimated year-end
056
051 |  |  | Flowers and meals
064
067 |  |  |  | Are you going to interview? | 4-6 people
 |  |  |  | Are you expecting any?
065 |  |  |  | Expecting any relocations? | 2 relocations
201 |  |  | Per Geroge McClellan
206 |  |  | Snelling Personnel Services, Charleston office
 |  |  | Pertains to Global Liquids
157 |  |  | Based on estimated year-end
352
165
160
351 |  |  | [NAME] for [NAME] ($1,200/month) and NYSE ($25/month) | Are others going to have Bloomberg connections?
153
161 |  |  | Based on estimated year-end
 |  |  | London office, $70/month, US $2,000/month, Australia, $50
697 |  |  | Based on estimated year-end | Are you expecting any large ad campaigns? | No
063 |  |  | Based on estimated year-end
657 |  |  | Based on estimated year-end
 |  |  | Based on $2,287 for Pittsburgh and $2,642 for Charleston office, additional $850 for repairs, $1,500 for office in Germany | How much is the rent for the Germany office? | $1500/month
252 |  |  | Quarterly fax rental
174/601/603/604 |  |  | Includes Bell Atlantic and Lucent charges, hardware/software purchase for new hires
845
810
 |  |  | Depreciation of technology expenses related to Charleston office
Spreadsheet: 71c22288-6f69-4113-adc3-f7d6cc59bce5
Sheet: Sheet1

athletes_idAthletes | Rk | Nation | Date of Birth | ID Number | Last Name | First Name | Total Pts | Fenc | Swim | Ride | Comb | Swim time
37925 | 1 | HUN | 22/04/86 | W037925 | GYENESEI | [NAME] | 5388 | 860 | 1248 | 1100 | 2180 | 2:09.42
2210 | 2 | CZE | 01/01/89 | W002210 | DIANOVA | [NAME] | 5368 | 860 | 1172 | 1180 | 2156 | 2:15.99
779 | 3 | CZE | 06/04/83 | W000779 | CERNA | Sylvie | 5364 | 1000 | 1056 | 1200 | 2108 | 2:25.44
38047 | 4 | GBR | 20/05/90 | W038047 | PRENTICE | Freyja | 5344 | 776 | 1064 | 1180 | 2324 | 2:24.71
1575 | 5 | GBR | 03/03/83 | W001575 | FELL | Heather | 5336 | 832 | 1128 | 1160 | 2216 | 2:19.44
1643 | 6 | GBR | 10/01/84 | W001643 | LIVINGSTON | [NAME] | 5324 | 832 | 1172 | 1140 | 2180 | 2:15.98
2853 | 7 | GER | 28/11/90 | W002853 | KOHLMANN | [NAME] | 5308 | 1000 | 1048 | 1180 | 2080 | 2:26.07
3945 | 8 | GER | 03/04/90 | W003945 | SCHLEU | Annika | 5296 | 944 | 1048 | 1068 | 2236 | 2:26.15
4647 | 9 | HUN | 08/09/88 | [NAME] | PATAKI | Viktoria | 5264 | 944 | 1084 | 1180 | 2056 | 2:23.17
285 | 10 | HUN | 04/05/77 | W000285 | VOROS | [NAME] | 5196 | 1000 | 1120 | 1180 | 1896 | 2:20.28
420 | 11 | CZE | 26/01/78 | [NAME] | GROLICHOVA | Lucie | 5188 | 832 | 1100 | 1120 | 2136 | 2:21.77
4637 | 12 | GBR | 25/09/89 | W004637 | MURRAY | Samantha | 5156 | 888 | 1168 | 1200 | 1900 | 2:16.10
3006 | 13 | POL | 11/10/88 | W003006 | SKARZYNSKA | Aleksandra | 5124 | 832 | 1008 | 1160 | 2124 | 2:29.40
2088 | 14 | GBR | 28/06/85 | W002088 | HELYER | [NAME] | 5124 | 748 | 1168 | 1180 | 2028 | 2:16.28
1503 | 15 | CAN | 05/02/77 | W001503 | PINETTE | [NAME] | 5064 | 944 | 904 | 1160 | 2056 | 2:38.22
1941 | 16 | CZE | 27/02/90 | W001941 | KODEDOVA | [NAME] | 5052 | 720 | 1036 | 1180 | 2116 | 2:27.14
5402 | 17 | FRA | 19/02/87 | [NAME] | DARRAS | [NAME] | 5040 | 692 | 1088 | 1200 | 2060 | 2:22.76
2204 | 18 | GBR | 27/11/88 | W002204 | GRANFIELD | Charlotte | 4952 | 916 | 1220 | 1180 | 1636 | 2:11.96
2695 | 19 | HUN | 25/07/88 | W002695 | BARTALIS | [NAME] | 4924 | 888 | 1020 | 984 | 2032 | 2:28.53
4640 | 20 | GBR | 11/02/91 | W004640 | FRENCH | [NAME] | 4920 | 748 | 1064 | 1200 | 1908 | 2:24.98
5442 | 21 | GBR | 22/11/87 | W005442 | ROSS-HARRIS | Fleur | 4876 | 580 | 1004 | 1200 | 2092 | 2:29.79
3940 | 22 | POL | 23/11/90 | W003940 | [NAME] | [NAME] | 4868 | 860 | 1200 | 540 | 2268 | 2:13.44
39428 | 23 | GBR | 10/06/83 | W039428 | HARES | [NAME] | 4780 | 720 | 1052 | 1200 | 1808 | 2:25.82
2906 | 24 | GER | 23/02/87 | W002906 | MAHROKH | Paria | 4748 | 804 | 944 | 996 | 2004 | 2:34.75
39429 | 25 | GBR | 22/07/91 | W039429 | WAIN | Rebecca | 4648 | 636 | 840 | 1200 | 1972 | 2:43.48
4158 | 26 | GBR | 06/10/88 | W004158 | JONES | Montana | 4536 | 860 | 1148 | 748 | 1780 | 2:17.78
38438 | 29 | GBR | 11/06/87 | W038438 | FERGUSON | [NAME] | 4076 | 804 | 1040 | 20 | 2212 | 2:26.69
39430 | 30 | GBR | 17/09/91 | W039430 | TROTTER | Venetia | 3908 | 568 | 924 | 1120 | 1296 | 2:36.39
735 | 31 | POL | 31/03/83 | W000735 | WOJCIK | [NAME] | 3652 | 776 | 948 | 0 | 1928 | 2:34.52
4160 | 32 | GBR | 01/06/89 | W004160 | BURKE | [NAME] | 1964 | 804 | 1160 | 0 | 0 | 2:16.89