tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 351ecf85-2262-4684-b45a-6efb34ac6262
Sheet: Sheet1

Table S1   List of analyzed samples and allocated  index sequences in theRAD-seq analysis using PacI.
ID of plants | Sex type | Index*
OHB61-5 | gynoecious | ACGCAG
OHB95-1A | monoecious | TAGGTA
F2F-3 | gynoecious | ACGCAG
F2F-9 | gynoecious | TAGGTA
F2F-15 | gynoecious | CGGATG
F2F-18 | gynoecious | CAAACA
F2F-25 | gynoecious | CATACT
F2F-26 | gynoecious | CACACC
F2F-27 | gynoecious | CAGACG
F2F-31 | gynoecious | TAGAGA
F2F-37 | gynoecious | CTTAGT
F2F-38 | gynoecious | CTCAGC
F2F-41 | gynoecious | CTGAGG
F2F-46 | gynoecious | GCATCG
F2F-55 | gynoecious | GTGTAT
F2F-63 | gynoecious | GTCTAC
F2F-69 | gynoecious | GTATAG
F2F-73 | gynoecious | GCGTCT
F2F-81 | gynoecious | [NAME]
F2F-85 | gynoecious | GGCTTC
F2F-91 | gynoecious | TTACTA
F2F-93 | gynoecious | TGACGA
F2F-99 | gynoecious | ATAGAG
F2F-107 | gynoecious | AGTGTA
F2F-109 | gynoecious | TCTGCG
F2F-119 | gynoecious | ATCCGC
F2M-1 | monoecious | ACGCAG
F2M-12 | monoecious | TAGGTA
F2M-24 | monoecious | CGGATG
F2M-28 | monoecious | CAAACA
F2M-30 | monoecious | CATACT
[NAME] | monoecious | CACACC
F2M-56 | monoecious | CAGACG
F2M-61 | monoecious | TAGAGA
F2M-65 | monoecious | CTTAGT
F2M-68 | monoecious | CTCAGC
F2M-74 | monoecious | CTGAGG
F2M-75 | monoecious | GCATCG
F2M-77 | monoecious | GTGTAT
F2M-90 | monoecious | GTCTAC
F2M-92 | monoecious | GTATAG
F2M-103 | monoecious | GCGTCT
F2M-108 | monoecious | [NAME]
F2M-123 | monoecious | GGCTTC
F2M-129 | monoecious | TTACTA
F2M-132 | monoecious | TGACGA
F2M-136 | monoecious | ATAGAG
F2M-146 | monoecious | AGTGTA
F2M-150 | monoecious | TCTGCG
F2M-154 | monoecious | ATCCGC
* RAD-tags from parental lines (OHB61-5 and OHB95-1A), gynoecious F2 and monoecious F2 were applied to respective lanes in a flowcell in the Illumina sequencer.
Spreadsheet: 83511d1283467402-formula-across-2-worksheets-results-in-0-in-blank-cells-book1
Sheet: Sheet1

Priority: | Job #: | Job name: | Supervisor: | Technician:
HIGH | 1234 | ABC & Co | [NAME] | [NAME]
Comments:
Priority: | Job #: | Job name: | Supervisor: | Technician:
LOW | 1235 | Smiths | [NAME] | [NAME]
Comments:
Priority: | Job #: | Job name: | Supervisor: | Technician:
MEDIUM | 1236 | Seven Inc | [NAME] | [NAME]
Comments:
Priority: | Job #: | Job name: | Supervisor: | Technician:
Comments:
Spreadsheet: 487063d1477902921-how-to-create-a-table-to-show-age-by-day-forum_range
Sheet: USER_Table

Username | AGENT ID | Name | Department | Manager
amann | 11111001 | [NAME] | Front Office | Helly Hansen
ddavies | 11111002 | [NAME] | Back Office | [NAME]
mowen | 11111003 | [NAME] | Front Office | Helly Hansen
mikeaj | 11111004 | AJ [NAME] | Complaints | [NAME]
michaele | 11111005 | [NAME] | Sales | [NAME]
pateld | 11111006 | [NAME] | SME | [NAME]
uchihas | 11111007 | [NAME] | Sales | [NAME]
[NAME] | 11111008 | Naruto Uzumaki | SME | [NAME]
[NAME] | 11111009 | [NAME] | Front Office | Helly Hansen
kcarney | 11111010 | [NAME] | Back Office | [NAME]
ckent | 11111011 | [NAME] | Sales | [NAME]
bwayne | 11111012 | [NAME] | Complaints | [NAME]
bbanner | 11111013 | [NAME] | Complaints | [NAME]
pparker | 11111014 | [NAME] | SME | [NAME]
[NAME] | 11111015 | [NAME] | Back Office | [NAME]
Spreadsheet: 839179d1691732601-need-help-to-make-formula-based-vba-help-for-make-a-report-from-none-indexed-data-report-joh555-
Sheet: DATA2

Date | Invoice No | Item | Qty.
2023-04-15 00:00:00 | 36 | 36W FITTINGS | 8
2023-04-15 00:00:00 | 36 | ADORE LED 3W DEEP SPOT 3K | 10
2023-04-01 00:00:00 | 1 | ADORE LED 3W DEEP SPOT 6K | 11
2023-04-01 00:00:00 | 1 | ASTRAL SPOT LIGHT 2W 3000K | 4
2023-04-05 00:00:00 | 7 | CENTURA PLUS LED FLOOD LIGHT 30W 6K IP65 | 3
2023-04-20 00:00:00 | 45 | COMET SURFACE PANEL 6W 6K RD | 8
2023-04-20 00:00:00 | 45 | CRYSTA COB SWIVEL SPOTLIGHT 3W 6500K | 4
2023-04-18 00:00:00 | 40 | ELEC BALLAST EL STAR SLIM-36W | 6
2023-04-18 00:00:00 | 40 | E-LITELED CURVE 20W 6K | 8
2023-04-21 00:00:00 | 48 | FAN  VENTIL AIR DX 250MM HAVELLS | 3
2023-05-15 00:00:00 | 57 | FAZER LED PANEL 18W 6K ROUND | 2
2023-05-15 00:00:00 | 57 | INNOVA NEO LED SPOT LIGHT 6W 6K RD | 11
2023-05-15 00:00:00 | 57 | KETTLE TRAVEL LITE 0.5L MAROON 1000W | 2
2023-05-01 00:00:00 | 50 | 36W FITTINGS | 10
2023-05-01 00:00:00 | 50 | ADORE LED 3W DEEP SPOT 3K | 11
2023-05-01 00:00:00 | 50 | ADORE LED 3W DEEP SPOT 6K | 3
2023-05-10 00:00:00 | 54 | LED ADORE 0.5W LAMP GREEN | 25
2023-05-10 00:00:00 | 54 | ASTRAL SPOT LIGHT 2W 3000K | 20
2023-05-14 00:00:00 | 56 | CENTURA PLUS LED FLOOD LIGHT 30W 6K IP65 | 10
2023-05-14 00:00:00 | 56 | COMET SURFACE PANEL 6W 6K RD | 9
Spreadsheet: tracy_geaccone__40390__EMNNG02PL
Sheet: Fuel-Depr-OtherTax

PRINT: PRINT
 |  | JAN | FEB | MAR | APR | MAY | JUN | JUL | AUG | SEP | OCT | NOV | DEC
 |  |  |  |  | 0
FUEL EXPENSE
Fuel / UAF - Fuel
- Other Fuel
- UAF
- Other UAF
Hyperion Entry / Reversal |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
TOTAL FUEL EXPENSE
DEPRECIATION & AMORTIZATION
Depreciation - Plant
- Lucent Phone System (1/99 - 12/08)
- Rate Case Impact
- Misc. Depreciation
Amortization - Plant
- TBPL Monetization Goodwill (FVA $21,764 over 63 Yrs.)
- IMP (Straight Line Impact, [NAME] in [NAME]. Amort.)
- Pipe Recoating | Link D.T.
- Black Marlin Fair Value Amortization
- Other
Hyperion Entry / Reversal |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
TOTAL DEPRECIATION & AMORTIZATION
TAXES OTHER THAN INCOME
Ad Valorem - NNG Accrual
- Black Marlin Ad Valorem Taxes
- Other | No Link | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
- Other | No Link | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Payroll Taxes (FICA / FUTA / SUTA / Medical)
Commercial
Market Services
Operations
Finance, Accounting and Administration
Other (Variable Pay Only) | No Link | 0 |  |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
FI/CO Reconciliation Adjustment
Information Technology
Legal
HR / Communications
Executive
Miscellaneous - Franchise Taxes
- Other
Hyperion Entry / Reversal |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
TOTAL TAXES OTHER THAN INCOME
Total Payroll Taxes
PAYROLL TAX PERCENTAGE USED IN PLAN |  | 0.1 | 0.1 | 0.085 | 0.085 | 0.08 | 0.08 | 0.08 | 0.08 | 0.077 | 0.077 | 0.077 | 0.077
Spreadsheet: 219367d1362738789-1st-time-pass-rate-percentage-pass-rate-first-time
Sheet: Sheet1

date/ name |  | first time pass rate | pass rate
01/04/12 Mark | fail | 0.4193548387096774 | 0.6666666666666666
12/04/12 [NAME] | pass
4/4/2012 lewis | pass 1st
4/4/2012 dec | pass 1st
01/06/2012 [NAME] | fail
7/06/2012 [NAME] | fail
20/06/2012 alex | pass
25/06/2012 charlotte | pass 1st
7/07/2012 elle mae | pass 1st
30/07/201 lewis | pass 1st
6/8/2012 [NAME] | pass 1st
12/8/2012 [NAME] | pass 1st
13/08/2012 azhar | pass 1st
24/08/20121 claire | pass 1st
leanne | fail
23/09/2012 leanne | pass
8/10/2012 muntahinah | pass 1st
charlotte | fail
25/10/2012 charlotte | pass
1/11/2012 sian | pass 1st
[NAME] berniece | pass
sadiqa | fail
sadiqa | fail
sadiqa | fail
sadiqa | pass
16/01/2013 nat | pass 1st
jess 1/03/2013 | pass 1st
luke | fail
luke | fail
luke | pass
Spreadsheet: 485081d1476696524-countifs-or-index-match-trying-to-count-how-many-times-it-happen-in-a-date-before
Sheet: Sheet1

 | Results | Date Conducted |  | Date | Number of Times Conducted | Passed | Failed
 | Passed | 2016-10-10 00:00:00 |  | 2016-10-10 00:00:00
 | Failed | 2016-10-10 00:00:00 |  | 2016-10-12 00:00:00
 | Passed | 2016-10-10 00:00:00 |  | 2016-10-13 00:00:00
 | Failed | 2016-10-10 00:00:00 |  | 2016-10-15 00:00:00
 | Passed | 2016-10-12 00:00:00
 | Failed | 2016-10-12 00:00:00
 | Failed | 2016-10-12 00:00:00
 | Passed | 2016-10-13 00:00:00
 | Passed | 2016-10-15 00:00:00
 | Passed | 2016-10-12 00:00:00
 | Failed | 2016-10-15 00:00:00
 | Passed | 2016-10-20 00:00:00
 | Passed | 2016-10-20 00:00:00
Spreadsheet: 857686d1706633013-need-help-with-kpi-reports-commerce-return-and-cancelled-orders-17012024-i_scarface-
Sheet: Legend

 | STATUS | RESPONSIBLE DEPT. | REASON CATEGORY
 | Pending | Sales | Merchandise Not Available
 | Cancelled | Merchandiser | Delivery Time Out
 | Re-Schedule | Logistics | Receiving Time Out
 | Returned | Planning | LPO Expired
 |  | Data Entry | Double Order
 |  |  | [NAME]
 |  |  | Rejected due to Short [NAME]
 |  |  | Road Closure
 |  |  | Rejected by Customer
 |  |  | Delivery Date Updated After Delivery
 |  |  | Wrong Customer Code
 |  |  | No Space at Outlet
 |  |  | Wrong LPO
 |  |  | Inventory at Customer Outlet
Spreadsheet: 134415d1325271305-find-max-of-an-item-same-units-of-measure-only-dave
Sheet: Sheet1

 | [NAME] |  | [NAME] |  | [NAME] |  | [NAME] |  | [NAME] |  | Nick
fish | 0.14 | LB | 0.55 | LB | 2.16 | CS | 0.09 | GAL | 0.18 | LB | 0.33 | LB
poultry | 0.16 | LB | 0.14 | LB | 2.16 | CS | 0.08 | LB | 0.14 | LB | 0.33 | LB
pork | 0.14 | LB | 0.05 | LB | 2.16 | CS | 0.08 | LB | 0.08 | GAL | 0.33 | LB
chips | 3.5 | CS | 0.34 | LB | 2.16 | CS | 0.17 | LB | 0.14 | LB | 0.33 | LB
burger | 0.18 | LB | 0.16 | LB | 2.16 | CS | 0.07 | LB | 0.09 | LB | 0.32 | GAL
I need a formula to compare category (column a) using dave's units (column c) as reference point and find a higher price than what dave is offering based on the same units
for example: who offers a more costlier fish than dave's at the same unit of measure
Spreadsheet: 830703d1685037359-return-a-value-from-the-chart-sample-work-book
Sheet: Seating Assignments

GUESTS | ID | Assigned | Table # |  |  | TABLE 1 - Numerical ID
NEEDS NAME | 1 |  |  |  |  | Table 1 | Table 2 | Table 3 | Table 4 | Table 5 | Table 6 | Table 7 | Table 8 | Table 9 | Table 10 | Table 11 | Table 12 | Table 13 | Table 14 | Table 15
[NAME] | 2 |  |  |  | 1 | 2
[NAME] | 3 |  |  | G | 2 | 3
[NAME] | 4 |  |  | N | 3 | 4
Greg | 5 |  |  | I | 4 | 5
Imogen | 6 |  |  | T | 5 | 6
Charlene | 7 |  |  | A | 6 | 7
[NAME] | 8 |  |  | E | 7 | 8
[NAME] | 9 |  |  | S | 8 | 9
Anna | 10
[NAME] | 11
George | 12 |  |  |  |  | Table 2 - Name THIS TABLE POPULATES AUTOMATICALLY
[NAME] | 34 |  |  |  |  | Table 1 | Table 2 | Table 3 | Table 4 | Table 5 | Table 6 | Table 7 | Table 8 | Table 9 | Table 10 | Table 11 | Table 12 | Table 13 | Table 14 | Table 15
[NAME] | 35 |  |  |  | 1
[NAME] | 36 |  |  | G | 2
[NAME] | 37 |  |  | N | 3
Danielle | 38 |  |  | I | 4
Emilie | 39 |  |  | T | 5
[NAME] | 40 |  |  | A | 6
[NAME] | 41 |  |  | E | 7
[NAME] | 42 |  |  | S | 8
Ian | 43
Erin | 44
[NAME] | 45
[NAME] | 46
Becky | 47
[NAME] | 48
Brittany | 49
Nathalie | 50
Amanda | 51
[NAME] | 52
[NAME] | 53
Heather | 54
[NAME] | 55
Mark | 56
[NAME] | 57
Meagan | 58
[NAME] | 59
Raj | 60
Garth | 61
Rose | 62
Kayla | 63
[NAME] | 64
[NAME] | 65
Spreadsheet: 497101d1484343649-running-total-for-15-accounts-managed-on-one-spreadsheet-ndnlawco
Sheet: Sheet1

Withdrawer | Amount |  | REMAINING:
[NAME] | 250 |  | [NAME]
suzy | 345 |  | suzy
[NAME] | 50 |  | bill
bill | 65 |  | [NAME]
[NAME] | 300
suzy | 225
[NAME] | 80
Spreadsheet: 877012d1723711852-please-help-with-if-formula-example
Sheet: Sheet1

Item number | Quantity | Unit price | Price unit | Currency | Exchange rate | Converted currency
A | 500 | 26.52 | 1 | GBP | 1
AB | 2000 | 5.39 | 1 | USD | 1.2791
ABC | 5400 | 0.533 | 1 | EUR | 0.85458
Spreadsheet: 770492d1646120941-need-help-solving-this-sumif-scenario-copy-of-sample-data
Sheet: SAMPLE (2)

 |  |  | ColumnName | NBM | MBMS | NBIS | DPIS
 |  |  | 0005 | 15 | 0 | 17 | 10 |  | LEGEND | VALUE
 |  |  | 0006 | 5 | 30 | 20 | 15 |  | COMP | 1
Helper Tables | >>>>>>>>>>>>> |  | 0007 | 8 | 0 | 0 | 0 |  | PEND | 0.5
 |  |  | 0010 | 10 | 0 | 0 | 0 |  | OUT | 0
 |  |  | 0015 | 5 | 0 | 0 | 8 |  | BLANK | 0
 |  |  | 0017 | 4 | 0 | 5 | 4
 |  |  | 0020 | 6 | 0 | 0 | 0
 |  |  | 0025 | 0 | 20 | 0 | 0
 |  |  | 0030 | 10 | 0 | 0 | 0
 |  |  | 0032 | 5 | 0 | 10 | 12
 |  |  | 0035 | 0 | 0 | 0 | 15
 |  |  | 0040 | 6 | 0 | 0 | 0
 |  |  | 0050 | 8 | 0 | 10 | 3
 |  |  | 0053 | 4 | 0 | 6 | 6
 |  |  | 0060 | 0 | 0 | 0 | 16
 |  |  | 0070 | 5 | 0 | 7 | 6
 |  |  | 0081 | 2 | 0 | 0 | 0
 |  |  | 0082 | 2 | 0 | 0 | 0
 |  |  | 0135 | 3 | 30 | 15 | 5
 |  |  | 0200 | 0 | 18 | 5 | 0
 |  |  | 0990 | 2 | 2 | 5 | 0
 |  |  | Total Percentage
 | The table below consist of ALL the columnName, but not all Type will utilize every columnName. The helper table for those [NAME] are listed below with the value. The ColumnName, although same, will have different value based on Type. Assuming all ColumnName are followed and COMP, they should equate to 100%
 | TABLE |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | What I want to achieve
 | Type | Code# | 0005 | 0006 | 0007 | 0010 | 0015 | 0017 | 0020 | 0030 | 0032 | 0040 | 0050 | 0053 | 0070 | 0081 | 0082 | 0135 | 0990 | 0035 | 0060 | 0025 | 0200 | Total %
 | NBM | a | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP | COMP |  |  |  |  | 100
 | NBM | b | OUT | PEND | COMP | PEND | COMP | OUT | OUT | OUT | PEND | PEND | OUT | COMP | COMP | COMP | OUT | OUT |  |  |  |  |  | 37
 | MBMS | c |  | COMP |  |  |  |  |  |  |  |  |  |  |  |  |  | COMP | COMP |  |  | COMP | COMP | 100
 | MBMS | d |  | OUT |  |  |  |  |  |  |  |  |  |  |  |  |  | PEND | COMP |  |  | OUT | PEND | 26
 | NBIS | e | COMP | COMP |  |  |  | COMP |  |  | COMP |  | COMP | COMP | COMP |  |  | COMP | COMP |  |  |  | COMP | 100
 | NBIS | f | PEND | PEND |  |  |  | OUT |  |  | OUT |  | COMP | COMP | OUT |  |  | PEND | PEND |  |  |  | COMP | 49.5
 | DPIS | g | COMP | COMP |  |  | COMP | COMP |  |  | COMP |  | COMP | COMP | COMP |  |  | COMP |  | COMP | COMP |  |  | 100
 | DPIS | h | PEND | OUT |  |  | PEND | COMP |  |  | OUT |  | PEND | COMP | COMP |  |  | OUT |  | PEND | PEND |  |  | 47
 | OTHER | i
Spreadsheet: 168937d1342633884-multiple-search-and-sumif-mock-up-v2-
Sheet: calc

 | PERSON | PLACE | COLOUR |  | 2012
 |  |  |  |  | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10
 | JACK | AUSTRALIA | RED |  | 1000 | 3000 | 4000 | 8000 | 9000 | 11000 |  |  |  | 22000
 | PETER | USA | BLUE |  |  | 3000 | 4000 | 8000 | 9000 | 11000 |  |  |  | 22001
 | [NAME] | UK | RED
 | SIMON | UK | BLUE
 | [NAME] | AFRICA | YELLOW
Spreadsheet: 122014d1316551995-indirect-erep_1gb-tigrovi_bkp
Sheet: Ivica Kavasaki

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This action restores as much health as possible by eating Food from your Storage.
You can recover up to: 450 / 450 Health
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[NAME]
offlineIvica Kavasaki
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Experience level 29
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Location: CroatiaCroatia, Central Croatia Citizenship: CroatiaCroatia
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National rank: 509
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Spreadsheet: ce514c1e-88c1-4a56-9e68-1ab73933dff8
Sheet: Sheet1

2008-11-04 00:00:00 | State Senate - District No. 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
 | Gallus, r | McLeod, d | [NAME]
Albany | 171 | 207 | 3
Atkinson and [NAME]. Gt. | -- | -- | --
[NAME] | 816 | 769 | 2
Bean's Grant | -- | -- | --
Bean's Purchase | -- | -- | --
[NAME] | 517 | 458 | 1
[NAME] | 581 | 452
[NAME] 3 | 705 | 590
[NAME] 4 | 460 | 465
Bethlehem | 540 | 759
Cambridge | 1 | 1
Carroll | 233 | 222
[NAME]'s Purchase | -- | -- | --
[NAME] | 101 | 43
Colebrook | 574 | 376 | 1
Columbia | 197 | 116
Crawford's Purchase | -- | -- | --
Cutt's Grant | -- | -- | --
[NAME] | 289 | 191
Dix's Grant | -- | -- | --
Dixville | 7 | 12
Dummer | 106 | 67
Errol | 113 | 69
Erving's Location | -- | -- | --
Franconia | 332 | 399 | 2
[NAME] | 709 | 770 | 1
Green's Grant | -- | 1 | --
Hadley's Purchase | -- |  | --
Hale's Location | 97 | 23
Hart's Location | 15 | 13
[NAME] | 269 | 328 | 1
[NAME] | 343 | 234
Kilkenny | -- | -- | --
Lancaster | 913 | 682
Lincoln | 384 | 342 | 2
Lisbon | 397 | 336
Littleton | 1465 | 1218
Livermore | -- | -- | --
Low and Burbank's Grant | -- | -- | --
[NAME] | 166 | 120
Martin's Location | -- | -- | --
Milan | 385 | 333 | 1
[NAME] | 11 | 4
Northumberland | 495 | 474
[NAME] | -- | -- | --
[NAME]'s Grant | -- | 4 | --
Pittsburg | 350 | 153
Randolph | 99 | 135
Sargent's Purchase | -- | -- | --
Second College Grant | -- | -- | --
Shelburne | 153 | 116
[NAME] | 169 | 117
Stewartstown | 222 | 133
[NAME] | 166 | 122
Success | -- | -- | --
[NAME] | 189 | 203
Thompson & Meserve's Purchase | -- | -- | --
Waterville Valley | 84 | 104
Wentworth's Location | 13 | 10
[NAME] | 558 | 491 | 1
Totals | 13395 | 11662 | 15
Spreadsheet: 1dc2a02c-e7fe-4b70-b813-28f0db6aae63
Sheet: Additional pages

Patient # | Last Name | First Name | Age | Sex | Resident/Staff | Room #/ Work Area | Date of Onset | Date Resolved | Days of Duration | Elevated Temperature | Highest Temperature | Chills | Cough | Shortness of breath | [NAME] | Hemoptysis | Nasal congestion | Pneumonia | Abnormal Chest X-Ray  (Y, N, ND) | Hospitalized | Days Hospitalized | Treated with Antivirals  (If Yes, please list agent) | Received antiviral prophylaxis | Vaccinated against influenza > 14 days prior to outbreak illness | Vaccinated against Streptococcus pneumoniae > 14 days prior to outbreak illness | Specimen Collection Date | [NAME] | Specimen Collection Type (Naso, Orophr, Throat, [NAME], Other) | Lab Results ( Fax results to Health Dept) | Other? (Describe)
Spreadsheet: 132569d1323817032-average-most-recent-7-scores-average-last-7-scores
Sheet: Avg

Agent | Last 7 Score Avg
Askew
Best
[NAME]
Coley-Alston
[NAME]
Corprew
Crummy
Dale
[NAME]
Diggs
[NAME]
[NAME]
Grant
[NAME]
Jones
Joy
Kearney
King
McCray
[NAME]
Mitchell
Montgomery
Moore
Pope
[NAME]
Rymer
Seawell
Shoultes
Simmons-Russ
Simmons-Russ Shateela
Smith
Tillis
Watkins
West
[NAME]
Wilson
[NAME]
Spreadsheet: b153e3ae-113b-4912-ab39-33f870eaec79
Sheet: Sheet1

Bevölkerung des Freistaates Sachsen nach ausgewählten Altersgruppen | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Elbe-Röder-Dreieck - Variante 2
Alter von ... bis                     unter ... Jahren | 2011 | 2015 | 2020 | 2025
1 000
unter 20 | 3479 | 3600 | 3419 | 3005
20 - 65 | 16451 | 14879 | 13006 | 11294
65 und mehr | 6682 | 6705 | 7138 | 7566
Insgesamt | 26612 | 25184 | 23563 | 21865
%
unter 20 | 13.07304975199158 | 14.29479034307497 | 14.51003692229343 | 13.74342556597302
20 - 65 | 61.81797685254772 | 59.0811626429479 | 55.19670670118406 | 51.65332723530756
65 und mehr | 25.10897339546069 | 26.62404701397713 | 30.29325637652251 | 34.60324719871942
Insgesamt | 100 | 100 | 100 | 100
Abhängigkeitsquotient
Jugendquotient | 21.1476505987478 | 24.19517440688218 | 26.28786713824389 | 26.60704799008323
Altenquotient | 40.61759163576683 | 45.06351233281806 | 54.88236198677533 | 66.99132282627944
Gesamtquotient | 61.76524223451462 | 69.25868673970025 | 81.17022912501922 | 93.59837081636267
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: 0e3b0ef5-3962-42ed-87d0-1940decf2017
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
261294 | 41634 | [NAME] | Stockwell | USA | 3051 | 00:12:28 | 00:02:45 | 00:46:22 | 00:02:08 | [NAME] | 1 | 01:35:38
261294 | 60940 | [NAME] | [NAME] | USA | 3052 | 00:17:44 | 00:04:48 | 00:48:33 | 00:02:20 | 00:30:14 | 2 | 01:43:37
261294 | 32629 | [NAME] | Reinertsen | USA | 3053 | 00:16:11 | 00:03:11 | 00:46:49 | 00:02:08 | 00:41:05 | 3 | 01:49:21
Spreadsheet: 866372d1713300077-looking-for-a-way-to-get-sum-of-data-kansas-scheduler-v4-5-
Sheet: Kitting Schedule

[NAME] from date below↓ | ↓Minimum # of Kits↓ | DO NOT EDIT IN THIS REPORT
2024-04-04 00:00:00 | 25
Client | Job # | # of Stores | # of Pieces | Ship Date | Notes
 | 246061 | 120 | 120 | 2024-04-10 00:00:00 | 0
HALL 246063 [10] | 246063 | 50 | 50 | 2024-04-10 00:00:00 | 0
P&S 246437 [10] | 246437 | ? | 5650 | 2024-04-10 00:00:00 | 0