tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 808510d1670501871-get-min-and-max-values-from-column-b-where-corresponding-column-a-matches-criteria-truck
Sheet: Sheet1

Citywise Vehicle
 | Date | 2022-04-20 00:00:00 | 2022-04-21 00:00:00 | 2022-04-22 00:00:00
Vehicle
 | City 1 | Truck 1 | Truck 4 | Truck 3
 | City 2 | Truck 2 | Truck 2 | Truck 4
 | City 3 | Truck 3 | Truck 1 | Truck 1
 | City 4 | Truck 1 | Truck 4 | Truck 1
 | City 5 | Truck 4 | Truck 2 | Truck 2
 | City 6 | Truck 3 | Truck 1 | Truck 4
[NAME]
 | City 1 | 1000 | 2130 | 1650
 | City 2 | 800 | 870 | 2320
 | City 3 | 1500 | 1240 | 1350
 | City 4 | 1100 | 2080 | 1300
 | City 5 | 2000 | 940 | 1020
 | City 6 | 1560 | 1150 | 2230
End Km
 | City 1 | 1100 | 2230 | 1750
 | City 2 | 870 | 940 | 2390
 | City 3 | 1560 | 1300 | 1410
 | City 4 | 1150 | 2130 | 1350
 | City 5 | 2080 | 1020 | 1100
 | City 6 | 1650 | 1240 | 2320
Truck Start Km |  | [NAME] must fill as below
 | Truck 1
 | Truck 2
 | Truck 3
 | Truck 4
Truck End Km
 | Truck 1
 | Truck 2
 | Truck 3
 | Truck 4
Spreadsheet: 35952d1233689359-formula-to-reset-a-count-based-on-cell-value-example-time_off_trkng
Sheet: Personal Days

PERSONAL DAYS - TIME USED
Last Name | First Name | DAY 1 | DAY 2 | DAY 3 | DAY 4 | DAY 5 | DAY 6 | DAY 7 | DAY 8 | DAY 9 | DAY 10 | DAY 11 | DAY 12 | DAY 13 | DAY 14 | DAY 15 | DAY 16 | DAY 17 | DAY 18 | DAY 19 | DAY 20 | DAY 21 | DAY 22 | DAY 23 | DAY 24 | DAY 25 | DAY 26 | DAY 27 | DAY 28 | DAY 29 | DAY 30 | DAY 31 | DAY 32
 |  | # HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS | HOURS
0 | 02
1 | 13
2 | 02
3 | 13
4 | 02
5 | 04
6 | 03
7 | 19
8 | 12
9 | 13
A | 18
B | 19
C | 05
D | 04
E | 10
F | 20
G | 10
H | 18
I | 01
J | 04
K | 10
L | 05
M | 13
N | 04
O | 19
P | 19
Q | 13
R | 03
S | 26
T | 10
U | 02
V | 04
W | 02
X | 11
Y | 02
Z | 02
Spreadsheet: 175196d1345453468-finding-data-that-match-in-two-different-sheets-or-list-example
Sheet: Subscribers

Name | Address | Phone number | MAC Address | Location | Connected Port
A | 1 | 123456 | 00 00 00 00 01
B | 2 | 123457 | 00 00 00 00 02
C | 3 | 123458 | 00 00 00 00 03
D | 4 | 123459 | 00 00 00 00 04
E | 5 | 123460 | 00 00 00 00 05
F | 6 | 123461 | 00 00 00 00 06
G | 7 | 123462 | 00 00 00 00 07
H | 8 | 123463 | 00 00 00 00 08
I | 9 | 123464 | 00 00 00 00 09
J | 10 | 123465 | 00 00 00 00 10
K | 11 | 123466 | 00 00 00 00 11
L | 12 | 123467 | 00 00 00 00 12
M | 13 | 123468 | 00 00 00 00 13
N | 14 | 123469 | 00 00 00 00 14
O | 15 | 123470 | 00 00 00 00 15
P | 16 | 123471 | 00 00 00 00 16
Q | 17 | 123472 | 00 00 00 00 17
R | 18 | 123473 | 00 00 00 00 18
S | 19 | 123474 | 00 00 00 00 19
T | 20 | 123475 | 00 00 00 00 20
U | 21 | 123476 | 00 00 00 00 21
V | 22 | 123477 | 00 00 00 00 22
W | 23 | 123478 | 00 00 00 00 23
X | 24 | 123479 | 00 00 00 00 24
Y | 25 | 123480 | 00 00 00 00 25
Z | 26 | 123481 | 00 00 00 00 26
AA | 27 | 123482 | 00 00 00 00 27
AB | 28 | 123483 | 00 00 00 00 28
AC | 29 | 123484 | 00 00 00 00 29
AD | 30 | 123485 | 00 00 00 00 30
Spreadsheet: 490236d1479756753-last-5-results-footie-example-book
Sheet: Sheet1

H/A | Status
Away | lost
Away | won |  |  |  |  |  |  |  |  |  |  |  |  | How to find last 5 results
Away | lost
Home | won |  |  |  | Example should be with formula |  |  |  | Manually input for example |  |  |  |  | i have 2 criteria s in 2 columns
Home | Won
Away | drew |  |  |  | Last 5 Home Results |  |  |  | Last 5 Home Results |  |  |  |  | in G5:G500 (Won, Lost, [NAME]) in H5:H500 (Home, Away)
Away | won |  |  |  | Home
Home | drew |  |  |  | Won | [NAME] | Lost |  | Won | [NAME] | Lost |  |  | im trying to get the last 5 results
Home | drew |  |  |  |  |  |  |  | 3 | 2 | 0
Home | won |  |  |  |  |  |  |  |  |  |  |  |  | Example Home - Won (3) [NAME] (2) Lost (0) (See Pic)
 |  |  |  |  | Last 5 Away Results |  |  |  | Last 5 Away Results |  |  |  |  | in R6 i want 3
 |  |  |  |  | Away
 |  |  |  |  | Won | [NAME] | Lost |  | Won | [NAME] | Lost |  |  | in S6 i want 2
 |  |  |  |  |  |  |  |  | 1 | 2 | 2
 |  |  |  |  |  |  |  |  |  |  |  |  |  | in T6 i want 0
 |  |  |  |  |  |  |  |  |  |  |  |  |  | is this possible?
Spreadsheet: 741586d1627162828-work-scheduling-looking-for-ideas-to-set-up-a-very-specific-constraints-in-solver-schedule-testing
Sheet: Sheet1

 | Veronica | 1
 | [NAME] | 2
 | [NAME] | 3
 | [NAME] | 4
 |  |  |  |  |  |  |  |  |  |  | For vacation or other reservation a macro could be used which will  include constraints in the solver engine based on the table on the left. Unless there's a better option. As of now vacation are not included, only preferences.
 |  | Vacation | 2021-08-01 00:00:00 | 2021-08-02 00:00:00 | 2021-08-03 00:00:00 | 2021-08-04 00:00:00 | 2021-08-05 00:00:00 | 2021-08-06 00:00:00 | 2021-08-07 00:00:00
 |  | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  |  |  |  |  |  |  |  |  |  | As of now, nobody has any preferences.
 |  | Preferences | 2021-08-01 00:00:00 | 2021-08-02 00:00:00 | 2021-08-03 00:00:00 | 2021-08-04 00:00:00 | 2021-08-05 00:00:00 | 2021-08-06 00:00:00 | 2021-08-07 00:00:00
 |  | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 1
 |  |  |  |  |  |  |  |  |  |  | The main problem is that when a person get works on a specific day, then he/she needs to rest the next day. I  struggle to program this limitation.
 |  |  | 2021-08-01 00:00:00 | 2021-08-02 00:00:00 | 2021-08-03 00:00:00 | 2021-08-04 00:00:00 | 2021-08-05 00:00:00 | 2021-08-06 00:00:00 | 2021-08-07 00:00:00 | Shifts
 |  | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0
 |  | 2 | 0 | 0 | 0 | 1 | 1 | 1 | 1
 |  | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0
 |  | 4 | 0 | 0 | 1 | 0 | 1 | 1 | 1
 |  | Min required
Spreadsheet: 148283d1333326012-vlookup-return-multiple-values-into-separate-cells-example
Sheet: Sheet1

products_id | categories_id
0 | 112
0 | 159
0 | 450
0 | 470
50 | 59
50 | 70
50 | 115
50 | 119
51 | 70
52 | 70
53 | 70
62 | 58
65 | 31
65 | 58
65 | 115
65 | 119
65 | 130
66 | 31
67 | 31
68 | 31
69 | 31
70 | 31
we need to compare column A in sheet 1 and 2 and wanting to return multiple values from column 2 on sheet 1.
sample of results we're looking for:
products_id | categories_id | categories_id | categories_id
50 | 70 | 115 | 119
Spreadsheet: 788662d1658612361-defined-names-with-sumifs-not-working-as-expected-dashboard-design-dataset-tms
Sheet: Dashboard

 |  |  |  |  |  |  |  |  |  |  |  |  |  | Department | Full Time | Contract | Half-Time | Hourly
 |  |  |  |  |  |  |  |  |  |  |  |  |  | ADC
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Training
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Environmental Compliance
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Facilities/Engineering
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Green Building
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Environmental Health/Safety
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Creative
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Human Resources
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Product Development
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Major Mfg Projects
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Manufacturing
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Manufacturing Admin
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Marketing
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Sales
 |  |  |  |  |  |  |  |  |  |  |  |  |  | IT
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Professional Training Group
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Account Management
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Quality Assurance
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Quality Control
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Research Center
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Research/Development
Spreadsheet: 707294d1607157591-formula-to-breakdown-time-into-half-hour-segments-sample
Sheet: Sheet1

What I Have
 |  |  | 09:00:00
 |  |  | 15:00:00
 | 09:00:00 | 09:30:00 | 10:00:00 | 10:30:00 | 11:00:00 | 11:30:00 | 12:00:00 | 12:30:00 | 13:00:00 | 13:30:00 | 14:00:00 | 14:30:00 | 15:00:00
What I Want
 |  |  | 09:00:00
 |  |  | 15:00:00
 | 09:00:00 | 09:30:00 | 10:00:00 | 10:30:00 | 11:00:00 | 11:30:00 | 12:00:00 | 12:30:00 | 13:00:00 | 13:30:00 | 14:00:00 | 14:30:00 | 15:00:00
 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
Spreadsheet: 28da28a8-c701-4f91-aeee-ef9d21fe7181
Sheet: Sheet1

ALL ROUND SPORT TURNIER | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Sportart | [NAME] | Ergebnis (Coolcat/Pasy) | [NAME] | [NAME]
Badminton | 2 Gewinnsätze | 6:21 / 5:21 |  | x
Schwimmen | [NAME] in gewisser Zeit oder Schneller bei 10 Bahnen
Tennis | 3 Gewinnsätze
Tischtennis | 3 Gewinnsätze
Squash | Zählart bis 11 3 Gewinnsätze
Joggen | [NAME] anzuhalten | - |  | x
Billard | 2 Gewinnspiele | 0:2 |  | x
Minigolf | [NAME] | 78:69 |  | x
Tauziehen | den anderen über [NAME] ziehen
Seilspringen | [NAME][NAME]
Bowling | 2 Gewinnspiele
Kegeln | 1 Stunde mehr Punkte. 3 Würfe | 172:155 | x
Armdrücken | Sieg mit Rechts und Links | 0:2 |  | x
Schach | 2 Gewinne
Luftspiel?? | 2 oder 3 [NAME]. Coolcat  entscheidet ob das gespielt wird.
Sprint | 100 Meter, zuerst ankomen
Fahrrad fahren | wer länger durchhält
Inliner fahren
Autorennen | wer zuerst ankommt
Frisbee
Fingerhakeln | 5 Siege á Daumen 3 Sec festhalten | 5:3 | x
Hanteln | wer länger schafft Rechts und Links???
Tauchen | wer länger Luft anhalten kann
Schießen | wer mehr trifft
Wasserball
Blobby Volley | 1 Sieg
Deutsch-Diktat | [NAME]
Englisch-Diktat | [NAME]
Summe |  |  | 2 | 5
Spreadsheet: 724882d1616430034-index-match-function-lookup-cell-is-formula-want-it-to-look-for-result-of-formula-example-for-hours-log
Sheet: 2

Ratio Coverage for |  |  | Monday
 | Residential |  |  |  |  |  |  |  |  |  | On Behalf Of Hours
 | Sched. | Actual | Deviation |  | Medical | Sick | Orientation | Review | Transport | Total OBO
R1 | 63
R2 | 41.5
R3 | 62
R4 | 40
R5 | 40
R6 | 53
R7 | 64
R8 | 34
R9 | 65
R10 | 63
R11 | 60.5
R12 | 63
R13 | 54.5
R14 | 26
R15 | 66.5
R16 | 21
R17 | 48
R18 | 62
R19 | 48.5
R20 | 39.5
R21 | 40
R22 | 63
R23 | 65
R25 | 54
R26 | 63
R27 | 48.25
R28 | 41.5
R29 | 65
R30 | 64
R31 | 49
R32 | 42
R33 | 55
Spreadsheet: 668422d1584812683-reverse-calculation-1-1-bay-reverse-calculation-6sj_test-bench_4
Sheet: Sheet1

 | Purchasing a Property |  | Values entered in yellow cells only
 | Enter Asking Price | 3100000
 | Purchase Price Offer | 3100000 |  |  |  | Notes:
 | Property Purchase Tax |  |  | Enter Negotiated Discount Required |  | - The Purchasing a Property table. Works OK
 | Total Purchase Price |  |  | 0 |  | - The Property Purchase Tax calculator places a value in C4 depending on the value in C3. Works OK
 | Legal Fees | 1200 |  |  |  | Problem:
 | Commission | 500 |  |  |  | - The Reverse Calculation table works up to $2,999,999 and gives the correct value in E15
 | Other Expenses | 1000 |  |  |  | At $3,000,000 or more, it returns an erronous value in E15
 | Total Purchase Cost |  |  |  |  | - Does the Reverse Table need an addition to make the Reverse Calculation Table work?
 | Difference |  |  |  |  | Or is it the formula in E15 that needs tweaking?
 | Reverse Calculation table: To find wanted Total Purchase Price
 |  |  | Enter Total Purchase Price required | 3170000
 |  |  |  |  |  | .
 |  |  | Negotiated Discount Required
 |  |  | Total Purchase Cost
 | Property Purchase Tax calculator (Calculation only. No entry needed)
 | Up to $2M | $2 to $3M | Over $3M
 | Price | Price | Price
 |  |  |  | Purchase price notes |  |  |  |  | <--Simplified example (Display only)
 |  |  |  | <-1% on first  $200,000
 |  |  |  | <-2% on value from $200,000 to $2,000,000
 | N/A |  |  | <-3% on value over $2,000,000
 | N/A | N/A |  | <-2% on value over $3,000,000
 |  |  |  | <-Total Property Purchase Tax
 | Reverse table. (Calculation only. No entry needed)
 | Price | TaxRate | Price+Tax
 | 0 | 0.01
 | 200000 | 0.02
 | 2000000 | 0.03
 | 3000000 | 0.02
Spreadsheet: 62947d1263931267-validation-on-entry-duplicates
Sheet: Sheet1

Date | Supplier | Value | Cheque No
2010-01-19 19:58:17 | a | 10 | 100
2010-01-19 19:58:17 | b | 10 | 101
2010-01-19 19:58:17 | c | 10 | 102
2010-01-19 19:58:17 | d | 10 | 103
2010-01-19 19:58:17 | e | 10 | 104
2010-01-19 19:58:17 | a | 10 | 102
2010-01-19 19:58:17 | b | 10 | 106
2010-01-19 19:58:17 | c | 10 | 107
2010-01-19 19:58:17 | d | 10 | 108
2010-01-19 19:58:17 | e | 10 | 104
2010-01-19 19:58:17 | a | 10 | 110
2010-01-19 19:58:17 | b | 10 | 111
2010-01-19 19:58:17 | c | 10 | 112
2010-01-19 19:58:17 | d | 10 | 113
2010-01-19 19:58:17 | e | 10 | 113
2010-01-19 19:58:17 | a | 10 | 115
2010-01-19 19:58:17 | b | 10 | 116
2010-01-19 19:58:17 | c | 10 | 117
2010-01-19 19:58:17 | d | 10 | 118
Spreadsheet: benjamin_rogers__1205__Retail Shorts version Debt-Equity 60-40 version2-Jin
Sheet: Returns Analysis

RETURNS ANALYSIS
 | 0
('000 $) | Close
EBITDA | 0
Less Interest Payments | 0
Pre-Tax Cashflow
Less Cash Taxes | 0
Less Principal Payments | 0
Less Capex | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Cashflow to Equity
Distribution to Equity | 1
Equity RROR | 0.14
Beginning Balance
RROR Target Coupon | 0
Actual Cash Flow
Equity Paydown | 0
Ending Balance
ENRON'S RETURNS ANALYSIS
Zero Residual Value
Equity Return
Actual Cash Flow
Total Cash Flow
 | IRR
Equity Return
Actual Cash Flow
Residual Value | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Total Cash Flow
 | IRR
Equity Return
Actual Cash Flow
Residual Value | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Total Cash Flow
 | IRR
Equity Return
Actual Cash Flow
Residual Value | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Total Cash Flow
 | IRR
Spreadsheet: 877543d1724343049-conditinal-formatting-psample
Sheet: Gears

 |  | 51 | 52 | 53 | 54 | 55 | 56
 |  | 45 | 44 | 43 | 42 | 41 | 40
76 | 20 | 1.263368421052631 | 1.317416267942584 | 1.373977968176255 | 1.433233082706767 | 1.495378690629011 | 1.560631578947368
75 | 21 | 1.344224 | 1.401730909090909 | 1.461912558139535 | 1.52496 | 1.591082926829268 | 1.660512
74 | 22 | 1.427264864864865 | 1.488324324324324 | 1.552223758642363 | 1.619166023166023 | 1.68937376400791 | 1.763091891891892
73 | 23 | 1.512580821917808 | 1.577290161892901 | 1.645009238611023 | 1.715953033268102 | 1.790357500835282 | 1.868482191780822
72 | 24 | 1.600266666666667 | 1.668727272727273 | 1.740372093023256 | 1.815428571428571 | 1.894146341463415 | 1.9768
71 | 25 | 1.690422535211267 | 1.762740076824584 | 1.838421225024566 | 1.917706237424547 | 2.000858811405015 | 2.088169014084507
70 | 26 | 1.783154285714286 | 1.859438961038961 | 1.939271760797342 | 2.02290612244898 | 2.110620209059233 | 2.20272
69 | 27 | 1.878573913043478 | 1.95894071146245 | 2.043045500505561 | 2.131155279503105 | 2.22356309650053 | 2.320591304347826
68 | 28 | 1.9768 | 2.061368983957219 | 2.149871409028728 | 2.242588235294118 | 2.339827833572453 | 2.441929411764705
67 | 29 | 2.077958208955224 | 2.166854816824966 | 2.259886150642138 | 2.357347547974414 | 2.459563159810702 | 2.566889552238806
66 | 30 | 2.182181818181818 | 2.275537190082645 | 2.37323467230444 | 2.475584415584415 | 2.582926829268292 | 2.695636363636364
65 | 31 | 2.289612307692307 | 2.387563636363636 | 2.49007084078712 | 2.59745934065934 | 2.710086303939962 | 2.828344615384615
Spreadsheet: 215081d1361260885-using-dependant-validation-show-error-or-blank-if-inital-validation-changes-dynamic-dv-and-cf-to-hide-mismatches
Sheet: Lists

Monday | Tuesday | Wednesday | Thursday | Friday | Saturday | Sunday
[NAME] | Laundry | Windows | Hobby | Fun | Family | Prepare
Clean |  | [NAME] | Emails | Friends |  | Relax
 |  | Cut Grass
Spreadsheet: 14b3d360-b240-4401-8ff3-909933a42055
Sheet: drop-down menu data

species |  | DNA Isolation |  |  | SampleSource |  |  | SamplesResuspendedIn |  |  | - Sample Source - |  |  |  | - Sample State - | 1
human |  | Microcon/Centricon Ultrapurification and concentration |  |  | biopsy material |  |  | water |  |  | 1 | - NOT SELECTED - |  |  | 1 | - NOT SELECTED -
[NAME] |  | Phenol-Chloroform extraction |  |  | blood or bone marrow |  |  | buffer |  |  |  | Blood |  |  |  | Fresh
Norway rat |  | [NAME] DNA Blood Maxi kit |  |  | dissected tissue |  |  |  |  |  |  | Bone Marrow |  |  |  | Frozen
baboon |  | PicoPure RNA (Arcturus) |  |  | established cell line |  |  |  |  |  |  | Dissected Tissue |  |  |  | [NAME]
Rhesus macaque |  | SDS/Protein K digestion |  |  | FACS |  |  |  |  |  |  | [NAME] |  |  |  | Other
Japanese macaque |  | [NAME] DNA purificaiton |  |  | laser capture microdissection |  |  |  |  |  |  | [NAME]
Thale Cress |  |  |  |  | primary culture |  |  |  |  |  |  | Primary Culture
C. elegans |  |  |  |  | whole tissue |  |  |  |  |  |  | [NAME]
hamster
fruit fly
zebrafish
E. coli |  |  |  |  | DNA Type
[NAME]'s yeast |  |  |  |  | genomic DNA
fission yeast |  |  |  |  | PCR product
other |  |  |  |  | enzyme digestion
 |  |  |  |  | other
Spreadsheet: 525458d1498739019-is-it-possible-to-auto-update-a-worksheet-while-saving-data-on-another-worksheet-inv
Sheet: Items

 | Product Code | Product Description | Price
 | Adore | LeReve-002 | 9.5 | Dispensers
 | Bloom | LeReve-003 | 9.5 | Adore
 | Cheer | LeReve-004 | 9.5 | Bloom
 | [NAME] | LeReve-005 | 9.5 | Cheer
 | Clean | LeReve-006 | 9.5 | [NAME]
 | Crush | LeReve-007 | 9.5 | Clean
 | Dispensers | LeReve-001 | 25 | Crush
 | Flair | LeReve-008 | 9.5 | Flair
 | [NAME] | LeReve-009 | 9.5 | [NAME]
 | Punch | [NAME] | 9.5 | Punch
 | Rouge | LeReve-011 | 9.5 | Rouge
 | Spa | LeReve-012 | 9.5 | Spa
 | Zeal | [NAME] | 9.5 | Zeal
 | Zing | [NAME] | 9.5 | Zing
Spreadsheet: 771613d1646756978-how-will-index-match-work-with-name-range-over-12-sheets-or-with-a-vba-test-greatinfoteam-
Sheet: Jan

Style No. | Unit Price
WTB181693 | 51
WTB371652 | 59.1
WTB371652 | 59.1
WTC181281 | 213
WTC181275 | 41.75
WTC181304 | 64.6
WTC181275 | 41.75
[NAME] | 38.5
WTB371647 | 64
WTC181313 | 87.5
WTC181313 | 87.5
WTC181313 | 87.5
WTB181693 | 51
WTC181281 | 213
WTC181304 | 64.6
[NAME] | 38.5
WTC181260 | 50.5
WTC181260 | 50.5
WTC181297 | 32.5
WTC181297 | 32.5
WTE181121 | 88.9
WTE181121 | 88.9
WTB181678 | 40
WTB181678 | 40
Spreadsheet: 799876d1665382375-formula-to-compute-diffrences-formula-to-sum-items-in-yellow-colour-
Sheet: Sheet1

On statement |  |  | Sum CF Items on Statement
2022-09-02 00:00:00 | 830 | 84.16
2022-09-09 00:00:00 | 657 | 41.1
2022-09-15 00:00:00 | 895 | 56639.27
2022-09-21 00:00:00 | 0221 | 52.11
2022-09-22 00:00:00 | 4893 | 593.4
2022-09-26 00:00:00 | 1005 | 188.43
On Ledger |  |  | [NAME] on Ledger
2022-09-12 00:00:00 | 175 | 41.1
2022-09-13 00:00:00 | 264 | 84.16
2022-09-16 00:00:00 | 633 | 56639.27
2022-09-27 00:00:00 | 165 | 188.44
2022-09-29 00:00:00 | 331 | 3607.6
2022-09-29 00:00:00 | 348 | 11849.13
2022-09-30 00:00:00 | 361 | 13645.41
2022-09-30 00:00:00 | 362 | 3607.62
Spreadsheet: 2bf4423a-3f62-47ab-9a23-b8a09ffb566e
Sheet: Customer Data

Forward Capacity Market Performance Settlement Report
SR_FCMPERFORMSTL_<customer id>_<settlement_date>_<version>.CSV
<[NAME]
Date: <mm/dd/yyyy> and Version: <mm/dd/yyyy hh:[NAME]:ss> GMT
Customer Performance Informance
Capacity Zone ID | Capacity Zone Name | Customer Capacity Supply Obligation | Customer Demand Reduction Value | [NAME] Output | Customer Capacity Value | Customer Negative Capacity Variance | Customer Positive Capacity Variance | Customer Performance Penalty | Customer Preliminary Performance Incentive | Customer Net Performance Incentive
Number | String | MW/Month | MW | MW | MW | MW | MW | $ | $ | $
Spreadsheet: 159788d1338843035-excel-2007-i-need-a-formula-to-calculate-six-months-at-a-time-from-separate-sheet-tabs-hr-calendar-with-formulas
Sheet: May

 | SUNDAY | MONDAY | TUESDAY | WEDNESDAY | THURSDAY | FRIDAY | SATURDAY |  | 1. Absent - EX  2. Absent - UN  3. Bereavement  4. Discipline  5. FMLA  6. Tardy
 |  |  |  | Bryant 3 | Bryant 3 | Bryant 3
 |  | Harris 1 | Harris 1 | Harris 1 | Harris 1 | Harris 1
 |  |  | NOTES:
 |  |  | Type in Employee's Last Name and the Corresponding Number
Spreadsheet: 157346d1337704702-trying-to-specify-a-lookup-list-from-a-specific-cells-contents-equipment-look-up-list
Sheet: Sheet2

Equipment Type | [NAME] | Patient Transport | Trailer | Personnel Transport
[NAME] | Auto (Cargo Only Up to 130hp) | Golf Cart | Trailer 11 (Medical Equip, Logistics) 10' | Truck (ex. Tahoe)
Trailer | [NAME] (ex. [NAME]) | Ambulance HP to 150 | Trailer 12 (Medical Equip, Logistics) 12' | Auto (Up to 130hp)
Patient Transport | 1 Ton (ex. F-350) | Ambulance HP to 210 | Trailer 10 (Medical Equip, Logistics) 14'
Personnel Transport | 1 1/2 Ton (ex. F-450) | Ambulance, Medical Bus | Trailer 3 (Pt. Cot & PPE) 16'
Bus | 1 3/4 Ton (ex. F-550) |  | Trailer 2 (X-ray eqipment) 24'
Generator |  |  | Trailer 4 (Pt. [NAME]) 24'
Tent
Miscellaneous
Spreadsheet: 735096d1622695959-how-to-expand-the-formula-for-second-salary-raise-in-budget-salary-raise-calculations
Sheet: Sheet1

2020 Hiring Plan: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Salary
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2020-01-01 00:00:00 |  |  |  |  |  |  |  |  |  |  |  | 2021-01-01 00:00:00
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2020-12-31 00:00:00 |  |  |  |  |  |  |  |  |  |  |  | 2021-12-31 00:00:00
 | Full-time:
 | Count | First Name | Last Name | Business Title | Department | Location | Hire date | Term date | Annual salary | Raise date | New salary |  | Raise date | New salary
 |  | x |  |  |  | San Francisco | 2019-06-17 00:00:00 |  | 96200 | 2020-01-01 00:00:00 | 190000 | 1 | 2021-07-01 00:00:00 | 200000 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 15833.33333
 |  | y |  |  |  | San Francisco | 2015-10-05 00:00:00 |  | 200000
2020 Hiring Plan: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Salary
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2020-01-01 00:00:00 |  |  |  |  |  |  |  |  |  |  |  | 2021-01-01 00:00:00
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2020-12-31 00:00:00 |  |  |  |  |  |  |  |  |  |  |  | 2021-12-31 00:00:00
 | Full-time:
 | Count | First Name | Last Name | Business Title | Department | Location | Hire date | Term date | Annual salary | Raise date | New salary |  | Raise date | New salary
 |  | x |  |  |  | San Francisco | 2019-06-17 00:00:00 |  | 96200 | 2020-01-01 00:00:00 | 190000 | 1 | 2021-07-01 00:00:00 | 200000
 |  | y |  |  |  | San Francisco | 2015-10-05 00:00:00 |  | 200000 |  | 200000
Spreadsheet: 820877d1678318033-matching-two-columns-and-returning-the-third-s666-pq-matching-two-columns-and-returning-the-third
Sheet: Transactions

Date | Type | Description | Value |  | [NAME] | Category should be
2023-03-01 00:00:00 |  | UKI T/A DIRECTLINE | -10 |  |  | wife
2023-03-01 00:00:00 |  | UKI T/A DIRECTLINE | -20 |  |  | me
2023-03-02 00:00:00 |  | UKI T/A DIRECTLINE | -30 |  |  | dog
2023-03-02 00:00:00 |  | UKI T/A DIRECTLINE | -40
2023-03-02 00:00:00 |  | Savings Account | -50 |  |  | To Savings
2023-03-03 00:00:00 |  | SAVINGS ACCOUNT | 60 |  |  | From Savings
2023-03-04 00:00:00 |  | BRITISH GAS | -20 |  |  | Energy
2023-03-05 00:00:00 |  | WATER | -150 |  |  | Energy
Date | Type | Description | Value | Category
2023-03-01 00:00:00 |  | UKI T/A DIRECTLINE | -20 | me
2023-03-01 00:00:00 |  | UKI T/A DIRECTLINE | -10 | wife
2023-03-02 00:00:00 |  | UKI T/A DIRECTLINE | -40
2023-03-02 00:00:00 |  | Savings Account | -50 | To Savings
2023-03-02 00:00:00 |  | UKI T/A DIRECTLINE | -30 | dog
2023-03-03 00:00:00 |  | SAVINGS ACCOUNT | 60 | From Savings
2023-03-04 00:00:00 |  | BRITISH GAS | -20 | Energy
2023-03-05 00:00:00 |  | WATER | -150 | Energy