tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 778366d1651030976-i-am-trying-to-group-together-rows-of-invoice-lines-into-a-specific-type-book3
Sheet: Sheet1

Description combined | Inv Date | Inv/Cn # | Rank | Result | Service Type | Net | GST | Total
 | 2022-04-22 00:00:00 | 32959836 | Top | Hotel | Agency Account Fee | 1.42 | 0 | 1.42
 | 2022-04-22 00:00:00 | 32959836 | Top | Hotel | [NAME] | 15 | 1.5 | 16.5
 | 2022-04-22 00:00:00 | 32959836 | Top | Hotel | Hotel | 430.73 | 43.07 | 473.8
 | 2022-04-22 00:00:00 | 32959836 | Top | Hotel | Agency Account Fee | 0.05 | 0 | 0.05
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Agency Account Fee | 0.08 | 0 | 0.08
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | New Booking Fee | 25 | 2.5 | 27.5
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Services | 90.9 | 9.1 | 100
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Agency Account Fee | 0.01 | 0 | 0.01
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Agency Account Fee | 0.04 | 0 | 0.04
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Sector Booking Fee | 12.25 | 1.23 | 13.48
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Agency Account Fee | 0.3 | 0 | 0.3
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Flight | 557.19 | 55.72 | 612.91
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Agency Account Fee | 1.84 | 0 | 1.84
 | 2022-04-22 00:00:00 | 32958921 | Middle | Flight | Sector Booking Fee | 2 | 0.2 | 2.2
 | 2022-04-22 00:00:00 | 32958735 | Top | Hotel | Agency Account Fee | 0.49 | 0 | 0.49
 | 2022-04-22 00:00:00 | 32958735 | Top | Hotel | Hotel | 148.18 | 14.82 | 163
 | 2022-04-22 00:00:00 | 32958735 | Top | Hotel | [NAME] | 15 | 1.5 | 16.5
 | 2022-04-22 00:00:00 | 32958735 | Top | Hotel | Agency Account Fee | 0.05 | 0 | 0.05
Spreadsheet: 87619aed-b72a-4c36-8ca1-47ccdf090a99
Sheet: Sheet1

Test Referenced | Entry Type | Mayo ID | Description | Reporting Description | Method | Collection Container | Temperature | Stability | [NAME] | Unit of Measure | [NAME] | Minimum Volume | Reject Due To | Reference Values | Days/Times Performed | Analytic Time | Maximum Lab Time | CPT Units | CPT Code | LOINC® Code | LOINC® Attributes | Always Performed | Orderable Separately | Performing Location
HPYA | Test | HPYA | Helicobacter pylori Antibody, IgA, Serum | Helicobacter pylori Ab, IgA, S | Enzyme-Linked Immunosorbent Assay (ELISA) | Serum Gel Tube: SGT |  |  | 0.6 | mL | Container/Tube:  Preferred: Red top Acceptable: Serum gel [NAME]: 0.5 mL | 0.4 mL | Hemolysis	Mild OK; Gross reject Thawing	Warm reject; Cold OK Lipemia	Mild OK; Gross reject Icterus	NA Other	NA | Negative (Results with index value of <18.00 are negative.) Equivocal (Results with index values of > or =18.00 but < or =20.00 are equivocal.) Positive (Results with index values of >20.00 are positive.) | Monday through Friday; 9 a.m. | Same day/1 day | 3 days | 1 | 86677 |  |  |  |  | Rochester
HPYA | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 14 days
HPYA | Result | HPYAQ | Helicobacter pylori Ab, IgA, S | Helicobacter pylori Ab, IgA, S | Alphanumeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | In Process
HPYA | Result | [NAME] | Index Value | Index Value | Numeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 6420-4 | Helicobacter pylori Ab.IgA:ACnc:Pt:Ser:Qn:EIA
Spreadsheet: phillip_m_love__30654__9902_OA
Sheet: TX-CON-GL 

ENRON CAPITAL & TRADE RESOURCES
OPERATIONAL ANALYSIS - ACTUALS
COMPANY:  ECTR (EGM) / HPL
REGION:  TEXAS
 |  |  | Total |  | Reclasses |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | September |  | October |  | November |  | December |  | January |  | February |  | March |  | April
 |  |  | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s | Volume | $'s
 | Sales:
1 |  | 3rd Party / Inter Enron
2 |  | Liquidations
3 |  | Interdesk
4 |  | Option Premiums
5 |  | Dmd Reimbursements
 | Total Sales:
 | Purchases:
6 |  | 3rd Party / Inter Enron
7 |  | Liquidations
8 |  | Interdesk
9 |  | Option Premiums
10 |  | [NAME]
 | Total Purchases:
 | Intra CTS (EGM / HPL / LRC):
11 |  | Sales
12 |  | Purchases
 | Total Intra CTS Sales / Purchases
 | Imbalances:
13 |  | In Kind
14 |  | Cash Out
15 |  | Cash In
16 |  | Synthetic Storage
 | Total Imbalances:
 | Storage:
17 |  | Injection (Sales to Stg)
18 |  | W/D (Purchase from Stg)
19 |  | Inventory Profit
 |  | Total W/D
 | Total Storage:
20 | Linepack:
21 | Shrinkage:
22 | UA4:
23 | Fuel:
 | Transport Expense:
24 |  | Commodity
25 |  | Demand
 | Total Transport Expense:
 | Transport Revenue:
26 |  | Interstate
27 |  | Intrastate
 | Total Transport Revenue:
 | Intra CTS (EGM / HPL / LRC):
28 |  | Transport Expense
29 |  | Transport Revenue
 | Total Intra CTS Transport
 | Tie Out Schedule Items:
 |  | MTM Income:
30 |  | Current Gross Book Balance
31 |  | Prior Month Book Balance
 |  | Total MTM Income
32 |  | Prudency
33 |  | Financial Liquidations
34 |  | Originations
35 |  | Broker Fees
36 |  | Asset Group Demand Charges
37 |  | [NAME]
38 |  | Interdesk Charges
39 |  | Canada
40 |  | Miscellaneous
 |  | TOTAL
FT-South Texas
 |  | Current Month MTM
 |  | Financial Liquidations
 |  | Originations
 |  | TOTAL FIRM TRADING
 |  | TOTAL GL
Spreadsheet: andy_zipper__497__11_26_01GO
Sheet: Sheet1

 |  |  | SCS  OPTION  DATA
 | TICKER | STRIKE | STR BID | STR ASK | B VOL | A VOL | M STD/DAY | WHEN
 | [NAME] | 52 | 180 | 280 | 82.8 | 128.9 | 3.46 | 2001-11-26 14:55:00
 | HU F2 | 52 | 700 | 800 | 59.1 | 67.5 | 2.07 | 2001-11-26 14:55:00
 | HU G2 | 53 | 940 | 1040 | 54 | 59.7 | 1.89 | 2001-11-26 14:55:00
 | [NAME] | 55 | 1080 | 1180 | 49.9 | 54.5 | 1.8 | 2001-11-26 14:55:00
 | [NAME] | 60 | 1320 | 1420 | 49.1 | 52.8 | 1.92 | 2001-11-26 14:55:00
 | [NAME] | 61 | 1400 | 1500 | 45.8 | 49.1 | 1.82 | 2001-11-26 14:55:00
 | [NAME] | 61 | 1500 | 1600 | 44.7 | 47.7 | 1.77 | 2001-11-26 14:55:00
 | HU N2 | 61 | 1520 | 1620 | 42.3 | 45.1 | 1.68 | 2001-11-26 14:55:00
 | [NAME] | 61 | 1540 | 1650 | 40.1 | 43 | 1.59 | 2001-11-26 14:55:00
 | HU U2 |  |  |  | 36 | 39.4 | 1.59 | 2001-10-29 14:33:00
 | [NAME] |  |  |  | 32.2 | 36.6 | 1.43 | 2001-10-22 14:23:00
 | [NAME] |  |  |  |  |  | 1.26 | 2001-08-20 15:44:00
 | [NAME]
 | HU F3
 | [NAME] |  |  |  |  |  | 0.56 | 2001-07-19 17:15:00
 | HU H3
Spreadsheet: 126270d1319609204-array-concatenate-formula-issue-ozwilly-2011-10-25
Sheet: Ranking Report

 |  | Ranking Report
SEOT | Keyword | URL |  |  |  | 2011-10-20 00:00:00
 | cosmetics | http://faceofaustralia.com.au
 |  | http://faceofaustralia.com.au/cosmetics
 | makeup | http://faceofaustralia.com.au
 |  | http://faceofaustralia.com.au/makeup
 | mascara | http://faceofaustralia.com.au
 |  | http://faceofaustralia.com.au/mascara
 | eyeliner | http://faceofaustralia.com.au
 |  | http://faceofaustralia.com.au/eyeliner
 | primer | http://faceofaustralia.com.au
 |  | http://faceofaustralia.com.au/primer
 | [NAME] | http://faceofaustralia.com.au
 |  | http://faceofaustralia.com.au/primer
Spreadsheet: 796078d1663089735-spill-range-with-countifs-of-unique-rows-countifs_unique
Sheet: Sheet1

Date_1 | Date_2 | Date_3 |  |  | Date_1 | Date_2 | Date_3 |  |  | COUNTIFS |  | COUNTIFS |  | COUNTIFS
2019-07-30 00:00:00 | 2019-06-25 00:00:00 | 2019-08-01 09:44:12 |  |  |  | 2019-06-25 00:00:00 | 2019-08-01 09:44:12
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  | 2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  | 1 |  | #[NAME]!
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  | 2019-08-01 00:00:00 | 2019-07-08 00:00:00 | 2019-08-01 12:19:15 |  |  | 1 |  | #[NAME]!
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  | 2019-08-22 00:00:00 | 2019-07-31 00:00:00 | 2019-09-20 06:54:36 |  |  | 1 |  | #[NAME]!
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  | 2019-09-03 00:00:00 | 2019-08-07 00:00:00 | 2019-09-05 12:57:23 |  |  | 1 |  | #[NAME]!
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  | 2019-09-05 00:00:00 | 2019-08-13 00:00:00 | 2019-09-05 09:55:58 |  |  | 1 |  | #[NAME]!
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  |  |  |  |  |  | 1 |  | #N/A
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  |  |  |  |  |  |  | 1 |  | #N/A
2019-08-01 00:00:00 | 2019-07-08 00:00:00 | 2019-08-01 12:19:15 |  |  |  |  |  |  |  | 2 |  | #N/A
2019-08-01 00:00:00 | 2019-07-08 00:00:00 | 2019-08-01 12:19:15 |  |  |  |  |  |  |  | 2 |  | #N/A
2019-08-22 00:00:00 | 2019-07-31 00:00:00 | 2019-09-20 06:54:36 |  |  |  |  |  |  |  | 2 |  | #N/A
2019-09-03 00:00:00 | 2019-08-07 00:00:00 | 2019-09-05 12:57:23 |  |  |  |  |  |  |  | 3 |  | #N/A
2019-09-05 00:00:00 | 2019-08-13 00:00:00 | 2019-09-05 09:55:58 |  |  |  |  |  |  |  | 4 |  | #N/A
2019-09-05 00:00:00 | 2019-08-13 00:00:00 | 2019-09-05 09:55:58 |  |  |  |  |  |  |  | 4 |  | #N/A
Spreadsheet: 145058d1331289499-giving-a-value-in-a-column-based-on-the-values-in-other-column-sample_mayurpatil
Sheet: sheet 1

Column A | Column B | Helper | Result
9XME8619
9XMS8960 | 9XMS8961 | 3 | 9XMS8961
 |  |  |  |  | Hi , I have a data in column A and I want to put such a formula in column B that will give me my desired results , I only want to put data in front of 9XMS containing values of column A . Such that from top whenever 9XMS is found in column A in front of that in column B it will place the next 9XMS value .I will mark with arrows to let it simplified .
9XMS8961 | 9XMS8926 | 6 | 9XMS8926
9XME8497
9XMS8926 | 9XMS8716 | 9 | 9XMS8716
9XMS8716 | 9XMS8973 | 11 | 9XMS8973
9XME8621
[NAME]
C030290
C029990
C030150
9XME8631
9XMS8973 |  | 19
Spreadsheet: 2b34287d-c096-421d-8e0d-9f60e2012b25
Sheet: Sheet1

Table 10--Global rice exporters, calendar years; monthly revisions and annual changes | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13
 | 2011 |  |  |  | 2012 |  |  |  |  |  | 2013 1/
 | December |  | November | December |  | Monthly | Annual |  | November | December |  | Monthly | Annual
 | 2012 |  | 2012 | 2012 |  | revisions | changes |  | 2012 | 2012 |  | revisions | changes
 |  |  |  |  |  |  | 1,000 metric tons (milled basis)
Argentina | 732 |  | 675 | 675 |  | 0 | -57 |  | 525 | 525 |  | 0 | -150
Australia | 311 |  | 450 | 450 |  | 0 | 139 |  | 500 | 500 |  | 0 | 50
Brazil | 1296 |  | 1200 | 1200 |  | 0 | -96 |  | 800 | 800 |  | 0 | -400
Burma | 778 |  | 700 | 700 |  | 0 | -78 |  | 600 | 600 |  | 0 | -100
Cambodia | 860 |  | 800 | 800 |  | 0 | -60 |  | 950 | 950 |  | 0 | 150
China | 487 |  | 400 | 400 |  | 0 | -87 |  | 500 | 500 |  | 0 | 100
Ecuador | 70 |  | 30 | 30 |  | 0 | -40 |  | 15 | 15 |  | 0 | -15
Egypt | 320 |  | 600 | 600 |  | 0 | 280 |  | 850 | 850 |  | 0 | 250
European Union-27 | 241 |  | 210 | 210 |  | 0 | -31 |  | 235 | 235 |  | 0 | 25
Guinea | 80 |  | 80 | 80 |  | 0 | 0 |  | 80 | 80 |  | 0 | 0
Guyana | 250 |  | 230 | 230 |  | 0 | -20 |  | 250 | 250 |  | 0 | 20
India | 4637 |  | 10000 | 10000 |  | 0 | 5363 |  | 6500 | 6500 |  | 0 | -3500
Japan | 200 |  | 200 | 200 |  | 0 | 0 |  | 200 | 200 |  | 0 | 0
Korea, South | 4 |  | 5 | 5 |  | 0 | 1 |  | 5 | 5 |  | 0 | 0
Pakistan | 3414 |  | 3750 | 3750 |  | 0 | 336 |  | 4000 | 4000 |  | 0 | 250
Paraguay | 208 |  | 250 | 250 |  | 0 | 42 |  | 200 | 200 |  | 0 | -50
Peru | 50 |  | 30 | 30 |  | 0 | -20 |  | 60 | 60 |  | 0 | 30
Russia | 142 |  | 200 | 200 |  | 0 | 58 |  | 170 | 170 |  | 0 | -30
Thailand | 10647 |  | 6500 | 6500 |  | 0 | -4147 |  | 8000 | 8000 |  | 0 | 1500
Turkey | 90 |  | 75 | 75 |  | 0 | -15 |  | 80 | 80 |  | 0 | 5
Uganda | 40 |  | 35 | 35 |  | 0 | -5 |  | 35 | 35 |  | 0 | 0
United States | 3247 |  | 3300 | 3300 |  | 0 | 53 |  | 3400 | 3450 |  | 50 | 150
Uruguay | 841 |  | 1050 | 1050 |  | 0 | 209 |  | 850 | 850 |  | 0 | -200
Vietnam | 7000 |  | 7200 | 7500 |  | 300 | 500 |  | 7000 | 7000 |  | 0 | -500
Subtotal | 35945 |  | 37970 | 38270 |  | 300 | 2325 |  | 35805 | 35855 |  | 50 | -2415
Other | 269 |  | 239 | 239 |  | 0 | -31 |  | 260 | 260 |  | 0 | 21
 |  |  |  |  |  |  |  |  |  |  |  | 0
World total | 36214 |  | 38209 | 38509 |  | 300 | 2295 |  | 36065 | 36115 |  | 50 | -2394
U.S. Share | 0.08966145689512343 |  | 0.08636708628857076 | 0.08569425329143837 |  | -- | -- |  | 0.09427422708997643 | 0.0955281738889658 |  | -- | --
-- Not available.  Note: All trade data are reported on a calendar-year basis.
1/ Projected.
Source: Production, Supply, & Distribution Online Data Base, FAS/USDA, http://www.fas.usda.gov/psdonline/psdHome.aspx.
Last updated December 12, 2012.
Spreadsheet: 781902d1653637739-need-formula-to-count-table-range-depending-on-conditions-in-selected-table-columns-hit-miss-aligw-3-
Sheet: Fighter1

Summary
Style | Won:Lost | Number Of Hits | Number Of Misses | Basic Defense
Aggressive
Defensive
Accurate
Balanced
 |  |  |  | Hit points:
Date | Result | Style | Attack Defense | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13
May 14, 2022 2:00am | Lost | Aggressive | Attack | 140 | 100 | 113 | 81 | 99 | 106 | MISS | 146
 |  |  | Defence | -144 | -180 | MISS | -116 | -185 | -151 | -181 | -147
May 13, 2022 10:30pm | Lost | Defensive | Attack | 177 | 85 | 141 | 137 | 138 | 47 | 182
 |  |  | Defence | -66 | -293 | -89 | -286 | MISS | MISS | -110
May 13, 2022 6:30pm | Lost | Accurate | Attack | 118 | 88 | MISS | 143 | 83 | 178 | 127 | MISS | 90 | 60 | 107
 |  |  | Defence | -124 | -99 | -142 | -58 | -110 | -106 | -85 | -11 | -187 | MISS | -107
May 13, 2022 6:30pm | Won | Aggressive | Attack | 121 | 144 | 198 | 85 | 114 | 107 | 31 | 182 | 98
 |  |  | Defence | -71 | MISS | -99 | -129 | -100 | -73 | MISS | -230
Spreadsheet: 887796d1738124426-fixed-asset-depreciation-v2-fixed-asset-depreciation-v3
Sheet: v3

 | Summary |  | 1 |  |  |  |  |  |  |  |  |  |  |  | Total
 | Net Book Value b/f |  | 0
 | Addition |  | 500000 |  | 300000 |  |  |  |  |  |  |  |  |  |  |  |  | Input cells
 | Initial Depreciation | 0.2 |  | 0 | -60000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  |  |  | [NAME] required
 | Annual Depreciation | 0.14 |  | -70000 | -112000 | -112000 | -112000 | -112000 | -42000.00000000001 | -42000.00000000001 | 0 | 0 | 0 | 0
 | Net Book Value c/f
 |  |  | 1 |  |  |  |  |  |  |  |  |  |  |  | Total
 | Net Book Value b/f |  | 0
 | Addition |  | 500000
 | Initial Depreciation
 | Annual Depreciation
 | Net Book Value c/f
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Remove this section
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Total
 | Net Book Value b/f |  | 0
 | Addition |  |  |  | 300000
 | Initial Depreciation
 | Annual Depreciation
 | Net Book Value c/f
 | Further to my post in:
 | https://www.excelforum.com/excel-formulas-and-functions/1432561-fixed-asset-depreciation.html#post6008830
 | I need a formula for Initial Depreciation and Annual Depreciation for the purchase of new assets without having to break down the 2 purchases and then add them up.
Spreadsheet: 747352d1631429000-lookup-of-multiple-rows-and-multiple-columns-lookup_example_data
Sheet: John

Name | [NAME]
Name | Value 1 | Value 2 | Value 3 | Value 4 | Value 5 | Value 6 | Value 7 | Value 8 | Value 9 | Value 10 | Value 11 | Value 12 | Value 13 | Value 14 | Value 15 | Value 16 | Value 17 | Value 18 | Value 19 | Value 20
Spreadsheet: 10b1dc05-7d7e-488a-9caa-d8e9a87fdd08
Sheet: Sheet1

Battle ID | Date & Time | Side | Victory | Score | Opp. Score | Opp. ID | Opp. Name | Scenario ID | Front | Start Date | End Date | Name EN | Name FR
42407802 | 2014-07-22 14:09:58 | AXIS | 0 | 1 | 5 | 828272 | hester24 | 6153 | western | 1944-08-24 | 1944-08-24 | Liberation of Paris | Libération de Paris
42407952 | 2014-07-22 14:23:34 | ALLIES | 1 | 5 | 0 | 828272 | hester24 | 6153 | western | 1944-08-24 | 1944-08-24 | Liberation of Paris | Libération de Paris
Spreadsheet: 149519d1333999479-finding-second-to-minimum-number-in-array-tissue-culture-sal-1
Sheet: Comparisons

 | Culture Dishes
 | 35mm |  |  | 60mm |  |  | 100mm |  |  | 150mm
Vendor | Price | Dishes/cs | $/tube | Price | Dishes/cs | $/tube | Price | Dishes/cs | $/tube | Price | Dishes/cs | $/tube
BD | 106 | 500 |  | 89 | 500 |  | 79.6 | 200 |  | 95.2 | 100
Corning | 90.79 | 500 |  | 84.06 | 500 |  | 159.25 | 500 |  | 89.66 | 60
Denville | 74.99 | 500 |  | 74.99 | 500 |  | 69.99 | 300 |  | 69.99 | 100 |  |  |  | Calculate my savings!
Other
 | Savings each month |  |  |  |  |  |  |  |  |  |  |  |  |  | How many cases per month do you use? |  |  |  | 2
 | Savings each year
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Company to compare against Denville? |  |  |  | BD
 | Cell Culture Plates
 | 6 well |  |  | 12 well |  |  | 24 well |  |  | 96 well
 | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate
BD | 47.5 | 50 |  | 57 | 50 |  | 55 | 50 |  | 59.5 | 50
Corning | 100.8 | 100 |  | 131.9 | 100 |  | 173.51 | 100 |  | 101.34 | 100
Denville | 46.99 | 50 |  | 53.99 | 50 |  | 49.99 | 50 |  | 89.99 | 100
Other
 | Savings each month
 | Savings each year
 | Cell Culture Flasks
 | 25cm2 (Plug Cap) |  |  | 25cm2 ([NAME]) |  |  | 75cm2 (Plug Cap) |  |  | 75cm2 ([NAME]) |  |  | 175cm2 (Plug Cap) |  |  | 175cm2 ([NAME])
 | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate | Price | Plates/cs | $/plate
BD | 76.8 | 200 |  | 79.6 | 200 |  | 83.6 | 100 |  | 86.4 | 100 |  | 62.64 | 40 |  | 68 | 40
Corning | 206.5 | 500 |  | 121.54 | 200 |  | 82.12 | 100 |  | 102.58 | 100 |  | 80.07 | 50 |  | 87.43 | 50
Denville | 81.99 | 200 |  | 89.99 | 200 |  | 81.99 | 100 |  | 89.99 | 100 |  | 69.99 | 40 |  | 79.99 | 40
Other
 | Savings each month
 | Savings each year
Spreadsheet: 245d3fc6-2797-4184-9a0b-e90929db64c1
Sheet: Sheet1

concept_id | concept_name | concept_vocabulary_code | concept_level | concept_code
73001 | Myositis | 1 | 2 | 26889001
79908 | Muscle weakness | 1 | 2 | 26544005
80800 | Polymyositis | 1 | 2 | 31384009
439142 | Myoglobinuria | 1 | 1 | 48165008
4001805 | Myositis unspecified | 1 | 1 | 203110007
4011037 | [D]Myoglobinuria | 1 | 0 | 207318008
4140389 | March myoglobinuria | 1 | 1 | 33033006
4207805 | Idiopathic myoglobinuria | 1 | 1 | 5523002
4218766 | Exertional rhabdomyolysis | 1 | 2 | 72960004
4230337 | Rhabdomyolysis | 1 | 0 | 89010004
4344138 | Traumatic rhabdomyolysis | 1 | 1 | 240125008
4344140 | Non-traumatic rhabdomyolysis | 1 | 1 | 240132004
4345578 | Rhabdomyolysis | 1 | 2 | 240131006
4147768 | Myopathy, unspecified | 2 | 1 | 359.9
4147768 | Myopathy, unspecified | 2 | 1 | 359.9
4217978 | Myalgia and myositis, unspecified | 2 | 1 | 729.1
4218609 | Muscle weakness (generalized) | 2 | 1 | 728.87
4240118 | Polymyositis | 2 | 1 | 710.4
4244909 | Myoglobinuria | 2 | 1 | 791.3
4248141 | Rhabdomyolysis | 2 | 1 | 728.88
4262118 | Other myopathies | 2 | 1 | 359.8
4262436 | Toxic myopathy | 2 | 1 | 359.4
4324178 | Antilipemic and antiarteriosclerotic drugs causing adverse effects in therapeutic use | 2 | 1 | E942.2
4344413 | Myoglobinuria | 7 | 0 | N0000002090
4345083 | Rhabdomyolysis | 7 | 0 | N0000002626
4345512 | Polymyositis | 7 | 3 | N0000003568
4346672 | Muscle Weakness | 7 | 3 | N0000003878
4347019 | Myositis | 7 | 3 | [NAME]
4355369 | Muscle Weakness | 7 | 3 | N0000003878
35205334 | Myoglobinuria | 15 | 2 | 10028629
35228229 | Myoglobinuria | 15 | 1 | 10028629
36009829 | Polymyositis | 15 | 2 | 10036102
36045641 | Polymyositis | 15 | 1 | 10036102
36211176 | Myopathy toxic | 15 | 2 | 10028648
36252554 | Myopathy toxic | 15 | 1 | 10028648
36503278 | Muscle weakness conditions | 15 | 3 | 10062913
36516833 | Myositis | 15 | 2 | 10028653
36516835 | Myositis-like syndrome | 15 | 2 | 10028654
36516886 | Myopathy | 15 | 2 | 10028641
36516888 | Rhabdomyolysis | 15 | 2 | 10039020
36569469 | Myositis | 15 | 1 | 10028653
36569474 | Myositis-like syndrome | 15 | 1 | 10028654
36569696 | Muscle weakness | 15 | 1 | 10028350
36569708 | Generalised muscle weakness | 15 | 1 | 10062571
36569709 | Generalized muscle weakness | 15 | 1 | 10062572
36569740 | Myopathy | 15 | 1 | 10028641
36569744 | Myopathy, unspecified | 15 | 1 | 10028649
36569756 | Rhabdomyolysis | 15 | 1 | 10039020
37080782 | Rhabdomyolysis-induced renal failure | 15 | 1 | 10050996
84675 | Myalgia and myositis, unspecified | 53 | 1 | 729.1
446370 | Antilipemic and antiarteriosclerotic drugs causing adverse effects in therapeutic use | 53 | 1 | E942.2
37690084 | Myopathy	 unspecified | 53 | 1 | 359.9
37690442 | Mylagia and myositis	 unspecified | 53 | 1 | 729.1
37691586 | Muscle weakness | 53 | 1 | 26544005
Spreadsheet: 718455d1613144325-return-difference-between-a-value-and-a-target-value-book1
Sheet: Sheet1

Emp. No. | Sun | Mon | [NAME] | Wed | Thu | Fri | Sat | Week | Snow |  |  | 11 | Sun | Mon | Tue | Wed | Thu | Fri | Sat | Week
 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | One | Hours | Reg | O/T | Min | 31 | 1 | 2 | 3 | 4 | 5 | 6 | Two
 | Reg | Reg | Reg | Reg | Reg | Reg | Reg |  | TOTAL |  |  |  | Reg | Reg | Reg | Reg | Reg | Reg | Reg
25 |  | 9.5 | 5.5 | 11 | 10 | 8 | 11 |  |  |  |  |  |  | 11 | 10 | 11 | 11 | 16 | 5
62 |  | 10 | 12.5 | 9.5 | 8.5 | 3.5 |  |  |  |  |  |  |  | 10.5 | 10 | 9.5 | 10 | 13
14 |  | 8 | 7 | 7.5 | 6 |  |  |  |  |  |  |  |  | 9 | 8.75 | 4 | 8 | 6.25
31 |  | 8 | 8 | 8 | 8 | 8 |  |  |  |  |  |  |  | 8 | 8 | 8 | 8 | 8
3 |  |  | 9 | 1 | 3 | 1.5 |  |  |  |  |  |  |  |  |  |  |  | 11
49 |  |  | 12.5 | 1.5 |  |  |  |  |  |  |  |  |  |  |  |  |  | 12
32 |  | 9 | 11.5 | 9.75 | 9 |  |  |  |  |  |  |  |  | 8.5 | 10 | 9 | 10.5 | 9
68 |  | 6 | 7 | 10 | 8.5 | 7 |  |  |  |  |  |  |  |  | 9 | 10 | 8 | 9.5 | 8
4 |  |  | 4 | 4.5 |  |  |  |  |  |  |  |  |  |  |  |  |  | 10.5
5 |  | 7 | 7 | 9.5 | 7 | 4.5 |  |  |  |  |  |  |  | 9 | 8.75 | 9 | 8 | 5.5
 |  |  |  |  |  |  |  |  | tring to get the overtime amount paid overtime after 44 hours
 |  |  |  |  |  |  |  |  | L5 should be 11 or every fomular I write comes back 0, this is the latest of about 20
Spreadsheet: 689092d1596119597-referencing-a-table-under-different-tabs-warranty-aligw
Sheet: 48

 | 60 | 75 | 85 | 100 | 125 | 150
1A | 519 | 547 | 571 | 595 | 651 | 729
1B | 540 | 577 | 609 | 642 | 716 | 820
1C | 564 | 612 | 654 | 696 | 792 | 926
2 | 602 | 667 | 724 | 781 | 911 | 1092
3 | 630 | 707 | 775 | 843 | 997 | 1213
4 | 696 | 803 | 896 | 989 | 1202 | 1501
5 | 781 | 925 | 1052 | 1178 | 1466 | 1870
6 | 820 | 981 | 1122 | 1263 | 1586 | 2038
7 | 891 | 1084 | 1253 | 1422 | 1808 | 2348
8 | 1012 | 1260 | 1476 | 1692 | 2186 | 2878
9 | 1143 | 1448 | 1715 | 1982 | 2592 | 3446
10 | 1395 | 1812 | 2177 | 2541 | 3375 | 4543
11 | 1803 | 2401 | 2925 | 3449 | 4646 | 6321
Spreadsheet: 7fa4a277-f3fc-46a7-8324-776e1f493f40
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
7099 | 25773 | [NAME] | Landier | FRA | 82 | 00:17:33 | [NAME] | 01:11:07 | 00:01:43 | 00:27:21 | 1 | [NAME]
7099 | 47258 | [NAME] | Ubeda Salmeron | ESP | 81 | 00:15:36 | 00:01:25 | 01:30:50 | 00:01:15 | 00:31:35 | 2 | 02:20:41
Spreadsheet: 89426d1289230705-copying-specific-data-from-one-file-into-another-file-example1
Sheet: Sheet1

Date | Location | Text | Amount
2010-06-30 00:00:00 | Location A | [NAME] | 98
2010-06-30 00:00:00 | Location A | Beds in Operation | 78
2010-06-30 00:00:00 | Location A | Days in Period | 91
2010-06-30 00:00:00 | Location A | Private | 709
2010-06-30 00:00:00 | Location A | Medicare | 636
2010-06-30 00:00:00 | Location A | Medicaid | 3469
2010-06-30 00:00:00 | Location A | Other | 0
2010-06-30 00:00:00 | Location B | [NAME] | 60
2010-06-30 00:00:00 | Location B | Beds in Operation | 55
2010-06-30 00:00:00 | Location B | Days in Period | 91
2010-06-30 00:00:00 | Location B | Private | 527
2010-06-30 00:00:00 | Location B | Medicare | 377
2010-06-30 00:00:00 | Location B | Medicaid | 3360
2010-06-30 00:00:00 | Location B | Other | 0