tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 1f64e765-c357-43c1-b2ee-941a66d66f56
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
4438 | 14920 | [NAME] | Macmartin | CAN | 0 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 1 | 01:57:50
4438 | 13943 | Mark | Bates | CAN | 0 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 2 | 01:58:11
4438 | 26147 | Harold | [NAME] | NZL | 0 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 3 | 01:58:53
4438 | 10349 | [NAME] | [NAME] | USA | 0 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 4 | 01:59:32
4438 | 5706 | [NAME] | Galindez | ARG | 0 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 00:00:00 | 5 | 00:00:00
Spreadsheet: 750441d1633452880-how-can-we-skip-value-error-while-calculating-numbers-in-formula-testing
Sheet: Output

 | 1 |  | 2
 |  |  |  |  |  |  | B5 to E5 is giving the top 5 numbers from Data sheet.
 |  |  |  |  |  |  | but B5 to C5 is giving #[NAME] error because #[NAME] error is present in B column in data sheet.
 |  |  |  |  |  |  | How can we skip that #[NAME] error while calculating formula in Output sheet.
 |  |  |  |  |  |  | Note - We can not change anything in Main sheet.
Spreadsheet: e2c8408f-ca7a-4368-8200-2ce2b58fab1b
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SNOWSHOE | T1 | SKATE | T2 | SKI | POSITION | TOTAL TIME
3596 | 15513 | Marion | Buchholz | GER | 195 | 00:28:26 | 00:00:00 | 00:48:24 | 00:00:00 | 00:36:05 | 1 | 01:52:55
Spreadsheet: 849146d1699663514-sorting-data-and-labelling-data-and-preserving-the-labelling-for-other-data-sets-example-for-forum-jean_sibelius-
Sheet: Labelling data

Copy column K (Selection of DATA) | Manually label each item in column A | Value | Label |  | [NAME] (via Data Validation / Allow List / ...)
 |  | An apparatus | System
An apparatus | System | An apparatus | System |  | System
A reticle stage | Module | A metrology tool | System |  | Module
A method for improving a nuisance rate | Method | A lithographic apparatus | System |  | Component
A height measurement sensor | Component | A litho cell | System |  | Method
A method for cleaning | Method | A reticle stage | Module
A membrane | Component | A lithographic system | System |  | Labelling of all the items in column A takes quite some time
A charge regulator | Component | A method of operating an EUV lithographic apparatus | Method |  | If I start with a new dataset (having partly overlap with this dataset, how I can make sure that)
A charged particle-optical device | Module | A method for improving a nuisance rate | Method |  | 1) I can (re)use the labelling as much as possible?
An apparatus | System | A system | System |  | 2) Add the new items at the bottom of column A (i.e. not to disrupt the linking between column A and B) <as I want to use VLOOKUP, see [NAME])
A lithographic apparatus | System | A non-transitory computer readable medium storing … | Component
A system | System | A height measurement sensor | Component
A metrology tool | System | An assessment system | Module
A lithographic system | System | A metrology system | System
A non-transitory computer readable medium storing … | Component | A method for determining a focus plane | Method
An assessment system | Module | A method for cleaning | Method
A pellicle | Component | A membrane | Component
A method of operating an EUV lithographic apparatus | Method | A pellicle | Component
A metrology system | System | A patterning device and pellicle assembly | Module
A patterning device and pellicle assembly | Module | A lithographic apparatus | System
A litho cell | System
A method for determining a focus plane | Method
A lithographic apparatus | System
Spreadsheet: 833091d1686772674-formulas-to-calculate-min-max-average-and-position-1st-4th-daily-scores
Sheet: Scores

 |  | Date | 2023-01-01 00:00:00 | 2023-01-02 00:00:00 | 2023-01-03 00:00:00 | 2023-01-04 00:00:00 | 2023-01-05 00:00:00 | 2023-01-06 00:00:00 | 2023-01-07 00:00:00
 |  | [NAME] | 20 | 25 | 31 | 26
 |  | [NAME] | 21 | 25 | 31 | 26
 |  | Maria | 22 | 25 | 32 | 26
 |  | [NAME] | 23 | 25 | 40 | 31
 |  | Position
 |  | [NAME] | 1st | 1st | 1st | 1st
 |  | [NAME] | 2nd | 1st | 1st | 1st
 |  | Maria | 3rd | 1st | 2nd | 1st
 |  | [NAME] | 4th | 1st | 3rd | 2nd
 |  | Average
 |  | [NAME] | 20
 |  | [NAME] | 21
 |  | Maria | 22
 |  | [NAME] | 23
 |  | Min/Max | Minimum | Maximum
 |  | [NAME]
 |  | [NAME]
 |  | Maria
 |  | [NAME]
 |  | Positions | 1st | 2nd | 3rd | 4th
 |  | [NAME]
 |  | [NAME]
 |  | Maria
 |  | [NAME]
Spreadsheet: 288060d1389082779-autofiltering-onto-seperate-spreadsheets-auto-filter-example
Sheet: Bank Balance Sheet

Bank Statement Analysis
Date | Code | Payment | Paid Out | Paid In
2014-01-01 00:00:00 | 200 | [NAME] | -30
2014-01-02 00:00:00 | 300 | Fuel | -10
2014-01-03 00:00:00 | 200 | [NAME] | -29.99
2014-01-04 00:00:00 | 100 | Insurance | -4
2014-01-05 00:00:00 | 100 | Insurance | -80
2014-01-06 00:00:00 | 300 | Fuel | -3
2014-01-07 00:00:00 | 200 | [NAME] | -23
2014-01-08 00:00:00 | 100 | Insurance | -12
2014-01-09 00:00:00 | 300 | Fuel | -50
Spreadsheet: 5b68010d-221f-4a17-9014-5880ffea5412
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
6513 | 50363 | [NAME] | Grőb | HUN | 120 | 00:22:02 | 00:03:55 | [NAME] | [NAME] | 00:58:21 | 1 | 03:26:56
6513 | 16914 | Endre | Szebeni | HUN | 121 | 00:31:43 | 00:01:27 | 02:08:49 | 00:01:19 | 01:04:35 | 2 | 03:47:57
6513 | 50362 | Henrik | Frönlich | HUN | 119 | 00:29:29 | 00:04:50 | 02:17:25 | 00:00:56 | 01:00:35 | 3 | 03:53:19
6513 | 8035 | Stuart | Lumb | GBR | 122 | 00:29:14 | 00:04:09 | 02:18:25 | 00:02:37 | 01:28:44 | 4 | [NAME]
Spreadsheet: 720826d1614299451-inserting-additional-criteria-to-an-if-statement-wrkswipes2erref
Sheet: Error 2

 | Overall Day | ARR | STRT | END | WRK | RT | WT |  | Overall Day | ARR | STRT | END | WRK | RT | WT
 |  | 07:35:00 | 07:45:00 | 10:51:00 |  |  |  |  |  | 05:28:00 | 05:38:00 | 10:25:00
 | Break | 12:40:00 | 12:50:00 | 16:23:00 |  |  |  |  | Break | 14:50:00 | 15:00:00 | 16:00:00
 |  |  |  | Total |  |  |  |  |  | 16:00:00 | 16:10:00 | 18:14:00
 |  |  |  |  |  |  |  |  |  |  |  | Total
 | 11th Hour |  |  |  | ST | OT
 | 11 1/2 Hour |  |  |  |  |  |  |  | 11th Hour |  |  |  | ST | OT
 | Guarantee | 8:00:00 |  |  |  |  |  |  | 11 1/2 Hour
 | 11 1/2-11 |  |  |  |  |  |  |  | Guarantee | 8:00:00
 |  |  |  |  |  |  |  |  | 11 1/2-11
Spreadsheet: 16c0646d-9f7b-4557-b1f0-b5748af1739e
Sheet: 12

 | [NAME] گسترش و نوسازی صنایع ایرانیان مانا ( سهامی خاص )
 | یادداشتهای توضیحی صورتهای مالی
 | دوره مالي شش ماهه منتهي به 31 خرداد ماه 1390
 | 4-3- موجودي تنخواه گردانها متشکل از اقلام ذیل می باشد :
 |  | يادداشت |  | 1390/03/31 |  | 1389/09/30
 |  |  |  | ریال |  | ریال
 | کارگاهها و دفتر مرکزی | 4-3-1 |  |  |  | 3613832378
 | دفتر مرکزی - ارزی ( 5267 دلار ) |  |  | 0 |  | 124934784
 | [NAME] آلات |  |  | 0 |  | 150000000
 | 4-3-1- موجودی تنخواه گردان کارگاهها و دفتر مرکزی متشکل از اقلام ذیل می باشد:
 |  |  |  | 1390/03/31 |  | 1389/09/30
 |  |  |  | ریال |  | ریال
 | [NAME] صادرات مشهد |  |  | 3441721520 |  | 299024099
 | سالن ورزشی شیراز |  |  | 10694 |  | 1511361
 | طرح میدان شهداء مشهد |  |  | 661573564 |  | 1822039408
 | کارگاه سرمایه گذاری [NAME] |  |  | 22428618 |  | 82819005
 | کارگاه آلومینیوم اراک |  |  | 35964200 |  | 835243
 | موننکو ایران |  |  | 1000000 |  | 64087590
 | کارگاه 35 متری بلوار معلم |  |  | 2647782563 |  | 31833957
 | [NAME] |  |  | 0 |  | 208888151
 | کارگاه استادیوم 50 هزار نفری شیراز |  |  | 957062383 |  | 152721660
 | [NAME] احمر استان فارس |  |  | 54086990 |  | 101942624
 | کارگاه تصفیه آب شرب مشهد |  |  | 147014285 |  | 320657515
 | کارگاه احداث کارخانه کک سازی زرند |  |  | 20046976 |  | 292546961
 | مشارکت فام-پروژه سیویل کنسانتره جلال آباد زرند |  |  | 720222253 |  | 25633956
 | کارگاه فرآوران ذغالسنگ پابدانا |  |  | 678657578 |  | 203662278
 | سایر |  |  | 1131758121 |  | 5628570
 | 5-حسابها ی دريافتنی تجاری  :
 | شــــــــرح | يادداشت |  | 1390/03/31 |  | 1389/09/30
 |  |  |  | ریال |  | ریال
 | بدهی کارفرمايان | 5-1
 | مشارکتها | 5-2 |  | 588623585
 | [NAME]
Spreadsheet: 160132d1338983974-how-to-simplify-criteria-conditions-for-dget-formula-proyecto-oeldere-
Sheet: Sales Monthly

 |  |  |  |  |  | Sales in 2011
 | Sold To | Company Name | Details | Note | Sales | 2011-01-01 00:00:00 | 2011-02-01 00:00:00 | 2011-03-01 00:00:00 | 2011-04-01 00:00:00 | 2011-05-01 00:00:00 | 2011-06-01 00:00:00 | 2011-07-01 00:00:00 | 2011-08-01 00:00:00 | 2011-09-01 00:00:00 | 2011-10-01 00:00:00 | 2011-11-01 00:00:00 | 2011-12-01 00:00:00 | YTD
 | 10926576 | Client 6 |  |  | Fixed NO | 0 |  |  |  |  |  |  |  |  |  |  |  | 0
 |  |  |  |  | Variable |  |  |  |  |  |  |  |  |  |  |  |  | 0
 |  |  |  |  | NO | #N/A |  |  |  |  |  |  |  |  |  |  |  | #N/A
 |  |  |  |  | PO |  |  |  |  |  |  |  |  |  |  |  |  | 0
 |  |  |  |  | AO |  |  |  |  |  |  |  |  |  |  |  |  | 0
 |  |  |  |  | CO |  |  |  |  |  |  |  |  |  |  |  |  | 0
 | 10904703 | Client 21 |  |  | Fixed NO | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 9124.6 | 109495.2
 |  |  |  |  | Variable
 |  |  |  |  | NO
 |  |  |  |  | PO
 |  |  |  |  | AO
 |  |  |  |  | CO
 | etc
 |  | Find the Client by the "Sold To" number and return all the sales for each month where Column 3 data ended in NO  or AO  or PO…etc
 | etc
 |  | Data in Raw data will always have the same number of columns but the number of rows will change depending if there was a a sale on the month or not.
 | (*) | For the Fixed cost in the current year, the data that i need to bring over to the Sales Monthly Sheet will always be in Column 8 and the data in Column 3 will end in "NO"
 | (*) | For the variable cost in the current year, the data that i need to bring over to the Sales Monthly Sheet will always be in Column 10 and the data in Column 3 will end in "NO" or "AO" or "PO" or "CO"
 |  | i tried using the DGET formula but the criteria will change by date and by Material Type (ending NO, PO, AO or CO) and this will mean that i need to create an enourmous matrix with all the different conditions.
 |  | I need something more automatic and simpler if possible
Spreadsheet: 707620d1607370415-calculating-pto-sample
Sheet: Sheet1

 |  |  |  |  |  | 1.25
Employee Names | Start Date | # of Days | comments
 | 2020-03-24 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00 |  | 2 rollover days from 2019
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-01-01 00:00:00
 | 2020-02-10 00:00:00
 | 2020-02-10 00:00:00
Spreadsheet: 270671d1381581138-nested-if-vlookup-formula-breaks-when-lookup-value-changes-colin-12-oct-13-v2
Sheet: DBM

date and IO | Date | Campaign name |  |  |  | Total cost
 | 2013-10-01 00:00:00 | UK - Chevrolet - Retail Q4 - Oct-Dec '13 |  |  |  | 65.67
 | 2013-10-01 00:00:00 | BE - Telenet - King Kong - Oct' 13 - DR |  |  |  | 66.67
 | 2013-10-02 00:00:00 | UK - Chevrolet - Retail Q4 - Oct-Dec '13 |  |  |  | 67.67
 | 2013-10-02 00:00:00 | BE - Telenet - King Kong - Oct' 13 - DR |  |  |  | 68.67
 | 2013-10-03 00:00:00 | UK - Chevrolet - Retail Q4 - Oct-Dec '13 |  |  |  | 69.67
 | 2013-10-03 00:00:00 | BE - Telenet - King Kong - Oct' 13 - DR |  |  |  | 70.67
Spreadsheet: 1fe98130-b1a4-471d-85f9-88d59326acaf
Sheet: 13c

 | Swap Dealers/MSPs5 |  | Others
Product1 | Cleared2 | Uncleared | Cleared | Uncleared
Index Tranche | 0 | 1491884 | 0 | 206468
Europe | 0 | 695262 | 0 | 105046
North America/Asia | 0 | 796622 | 0 | 101422
Index | 3619657 | 7193240 | 964147 | 2208845
Asia | 0 | 175299 | 0 | 46463
Europe | 1616904 | 3532536 | 462868 | 931803
North America | 1981034 | 3101280 | 495828 | 1173018
Other | 21719 | 384125 | 5451 | 57561
Other | 0 | 940786 | 0 | 417233
Exotic/Total Return Swap | 0 | 57245 | 0 | 29677
Swaptions | 0 | 883541 | 0 | 387556
TOTAL | 3619657 | 9625910 | 964147 | 2832546
Spreadsheet: 268477d1380650823-sla-calculator-sla-calculator
Sheet: Sheet1

Date Logged | Time Logged | Priority | Contract | SLA Expiry Date & Time
2013-10-01 00:00:00 | 09:00:00 | 1 | Enhanced | date here | time here
 |  | 1 | Enhanced
 |  | 2 | 24h
Priority 1 = 6 hours
Priority 2 = 10 hours
Contract:
Standard 8am - 8pm
Enhanced 6:30am-10:30pm
24h - 24h
Spreadsheet: 748984d1632443995-sumifs-offset-how-to-combine-successfully-example111
Sheet: Sheet1

Area | Items | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec
1 | 111 | 5 | 4 | 3 | 5 | 4 | 3 | 5 | 4 | 3 | 5 | 4 | 3 |  | Sum this many months | 9
1 | 112 | 1 | 1 | 5 | 1 | 1 | 5 | 1 | 1 | 5 | 1 | 1 | 5 |  | Area | 2
1 | 113 | 3 | 2 | 4 | 3 | 2 | 4 | 3 | 2 | 4 | 3 | 2 | 4
1 | 114 | 6 | 9 | 8 | 6 | 9 | 8 | 6 | 9 | 8 | 6 | 9 | 8 |  |  |  | Results
2 | 111 | 5 | 4 | 3 | 5 | 4 | 3 | 5 | 4 | 3 | 5 | 4 | 3 |  | Items | 111 | sum this many months "Q2", sum this area"Q3", sum items "Q6"
2 | 112 | 1 | 1 | 5 | 1 | 1 | 5 | 1 | 1 | 5 | 1 | 1 | 5 |  |  | 112 | same as above
2 | 113 | 3 | 2 | 4 | 3 | 2 | 4 | 3 | 2 | 4 | 3 | 2 | 4 |  |  | 113 | same as above
2 | 114 | 6 | 9 | 8 | 6 | 9 | 8 | 6 | 9 | 8 | 6 | 9 | 8 |  |  | 114 | same as above
7 | 111 | 5 | 4 | 3 | 5 | 4 | 3 | 5 | 4 | 3 | 5 | 4 | 3
7 | 112 | 1 | 1 | 5 | 1 | 1 | 5 | 1 | 1 | 5 | 1 | 1 | 5
7 | 113 | 3 | 2 | 4 | 3 | 2 | 4 | 3 | 2 | 4 | 3 | 2 | 4
7 | 114 | 6 | 9 | 8 | 6 | 9 | 8 | 6 | 9 | 8 | 6 | 9 | 8
Spreadsheet: 5c8a6216-13bc-4f81-a18a-42e751d638b4
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
TUNA | Test | TUNA | Tuna, IgE | Tuna, IgE | Fluorescence Enzyme Immunoassay (FEIA) | Serum Gel Tube: SGT |  |  | 0.5 | mL | Container/Tube: Preferred: Red top Acceptable: Serum gel [NAME]: 0.5 mL for each 5 allergens requested Additional Information: Designate specific allergens from the list in Allergens-IgE Antibodies in Special Instructions. Forms: If not ordering electronically, submit an Allergen Request Form (Supply T236) with the specimen. | For 1 allergen: 0.3 mL/For more | Hemolysis	Mild OK; Gross OK Thawing	Warm reject; Cold OK Lipemia	Mild OK; [NAME] OK Icterus	NA Other	NA | Class	IgE kU/L	Interpretation 0	<0.35	Negative 1	0.35-0.69	Equivocal 2	0.70-3.49	Positive 3	3.50-17.4	Positive 4	17.5-49.9	Strongly positive 5	50.0-99.9	Strongly positive 6	> or =100	Strongly positive Reference values apply to all ages. | Monday through Friday; 9 a.m.-8 p.m., Saturday; 8 a.m.-3 p.m. | Same day/1 day | 3 days | 1 | 86003 |  |  |  |  | Rochester
TUNA | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 14 days
TUNA | Result | TUNA | Tuna, IgE | Tuna, IgE | Numeric |  |  |  |  | kU/L |  |  |  |  |  |  |  |  |  | 6270-3
Spreadsheet: 03988ff7-178a-45aa-b472-4329f5d357ea
Sheet: Sheet1

Table 2.2c: Export and Import Price Indices | 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 | Unnamed: 14 | Unnamed: 15 | Unnamed: 16
Indicator | Partner State | 2000 | 2001 | 2002 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011
Export price index | Burundi | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | Tanzania, 1991=100 | 100 | 129.8082545521785 | 139.5800292748679 | 100 | 129.8082545521785 | 139.5800292748679 | 158.9925376589068 | 191.5257180730609 | 216.378317551134 | 236.3719805104564 | 263.9 | 291 | 0 | 0 | 0
 | Uganda | 0 | 0 | 75.5 | 91.1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | Kenya, 2009=100 | 620 | 637 | 657 | 620 | 637 | 657 | 620 | 638 | 677 | 869 | 83 | 99 | 100 | 111 | 132
 | Rwanda, 2000=100 | 0 | 125.7 | 94.7 | 0 | 125.7 | 94.7 | 116.8 | 158.8 | 183.8 | 205.5 | 242.9 | 283.4 | 261.1 | 322.1702552243298 | 464.2
 | EAST AFRICA | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Import price index | Burundi | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | Tanzania, 1991=100 | 100 | 107.790909753332 | 104.5797313049338 | 100 | 107.790909753332 | 104.5797313049338 | 129.7165377298316 | 168.663133653792 | 205.1191212906815 | 249.4403500182859 | 289.6 | 321.5 | 0 | 0 | 0
 | Uganda | 0 | 0 | 95.8 | 103.4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | Kenya, 1982=100 | 739 | 807 | 847 | 739 | 807 | 847 | 762 | 824 | 942 | 1215 | 110 | 130 | 100 | 126 | 157
 | Rwanda, 2000=100 | 0 | 134.1 | 131.4 | 0 | 134.1 | 131.4 | 154.7 | 170.2 | 171.4 | 157.9 | 161.4 | 225.4 | 196.2 | 212.4781615967849 | 227.4
 | EAST AFRICA | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Note: Indicies for Kenya before 2007 refer to base period 1982.
Source: Partner States
Table 2.2d: Producer Price Index
Partner State |  | 2000 | 2001 | 2002 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011
Burundi, 1999=100 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 93 | 91.8 | 95.2 | 96.5 | 98.2 | 95.9 | 111.9 | 120.2
Tanzania, 1995=100 |  | 284 | 302 | 322 | 142.5 | 188 | 171 | 192 | 272 | 276 | 324 | 335 | 404 | 212 | 224 | 0
Uganda, July 2004-Sept 2004=100 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 106 | 117 | 126.68 | 156.98 | 170.34 | 184.33 | 240.23
Kenya |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Rwanda, 2003=100 |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 107.4 | 117.1 | 121.4 | 127.5 | 149 | 155 | 161 | 170.1
EAST AFRICA |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Source: Partner States
Spreadsheet: a6b73234-92d6-42ae-b3cb-db48dbaaaf45
Sheet: Sheet1

Table 1--U.S. rice supply and use  1/ | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7
Item | 2007/08 | 2008/09 | 2009/10 | 2010/11 | 2011/12 | 2012/13 | 2013/14
 |  |  |  |  |  |  | 2/
TOTAL RICE |  |  |  | Million acres
Area:
Planted | 2.761 | 2.995 | 3.135 | 3.636 | 2.689 | 2.7 | 2.489
Harvested | 2.748 | 2.976 | 3.103 | 3.615 | 2.617 | 2.679 | 2.468
 |  |  |  | Pounds per harvested acre
Yield | 7219 | 6846 | 7085 | 6725 | 7067 | 7449 | 7694
 |  |  |  | Million cwt
Beginning stocks | 39.315 | 29.492 | 30.419 | 36.499 | 48.467 | 41.079 | 36.423
Production | 198.388 | 203.733 | 219.85 | 243.104 | 184.941 | 199.546 | 189.886
Imports | 23.9 | 19.218 | 19.023 | 18.338 | 19.359 | 21.062 | 21
Total supply | 261.603 | 252.443 | 269.292 | 297.941 | 252.767 | 261.687 | 247.309
Food, industrial,
& residual 3/ | 123.152 | 123.77 | 119.947 | 133.603 | 107.505 | 115.105
Seed | 3.697 | 3.87 | 4.488 | 3.324 | 3.332 | 3.067
Total domestic use | 126.849 | 127.64 | 124.435 | 136.927 | 110.837 | 118.172 | 120
Exports | 105.262 | 94.384 | 108.358 | 112.547 | 100.851 | 107.092 | 100
Rough | 37.663 | 31.633 | 40.351 | 34.595 | 32.94 | 34.165 | 36
Milled 4/ | 67.599 | 62.751 | 68.007 | 77.952 | 67.911 | 72.927 | 64
Total use | 232.111 | 222.024 | 232.793 | 249.474 | 211.688 | 225.264 | 220
Ending stocks | 29.49200000000002 | 30.41899999999998 | 36.49900000000002 | 48.46700000000004 | 41.07900000000004 | 36.423 | 27.309
 |  |  |  | Percent
Stocks-to-use ratio | 12.70598980660116 | 13.70077108781032 | 15.6787360444687 | 19.42767582994622 | 19.40544575034959 | 16.16902834008097 | 12.41318181818182
 |  |  |  | $/cwt
Average farm |  |  |  |  |  |  | 15.70 to
price 5/ | 12.8 | 16.8 | 14.4 | 12.7 | 14.5 | 15.1 | 16.3
 |  |  |  | Percent
Average
milling rate | 69.88 | 70.83 | 71.53 | 68.86 | 69.93 | 70 | 71
N/A = not available.  1/ August-July market year; rough equivalent.  2/ Projected.  3/ Residual includes unreported
use, processing losses, and estimating errors.  4/  Rough-rice equivalent.  5/ Market-year weighted average.
Source: World Agricultural Supply and Demand Estimates, WAOB, USDA.
Updated February 10, 2014.
Spreadsheet: 647755d1572612677-closest-match-with-multiple-criteria-3-criteria-boxes-breakdown-closest-match-sample
Sheet: Sheet1

ID | length | width |  |  |  | [NAME] | length | width
1 | 600 | 400 |  |  |  | Cont1 | 450 | 305
2 | 400 | 300 |  |  |  | Cont2 | 800 | 500
3 | 200 | 150 |  |  |  | Cont3 | 600 | 402
 |  |  |  |  |  | Cont4 | 250 | 200
 |  | WORKING
ID | length | width | depth |  |  | [NAME] | length | width | depth
1 | 600 | 400 | 119 |  |  | Cont1 | 450 | 305 | 430
2 | 400 | 300 | 220 |  |  | Cont2 | 800 | 500 | 135
3 | 200 | 150 | 420 |  |  | Cont3 | 600 | 402 | 250
 |  |  |  |  |  | Cont4 | 250 | 200 | 175
 |  | DON'T KNOW HOW TO GET WORKING
 | MOCKUP: | For ID 1
 | Length 600 matches: |  | Cont2 |  | CLOSEST MATCH |  |  | ANSWER:
 |  |  | Cont3 |  | Cont3 |  |  | Cont3
 | [NAME] 400 matches: |  | Cont2 |  | CLOSEST MATCH
 |  |  | Cont3 |  | Cont3
 | Depth 119 matches: |  | Cont2 |  | CLOSEST MATCH
 |  |  | Cont3 |  | Cont2
Spreadsheet: 32410cbb-212c-4f07-a0de-b6fd8b1c4960
Sheet: Sheet1

Adults Age 18 Years and Over With Current Asthma, Maine 2002-2010 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6
 | unweighted number | weighted number |  | % | LCL | UCL
Year
2002 | 255 | 99097.18861811371 |  | 10.04572075885014 | 8.714130949350405 | 11.37731056834988
2003 | 235 | 98475.45195235642 |  | 9.85526455620719 | 8.482694448436531 | 11.22783466397785
2004 | 346 | 98627.43351534195 |  | 9.639828693234016 | 8.464731416135756 | 10.81492597033228
2005 | 390 | 105581.8549760853 |  | 10.2461580714587 | 8.993233805214015 | 11.49908233770339
2006 | 408 | 100915.2846072373 |  | 9.676888773248093 | 8.578190435752706 | 10.77558711074348
2007 | 694 | 107576.1862213156 |  | 10.25593469522448 | 9.264098469274613 | 11.24777092117436
2008 | 683 | 107555.770418245 |  | 10.30381490172662 | 9.337652596140309 | 11.26997720731293
2009 | 848 | 112578.137125356 |  | 10.82638920659772 | 9.884109549737921 | 11.76866886345751
2010 | 843 | 103702.1370182384 |  | 9.981670397443672 | 9.10325316709372 | 10.86008762779362
Data Source:  Maine Behavioral Risk Factor Surveillance System.
All percentges are weighted to be more representative of the general child population of Maine and to adjust for non-response.
LCL = Lower confidence limit; UCL = Upper confidence limit
Spreadsheet: 713331d1610648213-sum-of-interval-overlapping-dates-with-gaps-multiple-rows-per-user-example-file2
Sheet: Sheet1

Issue Date | Expiration Date | User Defined Field | New Issue Date | New Expiration Date
07/10/1996 | 12/31/2020 | 1
11/22/1986 | 11/30/1987 | 2
08/24/1987 | 02/28/2021 | 2
11/21/1972 | 06/30/1980 | 3
10/20/1980 | 1991-07-31 00:00:00 | 3
08/24/1987 | 07/31/2021 | 3
05/01/1989 | 04/30/1990 | 3
Spreadsheet: 122953d1317256807-sumproduct-with-multiple-criteria-test
Sheet: Sheet1

Name | customer code | Trans action | Amount | CN | RI
TEST 1 | 125 | NB | 800
TEST 2 | 126 | CN | -200
TEST 3 | 127 | NB | 500
TEST 1 | 125 | CN | -100
TEST 2 | 126 | CN | -50
TEST 3 | 127 | CN | -500
TEST 1 | 125 | RI | 300
TEST 2 | 126 | RI | 50
TEST 3 | 127 | RI | 25
TEST 1 | 125 | RI | 75
TEST 2 | 126 | RI | 400
TEST 3 | 127 | RI | 200
Spreadsheet: e20f5341-251e-4e89-8427-8edbfa1291c4
Sheet: Sheet1

Representative in Congress - DEM (North Dakota) | Unnamed: 1 | Unnamed: 2
Downloaded at 5/22/2013 9:04:40 PM
Precincts Reporting: 565/565 - Total Ballots Cast: 111325
2006 Primary Election - OFFICIAL RESULTS
Precinct | [NAME] | TOTALS
Precinct 1002 | 102 | 102
Precinct 1003 | 75 | 75
Precinct 1501 | 293 | 293
TOTAL | 470 | 470
Results provided by the Office of North Dakota Secretary of State