tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 849975d1700350309-nested-if-with-and-or-and-equations-new-microsoft-excel-worksheet
Sheet: Sheet1

Entry $ | Total Ent. | [NAME] | Pays | Min Cash | 1st | 5th | 10th |  |  |  | Result
300 | 5 | 1 | 0.2 | 4.5 | 1350 | - | - |  |  |  | 1
300 | 6 | 1 | 0.3333 | 1.8 | 1080 | - | - |  |  |  | 1
300 | 7 | 1 | 0.2857 | 2.333333333333333 | 1200 | - | - |  |  |  | 1
300 | 11 | 1 | 0.2212 | 1.5 | 1500 | - | - |  |  |  | 1
300 | 14 | 1 | 0.2857 | 2 | 1500 | - | - |  |  |  | 1
300 | 17 | 1 | 0.2353 | 1.666666666666667 | 2000 | - | - |  |  |  | 1
555 | 134 | 4 | 0.2015 | 1.801801801801802 | 20000 | 3000 | 1500 |  |  |  | 4.054054054054054
555 | 170 | 5 | 0.2235 | 1.801801801801802 | 20000 | 3000 | 2000 |  |  |  | 4.504504504504505
555 | 200 | 6 | 0.2 | 1.801801801801802 | 20000 | 4000 | 2000 |  |  |  | 5.405405405405405
555 | 240 | 7 | 0.1917 | 1.801801801801802 | 30000 | 5000 | 1500 |  |  |  | 5.855855855855856
555 | 300 | 9 | 0.2167 | 1.801801801801802 | 50000 | 3000 | 2000 |  |  |  | 4.504504504504505
555 | 400 | 12 | 0.22 | 1.801801801801802 | 50000 | 5000 | 2000 |  |  |  | 6.306306306306307
1060 | 4 | 1 | 0.2 | 3.773584905660377 | 4000 | - | - |  |  |  | 1
1060 | 6 | 1 | 0.3333 | 1.886792452830189 | 4000 | - | - |  |  |  | 1
1060 | 8 | 1 | 0.25 | 2.830188679245283 | 5000 | - | - |  |  |  | 1
1060 | 10 | 1 | 0.3 | 1.886792452830189 | 5000 | - | - |  |  |  | 1
1060 | 12 | 1 | 0.25 | 1.886792452830189 | 6000 | - | - |  |  |  | 1
1060 | 15 | 1 | 0.2 | 1.886792452830189 | 8000 | - | - |  |  |  | 1
1 | 59 | 1 | 0.2542 | 1.5 | 10 | 3 | 2 |  |  |  | 1
1 | 89 | 2 | 0.2697 | 2 | 7.5 | 4 | 3 |  |  |  | 2
1 | 118 | 3 | 0.2288 | 2 | 12 | 5 | 3 |  |  |  | 3
1 | 178 | 5 | 0.236 | 1.5 | 30 | 5 | 3 |  |  |  | 4
1 | 237 | 7 | 0.2321 | 1.5 | 40 | 7.5 | 5 |  |  |  | 6.25
1 | 297 | 8 | 0.229 | 0 | 50 | 7.5 | 5 |  |  |  | 6.25
1 | 356 | 10 | 0.2331 | 1.5 | 50 | 10 | 5 |  |  |  | 7.5
1 | 416 | 12 | 0.2212 | 2 | 40 | 10 | 7 |  |  |  | 8.5
1 | 475 | 14 | 0.2295 | 2 | 50 | 11 | 6 |  |  |  | 14
1 | 594 | 17 | 0.229 | 1.5 | 50 | 16 | 9 |  |  |  | 12.5
1 | 743 | 20 | 0.2369 | 1.5 | 60 | 20 | 10 |  |  |  | 20
1 | 891 | 20 | 0.229 | 1.5 | 100 | 25 | 10 |  |  |  | 20
1 | 1189 | 20 | 0.2397 | 1.5 | 100 | 30 | 15 |  |  |  | 20
1 | 1486 | 20 | 0.186 | 1.5 | 125 | 50 | 15 |  |  |  | 13
1 | 1783 | 20 | 0.165 | 1.5 | 150 | 30 | 15 |  |  |  | 15
1 | 2080 | 20 | 0.2692 | 1.5 | 150 | 35 | 15 |  |  |  | 20
1 | 2378 | 20 | 0.259 | 1.5 | 200 | 35 | 20 |  |  |  | 20
Spreadsheet: 197433d1354353338-remove-certain-information-from-a-list-and-auto-create-new-list-on-other-sheet-01122012-enquiry
Sheet: DataBase

s/n | File Number | Name | ID | Status | Salary Mode
1 | K85465854 | [NAME] | 456841 | Present | Monthly
2 | K85465855 | Florence Garragh | 513512 | Present | Monthly
3 | K85465856 | [NAME] | 584381 | Present | Monthly
4 | [NAME] | [NAME] | 251001 | Resigned | Monthly
5 | K85465858 | [NAME] | 213510 | Present | Monthly
6 | K85465859 | [NAME] | 512358 | Resigned | Monthly
7 | K85465860 | Smalling Rach | 852852 | Resigned | Monthly
8 | [NAME] | [NAME] | 741596 | Present | Monthly
9 | K85465862 | [NAME] | 584623 | Present | Monthly
10 | K85465863 | Faith [NAME] | 584624 | Resigned | Monthly
11 | K85465864 | Simone Flower | 584625 | Resigned | Monthly
12 | K85465865 | [NAME] | 584626 | Present | Monthly
13 | K85465866 | [NAME] | 584627 | Present | Monthly
14 | K85465867 | [NAME] | 584628 | Present | Monthly
15 | K85465868 | [NAME] | 584629 | Present | Monthly
16 | K85465869 | Web Stone | 584630 | Present | Monthly
17 | K85465870 | [NAME] | 584631 | Present | Monthly
18 | [NAME] | [NAME] | 584632 | Present | Monthly
19 | K85465872 | [NAME] | 584633 | Present | Monthly
20 | K85465873 | [NAME] | 584634 | Present | Monthly
21 | K85465874 | [NAME] | 584635 | Present | Monthly
22 | K85465875 | [NAME] | 584636 | Present | Monthly
23 | K85465876 | Morinho Presley | 584637 | Resigned | Monthly
24 | K85465877 | [NAME] | 584638 | Present | Monthly
25 | K85465878 | [NAME] | 584639 | Resigned | Monthly
26 | K85465879 | [NAME] | 584640 | Present | Monthly
27 | [NAME] | [NAME] | 584641 | Present | Monthly
28 | K85465881 | [NAME] | 584642 | Resigned | Monthly
29 | K85465882 | [NAME] | 584643 | Present | Monthly
30 | [NAME] | Venus Gorth | 584644 | Present | Monthly
31 | [NAME] | Stam [NAME] | 584645 | Present | Monthly
32 | K85465885 | [NAME] | 584646 | Resigned | Monthly
33 | K85465886 | [NAME] | 584647 | Present | Monthly
Spreadsheet: 880181d1727797747-small-cash-book-for-a-dog-club-daliti-club-tms-v2
Sheet: Blad2

What | Person | Amount | Food | Costs | Transport | Membership | Training | Glasses
Item A |  | 100 |  |  | 100
Item B |  | 80 |  | 20 | 50 | 30
Item C |  | 50
Item D |  | 30
Item E |  | 40
[NAME] |  | 100
Spreadsheet: 776812d1649926493-automatically-copy-data-into-summary-book1-input
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  | Name |  | Date | Chit |  | Score
 |  |  |  |  |  |  |  |  |  | [NAME] |  | 2021-12-12 00:00:00 | S 015 |  | 2614.75
 |  |  |  |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  |  |  |  |  | [NAME] |  | 2021-12-18 00:00:00 | M 014 |  | 1899.18
 |  |  |  |  |  |  |  |  |  | [NAME] |  | 2022-01-04 00:00:00 | S 016 |  | 1874.23
 |  |  |  |  |  |  |  |  |  | AAA
 |  |  |  |  |  |  |  |  |  | AAA
 |  |  |  |  |  |  |  |  |  | AAA |  | 2022-01-05 00:00:00 | L 093 |  | 2255.24
 |  |  |  |  |  |  |  |  |  | BBB
 |  |  |  |  |  |  |  |  |  | BBB
 |  |  |  |  |  |  |  |  |  | BBB |  | 2022-02-16 00:00:00 | J 1224 |  | 2167.76
 |  |  |  |  |  |  |  |  |  | CCC
 |  |  |  |  |  |  |  |  |  | CCC |  | 2022-03-08 00:00:00 | M 015 |  | 2350.48
Spreadsheet: 735438d1622991334-average-multiple-rows-in-multiple-columns-based-off-multiple-criteria-points-test-sheet-avg-rop-calculator
Sheet: Avg ROP

Manual Fill In Operator and [NAME] |  | Phases | SUR: Surface |  |  |  | INT: Intermediate |  |  |  | INT2: Intermediate 2 |  |  |  | INT2: Intermediate 2 / CRV: CURVE |  |  |  | CRV/LAT: CURVE/LATERAL |  |  |  | LAT: Lateral |  |  |  | Overall Performance
 |  |  | ROTATE ROP | SLIDE ROP | AVG ROP |  | ROTATE ROP | SLIDE ROP | AVG ROP |  | ROTATE ROP | SLIDE ROP | AVG ROP |  | ROTATE ROP | SLIDE ROP | AVG ROP |  | ROTATE ROP | SLIDE ROP | AVG ROP |  | ROTATE ROP | SLIDE ROP | AVG ROP |  | ROTATE ROP | SLIDE ROP | AVG ROP
Operator | [NAME]
A | 1
B | 2
C | 3
D | 4
E | 5
F | 6
G | 7
Spreadsheet: 267357d1380052350-use-selections-from-two-data-validation-lists-to-lookup-and-return-a-mailing-address-state-county-fips-codes
Sheet: OHIO-34

 | COUNTY | CODE
 | Adams | 1
 | [NAME]
 | Ashland
 | Ashtabula
 | Athens
 | Auglaize
 | Belmont
 | [NAME]
 | Butler
 | Carroll
 | Champaign
 | [NAME]
 | Clermont
 | [NAME]
 | [NAME]
 | Coshocton
 | Crawford
 | Cuyahoga
 | Darke
 | Defiance
 | Delaware
 | Erie
 | Fairfield
 | Fayette
 | Franklin
 | Fulton
 | Gallia
 | [NAME]
 | Greene
 | Guernsey
 | [NAME]
 | Hancock
 | Hardin
 | [NAME]
 | [NAME]
 | Highland
 | Hocking
 | [NAME]
 | Huron
 | [NAME]
 | [NAME]
 | Knox
 | Lake
 | [NAME]
 | Licking
 | Logan
 | Lorain
 | Lucas
 | [NAME]
 | Mahoning
 | Marion
 | Medina
 | Meigs
 | Mercer
 | Miami
 | Monroe
 | Montgomery
 | Morgan
 | Morrow
 | Muskingum
 | Noble
 | Ottawa
 | Paulding
 | [NAME]
 | Pickaway
 | Pike
 | Portage
 | Preble
 | Putnam
 | Richland
 | [NAME]
 | Sandusky
 | Scioto
 | Seneca
 | Shelby
 | [NAME]
 | Summit
 | Trumbull
 | Tuscarawas
 | Union
 | Van Wert
 | Vinton
 | [NAME]
 | Washington
 | Wayne
 | [NAME]
 | Wood
 | Wyandot
Spreadsheet: 709061d1608141448-averaging-multiple-columns-average-mult-columns-help
Sheet: Sheet1

Name | Question 1 | Question 2 | Question 3 | Question 4 | Question 5 |  |  | Name: | [NAME] | <-- Enter name (in this case [NAME] or [NAME]) to generate averages below
[NAME] | 3 | 2 | 3 | 2 | 4 |  |  | Average 1: |  | <-- Average of columns B, D, and F
[NAME] | 4 | 3 | 4 | 2 | 4 |  |  | Average 2: |  | <-- Average of columns C, E
[NAME] | 3 | 2 | 5 | 3 | 3
[NAME] | 3 | 1 | 5 | 3 | 5
[NAME] | 1 | 3 | 5 | 3 | 2
[NAME] | 2 | 2 | 4 | 3 | 2
[NAME] | 2 | 3 | 4 | 4 | 1
[NAME] | 1 | 3 | 4 | 4 | 2
[NAME] | 3 | 4 | 1 | 5 | 3
Spreadsheet: 0da38198-f65d-46aa-8b35-29d9c607ba30
Sheet: Sheet1

Table 6--Cottonseed oil:  U.S. supply and disappearance | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9
 |  | Supply |  |  |  |  | Disappearance
Year begin. | Beginning |  |  |  |  |  |  |  | Ending
Oct. 1 | stocks | Imports | Production | Total |  | Domestic | Exports | Total | stocks
 |  |  |  | Million pounds
2010/11 | 92.539 | 0.202 | 835 | 927.741 |  | 598.913 | 163.828 | 762.741 | 165
2011/121 | 165 | 10 | 755 | 930 |  | 565 | 265 | 830 | 100
2012/132 | 100 | 0.3 | 830 | 930.3 |  | 700.3 | 130 | 830.3 | 100
1 Estimated.  2 Forecast.
Source:  USDA, Foreign Agricultural Service, PS&D Online.
Last update: | 2012-08-13 23:20:58.040000
Spreadsheet: 883397d1732021897-formula-error-help-ogecen-formul-error-v2-365-aligw
Sheet: MİP

Start Date | 2024-11-12 00:00:00 | Finish Date | 2024-11-12 00:00:00
GENEL BİLGİLER
Machine | Product Code | Product Description | Amount
Spreadsheet: 01126d27-02bc-4bc4-8cb3-dc4c56173d79
Sheet: Sheet1

Segment | Basin Characteristics | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Basin Land Use | Unnamed: 6 | Unnamed: 7 | [NAME] (2004) | [NAME] (2004) | Slope (ft/mile)
 | Ecoregion | Climate | Bedrock Geology | Hydrogeology ([NAME]) | Major Tributaries | Drainage Area (km2) | Percentage of Anthropogenic Land Use (1999)
[NAME] | Northern Lakes and Forests | USDA Zone 3 | Precambrian lava flows | Precambrian igneous and metamorphic rocks | Upper St. Croix River | 1649(2) | Rare | Well vegetated | Diverse particles in nine reaches; characterized with boulders | 6
II. Namekagon River - Yellow River |  |  |  |  | Namekagon River | 1482(2) | 0.025 |  | Reach 1: Diverse particles, but boulder is rare | 1.1
 |  |  |  |  | [NAME] | 245(1) | 0.024 |  | Reach 2: Sands and gravles dominate
III. Yellow River - Kettle River |  |  |  |  | Yellow River | 945(2) | 0.212 |  | Reach 1 & 2: Sands and gravels dominate | Reach 1: 1.1
 |  |  |  |  | Lower Tamarack River | 470(1) | 0.037
 |  |  |  |  | Crooked Creek | 244(1) | 0.175 |  | Reache 3: Diverse particles except sands | Reaches 2 & 3: 5.9
 |  |  |  |  | Clam River | 1049(2) | 0.324
 |  |  |  |  | Sand Creek |  | 0.232
 |  |  |  |  | Bear Creek
IV. Kettle River -  Snake River |  |  |  |  | Kettle River | 2805(2) | 0.273 |  | Reach 1: Diverse particles except sands | 5.9
 |  |  |  |  |  |  |  |  | Reach 2: Sands and gravels dominate
 |  |  |  |  |  |  |  |  | Reach 3: Diverse particles except boulder
[NAME] -  Sunrise River |  |  |  |  | Snake River | 2599(2) | 0.408 |  | Reach 1, 2 & 4: Diverse particles except boulder | 1.4
 |  |  |  |  | Wood River |  | 0.556 |  | Sands are also common in Reach 2
 | North Central Hardwood Forests |  | Cambrian sandstone | Mt. Simon-Hinckley-Fond du Lac | [NAME] |  |  |  | Reaches 3 & 5: Sands and gravels dominate
VI. Sunrise River - St. Croix Visitor Center |  |  |  |  | Sunrise River | 643(2) | 0.607 |  | Sands and gravles dominate (Neither was further divided into reaches) | 0.2
 |  |  |  |  | Trade River | 345(1) | 0.477
 |  |  |  |  | [NAME]
 |  |  | Precambrian lava flows
VII. Minnesota Interstate Park - Boomsite Park |  |  |  | Franconia-Ironton-Galesville (Minnesota) / Tunnel City-Wonewoc-Eau Claire (Wisconsin)
 |  |  | Cambrian sandstone
 |  | USDA Zone 4 | Ordovician dolmite |  |  |  |  |  |  | 0.3
 |  |  | Cambrian sandstone |  | Apple River | 1440(2) | 0.632
 |  |  |  |  | Silver Creek |  | 0.906
 |  |  |  |  | Brown Creek |  | 0.865
 |  |  |  |  | Willow River | 721(2) | 0.901
 |  |  |  |  | Valley Brook | 49(2) | 0.88
 |  |  |  |  | Kinnickinning River | 442(2) | 0.952
Note 1: The box heights of the segments are not propotional to the real lengths of the segments.
They are adjusted to the table content for the visualization convenience.
Note 2: The boundaries of the four Basin Characteristics categories are derived from the corrsponding maps.
They should be intermediate zones rather than clear-cut lines in real applications.
Note 3: (1) denotes the USGS report by [NAME] in 2003. (2) denotes the article by [NAME] in 1992.
Spreadsheet: 717646d1612789405-list-of-nearest-locations-in-a-lookup-to-a-given-lat-and-long-local-radius-locations-v2
Sheet: Lookup

 |  |  |  |  | Nearest |  |  |  | Local Radius
 |  | Lat | Long |  | ID | Dist | Cluster |  | ID | Dist | Cluster
Lookup |  | 52.71234 | -1.78945
Spreadsheet: 740055d1626167670-how-to-return-the-value-of-the-last-item-in-a-list-find-last-item-in-a-list-ans
Sheet: Sheet1

Latest Statistics
I want a formula to return the last item in each list below, with the reult displayed in the yellow highlight.
Economic Statistics
Date | Inflation rate | Money Supply $trillions | Gold Price
2020-12-31 00:00:00 | 0.011 | 20.1 | 1608.2
2021-04-30 00:00:00 | 0.028 | 21.9 | 1992.3
2021-05-31 00:00:00 | 0.047 |  | 1798.2
2021-06-30 00:00:00 |  |  | 1738.5
Spreadsheet: 872861d1719311028-transpose-row-data-to-columns-example-1
Sheet: Sheet1

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Date | Total | Nos | %
Date | 2014-07-01 00:00:00 |  |  | 2015-07-01 00:00:00 |  |  | 2016-07-01 00:00:00 |  |  | 2017-07-01 00:00:00 |  |  |  |  | 2014-07-01 00:00:00 | 831432.0644722196 | 10 | 0.1
Total | 831432.0644722196 |  |  | 894896.2574207592 |  |  | 955719.300573857 |  |  | 991473.3000295904 |  |  |  |  | 2015-07-01 00:00:00 | 894896.2574207592 | 15 | 0.15
Nos |  |  | 10 |  |  | 15 |  |  | 19 |  |  | 27 |  |  | 2016-07-01 00:00:00 | 955719.300573857 | 19 | 0.25
% |  | 0.1 |  |  | 0.15 |  |  | 0.25 |  |  | 0.45 |  |  |  | 2017-07-01 00:00:00 | 991473.3000295904 | 27 | 0.45
Spreadsheet: 743952d1628839747-count-specific-numbers-in-a-cell-and-not-characters-count-number-in-cells
Sheet: Plot Order All (2)

 |  |  |  | column to count he numbers only |  |  |  |  | this is the outcome I want
 |  |  | formula
 |  |  | 1 | 1 | 1 | The Lymner |  |  | 1
 |  |  | 1 | 1 | 2 | The Cutler |  |  | 1
 |  |  | 2 | 3 | 3-4 | The [NAME]-The Blacksmith |  |  | 2
 |  |  | 2 | 3 | 5-6 | The Thespian-The Tailor |  |  | 2
 |  |  | 1 | 1 | 7 | The Coppersmith M4(2) |  |  | 1
 |  |  | 1 | 1 | 8 | The Cobbler M4(2) |  |  | 1
 |  |  | 1 | 1 | 9 | The Mason |  |  | 1
 |  |  | 2 | 5 | 10-11 | The Joiner-The Joiner |  |  | 2
 |  |  | 1 | 2 | 12 | The Lymner |  |  | 1
 |  |  | 1 | 2 | 13 | The Lymner |  |  | 1
 |  |  | 1 | 2 | 14 | The Cobbler M4(2) |  |  | 1
 |  |  | 1 | 2 | 15 | The Cutler |  |  | 1
 |  |  | 2 | 5 | 16-17 | The [NAME]-The Blacksmith |  |  | 2
 |  |  | 3 | 12 | 18 - 19 - 20 | The Thespian-The Tailor |  |  | 3
 |  |  | 4 | 17 | 21 - 22 - 23 - 24 | The [NAME]-The Blacksmith - The Blacksmith-The Blacksmith |  |  | 4
Spreadsheet: 861763d1709607585-making-bulk-substitutions-from-list-sample-file
Sheet: Output

Text to Look for Value | The output
Kabul Afghanistan | Kabul ,Afghanistan
Tirana Albania | Tirana ,Albania
Algiers Algeria | Algiers ,Algeria
Andorra la Vella Andorra | Andorra la Vella ,Andorra
[NAME] | Luanda ,Angola
[NAME] Argentina | [NAME] ,Argentina
[NAME] | [NAME] ,[NAME]
Canberra Australia | Canberra ,Australia
[NAME] | Vienna ,Austria
[NAME] | Baku ,Azerbaijan
Nassau Bahamas | Nassau ,Bahamas
Manama Bahrain | Manama ,Bahrain
Dhaka Bangladesh | Dhaka ,Bangladesh
Bridgetown Barbados | Bridgetown ,Barbados
Minsk Belarus | Minsk ,Belarus
Brussels Belgium | Brussels ,Belgium
Belmopan Belize | Belmopan ,Belize
[NAME] | [NAME] ,Benin
Thimphu Bhutan | Thimphu ,Bhutan
Sucre Bolivia | Sucre ,Bolivia
Sarajevo Bosnia and Herzegovina | Sarajevo ,Bosnia and Herzegovina
Gaborone Botswana | Gaborone ,Botswana
Brasília Brazil | Brasília ,Brazil
[NAME] | [NAME] ,Brunei
Sofia Bulgaria | Sofia ,Bulgaria
Ouagadougou Burkina Faso | Ouagadougou ,Burkina Faso
[NAME] | Bujumbura ,Burundi
Phnom Penh Cambodia | Phnom Penh ,Cambodia
Yaoundé Cameroon | Yaoundé ,Cameroon
Ottawa Canada | Ottawa ,Canada
[NAME] | Praia ,Cape Verde
Bangui Central African Republic | Bangui ,Central African Republic
[NAME] | [NAME] ,Chad
Santiago Chile | Santiago ,Chile
Spreadsheet: 768044d1644806418-how-can-i-create-rows-automatically-when-new-data-emerge-automatic-row-creation
Sheet: Sheet1

 | bew | 100 | 10
 | edmundson | 100 | 50
 | plumbase | 200 | 70
 | cef | 300 | 50
 | bew | 100 | 40
 | edmundson | 200 | 60
 | tglynes | 100 | 40
 | edmundson | 300 | 800
 | bew | 400 | 900
 | edmundson | 200 | 100
 | bew | 100 | 700
 | cef | 100 | 900
 | cef | 300 | 400
 | bew | 100 | 200
Spreadsheet: 01d8bb0f-4c19-41fd-ad03-ec9799e1d47b
Sheet: FY 2001 Lease Turnover Analysis

FY 2001 Lease Turnover Analysis
Disposition Of Leases Expiring in FY 2001 | Sq Ft | % of Total Sq Ft | Count | % of Total Count
Leases Scheduled to Expire in FY 2001 | 23452652 | 1 | 1675 | 1
Extended in FY 2001 Beyond FY 2001 | 11702596 | 0.4989881741305844 | 746 | 0.4453731343283582
Renewed During FY 2001 | 1631423 | 0.06956241025535193 | 66 | 0.03940298507462687
Replaced in Same Building with New Leases | 3526517 | 0.1503675149403146 | 201 | 0.12
Subtotal | 16860536 | 0.7189180993262511 | 1013 | 0.604776119402985
Leases Terminated | 4970387 | 0.2119328338645881 | 527 | 0.3146268656716418
Leases Moved to Another Leased Building | 1621729 | 0.06914906680916086 | 135 | 0.08059701492537313
Subtotal | 6592116 | 0.2810819006737489 | 662 | 0.3952238805970149
Disposition of Leases Expiring After FY 2001
Leases Scheduled to Expire After FY 2001 | 127997374 | 1 | 5794 | 1
Lease Replaced In Same Leased Building After [NAME] | 269337 | 0.002104238482267613 | 13 | 0.002243700379703141
Lease Replaced In Same Leased Building Before Firm Term | 560874 | 0.004381918022786937 | 12 | 0.0020711080428029
Lease Replaced In Different Leased Building After [NAME] | 218044 | 0.001703503698443063 | 37 | 0.00638591646530894
Lease Replaced In Different Leased Building Before Firm Term | 15227 | 0.000118963378108054 | 5 | 0.0008629616845012082
Lease Terminate W/O Lease Replacement After [NAME] | 568641 | 0.00444259895519419 | 73 | 0.01259924059371764
Lease Terminate W/O Lease Replacement Before Firm Term | 422482 | 0.00330070834109456 | 15 | 0.002588885053503624
FY 2001 Lease Turnover
Total Leases At Start of FY 2001 | 151450026 | 1 | 7469 | 1
Same/Replacement Leases Continued Past FY 2001 | 143633516 | 0.948388850062 | 6677 | 0.8939617083946981
Same Lease Space Dis-Continued Past FY 2001 (Turnover) | 7816510 | 0.05161114993800001 | 792 | 0.1060382916053019
Spreadsheet: 759563d1639593412-error-trapping-if-and-multiple-cells-must-all-have-error-is-number
Sheet: Sheet1

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |  | CHECK | CHECK | CHECK | CHECK | CHECK | CHECK | CHECK | CHECK
5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |  |  |  |  |  |  |  |  |  |  | if statement here to check J through Q; if all are #N/A then write "error" otherwise stay blank
5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |  |  |  |  |  |  |  |  |  |  | if statement here to check J through Q; if all are #N/A then write "error" otherwise stay blank
 |  |  |  |  |  |  | 4 |  |  |  |  |  |  |  |  |  |  | if statement here to check J through Q; if all are #N/A then write "error" otherwise stay blank
5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |  |  |  |  |  |  |  |  |  |  | if statement here to check J through Q; if all are #N/A then write "error" otherwise stay blank
Spreadsheet: 178b2e5b-1b51-4e31-a030-a5949385dc62
Sheet: Sheet1

Table 8--Oilseed prices received by U.S. farmers | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6
Marketing | Soybeans2 | Cottonseed3 | Sunflowerseed2 | Canola4 | Peanuts3 | Flaxseed4
year
 | $/bushel | $/short ton | $/cwt. | $/cwt. | Cents/pound | $/bushel
2001/02 | 4.38 | 90.5 | 9.62 | 8.77 | 23.4 | 4.29
2002/03 | 5.53 | 101 | 12.1 | 10.6 | 18.2 | 5.77
2003/04 | 7.34 | 117 | 12.1 | 10.6 | 19.3 | 5.88
2004/05 | 5.74 | 107 | 13.7 | 10.7 | 18.9 | 8.07
2005/06 | 5.66 | 96 | 12.1 | 9.62 | 17.3 | 5.94
2006/07 | 6.43 | 111 | 14.5 | 11.9 | 17.7 | 5.8
2007/08 | 10.1 | 162 | 21.7 | 18.3 | 20.5 | 13
2008/09 | 9.97 | 223 | 21.8 | 18.7 | 23 | 12.7
2009/10 | 9.59 | 158 | 15.1 | 16.2 | 21.7 | 8.15
2010/11 | 11.3 | 161 | 23.3 | 19.3 | 22.5 | 12.2
2011/12 | 12.5 | 260 | 29.1 | 24 | 31.8 | 13.9
2012/131 | 13.55-15.55 | 245-275 | 25.35-28.65 | 24.65-27.95 | 27.85-31.15 | 12.55-14.55
2011/12
September | 12.2 | 245 | 32.5 | 23.1 | 23.5 | 13.6
October | 11.8 | 245 | 29.6 | 22.8 | 28.9 | 13.9
November | 11.7 | 268 | 29 | 23.3 | 33.2 | 13.9
December | 11.5 | 264 | 29.6 | 23 | 30.8 | 13.5
January | 11.9 | 281 | 28.9 | 23.4 | 33.7 | 13.7
February | 12.2 | 276 | 29.5 | 24.8 | 32.9 | 13.2
March | 13 |  | 28.8 | 27.1 | 34.8 | 13.3
April | 13.8 |  | 28.4 | 27.8 | 35.1 | 14.1
May | 14 |  | 27.8 | 27.7 | 33.8 | 14.8
June | 13.9 |  | 27.2 | 27.4 | 34.4 | 12.9
July | 15.4 |  | 27 | 26.6 | 34.5 | 13.3
August | 16.2 | 235 | 28.8 | 25.3 | 30.4 | 13.3
2012/13
September | 14.3 | 254 | 28.8 | 27 | 35.2 | 13.3
October | 14.2 | 257 | 25.9 | 26.6 | 33.8 | 13.5
November1 | 13.8 | 257 | 25.5 | 25.9 | 33 | 14
1 Preliminary.  2 September-August.  3August-July. 4 July-June.
NA = Not available. |  | cwt.=hundredweight.
Source: USDA, National Agricultural Statistics Service, Agricultural Prices.
Last update: | 2012-12-17 14:08:50.400000
Spreadsheet: 581993d1531658369-sumifs-function-not-returning-any-value-demo2
Sheet: ProductB

 | ProductB
 |  |  |  |  |  |  |  |  |  |  |  | Weeks
 |  |  |  |  |  |  |  |  |  |  |  | 21 | 22 | 23 | 24 | 25 | 26 | 27
 |  |  |  |  |  |  |  |  |  |  |  | I want this
 |  |  |  |  |  |  |  |  |  |  |  | Weeks
 |  |  |  |  |  |  |  |  |  |  |  | 21 | 22 | 23 | 24 | 25 | 26 | 27
 |  |  |  |  |  |  |  |  |  |  |  | 21.88673538521099 | 21.32912793271359 | 20.10529982918277 | 21.20667368824206 | 21.34651367253545 | 20.70833737981936 | 20.533344324458
Spreadsheet: 479381d1473343738-sync-data-between-two-sheets-including-new-rows-that-are-added-example-workbook-2-
Sheet: Sheet2

This sheet references the columns I require but needs to automatically update with new rows that are added to Sheet 1
Spreadsheet: 713062d1610544102-dynamic-arrays-applying-formulas-row-per-row-dynamicarrayproblem
Sheet: Sheet1

I would like to use Dynamic Arrays (so I can easily set the number of rows). I would like to apply formulas to each row such as MIN, AND, SUM etc but for these formulas to apply each row in the dynamic array separately and not all together. In Blue text I can use IF and manually calculate minimum. I would like to have a formula similar to red text which will use the MIN formula but row per row.
 |  | calculates minimum
=RANDARRAY(5,1) | =RANDARRAY(5,1) | =IF(A5#<B5#,A5#,B5#) | =IF(C5#=A5#,"A","not A") |  | =IF(MIN(A5#:B5#)=A5#,"A","not A")
 |  |  |  |  | calculates minimum
=RANDARRAY(5,1) | =RANDARRAY(5,1) | =RANDARRAY(5,1) | =RANDARRAY(5,1) |  | =IF(A16#<B16#,IF(C16#<D16#,IF(A16#<C16#,A16#,C16#),IF(A16#<D16#,A16#,D16#)),IF(C16#<D16#,IF(B16#<C16#,B16#,C16#),IF(B16#<D16#,B16#,D16#))) | =IF(F16#=A16#,"A","not A") |  | =IF(MIN(A16#,B16#,C16#,D16#)=A16#,"A","not A")
Spreadsheet: 763190d1642030390-if-and-or-and-sum-assistance-sample-2-
Sheet: Sheet1

 |  |  |  | Budget | Proposal Received | Change Order(s) | Vendor | Notes | Proj. Completion Month | Jan-22 | Feb-22 | Mar-22 | Apr-22 | May-22 | Jun-22 | Jul-22 | Aug-22 | Sep-22 | Oct-22 | Nov-22 | Dec-22
 |  |  |  | 7500 |  |  |  |  | 2022-01-01 00:00:00
 |  |  |  | 12500 |  |  |  |  | 2022-01-01 00:00:00
 |  |  |  | 35000 | 30000 | 2500 |  |  | 2022-12-01 00:00:00
 |  |  |  |  |  |  |  |  | 2022-02-01 00:00:00
 |  |  |  | 50000 |  |  |  |  | 2022-03-01 00:00:00
 |  |  |  | 45000 | 37500 |  |  |  | 2022-01-01 00:00:00
 |  |  |  | 7500 |  |  |  |  | 2022-10-01 00:00:00
 |  |  |  | 35000 |  |  |  |  | 2022-01-01 00:00:00