tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 140093d1328622649-daily-food-calculator-feb-food-total-values
Sheet: 2-3-12

 |  | Breakfast | Food Item | Cost | Daily Points
 |  |  | 1 cup cheerios | 0.19 | 5
 |  |  | 3/4 cup milk | 0.28 | 1.4
 |  | Lunch | Food Item | Cost | Daily Points
 |  |  | 1 Bagel | 0.23 | 8
 |  |  | 1 Ham | 0 | 1
 |  |  | Butter | 0 | 1
 |  |  | 1/2 Cucumber | 0.67 | 0
 |  |  | 2 Carrots | 0.56 | 0
 |  |  | tomatoes | 0 | 0
 |  |  | 1 Honey and Oats | 0 | 5
 |  | Gym | 1/4 Cup Milk | 0.093 | 0.8
 |  | Movie | Popcorn |  | 8
 |  | Dinner | Food Items | Cost | Daily Points
 |  |  | 2 Cups [NAME] |  | 10
 |  |  | 1/2 Cup Newman's Own Pasta Sauce |  | 3
Spreadsheet: 762795d1641823849-how-to-ignore-blanks-with-index-and-how-to-combine-and-consolidate-data-testplanner
Sheet: Dinner

 | Meal | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | U | C
1 | Out
2 | Steak and chips | Steak | Potatoes | Tomato | Peas
3 | Chicken and chips | Chicken | Potatoes | Sweetcorn
4 | Fish and chips | Fish | Potatoes | Peas
5 | Pasta bolognese and garlic bread | Pasta | [NAME] | Mince Beef | Peas | [NAME]
6 | Chicken roast dinner | Chicken | Potatoes | Gravy | Brocolli
7 | Pizza | Pizza | [NAME]
8 | Curry | Chicken | [NAME] | [NAME] | [NAME]
Spreadsheet: 155677d1337007425-vlookup-and-concatenate-all-matches-string-concatenates-example
Sheet: possible solution

Name | Number | Example results (vlookup the name and concatenate all matches) |  | RESULT |  | [NAME] | [NAME]
[NAME] | 12 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 13 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 11 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7, |  |  |  |  |  |  | CONCATENATE Matrix:
[NAME] | 123 | [NAME], 234, 234, 2, 56, 989, 89, 98 |  |  |  |  |  |  | Concatenates all the values below the name to create the output for each name.
[NAME] | 141 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7, |  |  |  |  |  |  | Becaues CONCATENATE() doesn't accept array functions (eg D1:D4), the values have to be entered individually (eg D1,D2,D3,D4).
[NAME] | 4543 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 5467 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 547 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 234 | [NAME], 234, 234, 2, 56, 989, 89, 98
[NAME] | 234 | [NAME], 234, 234, 2, 56, 989, 89, 98
[NAME] | 2 | [NAME], 234, 234, 2, 56, 989, 89, 98
[NAME] | 56 | [NAME], 234, 234, 2, 56, 989, 89, 98
[NAME] | 5 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 6 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 7 | [NAME], 13, 11, 141, 4543, 5467, 547 5, 6, 7,
[NAME] | 989 | [NAME], 234, 234, 2, 56, 989, 89, 98
[NAME] | 89 | [NAME], 234, 234, 2, 56, 989, 89, 98
[NAME] | 98 | [NAME], 234, 234, 2, 56, 989, 89, 98
 |  |  |  |  |  | IF Matrix:
 |  |  |  | Use HLOOKUP to match the name on the column to the name in the CONCATENATE matrix. |  | One column for each person
 |  |  |  |  |  | Each row checks IF the input array matches the person up top
 |  |  |  |  |  |  | True: returns the number + a little text formatting
 |  |  |  |  |  |  | False: a totally empty text string
 |  |  |  |  |  | If you have more names, insert columns; the formula can just pull across
Spreadsheet: 726725d1617386116-predictive-modeling-of-unit-sales-by-day-of-week-dow-book3
Sheet: Sheet1

Candy Bars
 | Orig Data
 |  | Flavor | location | Flavor, Location | mon | tue | wed | thu | fri | sat | [NAME] | mon | tue | wed |  | If [NAME], Last non-zero
 |  |  |  |  | 2021-01-01 00:00:00
 |  | Carmel | shelf |  | 1 | 2 | 4 | 2 | 5 | 2 | 4 | 2 | 5 | 4
 |  | Chocolate | shelf |  | 2 | 3 | 4 | 2 | 0 | 2 | 4 | 3 | 0 | 4
 |  | Vanilla | table |  | 3 | 5 | 6 | 2 | 8 | 0 | 0 | 0 | 0 | 0 |  | 9
 |  | Vanilla | shelf |  | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 0 | 2 |  | 14
 |  | [NAME] | table |  | 2 | 3 | 4 | 2 | 0 | 2 | 4 | 3 | 0 | 4
 |  | Caramel | table |  | 2 | 5 | 6 | 4 | 2 | 4 | 6 | 5 | 2 | 6
 | Final Data
 |  | Flavor | location | Flavor, Location | Mon Ave | Tue Ave | Wed Ave | [NAME] | Fri Ave | Sat Ave | Sun Ave
 |  | Carmel | shelf
 |  | Chocolate | shelf
 |  | Vanilla | shelf |  | 1 | 0 | 2 | 0 | 0 | 3 | 2
 |  | [NAME] | table
 |  | Caramel | table
Spreadsheet: 767625d1644560268-how-to-use-the-let-function-to-achieve-the-same-effect-in-one-step-2-11
Sheet: Sheet1

 |  |  | MAX | MIN
A | 1 |  |  |  |  |  | 1 |  | 1
A | 3
A | 555
A | 7
A | 9
B | 10 |  |  |  |  | 78 | 10 | 78 | 10
B | 45
B | 78
C | 15 |  |  |  |  | 999 | 8 | 999 | 8
C | 8
C | 999
C | 8
C | 81
C | 81
C | 81
Spreadsheet: 887232d1737474309-excel-formula-to-filter-by-2-criteria-sample-filter
Sheet: Sheet2

Search By | M/S Fabwell
 |  |  |  |  |  |  |  |  |  | Vendor List
Vendor | MT. | [NAME]. | Qty (Nos) |  |  | Filter By |  |  |  | M/S Fabwell
 |  |  |  |  |  | 9/CP-3 |  |  |  | M/S Bharat Enterprises
 |  |  |  |  |  | 9/CP-4 |  |  |  | M/S Sanika Ent.
 |  |  |  |  |  | 9/CP-5 |  |  |  | M/S Y K Enginnering
 |  |  |  |  |  | 9/CP-6
Spreadsheet: joe_parks__14951__BridgeDPR0429
Sheet: Bridgeline DPR2

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | BRIDGELINE GAS MARKETING
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | DAILY POSITION REPORT
 |  | Position |  |  | Maturity / Gap Risk |  |  | Value-at-Risk |  |  |  | P&L ($000)
Business Unit - Commodity Group |  | Net Open | Limit |  | Sensitivity | Limit |  | 1-Day |  | Limit |  | Today | 5 Day Rolling | MTD | QTD | YTD |  | Yesterday's MTD | Yesterday's QTD | Yesterday's YTD
BRIDGELINE GAS MARKETING
GAS TRADING |  |  | 15 Bcf |  |  |  |  |  |  | 2000
1 Month |  |  |  |  |  | 9 Bcf 1 Month
2-12 Months |  |  |  |  |  | 25 Bcf 2-12 Months
13-18 Months |  |  |  |  |  | 5 Bcf 13-18 Months
TOTAL TRADING
Notes to File
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | MTD | QTD | YTD
 |  |  |  |  |  |  |  |  |  |  |  |  | ENRON NORTH AMERICA | 2006.869429 | 2006.869429 | 7297.869429
 |  |  |  |  |  |  |  |  |  |  |  |  | GAS TRADING | 2006.869429 | 2006.869429 | 7297.869429
 | 0
 |  |  |  |  |  |  |  |  |  | 5923.328615262726
 |  |  |  |  |  |  |  |  |  | 0
 |  |  |  |  |  |  |  |  |  | 5923.328615262726
 |  |  |  |  |  |  |  |  |  | 0
 |  |  |  |  |  |  |  |  |  | -2243.48
 |  |  |  |  |  |  |  |  |  | 998027.0603850778
Spreadsheet: 104449d1302044645-hlookup-sum-problem-hlookup-problem
Sheet: Sheet1

 | 2010-09-26 00:00:00
 | Sun | Mon | Tue | Wed | Thu | Fri | Sat |  | Sun | Mon | Tue | Wed | Thu | Fri | Sat
Rebag | 1.454099566169029 | 5.956355985824467 | 6.099039364686471 | 5.751586392330017 | 5.213364319967178 | 6.350147132434706 | 1.366769782425621 | 0.0251238632172726 | 2.481738306473405 | 10.03309268377597 | 8.558098608491873 | 8.10355579494363 | 7.801431380887908 | 9.70270751755319 | 2.233564475826064 | 0.04665811501249964
Exceptions | 0.6707321161918225 | 2.747486725196828 | 2.813302249027599 | 2.653032709824194 | 2.404767159117667 | 2.929130661587898 | 0.6304495303087172 | 0.01158887763582228 | 1.000815563167387 | 4.046065323822426 | 3.451241517350374 | 3.267937129156675 | 3.146098813323339 | 3.912830238022718 | 0.9007340068506478 | 0.01881591122269439
 | I want [NAME] to look the date and sum 7 cell togeather
 | example rebag lookup date 26-Sep and total should be = 32.19
Spreadsheet: 761671d1641145987-dynamic-dropdown-in-excel-dnamic-dropdown
Sheet: Acct

YEAR | MONTH | PARTNAME | SRCKEY | TARGKEY
2021 | Oct | IF1222_FM | 640003-LF00E30100303 | AC_531
2021 | Oct | [NAME] | [PHONE] | AC_221
2021 | Oct | [NAME] | [PHONE] | AC_521
2021 | Oct | IF1222_FM | 600515000-11112 | AC_505
2021 | Oct | IF1222_FM | XXX581000-W0059 | AC_504
2021 | Oct | [NAME] | [PHONE] | AC_506
2021 | Oct | [NAME] | [PHONE] | AC_113
2021 | Oct | [NAME] | [PHONE] | [NAME]
2021 | Oct | MC_SAP_FM | 654021-LF00E33100801 | AC_502
2021 | Oct | MC_SAP_FM | [PHONE] | AC_131
Spreadsheet: 113735d1309548023-find-maximum-across-multiple-sheets-crossfit-tracker-2011
Sheet: Mar

Crossfit Progression
Date | WOD |  | Actual Reps | Time | Weight | Pre wght | Pos wght
2010-03-22 00:00:00 | 10 | Pushups | 3R | 00:05:45 | N/A
 | 10 | Situps
 | 10 | [NAME]
 | 10 RFT
2011-03-23 00:00:00 | 70 | Burpees | 21 Burpees | 00:08:45
 | 60 | Situps | 18 Situps
 | 50 | KB Swings 1.5 pood | 15 KB Swings |  | 35#
 | 40 | Pull Ups | 12 Pull Ups
 | 30 | Handstand PU | 9 HSPU (modified)
2011-03-25 00:00:00 | 800m Run |  | 400m | 00:13:20
 | 12 | Pullups | Rx
 | 7 | Hang Cleans |  |  | 65#
 | 3 RFT
2011-03-28 00:00:00 | 800m Run |  | Rx | 00:13:28
 | 21 | Deadlifts |  |  | 135#
 | 15 | Pushups
 | 9 | [NAME]
 | 800m Run
2011-03-29 00:00:00 | 400m overheard walk |  | CNC (back) |  | N/A
 | 400m [NAME] |  | Rx | 00:17:28
 | 400m [NAME] swing walk |  | CNC
 | 400m lunges |  | CNC
2011-03-31 00:00:00 | 9 | Deadlifts | 4R + 9DL | 00:15:00 | 95#
 | 12 | Pushups
 | 15 | [NAME]
 | 15 Min AMRAP
Spreadsheet: 871277d1717667091-returning-a-value-where-a-condition-ends-get-last-header-in-block-1-rs-aligw
Sheet: Sheet2

 |  |  | Y | Y | Y |  | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y | Y |  | Y |  | Y
 | Dataset | Image | Team Freeze | [NAME] | Hits released | Total Hits | P&D status | Sourcing status | Merchant status | Planning status | General comments | P&D comments | Sourcing comments | Merchant comments | Planning comments | Alloc. comments | USIM | Style | Colour | Class | Class helper | Code Sub-class | Code | Class code | Test
Spreadsheet: 739562d1625774407-extracting-overlapping-date-ranges-finding-date-conflicts-breathin-
Sheet: page 1

Pers.no. | Name Last Name | Start | End | Company
310 | [NAME] | 2015-07-01 00:00:00 | 2015-10-31 00:00:00 | Johnson &Johnson
310 | [NAME] | 2015-11-01 00:00:00 | 2015-12-31 00:00:00 | Johnson &Johnson
310 | [NAME] | 2016-01-01 00:00:00 | 2020-05-01 00:00:00 | A Tech
310 | [NAME] | 2016-02-01 00:00:00 | 2017-07-31 00:00:00 | A Tech
310 | [NAME] | 2017-08-01 00:00:00 | 2017-10-31 00:00:00 | A Tech
310 | [NAME] | 2017-11-01 00:00:00 | 2018-12-31 00:00:00 | A Tech
310 | [NAME] | 2019-01-01 00:00:00 | 2020-11-30 00:00:00 | A Tech
310 | [NAME] | 2020-12-01 00:00:00 | 2020-12-31 00:00:00 | A Tech
310 | [NAME] | 2021-01-01 00:00:00 | 9999-12-31 00:00:00 | A Tech
313 | [NAME] | 2015-07-01 00:00:00 | 2016-12-31 00:00:00 | B Tech
313 | [NAME] | 2016-01-01 00:00:00 | 2016-01-31 00:00:00 | B Tech
313 | [NAME] | 2016-02-01 00:00:00 | 2016-03-31 00:00:00 | B Tech
313 | [NAME] | 2016-04-01 00:00:00 | 2016-09-30 00:00:00 | B Tech
313 | [NAME] | 2016-10-01 00:00:00 | 2017-01-31 00:00:00 | C Tech
313 | [NAME] | 2017-02-01 00:00:00 | 2017-08-01 00:00:00 | C Tech
313 | [NAME] | 2017-07-01 00:00:00 | 2020-12-31 00:00:00 | C Tech
313 | [NAME] | 2021-01-01 00:00:00 | 9999-12-31 00:00:00 | C Tech
318 | PETE PACKETT | 2015-07-01 00:00:00 | 2015-12-31 00:00:00 | D Tech
318 | PETE PACKETT | 2016-01-01 00:00:00 | 2016-01-31 00:00:00 | D Tech
318 | PETE PACKETT | 2017-02-01 00:00:00 | 2017-02-28 00:00:00 | D Tech |  | I replaced 1/31/2017 with 2/28/2017
318 | PETE PACKETT | 2017-02-01 00:00:00 | 2017-04-30 00:00:00 | D Tech
318 | PETE PACKETT | 2017-05-01 00:00:00 | 2017-06-30 00:00:00 | D Tech
318 | PETE PACKETT | 2017-07-01 00:00:00 | 2017-09-30 00:00:00 | D Tech
318 | PETE PACKETT | 2017-10-01 00:00:00 | 2020-06-30 00:00:00 | D Tech
318 | PETE PACKETT | 2020-07-01 00:00:00 | 9999-12-31 00:00:00 | D Tech
Spreadsheet: 764785d1642988908-sum-up-date-difference-between-multiple-dates-testdoc
Sheet: Sheet1

 |  |  |  |  |  |  |  |  | Start Date |  | End Date
 |  |  |  |  |  |  |  |  | 2022-01-12 14:33:28
 |  |  |  |  |  |  |  |  | 2021-11-30 00:39:42
 |  |  |  |  |  |  |  |  | 2021-10-01 09:18:12 |  | 2021-10-26 02:12:58
 |  |  |  |  |  |  |  |  | 2021-10-05 11:07:57 |  | 2021-10-13 02:10:57
 |  |  |  |  |  |  |  |  | 2021-02-19 11:32:41
 |  |  |  |  |  |  |  |  | 2022-01-11 13:50:00
 |  |  |  |  |  |  |  |  | 2022-01-11 11:54:45
 |  |  |  |  |  |  |  |  | 2022-01-11 11:43:59
 |  |  |  |  |  |  |  |  | 2022-01-11 16:04:06
 |  |  |  |  |  |  |  |  | 2022-01-09 13:15:14 |  | 2022-02-12 14:50:00
 |  |  |  |  |  |  |  |  | 2022-01-12 12:28:19
 |  |  |  |  |  |  |  |  | 2022-01-04 11:00:55
 |  |  |  |  |  |  |  |  | 2021-12-10 12:50:33
 |  |  |  |  |  |  |  |  | 2021-03-09 09:52:54
 |  |  |  |  |  |  |  |  | 2021-10-13 11:44:42
 |  |  |  |  |  |  |  |  | 2021-04-13 13:18:56
 |  |  |  |  |  |  |  |  | 2021-12-07 08:18:52 |  | 2021-12-08 09:05:53
 |  |  |  |  |  |  |  |  | 2021-11-18 16:06:32
 |  |  |  |  |  |  |  |  | 2021-10-01 11:52:11 |  | 2021-12-06 03:00:00
 |  |  |  |  |  |  |  |  | 2021-11-11 08:11:45
 |  |  |  |  |  |  |  |  | 2021-11-07 20:52:37
 |  |  |  |  |  |  |  |  | 2021-10-21 09:23:27 |  | 2021-11-19 02:02:18
 |  |  |  |  |  |  |  |  | 2021-10-07 15:17:19 |  | 2021-10-26 10:14:45
 |  |  |  |  |  |  |  |  | 2021-07-20 11:57:53 |  | 2021-07-30 02:08:05
 |  |  |  |  |  |  |  |  | 2021-04-29 14:01:03
 |  |  |  |  |  |  |  |  | 2021-04-22 13:03:31 |  | 2021-05-12 08:20:35
 |  |  |  |  |  |  |  |  | 2021-04-23 15:45:29 |  | 2021-04-27 07:17:47
 |  |  |  |  |  |  |  |  | 2021-04-16 13:59:53 |  | 2021-04-19 07:05:43
 |  |  |  |  |  |  |  |  | 2021-04-07 10:21:04 |  | 2021-04-12 09:34:06
Spreadsheet: 5b7752f2-5ed7-4cb2-893d-da9f0d883d96
Sheet: 9c

Product1 | 0-34 | 3-6 | 6-12 | 12-24 | 24-60 | 60-120 | 120-360 | 360+ | TOTAL
Fixed-Float | 2101 | 2002 | 5825 | 12142 | 95631 | 153519 | 226486 | 33059 | 530765
FRA | 11358 | 5713 | 11452 | 2447 | 3619 | - | - | - | 34589
OTHER* | 8540 | 472 | 5967 | 2623 | 52504 | 20881 | 22556 | 929 | 114472
TOTAL | 21999 | 8187 | 23244 | 17212 | 151754 | 174400 | 249042 | 33988 | 679826
*OTHER variable includes the following products: Cap/Floor, Debt Option, Exotic, Fixed-Fixed, Inflation, OIS, Swaption, and Basis.
Spreadsheet: 722395d1615233628-formula-module-base-on-previous-cells-test111
Sheet: Sheet1

 |  |  |  |  | odds |  | 500
 |  |  |  |  | 3.58
 |  |  |  |  | 1.58
 |  |  |  |  | 2.77
 |  |  |  |  | 15.12
 |  |  |  |  | 7
 |  |  |  |  | 1.8
 |  |  |  |  | 3.56
 |  |  |  |  | 2.78
 |  |  |  |  | 3.58
 |  |  |  |  | 1.58
 |  |  |  |  | 2.77
 |  |  |  |  | 1.8
 |  |  |  |  | 3.56
Spreadsheet: 822319d1679263556-shopping-list-generator-find-recipe-in-table-return-ingredients-and-amounts-shopping-list-generator-find-recipe-in-table-return-ingredients-and-amounts-v2
Sheet: Sheet1

 |  |  | Ingredients | Amounts
 | Meals | [NAME] |  | 240 |  | Meal | Sausage | Fish | Potatoes | Mushroom (g) | Pasta (g)
 |  |  | Pasta (g) | 150 |  | Sausage and [NAME] | 2 |  | 3
 |  |  |  |  |  | Fish and Chips |  | 1 | 3
 |  |  |  |  |  | [NAME] |  |  |  | 240 | 150
Spreadsheet: 875426d1721997434-sum-based-on-multiple-criteria-demo-250724-sumifs
Sheet: Vertical

Criteria marked in red font
 |  |  |  |  | Months |  |  | SUMPRODUCT |  | SUMIFS
Main Vertical | PC Name | PC Code | FS Item/Acct/FA Long | GL Code | 2024-04-01 00:00:00 | 2024-05-01 00:00:00 |  | 2024-04-01 00:00:00 | 2024-05-01 00:00:00 | 2024-04-01 00:00:00 | 2024-05-01 00:00:00
Head Office | Head Office | 629050001 | Fully Paid Equity Sh MMC /10010000 | 10010000 |  |  | <------Result
Franchisee | [NAME] | 629060001 | Fully Paid Equity Sh MMC /10010000 | 10010000 |  |  | <------Result
Franchisee | Fran East | 629060002 | Fully Paid Equity Sh MMC /10010000 | 10010000 |  |  | <------Result
Franchisee | Fran South | 629060003 | Fully Paid Equity Sh MMC /10010000 | 10010000 |  |  | <------Result
Head Office | Head Office | 629050001 | Share Application Eq MMC /10050000 | 10050000 |  |  | <------Result
Franchisee | [NAME] | 629060001 | Share Application Eq MMC /10050000 | 10050000 |  |  | <------Result
Franchisee | Fran East | 629060002 | Share Application Eq MMC /10050000 | 10050000 |  |  | <------Result
Franchisee | Fran South | 629060003 | Share Application Eq MMC /10050000 | 10050000 |  |  | <------Result
Spreadsheet: 0c7d9c52-dfcf-40ff-b1ab-1e2b89e9804a
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | 报表 C
 | 国际民航组织
 | 航空运输报表
 | 航段运输业务量统计表
 | 国际航线定期（营利）航班
 | 联系人： |  |  |  |  |  | 国家名称：
 | 单位： |  |  |  |  |  | [NAME]
 | 电话：
 | 传真： |  |  |  |  |  | 年度：
 | 电子邮件：
 | 航站 |  |  |  | 可提供的运力 |  | 收费运输业务量
 |  |  |  |  | 旅客座位 | 业载运力总数 | 旅客 | 货物 | 邮件
 | 出港 | 进港 | 航空器型号 | 航班架次 | （数） | （吨） | （人数） | （吨） | （吨）
 | a | b | c | d | e | f | g | h | i
 | 备注（描述与填报说明存在任何无法避免的偏差情况）：
 |  |  |  |  |  |  |  | [NAME]
Spreadsheet: 16ee0c3c-e85f-450b-90d4-fb2f4c0665b2
Sheet: Sheet1

Table 9--U.S. cotton textile exports, by destination | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
 | May | June | July | July
Region/country | 2012 | 2012 | 2012 | 2011
 | 1,000 pounds 1/
North America | 122877.292 | 130616.85 | 124109.145 | 151502.807
Bahamas | 92.1 | 102.421 | 132.246 | 133.991
Canada | 10411.483 | 11647 | 10567.837 | 9871.057
Costa Rica | 232.533 | 382.324 | 307.365 | 266.425
Dominican Republic | 20721.056 | 21431.989 | 24497.503 | 34485.71
El Salvador | 10249.724 | 12449.128 | 10201.871 | 13209.575
Guatemala | 1929.061 | 2952.988 | 1751.625 | 2027.504
Haiti | 757.265 | 810.384 | 680.866 | 686.951
Honduras | 50709.221 | 51439.917 | 49162.937 | 62656.263
Jamaica | 80.089 | 59.413 | 65.624 | 136.781
Mexico | 25545.613 | 27280.302 | 24647.769 | 26134.225
Nicaragua | 1320.92 | 1596.858 | 1515.354 | 1379.332
Panama | 394.63 | 252.233 | 289.96 | 317.46
South America | 2717.123 | 3194.481 | 3550 | 2559.935
Brazil | 429.855 | 546.748 | 451.699 | 565
Chile | 186.506 | 133.622 | 250.129 | 231.872
Colombia | 961.146 | 1435.844 | 2022.003 | 569.25
Peru | 147.997 | 121.711 | 198.867 | 355.642
Venezuela | 681.714 | 642.596 | 360.287 | 575.497
Europe | 2912.668 | 2938.006 | 2706.087 | 3445.622
Belgium | 218.767 | 262.581 | 210.277 | 379.482
France | 128.391 | 92.98 | 89.019 | 150.015
Germany | 443.286 | 413.834 | 394.631 | 652.673
Italy | 134.25 | 216.809 | 155.695 | 184.483
Netherlands | 390.914 | 357.632 | 348.205 | 419.209
Russia | 98.863 | 61.02 | 56.285 | 124.09
Turkey | 66.078 | 70.968 | 143.499 | 105.994
United Kingdom | 874.633 | 1043.265 | 956.027 | 968.215
Asia | 9398.757 | 8959.988 | 8836.206 | 7482.572
Bangladesh | 31.268 | 15.14 | 8 | 87.327
China | 5116.788 | 4922.782 | 5606.632 | 3531.872
Hong Kong | 712.584 | 734.327 | 500.135 | 512.118
India | 336.96 | 188.517 | 242.531 | 271.608
Israel | 180.614 | 204.358 | 76.469 | 321.603
Japan | 877.917 | 893.878 | 965.865 | 844.177
Pakistan | 31.233 | 48.751 | 30.44 | 24.684
Saudi Arabia | 128.955 | 82.803 | 124.544 | 140.052
Singapore | 319.614 | 244.997 | 188.906 | 222.571
South Korea | 526.779 | 508.011 | 301.668 | 656.867
Taiwan | 94.855 | 125.905 | 80.038 | 129.957
United Arab Emirates | 274.3 | 291.007 | 212.411 | 262.818
Oceania | 747.83 | 753.904 | 705.004 | 872.713
Australia | 571.671 | 620.409 | 577.708 | 666.278
Africa | 261.836 | 296.05 | 313 | 987.403
South Africa | 58.409 | 126.162 | 98 | 46.449
World 2/ | 138915.158 | 146759.28 | 140219.039 | 166893.921
1/ Raw-fiber equivalent.  2/ Totals may not add due to rounding.
Last update: 10/12/12.
Sources: USDA, Economic Research Service; and USDC,
U.S. Census Bureau.
Spreadsheet: 674294d1587747243-find-a-of-a-certain-item-in-large-and-multi-variable-list-data-example
Sheet: Sheet2

ABC123 | ABC123 | ABC123 | ABC123 | ABC123 | ABC123 | ABC123 |  | ABCD123 | ABCD123 | ABCD123 | ABCD123 |  | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 | ABCDE123 |  | ABCDEF123 | ABCDEF123 | ABCDEF123
Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and Mrs Jones Total | Mr and Mrs Jones Total | Mr and Mrs Jones Total | Mr and Mrs Jones Total | Mr and Mrs Hones Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] Total | Mr and [NAME] | Mr and [NAME] | Mr and [NAME]
Fund A | Fund B | Fund C | Fund D | Fund E | Fund F | Fund G |  | Fund A | Fund B | Fund C | Fund D |  | Fund A | Fund B | Fund C | Fund D | Fund E | Fund F | Fund G | Fund H | Fund I | Fund J |  | Fund A | Fund B | Fund C
100 | 250 | 500 | 1000 | 2000 | 3000 | 4000 | 10850 | 300 | 400 | 700 | 1000 | 2400 | 50 | 250 | 250 | 1000 | 100 | 5000 | 2000 | 350 | 1000 | 200 | 10200 | 50 | 250 | 250
Spreadsheet: 703773d1605170309-formula-required-for-return-a-section-wise-different-objects-number-of-quantities-formula-required-for-return-a-section-wise-different-objects-number-of-quantities
Sheet: Sheet

Section-1
Lot Name | Timber | Plywood | Lights | Table | Blocks |  |  |  | Return a Quantities section wise
ABC | 71 | 53 | 89 | 63 | 44 |  |  |  |  | Section-1 |  | Section-2 |  | Section-3
BJH | 88 | 45 | 55 | 70 | 56 |  |  |  |  | Timber | Table | Timber | Blocks | Plywood | Lights
POL | 44 | 28 | 54 | 37 | 93 |  |  |  | POL
ASH | 97 | 70 | 73 | 41 | 40 |  |  |  |  | Plywood | Lights | Blocks | Plywood | Table | Lights
QWS | 47 | 34 | 38 | 88 | 90 |  |  |  | QWS ASH
 |  |  |  |  |  |  |  |  | Above return a quantities for joint look up values section wise
Section-2
Lot Name | Timber | Plywood | Lights | Table | Blocks
ABC | 79 | 69 | 63 | 53 | 70
BJH | 47 | 71 | 70 | 45 | 51
POL | 95 | 63 | 37 | 28 | 51
ASH | 98 | 89 | 41 | 70 | 46
QWS | 71 | 60 | 88 | 34 | 50
Section-3
Lot Name | Timber | Plywood | Lights | Table | Blocks
ABC | 70 | 44 | 66 | 69 | 71
BJH | 51 | 56 | 71 | 71 | 88
POL | 51 | 93 | 55 | 63 | 44
ASH | 46 | 40 | 64 | 89 | 97
QWS | 50 | 90 | 85 | 60 | 47
Spreadsheet: 287919d1389035052-dynamic-table-automatic-adjustments-dynamictable
Sheet: Sheet1

Date |  |  | Date 2 |  |  | Date 3
Spreadsheet: 130179d1322113439-how-to-use-if-formula-for-change-price-december
Sheet: 6

 |  |  |  | 2011-12-06 00:00:00
Newspaper | Price | Quantity | Total
Value | 0.88 |  | 0
Value1 | 0.98 |  | 0
Value2 | 1.22 |  | 0
Value3 | 1.22 |  | 0
Value4 | 0.83 |  | 0
Value5 | 1.01 |  | 0
Value6 | 1.03 |  | 0
Value7 | 1.01 |  | 0
Value8 | 0.8 |  | 0
Value9 | 1.04 |  | 0
Value10 | 1.04 |  | 0
Value11 | 1.04 |  | 0
Total |  |  | 0
 | Grand Total |  | 0
Spreadsheet: 754063d1635925209-index-formula-where-am-i-going-wrong-3rd-nov-list
Sheet: Sheet1

 | CODE | RETAILER |  |  | 1 | A | 5 | 50
 |  | D |  |  | 2 | B | 10 | 60
 |  |  |  |  | 3 | C | 15 | 70
 |  |  |  |  | 4 | D | 20 | 80
 |  |  |  |  | 5 | E | 25 | 90
Spreadsheet: 675709d1588437114-create-summary-list-from-multiple-worksheets-pq-box-location-summary-aligw
Sheet: Sheet2

Manufacturer | Model | Store location
A | [NAME] | Box 1
B | nn | Box 1
C | oo | [NAME]
D | qq
M | x
N | y | Box 1
O | w | [NAME]
P | z | [NAME]
Spreadsheet: 749140d1632522930-dynamic-column-table-into-dynamic-chart-pivot-charts-from-proper-data-set-chistopher-
Sheet: Sheet1

Service | Total | Customer 1 | Customer 2 | Customer 3
Level 1 service |  | 30 | 30 | 0
invoiced |  | 1 | 1 | 0
expected |  | 2 | 1 | 1
Level 2 service |  | 100 | 150 | 200
invoiced |  | 10 | 15 | 20
expected |  | 30 | 40 | 50
Level | Customer | Attribute | Amount |  |  | Sum of Amount | Attribute |  |  |  | Sum of Amount | Attribute
1 | 1 | Service | 30 |  |  | Level | Service | Invoiced | Expected |  | Level | Service | Invoiced | Expected
1 | 1 | Invoiced | 1 |  |  | 1 | 60 | 2 | 4 |  | 2 | 450 | 45 | 120
1 | 1 | Expected | 2
1 | 2 | Service | 30
1 | 2 | Invoiced | 1
1 | 2 | Expected | 1
1 | 3 | Service | 0
1 | 3 | Invoiced | 0
1 | 3 | Expected | 1
2 | 1 | Service | 100
2 | 1 | Invoiced | 10
2 | 1 | Expected | 30
2 | 2 | Service | 150
2 | 2 | Invoiced | 15
2 | 2 | Expected | 40
2 | 3 | Service | 200
2 | 3 | Invoiced | 20
2 | 3 | Expected | 50
Spreadsheet: 864595d1711702073-indexing-correct-match-using-large-formula-with-criteria-book1-282-aligw
Sheet: Stock Items Summary

Material
 |  |  |  |  | -333 |  | Amount in LC
 |  | 898-555222 DESCRIPTION 2 |  | 898-555222 DESCRIPTION 2 | -333 | 898-188888 DESCRIPTION 1 | -333
 |  | 855-895215 DESCRIPTION 3 |  | 855-895215 DESCRIPTION 3 | -214.68 | 898-555222 DESCRIPTION 2 | -333
 |  |  |  |  |  | 855-895215 DESCRIPTION 3 | -214.68