tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: kimberly_watson__20552__imbalsumm0108
Sheet: PGETX

 |  |  |  |  | 12283
 | [NAME] |  | Pecos Del |  | Gunpoint #2
Day | Measured | Scheduled | Measured | Scheduled | Measured | Scheduled
1 | -132997 | -79207 | -39109 | -92874
2 | -112568 | -53005 | -40001 | -99950
3 | -144086 | -117734 | -40000 | -65000
4 | -151514 | -150002 | -55771 | -56162
5 | -151656 | -150001 | -55077 | -56162
6 | -153786 | -150001 | -52179 | -56162
7 | -138012 | -58418 | -1800 | -79718
8 | -144890 | -82115 | -48170 | -109950
9 | -123111 | -64023 | -1611 | -59950
10 | -150419 | -90703 |  | -59808
11 | -159142 | -138136 | -58416 | -79950
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
 |  |  |  | 2001-07-31 00:00:00 |  |  | 460835.37
 |  |  |  | 2001-08-11 00:00:00
 | CBS Volume
 |  |  |  | 111236
Spreadsheet: 742531d1627866602-indirect-returning-ref-to-cell-reference-bcardtest
Sheet: Inventory

UIG | Player | OVR | Series | Set | Team | POS | OWN |  |  |  |  | Lines:
 | Wander Franco | 99 | Future Stars | Flashback | Rays | SS | Yes
 | [NAME] | 99 | 2021 All-Star | Flashback | Braves | RF | Yes
 | [NAME] | 99 | The 42 | Legend | Dodgers | 2B | Yes
 | Mariano Rivera | 99 | Milestone | Legend | Yankees | CP | Yes
 | [NAME] deGrom | 99 | 2021 All-Star | Flashback | Mets | SP | Yes
 | Prince Fielder | 99 | Home Run Derby | Legend | Tigers | 1B | Yes
 | [NAME] | 98 | Monthly Awards | Flashback | Nationals | LF | Yes
 | Ozzie Albies | 98 | 2021 All-Star | Flashback | Braves | 2B | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Nationals | SS | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Reds | RF | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Padres | 2B | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Orioles | CF | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Red Sox | 3B | Yes
 | [NAME] Judge | 98 | 2021 All-Star | Flashback | Yankees | RF | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Indians | 3B | Yes
 | [NAME] | 98 | 2021 All-Star | Flashback | Athletics | 1B | Yes
Spreadsheet: 211268d1359704994-combo-box-index-number-problems-refresh-and-duplication-combo-box-problem
Sheet: Sheet1

Size |  | Effect |  | Card Direction |  | Stock
1 |  | 3 |  | 2 |  | 2
Size |  | Effect |  | Direction |  | Stock
51 W x 89 H mm | 1 | Flip | 1 | Turn Left-to-Right | 1 | Fine | 1
 |  | Animation | 2 | [NAME]Bottom | 2 | Fine3D | 2
 |  | 3D | 3 |  |  | Coarse | 3
 |  |  |  | Both |  | MotionStock
 |  |  |  | Turn Left-to-Right |  | Fine
 |  |  |  | [NAME]Bottom
 |  |  |  |  |  | Coarse
 |  |  |  | LeftToRight
 |  |  |  | Turn Left-to-Right |  | DepthStock
 |  |  |  | TopToBot |  | Fine3D
 |  |  |  |  |  | Coarse
 |  |  |  | [NAME]Bottom
Selections
51 W x 89 H mm |  | 3D |  | [NAME]Bottom |  | Fine3D
You have selected:
[NAME]: 51 W x 89 H mm
Effect: 3D
Direction: Tilt Top-to-Bottom
Stock: Fine3D
Spreadsheet: 48529d1247744750-lookup-nutritional_content-1-
Sheet: Diet Sheet

Meal 1 | Description | No. Off | Cals | Protein (g) | Fat (g) | Carbs (g)
 | Egg (white) |  | 32 | 7 | 0 | 0 |  | Training 1-2 hours, 3-6 times per week
 | Wholemeal Bread |  | 56 | 3 | 0.4 | 10 |  | Body weight (15/07/09) = 226lbs/101kg
 | [NAME] |  | 124 | 2 | 0 | 29
 | Pear |  | 70 | 1 | 1 | 24 |  | Daily Intake Requirements
Subtotal |  |  | 282 | 13 | 1.4 | 63
Meal 2 | Egg (white) | 1 | 32 | 7 | 0 | 0 |  | Type | [NAME]* | Cals* | %
 | Wholemeal Bread | 2 | 112 | 6 | 0.8 | 20 |  | Protein | 260 | 1040 | 40.24767801857585
 | [NAME] | 1 | 124 | 2 | 0 | 29 |  | Carbs | 260 | 1040 | 40.24767801857585
 | Pear | 2 | 140 | 2 | 2 | 48 |  | Fats | 56 | 504 | 19.5046439628483
 | [NAME] | 10 | 960 | 40 | 80 | 20 |  | Total | 576 | 2584 | 100
Subtotal |  |  | 1368 | 57 | 82.8 | 117
Meal 3
 |  |  |  |  |  |  |  |  |  | *minimum requirements
 |  |  |  |  |  |  |  | [NAME]
Subtotal |  |  | 0 | 0 | 0 | 0
Meal 4 |  |  |  |  |  |  |  | Type | [NAME] | Cals | Kilojoules
 |  |  |  |  |  |  |  | Protein | 1 | 4 | 16.7
 |  |  |  |  |  |  |  | Carbs | 1 | 4 | 16.7
 |  |  |  |  |  |  |  | Fats | 1 | 9 | 37.7
Subtotal |  |  | 0 | 0 | 0 | 0
Meal 5
Subtotal |  |  | 0 | 0 | 0 | 0
Meal 6
Subtotal |  |  | 0 | 0 | 0 | 0
Meal 7
Subtotal |  |  | 0 | 0 | 0 | 0
Meal 8
Total |  |  | 0 | 0 | 0 | 0
Daily Total |  |  | 3300 | 140 | 168.4 | 360
Daily Target |  |  | 0 | 260 | 56 | 260
Spreadsheet: 710331d1608847257-help-pulling-data-from-a-range-copy-of-attendance-template-w-formula
Sheet: April

Employee Absence Schedule
April | Dates of Absence
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | TOTAL
Employee Name | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | CL | T | NCNS | Total Points
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
[NAME]
Obed Attamah
[NAME]
[NAME]
Keath Grimes
[NAME]
[NAME]
[NAME]
[NAME]
Spreadsheet: 154544d1336482028-vlookup-possibility-sample-text_solution
Sheet: Sheet1

Project | Count |  |  | Project | Count |  |  | Solution | 1st Lookup | 2nd Lookup | 3rd lookup
A |  |  |  | A | 8 |  |  | A
B |  |  |  | A | 10 |  |  | B
C |  |  |  | B | 12 |  |  | C
 |  |  |  | C | 14
 |  |  |  |  |  |  |  | Solution using Pivot
 |  |  |  |  |  |  |  | Row Labels
 |  |  |  |  |  |  |  | A
 |  |  |  |  |  |  |  | 8
 |  |  |  |  |  |  |  | 10
 |  |  |  |  |  |  |  | B
 |  |  |  |  |  |  |  | 12
 |  |  |  |  |  |  |  | C
 |  |  |  |  |  |  |  | 14
 |  |  |  |  |  |  |  | Grand Total
Spreadsheet: 792848d1661185757-index-and-match-for-for-two-criteria-data-by-rows-populated-horizontally-2022-08-22-oeldere-msoghomonyan-device_database-edit
Sheet: DataViewer

 | Workorder# | W0001
 | ID# | 11
 | Device DB
 | ID
 | WO
 | SO
 | Date
 | PSI @ 0%
 | mA @ 0%
 | PSI @ 20%
 | mA @ 20%
 | PSI @ 40%
 | mA @ 40%
 | PSI @ 60%
 | mA @ 60%
 | PSI @ 80%
 | mA @ 80%
 | PSI @ 100%
 | mA @ 100%
 | PASS or FAIL?
Spreadsheet: 471220d1468927174-next-column-value-of-specific-text-samkhan
Sheet: Sheet1

 |  |  |  | String | Time |  | Output
 |  |  |  | P | 05:17:00
 |  |  |  | P | 06:08:00
 |  |  |  | A | 00:00:00
 |  |  |  | R | 00:00:00
 |  |  |  | L | 05:21:00
 |  |  |  | R | 00:00:00
 |  |  |  | L | 05:34:00
Spreadsheet: 552575d1513660537-extracting-value-from-next-column-if-current-column-is-blank-extracting-value-from-next-column-if-current-column-is-blank
Sheet: Sheet1

Product | Ingredients (%) |  |  |  |  |  |  |  |  |  |  |  |  |  | Cost of Ingredient ($)
 | Sugar | Spice | Salt | Pepper | Tomato | [NAME] | Apple | Orange | Grapes | Melon | Guava | [NAME] | Total (%) |  | Sugar | 1
A | 90 |  |  |  | 5 |  |  | 5 |  |  |  |  |  |  | Spice | 2
B |  | 85 |  | 10 |  | 5 |  |  |  |  |  |  |  |  | Salt | 3
C | 30 |  | 20 |  |  |  |  |  | 10 |  |  | 40 |  |  | Pepper | 4
D |  | 40 | 20 |  | 10 |  |  |  |  |  |  | 30 |  |  | Tomato | 5
E | 100 |  |  |  |  |  |  |  |  |  |  |  |  |  | [NAME] | 6
F | 50 |  |  |  |  | 30 |  |  | 10 |  | 10 |  |  |  | Apple | 7
G | 30 |  | 30 |  | 40 |  |  |  |  |  |  |  |  |  | Orange | 8
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Grapes | 9
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Melon | 10
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Guava | 11
Product | G | << Drop down list of the products in Column A |  |  |  |  |  |  |  |  |  |  |  |  | [NAME] | 12
Ingredient 1
Ingredient 2
Ingredient 3
Ingredient 4
Ingredient 5
Spreadsheet: 44833d1243557466-calculate-date-automatically-seroleh-4
Sheet: Sheet1

 | Data
no | employee | Retire age | DO Birth | DO retire
1 | a | 58 | 1973-03-14 00:00:00
2 | b | 58 | 1967-07-24 00:00:00
3 | c | 56 | 1987-09-21 00:00:00
4 | d | 55 | 1977-06-02 00:00:00
5 | e | 58 | 1968-05-05 00:00:00
6 | f | 56 | 1955-12-19 00:00:00
7 | e | 55 | 1976-05-27 00:00:00
 |  |  |  |  |  |  | from the data the yellow is false because 55 years only have 20088 days.but it calculate D8 and D11 add with 20454 days.
 |  |  |  |  |  |  | Refer to the data, I want that DO retire is automatically calculated base on retire age and DOB. Just use simple Excel code such as if, vlookup, etc. Not the macros or vb.so the question is how do we calculate it using only 1 formula…
Spreadsheet: 710211d1608775919-need-to-move-random-data-from-one-worksheet-to-another-my-dmc-thread-inventory-template
Sheet: Satins

Color | Number | Description | Skeins available | Skeins needed | Project notes | type
 | S211 | Lavender – light | 0 | 0 |  | satins
 | S307 | lemon | 0 | 0 |  | satins
 | S310 | black | 0 | 0 |  | satins
 | S321 | red | 0 | 0 |  | satins
 | S326 | Rose – very dark | 0 | 0 |  | satins
 | S336 | Blue | 0 | 0 |  | satins
 | S3371 | Black Brown | 0 | 0 |  | satins
 | S351 | Coral | 0 | 0 |  | satins
 | S352 | Coral – light | 0 | 0 |  | satins
 | S3607 | Plum – light | 0 | 0 |  | satins
 | S367 | Pistachio Green – dark | 0 | 0 |  | satins
 | S3685 | Mauve – very dark | 0 | 0 |  | satins
 | S3820 | Straw – dark | 0 | 0 |  | satins
 | S414 | Steel Gray – dark | 0 | 0 |  | satins
 | S415 | [NAME] | 0 | 0 |  | satins
 | S434 | Brown – light | 0 | 0 |  | satins
 | S469 | Avocado Green | 0 | 0 |  | satins
 | S471 | [NAME] – very light | 0 | 0 |  | satins
 | S472 | [NAME] – ultra light | 0 | 0 |  | satins
 | S501 | Blue Green – dark | 0 | 0 |  | satins
 | S504 | Blue Green – very light | 0 | 0 |  | satins
 | S5200 | white | 0 | 0 |  | satins
 | S550 | Violet – very dark | 0 | 0 |  | satins
 | S552 | Violet – medium | 0 | 0 |  | satins
 | S553 | Violet | 0 | 0 |  | satins
 | S601 | Cranberry – dark | 0 | 0 |  | satins
 | S602 | [NAME] – medium | 0 | 0 |  | satins
 | S606 | Orange–red – bright | 0 | 0 |  | satins
 | S666 | Red – bright | 0 | 0 |  | satins
 | S676 | Old Gold – light | 0 | 0 |  | satins
 | S700 | Green – bright | 0 | 0 |  | satins
 | S702 | [NAME] | 0 | 0 |  | satins
 | S712 | Cream | 0 | 0 |  | satins
 | S726 | Topaz – light | 0 | 0 |  | satins
 | S738 | [NAME] – very light | 0 | 0 |  | satins
 | S739 | [NAME] – ultra very light | 0 | 0 |  | satins
 | S741 | Tangerine – medium | 0 | 0 |  | satins
 | S744 | Yellow – pale | 0 | 0 |  | satins
 | S745 | Yellow – light pale | 0 | 0 |  | satins
 | S762 | [NAME] – very light | 0 | 0 |  | satins
 | S776 | Pink – medium | 0 | 0 |  | satins
 | S797 | Royal Blue | 0 | 0 |  | satins
 | S798 | Delft Blue – dark | 0 | 0 |  | satins
 | S799 | Delft Blue – medium | 0 | 0 |  | satins
 | S800 | Delft Blue – pale | 0 | 0 |  | satins
 | S818 | [NAME] | 0 | 0 |  | satins
 | S820 | Royal Blue – very dark | 0 | 0 |  | satins
 | S841 | [NAME] – light | 0 | 0 |  | satins
 | S898 | [NAME] – very dark | 0 | 0 |  | satins
 | S899 | Rose – medium | 0 | 0 |  | satins
 | S909 | [NAME] – very dark | 0 | 0 |  | satins
 | S915 | Plum – dark | 0 | 0 |  | satins
 | S931 | Antique Blue – medium | 0 | 0 |  | satins
 | S932 | Antique Blue – light | 0 | 0 |  | satins
 | S943 | Aquamarine – medium | 0 | 0 |  | satins
 | S959 | Seagreen – medium | 0 | 0 |  | satins
 | S964 | Seagreen – light | 0 | 0 |  | satins
 | S976 | [NAME] – medium | 0 | 0 |  | satins
 | S991 | Aquamarine – dark | 0 | 0 |  | satins
 | S995 | Electric Blue – dark | 0 | 0 |  | satins
Spreadsheet: 0ec78285-855d-407a-ab8d-53340a147183
Sheet: Sheet1

Table 2--Feed and residual use of wheat and coarse grains, 12/12/2013 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10
Market year and quarter 1/ |  | Corn  (million metric tons) | Sorghum  (million metric tons) | Barley  (million metric tons) | Oats  (million metric tons) | Feed grains  (million metric tons) | Wheat  (million metric tons) | Energy feeds  (million metric tons) | Grain consuming animal units  (millions) | Energy feeds per grain consuming animal unit  (tons)
2011/12 | Q1 Sep-Nov | 46.3887777587269 | 1.125526280695738 | -0.04739860166504735 | 0.3396545983846662 | 47.80656003614225 | -0.459970008464036 | 47.34659002767822
 | [NAME] | 39.20255535869642 | 0.1432626545503038 | 0.2699564823357473 | 0.2214356928307892 | 39.83721018841326 | 1.183849204081244 | 41.0210593924945
 | [NAME] | 21.80958005499356 | 0.3902129253903844 | 0.02769454355440525 | 0.2170485461906847 | 22.44453607012903 | -1.919213361746368 | 20.52532270838266
 | [NAME] | 8.343220742603496 | 0.1344738463101611 | 0.9843320079360544 | 0.7427577153815939 | 10.2047843122313 | 11.60236993008325 | 21.80715424231456
 | MY Sep-Aug | 115.7441339150204 | 1.793475706946588 | 1.23458443216116 | 1.520896552787734 | 120.2930906069159 | 10.40703576395409 | 130.7001263708699 | 92.92875735835372 | 1.406455117729182
2012/13 | Q1 Sep-Nov | 52.88833006293143 | 2.003289452795082 | 0.06856141324907399 | 0.372022959037876 | 55.33220388801346 | -0.8694007408072677 | 54.46280314720619
 | [NAME] | 27.47792954982759 | 0.1169470321896452 | 0.2062503231846548 | 0.3402923494367741 | 28.14141925463867 | 0.2600990101704511 | 28.40151826480912
 | [NAME] | 23.42514589802697 | 0.4197036952366438 | 0.032244983493769 | 0.222580560295597 | 24.09967513705298 | -0.4304411368479495 | 23.66923400020503
 | [NAME] | 6.266725089380402 | -0.1728804302959873 | 1.275190032577013 | 0.6085850544900668 | 7.977619746151495 | 11.6225366525418 | 19.60015639869329
 | MY Sep-Aug | 110.0581306001664 | 2.367059749925384 | 1.582246752504511 | 1.543480923260314 | 115.5509180258566 | 10.58279378505703 | 126.1337118109136 | 92.064249715 | 1.37006180142
2013/14 | MY Sep-Aug | 132.0861354009894 | 2.540117988480565 | 1.237732726970882 | 1.602543386161787 | 137.4665295026026 | 3.903689612096769 | 141.3702191146994 | 91.3865021 | 1.546948574090346
1/ Corn and sorghum, September 1-August 31 marketing year; Barley and oats, June 1-May 31 marketing year. Source: USDA, World Agricultural Outlook Board, World Agricultural Supply and Demand Estimates and supporting materials.
Data run: 12/12/2013
Spreadsheet: 685121d1593747031-difficulties-using-solver-for-staff-schedule-complicated-criteria-set-schedule2
Sheet: Constraints(Days)

Count of shifts per day per person |  |  | Can only be 1 or 0 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Count of number of shifts in the next 7 days (forward) |  |  |  |  |  | On Pay days, we can't have more than 75 hours in 14 days |  |  |  |  |  |  | =6 days
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Constraint | <=6
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Category
 |  | Employee |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | [NAME]
Date | Week | [NAME] | [NAME] | Ayisha | [NAME] | Kaitlin | Jayme | [NAME] | [NAME] | Felix | [NAME] | Casual1 | Casual2 | Casual3 | Casual4 | Casual5 |  | Start of week
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 3
Spreadsheet: 90235d1289996705-calculate-year-month-and-days-and-add-them-year-calculation_rex
Sheet: Sheet1

 |  |  |  |  |  | MANUALY ADDED
Serial No |  |  |  |  | Years | Months | Days
1 | 2009-01-01 00:00:00 | 2010-02-05 00:00:00 | 1 years 1 months 4 days |  | 1 | 1 | 4
2 | 1976-03-15 00:00:00 | 1986-02-10 00:00:00 | 9 years 10 months 26 days |  | 9 | 10 | 26
3 | 1988-11-10 00:00:00 | 1995-09-15 00:00:00 | 6 years 10 months 5 days |  | 6 | 10 | 5
4 |  |  | 0 years 0 months 0 days
5 |  |  | 0 years 0 months 0 days
6 |  |  | 0 years 0 months 0 days
7 |  |  | 0 years 0 months 0 days
8 |  |  | 0 years 0 months 0 days
9 |  |  | 0 years 0 months 0 days
10 |  |  | 0 years 0 months 0 days
11 |  |  | 0 years 0 months 0 days
12 |  |  | 0 years 0 months 0 days
13 |  |  | 0 years 0 months 0 days
14 |  |  | 0 years 0 months 0 days
15 |  |  | 0 years 0 months 0 days
16 |  |  | 0 years 0 months 0 days
 |  |  |  | TOTAL | 16 | 21 | 35
 |  |  |  | Final RESULT | 17 | 9 | 5
Spreadsheet: 98638d1297498631-automatically-show-data-for-3-weeks-before-and-after-current-week-in-graph-copy-of-line_chart-1
Sheet: Sheet1

 | 2011-02-07 00:00:00
FC | 13 | 17 | 25 | 34 | 39 | 45 | 48 | 55 |  |  | Enter week number manually
AC | 23 | 30 | 32 | 48 | 50 | 50 | 55 | 60 |  | I'm now in week | 9
Spreadsheet: 726467d1617260978-counting-only-nonblank-cells-in-two-columns-filtered-column-filter
Sheet: Filter Count

 |  |  | Phase | Quiz 1 (T1) | Exam A | [NAME] (T2)
 |  | [NAME] | 1 | 3 | 43 | 3
 |  | Ian | 1 | 4 | 74 | 5
 |  | [NAME] | 1 | 3 | 35
 |  | [NAME] | 1 | 3 | 53 | 3
 |  | Zoe | 2 | 2 | 54 | 3
 |  | [NAME] | 2 | 5 | 12 | 5
 |  | Polly | 2 | 4 | 43 | 5
 |  | Tegan | 4 |  | 55 | 5
 |  | Turlough | 5 | 5
 |  | [NAME] | 4 | 2 | 67 | 2
 |  | [NAME] | 3 | 3 | 56
 |  | [NAME] | 4 | 2 | 63 | 4
 |  | # of scores increased from T1 to T2:
 |  | # of people who were present at both T1 and T2:
 |  | [Must be able to filter by Phase]
Spreadsheet: 834199d1687524226-restructure-zip-code-data-s666-pq-zip-code-example-data-set-v3
Sheet: Data Set with Desired Results

zip | primary_city | acceptable_cities | state | county |  | DESIRED RESULTS
1093 | Whately |  | MA | Franklin County |  | Unique City | Zip Code(s) | State | County(s)
1094 | Wheelwright |  | MA | Worcester County |  | Pittsfield | 1201, 1202, 1203 | MA | Berkshire County
1097 | Woronoco |  | MA | Hampden County |  | Indian Orch | 1151 | MA | Hampden County
1098 | Worthington |  | MA | Hampshire County |  | [NAME] | 1151 | MA | Hampden County
1101 | Springfield |  | MA | Hampshire County |  | East Longmeadow | 1116 | MA | Hampden County
1102 | Springfield |  | MA | Hampden County |  | E Longmeadow | 1116 | MA | Hampden County
1103 | Springfield |  | MA | Hampden County |  | Longmeadow | 1116 | MA | Hampden County
1104 | Springfield |  | MA | Hampden County |  | Longmeadow | 1106 | MA | Hampden County
1105 | Springfield |  | MA | Hampden County |  | Woronoco | 1097 | MA | Hampden County
1106 | Longmeadow | Springfield | MA | Hampden County |  | Springfield | 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1111, 1115, 1118, 1119, 1128, 1129, 1133, 1138, 1139, 1144, 1151, 1152, 1195, 1199 | MA | Hampden County, Hampshire County
1107 | Springfield |  | MA | Hampden County |  | Worthington | 1098 | MA | Hampshire County
1108 | Springfield |  | MA | Hampden County |  | Whately | 1093 | MA | Franklin County
1109 | Springfield |  | MA | Hampden County |  | Wheelwright | 1094 | MA | Worcester County
1111 | Springfield |  | MA | Hampden County
1115 | Springfield |  | MA | Hampden County
1116 | Longmeadow | E Longmeadow, East Longmeadow | MA | Hampden County
1118 | Springfield |  | MA | Hampden County
1119 | Springfield |  | MA | Hampden County |  | cty | zip | state | county
1128 | Springfield |  | MA | Hampden County |  | Pittsfield | 01201,01202,01203 | MA | Berkshire County
1129 | Springfield |  | MA | Hampden County |  | Springfield Bmc | 01195 | MA | Hampden County
1133 | Springfield |  | MA | Hampden County |  | [NAME] | 01151 | MA | Hampden County
1138 | Springfield |  | MA | Hampden County |  | Indian Orch | 01151 | MA | Hampden County
1139 | Springfield |  | MA | Hampden County |  | E Longmeadow | 01116 | MA | Hampden County
1144 | Springfield |  | MA | Hampden County |  | East Longmeadow | 01116 | MA | Hampden County
1151 | [NAME] | Indian Orch, Springfield | MA | Hampden County |  | Longmeadow | 01106,01116 | MA | Hampden County
1152 | Springfield |  | MA | Hampden County |  | Springfield | 01101,01102,01103,01104,01105,01106,01107,01108,01109,01111,01115,01118,01119,01128,01129,01133,01138,01139,01144,01151,01152,01195,01199 | MA | Hampshire County,Hampden County
1195 | Springfield | Springfield Bmc | MA | Hampden County |  | Worthington | 01098 | MA | Hampshire County
1199 | Springfield |  | MA | Hampden County |  | Woronoco | 01097 | MA | Hampden County
1201 | Pittsfield |  | MA | Berkshire County |  | Wheelwright | 01094 | MA | Worcester County
1202 | Pittsfield |  | MA | Berkshire County |  | Whately | 01093 | MA | Franklin County
1203 | Pittsfield |  | MA | Berkshire County
Spreadsheet: 146413d1332173440-automaticaly-copy-data-from-worksheet-worksheet-registru-de-casa
Sheet: 3

SC FIRMA SRL |  |  |  |  | Data |  |  | Contul
 |  |  | REGISTRU DE CASA |  | Zi | Luna | An | casa
 |  |  |  |  | 3 | 1 | 2011 | 5311
Nr. [NAME] | Nr. Act casa | Nr. Anexa | Explicatii | Incasari | Plati |  |  | Simbol cont
Report/Sold [NAME] |  |  | Sold initial
1 | xc | 111 | sdfasdfas | 111
2 | sd | 12 | sample 2 | 321
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
 |  |  | [NAME]
 |  |  | Sold final
 |  |  |  | Compartiment Financiar-Contabil
 | Casier
Spreadsheet: 6b9434ff-6695-4ec4-9578-841d28017308
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | RUN | T1 | BIKE | T2 | RUN.1 | POSITION | TOTAL TIME
258974 | 57037 | [NAME] | [NAME] | LUX |  | 01:01:26 | 00:01:41 | 01:52:57 | 00:02:01 | 00:34:40 | 1 | 03:32:43
258974 | 26235 | Sandra | Fuchs | GER |  | 01:07:28 | [NAME] | 01:52:28 | [NAME] | 00:36:52 | 2 | 03:39:43
258974 | 70794 | Marian | [NAME] | NED |  | 01:06:08 | 00:01:57 | 01:54:16 | 00:01:54 | 00:37:59 | 3 | 03:42:12
258974 | 57192 | Esther | Vanduijnhoven | NED |  | 01:10:50 | 00:01:44 | 01:54:07 | 00:01:52 | [NAME] | 4 | 03:46:59
Spreadsheet: 679806d1590643255-wildcards-in-the-table_array-of-vlookup-excel-help
Sheet: Excel Help

Table_array |  |  |  | Lookup_Value
 |  |  | Transaction Listing (TL)
Project Id | Category |  | [NAME] | Project ID | Expected Value
 |  |  |  | ED.001.001.UNB.001
ED.001.001.UNB* | Excluded |  |  | ED.001.001.UNB.002 | Excluded
ED.OPR.ADV* | Personnel |  |  | ED.LTA.FCD.SAL.000 | Personnel
ED.OPR.LES* | Personnel |  |  | ED.OPR.ADV.BFM.SUP | Personnel
ED.ASC.* | Personnel |  |  | ED.OPR.ADV.DCM.SAL | Personnel
ED.LTA.* | Personnel |  |  | ED.OPR.OPS.FAC.000 | Office
ED.015.* | Personnel |  |  | ED.001.001.UNB.003 | Excluded
ED.OPR.OPS.FAC* | Office |  |  | ED.ASC.FCD.SUP.000 | Personnel
[NAME] |  |  |  | ED.OPR.ADV.TVE.ACT
 |  |  |  | ED.OPR.ADV.STV.ACT
 |  |  |  | ED.OPR.LES.PSL.000
 |  |  |  | ED.OPR.ADV.TVE.SAL
 |  |  |  | ED.OPR.ADV.TLP.ACT
 |  |  |  | ED.OPR.ADV.STV.SAL
 |  |  |  | ED.OPR.ADV.EMI.SAL
 |  |  |  | ED.OPR.ADV.STV.SUP
 |  |  |  | ED.LTA.FCD.SAL.000
 |  |  |  | ED.OPR.ADV.MNE.SAL
 |  |  |  | ED.OPR.ADV.TRF.SAL
 |  |  |  | ED.ASC.FCD.SUP.000
 |  |  |  | ED.OPR.ADV.PSL.000
 |  |  |  | ED.001.001.UNB.002
 |  |  |  | ED.001.001.UNB.001
 |  |  |  | ED.OPR.LES.IT1.SAL
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.LES.OO1.SAL
 |  |  |  | ED.OPR.ADV.BFM.SAL
 |  |  |  | ED.OPR.GRA.CAL.GMA
 |  |  |  | ED.OPR.ADV.MNE.SUP
 |  |  |  | ED.OPR.ADV.TLP.SAL
 |  |  |  | ED.OPR.ADV.BFM.SAL
 |  |  |  | ED.OPR.ADV.TLP.ACT
 |  |  |  | ED.OPR.ADV.RSC.ACT
 |  |  |  | ED.OPR.ADV.MNE.ACT
 |  |  |  | ED.OPR.ADV.DCM.ACT
 |  |  |  | ED.OPR.ADV.EMI.SAL
 |  |  |  | ED.OPR.ADV.STV.SUP
 |  |  |  | ED.OPR.LES.ALL.000
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.LES.ACO.SAL
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.ADV.TLP.SUP
 |  |  |  | ED.LTA.OPM.SAL.000
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.ADV.MED.ACT
 |  |  |  | ED.001.001.UNB.002
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.LES.DR1.SAL
 |  |  |  | ED.OPR.OPS.FAC.000
 |  |  |  | ED.OPR.ADV.TLP.SAL
 |  |  |  | ED.OPR.ADV.BFM.SAL
Spreadsheet: 267597d1380118867-using-tables-contraload-deliveries-into-purfleet
Sheet: Forward Production Requirements

 |  |  |  |  | Starting Stock | 150
Production Date | Tool | Order Reference | [NAME] | Qty per Pallet | No. Pallets |  |  |  | Stock Checks
2013-10-09 00:00:00 | 13985 | 13/0015/1/42 | 547008 | 2072 |  |  |  |  | 2013-09-23 00:00:00
2013-09-25 00:00:00 | 14139 | 13/0708/2/38-PLASTIC | 20250 | 2025
2013-10-05 00:00:00 | 14138 | 13/0707/2/40 | 126000 | 4200
2013-11-04 00:00:00 | 14139 | 13/07082/45-PLASTIC | 20250 | 2025
2013-11-08 00:00:00 | 13985 | 13/0015/1/45 | 532504 | 2072
2013-11-11 00:00:00 | 14138 | 13/0707/2/46 | 105000 | 4200
2013-12-09 00:00:00 | 13985 | 13/0015/1/50 | 476560 | 2072
2013-12-09 00:00:00 | 14138 | 13/0707/2/50 | 75600 | 4200