tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 088be131-4df2-4682-a86f-90ba97f36c77
Sheet: Sheet1

Unnamed: 0 | 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
Table S5:  Lung cancer mortality rates (per 100,000) among Asian female lifelong never smokers in individual cohort studies
 |  | Cohorts
 |  | [NAME] |  | [NAME] |  | KCPS |  |  |  | MEC |  |  |  | Three Prefectures
Follow-up |  | 1966-82 |  | 1988-90 |  | 1992-2004 |  |  |  | 1993-2003 |  |  |  | 1983-
 |  | Rate |  | Rate |  | Deaths | PY | Rate (95% CI)† |  | Deaths | PY | Rate (95% CI)† |  | Deaths | PY | Rate (95% CI)†
Age
25-29 |  | - |  | - |  | 0 | 0 | - |  | 0 | 0 | - |  | 0 | 0 | -
30-34 |  | - |  | - |  | 1 | 137679 | 0.7 (0.01, 4.0) |  | 0 | 0 | - |  | 0 | 0 | -
35-39 |  | - |  | - |  | 9 | 387241 | 2.3 (1.1, 4.4) |  | 0 | 0 | - |  | 0 | 0 | -
40-44 |  | 0 |  | 14.6 |  | 21 | 646379 | 3.2 ( 1.9, 4.6) |  | 0 | 0 | - |  | 1 | 16105 | 6.2 (0.2, 34.6)
45-49 |  | 0 |  |  |  | 40 | 762015 | 5.2 ( 3.6, 6.9) |  | 0 | 8282 | 0.0 ( 0.0, 0.0) |  | 2 | 46175 | 4.3 (0.5, 15.6)
50-54 |  | 5.3 |  | 12.5 |  | 75 | 811882 | 9.2 ( 7.1, 11.3) |  | 2 | 21021 | 9.5 (1.1, 34.3) |  | 5 | 57280 | 8.7 (2.8, 20.4)
55-59 |  | 16 |  |  |  | 94 | 755415 | 12.4 ( 9.9, 15.0) |  | 1 | 22522 | 4.4 (0.1, 24.7) |  | 5 | 53403 | 9.4 (3.0, 21.8)
60-64 |  | 20.8 |  | 36.1 |  | 149 | 681821 | 21.9 ( 18.3, 25.4) |  | 2 | 23951 | 8.4 (1.0, 30.2) |  | 9 | 46990 | 19.2 (8.8, 36.4)
65-69 |  | 33.8 |  |  |  | 162 | 512769 | 31.6 ( 26.7, 36.5) |  | 5 | 31951 | 15.6 (5.1, 36.5) |  | 16 | 37534 | 42.6 ( 21.7, 63.5)
70-74 |  | 59.4 |  | 57.8 |  | 131 | 318208 | 41.2 ( 34.1, 48.2) |  | 8 | 37997 | 21.1 (9.1, 41.5) |  | 10 | 28929 | 34.6 ( 13.1, 56.0)
75-79 |  | 46.6 |  |  |  | 101 | 169166 | 59.7 ( 48.1, 71.3) |  | 11 | 28716 | 38.3 ( 15.7, 60.9) |  | 19 | 21493 | 88.4 ( 48.7, 128.2)
80-84 |  | - |  | - |  | 100 | 111331 | 89.8 ( 72.2, 107.4) |  | 5 | 8665 | 57.7 (18.7, 134.7) |  | 11 | 11056 | 99.5 ( 40.7, 158.3)
85+ |  | - |  | - |  | 0 | 0 | - |  | 0 | 0 | - |  | 1 | 2206 | 45.3 (1.1, 252.6)
 |  |  |  |  |  | 883 |  |  |  | 34 |  |  |  | 79
Age-standardized rate*
40-69 |  |  |  |  |  |  |  | 11.8 (10.8, 12.8) |  |  |  | 5.2 (1.7, 8.7) |  |  |  | 12.5 (8.0, 16.9)
40-79 |  |  |  |  |  |  |  | 15.2 (13.7, 16.7) |  |  |  | 7.3 (4.7, 9.9) |  |  |  | 16.3 (13.4, 19.3)
40+ |  |  |  |  |  |  |  | 16.1 (14.7, 17.6) |  |  |  | 8.0 (5.4, 10.5) |  |  |  | 18.1 (15.1, 21.1)
*Age-standardized to the 2000 IARC World population, ages 40-79, only presented if 10 or more events occurred within specified age-range
†  For strata with less than 10 events, the confidence intervals were calculated using Fisher's exact test
Abbreviations as follows:
[NAME] = Six Prefectures Study [24]
JACC = Japanese Collaborative Cohort Study [25]
KCPS = Korean Cancer Prevention Study [27]
MEC = Mutliethnic Cohort [22]
Three Prefectures = Three Prefectures Study [26]
Spreadsheet: 32d33711-88ae-43a5-a59b-1115ab6ca951
Sheet: Sheet1

analytica 2012 - List of exhibitors | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
 | Search by product and service index (34 Entries):
 | 2 Analysis 2.2 Chromatography 2.2.1 Chromatography equipment and procedures
No. | Company | Country | City | [NAME] | Hall/Booth
1 | [NAME] u. Adsorptionstechnik AG & Co.GmbH | Germany | Berlin | 12169 | A1.212
2 | Akzo Nobel AB | Sweden | Bohus | 445 80 | A2.216
3 | Axel Semrau GmbH & Co. [NAME] | Germany | Sprockhövel | 45549 | A2.312
4 | BIO-RAD Laboratories GmbH | Germany | München | 80939 | B1.504
5 | Bruker Daltonik GmbH | Germany | Bremen | 28359 | A2.331/432
6 | Büchi Labortechnik GmbH | Germany | Essen | 45127 | A2.405
7 | Chromophor Technologies GmbH | Germany | Füssen | 87629 | A1.340
8 | CHROMSYSTEMS Instruments & Chemicals GmbH | Germany | Gräfelfing / München | 82166 | B1.211
9 | dichrom GmbH | Germany | Marl | 45770 | A1.411
10 | [NAME] | Germany | Riemerling | 85521 | A2.305
11 | fischer analytics OHG | Germany | Bingen | 55411 | A1.236
12 | G.A.S. Gesellschaft für analytische Sensorsysteme mbH | Germany | Dortmund | 44227 | A1.235
13 | GE Healthcare | Germany | München | 80807 | A3.331/430
14 | GERSTEL GmbH & Co. [NAME] | Germany | Mülheim an der Ruhr | 45473 | A1.323/424
15 | Gilson International B.V. Deutschland | Germany | Limburg | 65555 | A2.123
16 | [NAME] GmbH | Germany | [NAME] Hallertau | 84072 | A1.119/216
17 | Grace Davison Discovery Sciences | Germany | Worms | 67547 | A1.523
18 | INRAG AG / I-GRAPHX | Switzerland | Birsfelden | 4127 | A2.548
19 | Jasco Europe s.r.l. | Italy | Cremella | 23894 | A2.121/220
20 | JSB BV | Netherlands | Eindhoven | 5653 [NAME] | A2.130
21 | KNAUER [NAME] Dr. [NAME]. [NAME] | Germany | Berlin | 14163 | A2.307
22 | Laborgerätebörse GmbH | Germany | Burladingen | 72393 | A2.313/412
23 | LECO Instrumente GmbH | Germany | Mönchengladbach | 41199 | A1.324
24 | PG Instruments Limited | United Kingdom | Wibtoft | LE17 5BH | B2.215A
25 | Postnova Analytics GmbH | Germany | [NAME] | 86899 | A2.323
26 | PSS Polymer Standards Service GmbH | Germany | [NAME] | 55120 | A1.223
27 | Schambeck SFD GmbH | Germany | Bad Honnef | 53604 | A1.404
28 | Shanghai Anpel Scientific Instrument Co.,Ltd. | China | Shanghai | 200030 | A1.525
29 | [NAME] Europe GmbH | Germany | München | 81829 | A1.326
30 | SIM Scientific Instruments Manufacturer GmbH | Germany | Oberhausen | 46149 | A1.341
31 | Thermo Scientific | Germany | Dreieich | 63303 | B1.101/202
32 | Waters GmbH | Germany | Eschborn | 65760 | A1.243/336
33 | Wyatt Technology Europe GmbH | Germany | Dernbach | 56307 | A1.439
34 | YMC Europe GmbH | Germany | [NAME] | 46539 | A1.407
Spreadsheet: 158049d1337962060-conditional-concatenate-conditional-concatenate
Sheet: Main Title Page 

2012-07-01 00:00:00 | Languages
Title
Best Exotic Marigold Hotel, The | En | Ces | Les | Ru | Zhs | En, Ces, Les, Ru, Zhs
[NAME], The | En | [NAME] |  |  | Zhs | En, [NAME]
Dr. [NAME]' The Lorax | En | Fr | Ces | Ru | Ars | En, Fr, Ces, Ru, Ars
Flicka: Country Pride | En | Fr | Ces | BPt | Ars | En, Fr, Ces, BPt, Ars
Hunger Games, The | En | Ces | Ja | Ru | Zhs | En Ces, [NAME], Ru. Zhs
Salmon Fishing In The Yemen | En | De | [NAME] | Les | Zhs | En, [NAME], [NAME],  [NAME], Zhs
Seeking Justice | En | Fr | Les |  | Ars | En, Fr, Les, Ars
Thousand Words, A | En | Fr | De | Ita | Ars | En, Fr, De, Ita, Ars
Wanderlust | En | Fr | De | Les |  | En, Fr, De, Les
Wrath of the Titans | En | Fr | De | Ja | Ars | En, Fr, De, [NAME], Ars
Spreadsheet: 683028d1592446397-search-list-for-each-instance-with-the-same-value-sample-contact-listv2
Sheet: Directory

DIRECTORY
 | # | Name | WORK PHONE |  | # | Name | WORK PHONE
 | 1 |  | IFERROR(INDEX(ContactList[[#All],[PHONE]],MATCH(Directory!B4,ContactList[[#All],[Row]],0)),"")
 | # | Name | Phone |  | # | Name | Phone
Spreadsheet: 117780d1313012880-macro-button-to-pull-and-dump-data-help-master-file
Sheet: Raw Data

libeguid | [NAME] | FirstName | Middlename | LastName | House_number | Unit | Street_name | Street_Suffix | PostDirection | AddressLine1 | City | Province | Postalcode | RidingCode | RidingName | Pollnum | HomePhone | NewPhone | [NAME] | Age | Gender | Date | Election_Following | Election_PartyID | Election_SupportStrength | Election_WillVote | Election_VotingStatus | Election_Sign | Election_Activity | Election_Ride | Election_Info | Election_KeyIssue | Election_AddressChange | Election_Note | Election_CanvassType | Election_Canvasser | Election_CanvassResult
25636 | 160255 | [NAME] | Yahya | [NAME] | 5711 |  | Wells | Pl |  | 5711 Wells Place | Mississauga | ON | L5M 5T6 | 106 | Mississauga-Erindale | 236 | [PHONE]
25636 | 160255 | [NAME] | H | Smith | 5896 | 52 | [NAME] | [NAME] |  | 5896 [NAME] | Mississauga | ON | L5M 5T6 | 106 | Mississauga-Erindale | 236 | [PHONE]
25636 | 160255 | Mark | K | [NAME] | 5478 | 89 | Father [NAME] | Dr |  | 5478 Father D'Sousa Dr | Mississauga | ON | L5M 5T6 | 106 | Mississauga-Erindale | 236 | [PHONE]
25636 | 160255 | Adam | J | Silva | 6523 |  | [NAME] | Blvd |  | 6523 [NAME] | Mississauga | ON | L5M 5T6 | 106 | Mississauga-Erindale | 236 | [PHONE]
25636 | 160255 | [NAME] | Ma | Hood | 7899 |  | Fudge | [NAME] |  | 7899 [NAME] | Mississauga | ON | L5M 5T6 | 106 | Mississauga-Erindale | 236 | [PHONE]
Spreadsheet: 148610d1333481318-automating-multiple-sheets-data-display-racetest123
Sheet: Sheet2

I seperated by .5 [NAME] |  |  |  |  |  |  |  | TieBreakBy#
[NAME] | Car Model | 1D | 2D | 3D | 4D | 5D | No Place |  | 1D |  |  | Pay | 2D |  |  | pay | 3D |  |  | 4D |  |  | 5D
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | [NAME] | M3 | 16.348
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | [NAME] | [NAME] | 16.348
 |  |  |  |  |  |  |  |  | ^ | ^ | ^ | ^
 |  |  |  |  |  |  |  |  | I | I | I | I
 |  |  |  |  |  |  |  |  | I | I | I | I will be pulling this number from another sheet when I finish it.
 |  |  |  |  |  |  |  |  | I | I | I
 |  |  |  |  |  |  |  |  | Now I need to sort them in ascending order by division which is figured out
 |  |  |  |  |  |  |  |  | in the table to the left.
 |  |  |  |  |  |  |  |  | The green is what I need it to do automatically.
 |  |  |  |  |  |  |  |  | The reason why, is that I am then going to place cells I4,J4,J5 into a final sheet
 |  |  |  |  |  |  |  |  | in order to show their payouts.
 |  |  |  |  |  |  |  |  | At the last step I need to just have the persons [NAME],
 |  |  |  |  |  |  |  |  | car model, time and how much they won on a sheet. Which I think I can do.
Spreadsheet: 774162d1648250784-check-against-all-conditions-listed-in-column-book7
Sheet: Sheet1

Rule Name | Variable | Variable |  |  |  |  | A | B | C | D |  |  |  |  |  | Code Name | Rule
Correction | 2 | 3 |  |  |  |  |  | 2 | 3 | 12 |  |  |  |  |  | Correction | AND(I2=2,J2=3)
Correction2 | 4 | 3 |  |  |  |  |  | 4 | 1 | D14 |  |  |  |  |  | Correction2 | AND(I2=4,J2=3)
Correction3 | 4 | 1 |  |  |  |  |  | 4 | 3 | 32 |  |  |  |  |  | Correction3 | OR(AND(I2=4,J2=1),AND(I2=4,J2=4))
Correction3 | 4 | 4 |  |  |  |  |  | 4 | 4 | 1
Spreadsheet: a5bd299a-d13f-41c6-a8d9-98973ba1be20
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
259396 | 7597 | Hilary | Stevenson | GBR | 1602 | 00:34:43 | 00:01:25 | 01:25:38 | 00:01:24 | 01:08:46 | 1 | 03:10:31
259396 | 52614 | Sandra | Abrams | GBR | 1601 | [NAME] | 00:01:31 | 01:30:13 | 00:01:03 | 01:07:59 | 2 | 03:17:17
Spreadsheet: 888935d1739559200-template-for-weekly-schedule-that-will-look-like-my-example-weekly-schedule-working-template
Sheet: Job List

Day | Date | Last Name | First Name | Full Name | Location | Job Name | Shift | Job Number
Monday | 2022-10-03 00:00:00 | [LEAD] Barnes | Chase |  | FM Morenci | 2410 Belt Replacement | Day | XXXXXXXXXX/1234567
Monday | 2022-10-03 00:00:00 | Cape | Brage |  | FM Safford | 2420 Saddle Repair |  | XXXXXXXXXX/4567890
Monday | 2022-10-03 00:00:00 | Currier | Stephen |  | FM Morenci | 2410 Belt Replacement | Night | XXXXXXXXXX/1234567
Tuesday | 2022-10-04 00:00:00 | [LEAD] Barnes | Chase |  | FM Morenci | 2410 Belt Replacement |  | XXXXXXXXXX/1234567
Tuesday | 2022-10-04 00:00:00 | Cape | Brage |  | FM Safford | 2420 Saddle Repair |  | XXXXXXXXXX/4567890
Tuesday | 2022-10-04 00:00:00 | Currier | Stephen |  | FM Morenci | 2410 Belt Replacement |  | XXXXXXXXXX/1234567
Tuesday | 2022-10-04 00:00:00 | Driver | [NAME] |  | FM Safford | 2420 Saddle Repair |  | XXXXXXXXXX/4567890
Monday | 2022-10-10 00:00:00 | [LEAD] Barnes | Chase |  | FM Morenci | 2410 Belt Replacement |  | XXXXXXXXXX/1234567
Monday | 2022-10-10 00:00:00 | Cape | Brage |  | FM Safford | 2420 Saddle Repair |  | XXXXXXXXXX/4567890
Monday | 2022-10-10 00:00:00 | Currier | Stephen |  | FM Morenci | 2410 Belt Replacement |  | XXXXXXXXXX/1234567
Spreadsheet: 94953d1294692203-make-a-calendar-with-noted-birthdays-etc-my2011-23
Sheet: w2

 |  |  |  |  |  | Anniversaries
 |  |  |  |  |  | Sam & Betty wed | 2004-01-07 00:00:00
 |  |  |  |  |  | Mel & Ann wed | 1987-02-05 00:00:00
 |  |  |  |  |  | Tom & Sis wed | 1978-05-12 00:00:00
 |  |  | These Birthdays and Anniversaries would actually
 |  |  | be on the "Dates" worksheet (see the tab below).
 |  |  |  |  |  | DATEDIF figured out [NAME]'s age.
 |  |  | Shown here is only the first page for Weeks 1 and 2.
 |  |  | Of course, I'll make more worksheets for…
 | [NAME] is 35 |  | Weeks 3, 4, 5, 6, 7, etc…  for the year.
 |  |  | Sometimes, more than 1 event is on a certain date.
 |  |  | Sometimes even, more than 1 Birthday is on the same date.
 |  |  | I just want them all to go on lower lines.
 | [NAME] is 15
 | Sam & Betty wed: 7
This is 5 and 1/2 inches wide
Spreadsheet: 745462d1629943955-how-to-return-differences-between-two-columns-how-to-return-differences-between-two-columns
Sheet: Sheet1

ID | Name |  |  | Old ID
1234567 | Apples |  |  | 9876543
2456778 | Oranges |  |  | 43219056
4567890 | Bananas |  |  | 6594032
345321 | Pears |  |  | 1987234
9876543 | Nectarines |  |  | 11122233
9873456 | Plums |  |  | 99884455
2345678 | Cherries |  |  | 22335577
4567934 | Pineapples |  |  | 7644311
43219056 | Avocados |  |  | 10293485
5646870 | Grapes
43192355 | Strawberries
4563845 | Blueberries
6594032 | Mangos
3456092 | Blackberries
10293485 | Raspberries
Spreadsheet: 688317d1595705640-find-value-according-to-multiple-criteria-warp-planning-sheet
Sheet: desired result

WARP PLANING
 |  | 2020-07-13 00:00:00 | DAY | NIGHT
 |  |  | WARP CUT | WARP CUT
LOOM NO | CURRENT WARP | PENDING MTRS | ON | ON | MATERIAL TO BE IN HOUSE BY -7 DAYS | MATERIAL TO BE PURCHASED ON -3 DAYS | NEXT WARP ORDERED
3
4
5
6
7
8
9
10
13
14
15
16
Spreadsheet: 49e2d06f-02b6-4131-8d4a-0770c5d846e3
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
2D6FG | Test | 2D6FG | CYP2D6 [NAME], B ([NAME] Only) | CYP2D6 [NAME], B |  |  |  |  |  |  | This test is for billing purposes only. This is not an orderable test. |  |  | This test is for billing purposes only. This is not an orderable test. |  |  |  | 1 | 81479 |  |  |  |  | Rochester
Spreadsheet: 25dd81cc-e94d-4d6a-bb81-66961ea06263
Sheet: T45

الجدول 45: النسبة المئوية للمسنين (65+) سنة، خلال سنوات التعداد
Table 45: Percentage of elderly (65+) years, during the census years
Country | Round 2000           دورة 2000 |  |  |  | Round 2010           دورة 2010 |  |  |  | البلد
 | Census year سنة التعداد | % [NAME]نسبة الذكور | % [NAME]نسبة الإناث | % Total   نسبة المجموع | Census year سنة التعداد | % [NAME]نسبة الذكور | % [NAME]نسبة الإناث | % Total   نسبة المجموع
Bahrain | 2001 | 1.274046885663168 | 1.24100067014651 | 2.515047555809678 | 2010 | 1.045302376291036 | 1.079646290087812 | 2.124948666378847 | البحرين
Egypt | 1996 | 1.792450143763857 | 1.601589441998368 | 3.394039585762225 | 2006 | 1.794689040278056 | 1.603768812701279 | 3.398457852979335 | مصر
Iraq | 1997 | 1.500518637097548 | 1.902559909978317 | 3.403078547075865 | … | ... | ... | ... | العراق
Jordan | 2004 | 1.634380062092716 | 1.600476725231789 | 3.234856787324505 | … | ... | ... | ... | الاردن
Kuwait | 1995 | 0.6910514924757389 | 0.6199026384102261 | 1.310954130885965 | 2011 | 0.9546129132214557 | 0.8879429848166087 | 1.842555898038065 | الكويت
Lebanon | … | ... | ... | ... | … | ... | ... | ... | لبنان
Libya | … |  |  |  | 2006 | 2.044712948967866 | 1.883449172466173 | 3.92816212143404 | ليبيا
Morocco | 2004 | 2.825067024128686 | 2.654155495978552 | 5.479222520107239 |  |  |  |  | [NAME]
Oman | 2003 | 1.374894866762854 | 1.212023823362486 | 2.586918690125339 | 2010 | 1.377692061126116 | 1.28369459440652 | 2.661386655532636 | عمان
Palestine | 1997 | 1.541516142752432 | 1.927962337551464 | 3.469478480303896 | 2007 | 1.447826755640433 | 1.670343786755065 | 3.118170542395498 | فلسطين
Qatar | 2004 | 0.7626046834195979 | 0.4528049309905931 | 1.215409614410191 | 2010 | 0.4795123085025317 | 0.3335226119269051 | 0.8130349204294368 | قطر
Saudi Arabia | 2004 | 1.462585624947802 | 1.327209289671316 | 2.789794914619119 | … | ... | ... | ... | المملكة العربية السعودية
Sudan | … | ... | ... | ... | 2008 | 1.910907280365547 | 1.472878334004606 | 3.383785614370153 | السودان
Syrian Arab Republic | 2004 | 1.758512544802867 | 1.528897849462366 | 3.287410394265233 | … | ... | ... | ... | الجمهورية العربية السورية
Tunisia | 2004 | 3.500166282038554 | 3.390922615083718 | 6.891088897122271 | … |  |  |  | تونس
United Arab Emirates | 1995 | 0.5801210846182052 | 0.4728571689294679 | 1.052978253547673 | 2005 | 0.4823272986770973 | 0.3348506698597595 | 0.8171779685368568 | [NAME] المتحدة
Yemen | 2004 | 1.806926561136767 | 1.620929656154545 | 3.427856217291313 | … | ... | ... | ... | اليمن
Spreadsheet: 82185d1282211858-comparing-two-columns-using-vlookup-sample
Sheet: Sheet1

ColumnA | ColumnB | Resultant Column | Expected Result
ROSE1 | rose1 | rose1 | ROSE1
[NAME] | lily | rose1 | [NAME]
MARRI2 | marri | marri | MARRI2
MARRIGOLD | jasmine | marri | MARRIGOLD
CARNETION |  | #N/A | #N/A
Spreadsheet: 9f0ac3dd-7b5c-4eb8-99d1-877d0940ddea
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | RUN | T1 | BIKE | T2 | SKI | POSITION | TOTAL TIME
2853 | 15573 | [NAME] | Lindquist | USA | 0 | 00:44:55 | 00:01:41 | 01:08:42 | [NAME] | 00:40:25 | 1 | 02:37:29
2853 | 15579 | Marian | Mead | USA | 0 | 00:48:40 | 00:03:10 | 01:18:18 | [NAME] | 00:46:25 | 2 | 03:00:11
2853 | 15661 | [NAME] | Shik | USA | 0 | 00:54:18 | 00:03:01 | 01:26:42 | 00:03:06 | 00:43:55 | 3 | 03:11:01
Spreadsheet: 285809d1387861242-need-all-sheet-to-be-change-if-i-change-the-master-sample10
Sheet: Whole Poultry

Item Number | Item Description | Packing | Brand | Category | Total
FCHIWP0008 | [NAME] IN BOX | 12X900 GM | KESKINOGLU | WHOLE POULTRY | 1973.18
FCHIW00998 | [NAME] 1100 [NAME] IN BOX | 10X1100 GM | KESKINOGLU | WHOLE POULTRY | 1886.8
FCHIW00987 | [NAME] GMX12 CHICKEN IN BOX | 12X1000 GM | KESKINOGLU | WHOLE POULTRY | 1844.66
FCHIW00989 | [NAME] GMX10 CHICKEN IN BOX | 10X1200 GM | KESKINOGLU | WHOLE POULTRY | 1676
FCHIW800GM | [NAME] IN BOX | 12x800 gm | KESKINOGLU | WHOLE POULTRY | 1477.92
FCHIW00990 | [NAME] GMX10 CHICKEN IN BOX | 10X1300 GM | KESKINOGLU | WHOLE POULTRY | 950.9
FCHIW00991 | [NAME] 1400 [NAME] IN BOX | 10X1400 GM | KESKINOGLU | WHOLE POULTRY | 877.1
PROC004 | WHOLE CHICKEN 800GMX2 | 6X2X800G | KESKINOGLU | WHOLE POULTRY | 113.34
PROC005 | WHOLE CHICKEN 1100 GM + 1200 GM | 5x2x(1100+1200) | KESKINOGLU | WHOLE POULTRY | 109
PROC003 | WHOLE CHICKEN 1000GM X 2 | 6X2X1000G | KESKINOGLU | WHOLE POULTRY | 95.83
11001GET1 | WHOLE CHICKEN 1100GM TWIN PACK BUY 1 GET 1 FREE | 2X6X1100GM | KESKINOGLU | WHOLE POULTRY | 10.67
 |  |  |  | Total | 11015.4
Spreadsheet: 768908d1645197105-icon-set-formatting-for-month-by-month-tracking-formating
Sheet: Sheet1

Divisions | Start | 01.2021 | 02.2021 | 03.2021 | 04.2021 | 05.2021 | 06.2021 | 07.2021 | 08.2021 | 09.2021 | 10.2021 | 11.2021 | 12.2021
Division 1 | 31.55 | 31.55 | 30.4 | 31.5 | 31.5 | 31.5 | 30.5 | 30.5 | 30.5 | 32.5 | 31.5 | 32.5 | 30.5 |  | Show the changes in division 1 from month to month using directional arrows.
Division 2 | 44.57839999999999 | 44.57839999999999 | 44.57839999999999 | 44.57839999999999 | 43.77839999999998 | 43.77839999999998 | 43.77839999999998 | 42.77839999999998 | 41.73839999999998 | 41.43839999999999 | 41.7884 | 41.7884 | 41.7759
Division 3 | 134.4064 | 134.4064 | 133.5964 | 132.4964 | 130.8964 | 128.1635 | 126.1635 | 127.1635 | 129.1035 | 96.90349999999998 | 114.1035 | 126.3535 | 126.371
Division 4 | 28.05 | 28.05 | 26.3 | 26.3 | 24.3 | 23.28 | 20.54 | 19.54 | 19.74 | 21.74 | 21.74 | 21.74 | 17.49
 |  |  |  |  | [Green]⬆* 0.00
 |  |  |  |  | [Color44]➜* 0.00
 |  |  |  |  | [Red]⬇* 0.00
Spreadsheet: 117623d1312914934-referencing-group-summary-and-sorting-example1
Sheet: Sheet2

 | Example
ID | Merchant Name | Amount | Sold | Total | Available | Month
 | Merchant A
 | Merchant B
 | Merchant C
 | Merchant D
 | Merchant E
 | Merchant F
 | Merchant G
 | Merchant H
 | Merchant I
 | Merchant J
 | Merchant K
 | Merchant L
 | Merchant M
 | Merchant N
 | Merchant O
 | Merchant P
 | Merchant Q
Spreadsheet: 90995d1290680267-counting-completed-cells-across-rows-sample
Sheet: Sheet2

 | 1 | 2 | 2a |  | 3 | 4 | 5 | 6 |  |  | Code | Code table | 1 | 2 | 2a | 3 | 4 | 5 | 6
Account name | Industry | No Of PC (Exact) | No. Of PC (range) | No. Of Employee - Cisco | No. Of Employee | No. Of Sites | No. Of Tel | No. Of Servers | Profiled code FP to P1 |  | FP | If 1-6 have non blank values (2 is counted either as 2 or 2a filled) | yes | yes, or | yes | yes | yes | yes | yes
 |  | 0 | No Response | 50 - 99 | No Response | 0 | 0 | 0 | P0 |  | P5 | Any of5  filled (same note about 2)
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0 | PO |  | P4 | Any of 4 filled (same note about 2)
 | Media - Broadcast | 50 | No Response | No Response | 20 - 49 | 1 | 40 | 5 | FP |  | P3 | Any of 3 filled (same note about 2)
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0 | P0 |  | P2 | Any of 2 filled (same note about 2)
 |  | 65 | 50 - 99 | 100 - 249 | 50 - 99 | 4 | 60 | 4 | P5 |  | P1 | Any of 1 filled (same note about 2)
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0 | P0 |  | P0 | No fields
 | Manufacturing | 10 | No Response | No Response | No Response | 6 | 0 | 0 | P3
 | Manufacturing | 22 | 20 - 49 | No Response | No Response | 0 | 0 | 0 | P2
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 | Property & Construction | 50 | No Response | No Response | 100 - 249 | 5 | 30 | 10
 | Manufacturing | 20 | 20 - 49 | No Response | 20 - 49 | 15 | 15 | 0
 |  | 0 | No Response | 50 - 99 | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 | Computer Software & Services | 100 | No Response | No Response | 100 - 249 | 3 | 100 | 18
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 | Government | 0 | 20 - 49 | No Response | 20 - 49 | 1 | 20 | 3
 |  | 0 | No Response | No Response | No Response | 0 | 0 | 0
 | Manufacturing | 280 | 100 - 499 | 250 - 499 | 250 - 499 | 2 | 200 | 15
 |  |  |  |  |  |  |  |  | counts of values above
Spreadsheet: 160341d1339060008-comparing-a-certain-number-of-text-in-a-different-worksheet-sample-1-1-
Sheet: Sheet2

79 SOUTH CHINA IMPORT INC.
ASALCO INC
ASAMA ENTERPRISE CORPORATION
ASANO AND ASSOCIATES  INC.
ASAP-AMERICAN SPECIALTY ADHESIVE
ASAP-AMERICAN SPECIALTY ADHESIVE
ASAT OUTDOORS LLC WAREHOUSE
ASB-SEA BUSINESS
ASBURY GRAPHITE MILLS
ASC INC C O TRION
ASC IND INC
A.PACIFIC EXPRESS ENTERPRISES
A A IMPORTING, INC.
A.S. MILL PRODUCTS INC.
ASCEND ACOUSTICS, INC.
ASCEND LABORATORIES LLC
ASCENDA CORP.
[NAME] LINGERIE LLC
ASCENT AVIATION GROUP INC
ASCENT TECHNOLOGY INC
ASCO POWER TECHNOLOGIES
ABBOTT NUTRITION