tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 476916d1472065221-continuous-audio-alert-audio-alert-worksheet
Sheet: Sheet1

[NAME]
 | Hedge Fund | VAR%
EM
FIN
ENERGY
SPX
NDX
[NAME]
Spreadsheet: 92888d1292419618-looking-for-ranking-template-example
Sheet: Ranking

 |  | Total Pts
1. | [NAME] | 396
2. | Marlon | 396
3. | [NAME] | 296
4.
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9.
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Spreadsheet: 708720d1607978331-array-index-problems-need-assistance-or-any-advice-to-help-to-create-formula-to-enable-to-book1indexandaggregate
Sheet: AFTER Sheet

Family ID | No of Children | Student ID | Student Name
2022 | 2
2022 | 2
2023 | 2
2023 | 2
2841 | 2
2841 | 2
2405 | 3
2026 | 2
2378 | 3
2377 | 1
2378 | 3
2028 | 3
2691 | 2
2331 | 1
Spreadsheet: 122014d1316551995-indirect-erep_1gb-tigrovi_bkp
Sheet: Ban Josip Jelacic II

Ambient on/off
eRepublik – Online Strategy Game
Sep20 Day 1,400 of the New World
Home
My Land
Wars
Market
Marketplace
Job market
Monetary market
Companies for sale
Community
World Map
News
My Party
Elections
Military Unit
Country administration
Invite friends
Badges
Get Gold & Extras
[NAME]
[NAME]
27
60
Eat food
Gold2.24 Gold
BAM411 BAM
HRK1625 HRK
Missions
X
You don't have enough Gold to complete the task Get Gold
Completed!
2011-10-03 00:00:00
2011-10-03 00:00:00
2011-10-03 00:00:00
Reward
Ok
Congratulations, your rank is now
Rank Bonus on attack +5%
Energy bar
Ok
Strength
Experience points
Health
Rank points
Gold
Energy bar
[NAME]
Free Lands
Scope
Bazooka
Weapons
Weapons
Weapons
Food units
Food units
Food units
Grain Farms
0 0
Logout
Experience level: 27
Experience points: 10027
Next level at: 15000
• Working, training and fighting decreases health
[NAME], health boxes, food, hospitals restore health.
This action restores as much health as possible by eating Food from your Storage.
You can recover up to: 450 / 450 Health
100 more recoverable Health in: 00:59:59
Food limit reached
You have reached your food consumption limit.
You can recover 100 health every hour.
100 more recoverable Health in: [NAME]
Buy health kit Close
Ban Josip Jelacic II
offlineBan Josip Jelacic II
Remove friend Send message Donate
Experience level 33
42,867 / 45,000
Location: CroatiaCroatia, Central Croatia Citizenship: CroatiaCroatia
eRepublik birthday
Aug 07, 2010
National rank: 19
Party Member
[NAME] eHrvatskeSavez Komunista eHrvatske Far-left Wing
Member
HV 1.GB Tigrovi HV 1.GB Tigrovi
Press director
Guess What?!...
Friends(290)
dariuss444
hurkancs
[NAME]
Jaykoq
Phantom II
BeDva
gorancro
figuar_zg
IvanS10
view all
Land of Ban Josip Jelacic II: 21 buildings
Visit
About me
Wiki page
...Speculum mentis est facies et taciti oculi cordis fatentur arcana...
Achievements
hard worker
13
Hard Worker
Worked 30 days in a row
congressman
2
Congress Member
Won the Congress elections
president
Country President
Win the Presidential elections
media mogul
Media Mogul
Reach 1000 subscribers to your newspaper
battle hero
65
Battle Hero
Reach the highest war influence in a battle
campaign hero
11
Campaign Hero
Reach the highest war influence in a campaign
resistance hero
Resistance Hero
Start a resistance war and liberate that region
super soldier
24
Super Soldier
Advance 250 strength points
society builder
Society Builder
Invite 10 people to eRepublik and help them reach level 10
mercenary
Mercenary
Defeat 25 enemies for 50 different countries
Coming soon
Coming soon
Military Skills
Strength
6,117.31
Super soldier:6,117 / 6,250
Rank
National Force **National Force **
Rank points:
8,805,348 / 9,000,000
Forum   |   [NAME]   |   Blog   |   Press   |   Contact   |   [NAME]   |   Terms of Service   |   Privacy  |   Affiliates  |   [NAME]
Follow us: FacebookFacebook TwitterTwitter
Copyright © 2007-2011 eRepublik
Spreadsheet: 755731d1637063110-formulas-with-multiple-range-criteria-not-returning-result-sample1_jt
Sheet: Sheet2

Customer Name | [NAME] | Dr Del Date | Int Date | Dr Doc No | Dr Type | Dr GST [NAME] | Billing Type | Debit | @EP | [NAME] | Clrearing Date | [NAME] | [NAME] | Cr GST Bill No | Credit | D1 | D2 | [NAME] | DR Int%13.00 | DR Int%16.00 | EP Dis%7.50 | Ad Dis%0.00 |  | SUMPRODUCT | ZSOR |  |  |  | DN
xyx | 2021-07-01 00:00:00 |  | 2021-07-01 00:00:00 |  |  |  |  | 0 |  |  | 2021-07-01 00:00:00 | Opn |  |  | 6428.65 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  |  | 0 | 0.1 | 0.1 |  | 0 | 0.1 | 0.1
xyx | 2021-07-04 00:00:00 | 2021-07-05 00:00:00 | 2021-07-13 00:00:00 | [PHONE] | RV | SI3001111565 | ZSOR | 1179449 | Y | 2021-06-30 00:00:00 | 2021-06-30 00:00:00 | [PHONE] | 1X |  | 6428.65 | -13 | -13 | 0 | 0 | 0 | 11 | 0 |  |  | 7 | 0.13 |  |  | 15 | 0.13
xyx | 2021-07-04 00:00:00 | 2021-07-05 00:00:00 | 2021-07-13 00:00:00 | [PHONE] | RV | SI3001111565 | ZSOR | 1173020.35 | Y | 2021-07-26 00:00:00 | 2021-07-26 00:00:00 | [PHONE] | DG |  | 1901.05 | 26 | 13 | 2250 | 2507 | 0 | 0 | 0 |  |  | 52 | 0.16 |  |  | 60 | 0.16
xyx | 2021-07-04 00:00:00 | 2021-07-05 00:00:00 | 2021-07-13 00:00:00 | [PHONE] | RV | SI3001111565 | ZSOR | 1171119.3 | Y | 2021-08-10 00:00:00 | 2021-08-10 00:00:00 | [PHONE] | DX |  | 1150000 | 15 | 28 | 0 | 6257 | 0 | 0 | 0
xyx | 2021-07-04 00:00:00 | 2021-07-05 00:00:00 | 2021-07-13 00:00:00 | [PHONE] | RV | SI3001111565 | ZSOR | 21119.3 | Y | 2021-09-30 00:00:00 | 2021-09-30 00:00:00 |  |  |  | 0 | 52 | 80 | 0 | 181 | 259 | 0 | 0
xyx | 2021-07-26 00:00:00 | 2021-07-26 00:00:00 | 2021-07-26 00:00:00 | [PHONE] | DN |  |  | 42527.55 |  | 2021-09-30 00:00:00 | 2021-09-30 00:00:00 |  |  |  | 0 | 66 | 67 | 175 | 682 | 131 | 0 | 0
xyx | 2021-08-12 00:00:00 | 2021-08-13 00:00:00 | 2021-08-21 00:00:00 | [PHONE] | RV | SI3001112214 | ZSOR | 1299026 | Y | 2021-09-30 00:00:00 | 2021-09-30 00:00:00 |  |  |  | 0 | 40 | 41 | 2491 | 15731 | 0 | 0 | 0
Spreadsheet: 01aba8ac-b876-4ff1-b27d-d4e28919c2e3
Sheet: CDS-E

E. ACADEMIC OFFERINGS AND POLICIES
E1 | Special study options: Identify those programs available at your institution. Refer to the glossary for definitions.
E1 | Accelerated program
E1 | Cooperative education program
E1 | Cross-registration | X
E1 | Distance learning
E1 | Double major | X
E1 | Dual enrollment | X
E1 | English as a Second Language (ESL)
E1 | Exchange student program (domestic) | X
E1 | External degree program
E1 | Honors Program | X
E1 | Independent study | X
E1 | Internships | X
E1 | Liberal arts/career combination | X
E1 | Student-designed major | X
E1 | Study abroad | X
E1 | Teacher certification program | X
E1 | Weekend college
E1 | Other (specify):
E2 | This question has been removed from the Common Data Set.
E3 | Areas in which all or most students are required to complete some course work prior to graduation:
E3 | Arts/fine arts | X
E3 | Computer literacy
E3 | English (including composition) | X
E3 | Foreign languages | X
E3 | History
E3 | Humanities | X
E3 | Mathematics | X
E3 | Philosophy
E3 | Sciences (biological or physical) | X
E3 | Social science | X
E3 | Other (describe):      First-year Seminar | X
 | Library Collections: The CDS Publishers will collect library data again when a new Academic Libraries Survey is in place.
Spreadsheet: 856620d1705819912-match-and-extract-lambda-map-filter-extract_3
Sheet: L3

 |  |  |  |  | Match |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | <<< Extract >> | <<< Extract >> |  |  | <<< Extract >>
 |  |  |  |  | B-1/2/3 | fsf | vfsdfs | gdsf | dfgsd | fas | sfasdf | afs | asdfeas | fasdf | asdf | asdf | dasf | asdf | asdf |  |  |  |  |  |  | x | x
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | x | x
 |  |  |  |  | Lon-2/5 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | x | x
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | x | x
 |  |  |  |  | Lon-1 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | x | x
 |  |  |  |  | S-4 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | x | x
 |  |  |  |  | x
 |  |  |  |  | S-1
 |  |  |  |  | ab
Spreadsheet: 230978d1366914242-web-address-needed-for-excel-file-book1
Sheet: Sheet1

 | Three Matches Table (Sat 20 Apr - Mon 22 Apr)
 | Pos | LW | Name | Played | Matches | AGPM | Total Goals
 | 1 | 1 | Rooney34 | 53 | 159 | 3.257861635220126 | 518
 | 2 | 3 | [NAME] | 54 | 162 | 3.04320987654321 | 493
 | 3 | 2 | [NAME] | 54 | 162 | 2.993827160493827 | 485
 | 4 | 4 | spurslad | 53 | 159 | 2.880503144654088 | 458
 | 5 | 5 | gb | 52 | 156 | 2.647435897435897 | 413
 | 6 | 6 | geordieloon | 38 | 114 | 3 | 342
 | 7 | 7 | NorthernEagle | 12 | 36 | 3.472222222222222 | 125
 | 8 | 8 | [NAME] | 6 | 18 | 4.111111111111111 | 74
 | 9 | 9 | Paul1985 | 4 | 12 | 2.833333333333333 | 34
Spreadsheet: 866435d1713349462-calculation-of-step-tax-with-sumproduct-function-under-the-condition-of-non-exemption-data
Sheet: Sheet1

Amount | Rate |  | Amount | Tax
12000 | 0 |  | 24000
20000 | 0.1 |  |  |  |  | 8000
27000 | 0.15 |  | This is absolutely true |  |  | 4000
40000 | 0.2
 | 0.25
Amount | Rate |  | Amount | Tax
12000 | 0.1 |  | 24000 |  |  | 12000
20000 | 0.15 |  |  |  |  | 8000
27000 | 0.2 |  |  |  |  | 4000
40000 | 0.25 |  | The expected answer in this case
 | 0.3
Spreadsheet: cc052cab-5fc3-4fc9-8cf4-a55858f894a3
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
CKMB | Test | CKMB | [NAME] (CK) MB Isoenzyme, Serum | [NAME] Kinase(CK) MB Isoenzyme, S | Electrochemiluminescent Immunoassay | Serum Gel Tube: SGT |  |  | 1 | mL | Collection Container/Tube:  Preferred: Serum gel Acceptable: Red top or rapid serum tube (RST) Submission Container/Tube: Plastic vial [NAME]: 1 mL | 0.5 mL | Hemolysis	Mild OK; Gross OK Thawing	Warm reject; Cold OK Lipemia	NA Icterus	NA Other	NA | Males: <6.7 ng/mL Females: <3.8 ng/mL | Monday through Sunday; Continuously | Same day/1 day | 1 day | 1 | 82553 |  |  |  |  | Rochester
CKMB | [NAME] | SERUM | Serum |  |  |  | Frozen | 90 days
CKMB | Result | CKMB | [NAME] Kinase(CK) MB Isoenzyme, S | [NAME] Kinase(CK) MB Isoenzyme, S | Numeric |  |  |  |  | ng/mL |  |  |  |  |  |  |  |  |  | 13969-1 | [NAME] kinase.MB:MCnc:Pt:Ser/Plas:Qn:
Spreadsheet: 12ae4914-9db9-413a-8128-64f01916d0aa
Sheet: Sheet1

Table 8--U.S. cotton textile imports, by origin | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
 | Feb. | Mar. | Apr. |  | Apr.
Region/country | 2013 | 2013 | 2013 |  | 2012
 | 1,000 pounds 1/
North America | 132256.313 | 143308.444 | 133329.089 |  | 122628.495
Canada | 2724.511 | 2852.062 | 3023.839 |  | 3325.033
Costa Rica | 788.641 | 687.865 | 494.079 |  | 546.599
Dominican Republic | 6358.245 | 6838.911 | 6469.577 |  | 5627.788
El Salvador | 18308.671 | 20297.836 | 17105.447 |  | 16829.256
Guatemala | 7761.34 | 8251.197 | 7791.908 |  | 8114.954
Haiti | 12292.378 | 13662.017 | 14497.4 |  | 11825.505
Honduras | 28209.277 | 31598.707 | 24816.975 |  | 22771.042
Mexico | 42105.729 | 40749.508 | 43253.536 |  | 39670.06
Nicaragua | 13652.658 | 18363.675 | 15863.65 |  | 13901.652
South America | 3865.94 | 5341.988 | 4177.306 |  | 4220.969
Brazil | 131.639 | 163.117 | 158.431 |  | 187.938
Colombia | 1663.199 | 2465.582 | 1909.056 |  | 1722.563
Peru | 2020.194 | 2675.035 | 2066.811 |  | 2221.755
Europe | 10037.095 | 11153.073 | 10981.382 |  | 10152.663
Germany | 958.4 | 1009.684 | 1085.452 |  | 828.58
Italy | 1448.906 | 1651.119 | 1712.519 |  | 1568.509
Portugal | 1107.773 | 1106.525 | 998.822 |  | 871.185
Turkey | 4480.481 | 4728.641 | 4685.644 |  | 4393.456
Asia | 521706.88 | 429782.725 | 479170.471 |  | 456736.891
Bahrain | 1331.887 | 1536.084 | 1637.504 |  | 1256.572
Bangladesh | 51746.584 | 51585.066 | 48322.046 |  | 40205.521
Cambodia | 17091.386 | 17790.319 | 17637.185 |  | 19245.755
China | 229485.161 | 128014.848 | 177001.036 |  | 187318.262
Hong Kong | 811.289 | 761.378 | 859.611 |  | 649.251
India | 58861.543 | 66365.713 | 66857.585 |  | 54719.592
Indonesia | 29632.134 | 29048.129 | 29199.272 |  | 26459.726
Israel | 792.455 | 774.485 | 574.821 |  | 745.162
Japan | 914.717 | 1166.333 | 1055.003 |  | 1169.016
Jordan | 4332.655 | 4065.946 | 4276.171 |  | 4161.101
Malaysia | 2963.467 | 2651.68 | 2369.554 |  | 2250.929
Pakistan | 52624.61 | 61731.93 | 61264.362 |  | 52590.885
Philippines | 4892.683 | 5084.08 | 5022.731 |  | 4917.232
South Korea | 5039.854 | 4852.106 | 5772.812 |  | 6043.103
Sri Lanka | 6420.051 | 7296.354 | 7473.313 |  | 5884.383
Taiwan | 2471.331 | 1655.188 | 2350.173 |  | 2673.661
Thailand | 6658.897 | 5856.408 | 6239.354 |  | 6358.745
Vietnam | 44717.441 | 38617.097 | 40438.512 |  | 38521.37
Oceania | 10.305 | 29.158 | 15.875 |  | 49.711
Africa | 11443.885 | 14575.522 | 14683.935 |  | 12352.191
Egypt | 6835.211 | 8556.056 | 7932.711 |  | 7039.47
Kenya | 1250.237 | 1985.906 | 1793.546 |  | 1548.383
[NAME] | 1522.063 | 2245.999 | 2767.698 |  | 1834.912
[NAME] | 726.662 | 703.699 | 829.035 |  | 653.496
World 2/ | 679320.418 | 604190.911 | 642358.058 |  | 606140.921
 |  |  |  |  |  |  |  | 95
1/ Raw-fiber equivalent.  2/ Totals may not add due to rounding.
Sources: USDA, Economic Research Service; and
U.S. Dept. of Commerce, U.S. Census Bureau.
Last update:  06/14/13.
Spreadsheet: c2108ba1-1db2-41cb-89fd-6a55217aeab1
Sheet: Table 4.1

Monthly Statistical Bulletin
4.1 Turnover of retail establishments
Month | 2008–09 | 2009–10 | 2010–11 | 2011–12 | 2012–13
Value (a)(b) – $ million
July
August
September
October
November
December
January
February
March
April
May
June
Annual
Annual change (a) – per cent
July
August
September
October
November
December
January
February
March
April
May
June
Annual
(a) Monthly figures are seasonally adjusted.
(b)  Excludes hotels, licensed clubs, video hire outlets, hairdressing and beauty salons,
motor vehicle sales, motor vechile parts and tyre retailing, fuel retailing and
marine equipment retailing. |  |  |  |  |  |  |  | Update
Source: ABS, Retail trade Australia, Cat. no. 8501.0
Spreadsheet: 875977d1722608957-return-multiple-match-values-in-columns-example
Sheet: Data 1

Area Code | Surname | Foreame | DOB | Main reason Y/N | Reason1
A0987 | Smith | Fred | 1967-02-02 00:00:00 | Y | Left in car
A0987 | Smith | Fred | 1967-02-02 00:00:00 | N | no transport
A5678 | Doe | [NAME] | 1966-12-25 00:00:00 | Y | left on bus
A5678 | Doe | [NAME] | 1966-12-25 00:00:00 | N | theft
A1234 | Bloggs | [NAME] | 1950-01-01 00:00:00 | Y | Left on train
A1234 | Bloggs | [NAME] | 1950-01-01 00:00:00 | N | accident
A1234 | Bloggs | [NAME] | 1950-01-01 00:00:00 | N | no transport
A1234 | Bloggs | [NAME] | 1950-01-01 00:00:00 | N | car
A4567 | Black | [NAME] | 1970-02-03 00:00:00 | Y | no transport
A2345 | Red | [NAME] | 1978-03-23 00:00:00 | Y | left in car
A2345 | Red | [NAME] | 1978-03-23 00:00:00 | N | left on bus
A2345 | Red | [NAME] | 1978-03-23 00:00:00 | N | theft
A2345 | Red | [NAME] | 1978-03-23 00:00:00 | N | nothing found
 | I need the Main Reason "N" to be transferred into Tranche 1, but into columns, rather than rows, example in red
Spreadsheet: 453633d1459386336-count-unique-association-across-overlapping-groups-example
Sheet: Data

Group | ID | Unique Associations | Count of Unique Associations
A | 1 | 2,3,4,5,6,7,8,9,10 | 9
A | 2 | 1,3,4,8,9,10 | 6
A | 3 | 1,2,4 | 3
A | 4 | 1,2,3,5,6,7,8, | 7
B | 5 | 1,4,6,7,8 | 5
B | 1 | 2,3,4,5,6,7,8,9,10 | 9
B | 4 | 1,2,3,5,6,7,8, | 7
B | 6 | 5,1,4,7,8 | 5
B | 7 | 1,4,6,8 | 4
B | 8 | 5,1,4,6,7 | 5
C | 1 | 2,3,4,5,6,7,8,9,10 | 9
C | 2 | 1,3,4,8,9,10 | 6
C | 8 | 5,1,4,6,7 | 5
C | 9 | 1,2,8,10 | 4
C | 10 | 1,2,8,9 | 4
Spreadsheet: 884895d1734223071-help-with-dynamic-calendar_incorrect-event-text-color-dynamic-event-and-holiday-calendar-in-excel-test1-jt-
Sheet: Holiday Calendar

 |  |  |  |  |  |  |  |  | June |  |  |  |  |  | 2025
 | Sunday |  |  |  | Monday |  |  |  | Tuesday |  |  |  | Wednesday |  |  |  | Thursday |  |  |  | Friday |  |  |  | Saturday
 | Notes |  | :
Spreadsheet: 0052691d-8bc7-45f8-82b4-15c2b27c808e
Sheet: Sheet1

Mountains | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
Round 1
 |  | [NAME]
 |  | Garbanzo | Pea | Lentil | Total
Predators |  | 300 | 300 | 300 | 900 | % captured | Utensils for next generation | Rounded to equal 9
Forks | 2 |  |  |  | 0
Spoons | 2 |  |  |  | 0
Knives | 2 |  |  |  | 0
 | Total Captured | 0 | 0 | 0 | 0
 | Left Over | 300 | 300 | 300 | 900
 | Add | 30 | 30 | 30
Round 2
 |  | [NAME]
 |  | Garbanzo | Pea | Lentil | Total
Predators |  | 330 | 330 | 330 | 990 | % captured | Utensils for next generation | Rounded to equal 9
Forks | 0 |  |  |  | 0
Spoons | 0 |  |  |  | 0
Knives | 0 |  |  |  | 0
 | Total Captured | 0 | 0 | 0 | 0
 | Left Over | 330 | 330 | 330 | 990
 | Add | 33.00000000000006 | 33.00000000000006 | 33.00000000000006
Round 3
 |  | [NAME]
 |  | Garbanzo | Pea | Lentil | Total
Predators |  | 363.0000000000001 | 363.0000000000001 | 363.0000000000001 | 1089 | % captured | Utensils for next generation | Rounded Final Total
Forks | 0 |  |  |  | 0
Spoons | 0 |  |  |  | 0
Knives | 0 |  |  |  | 0
 | Total Captured | 0 | 0 | 0 | 0
 | Left Over | 363.0000000000001 | 363.0000000000001 | 363.0000000000001 | 1089
 | Add | 36.30000000000001 | 36.30000000000001 | 36.30000000000001
Round 4
 |  | [NAME]
 |  | Garbanzo | [NAME] bean | Lentil | Total
Predators |  | 399.3000000000001 | 399.3000000000001 | 399.3000000000001 | 1197.9 | % captured | Utensils for next generation | Rounded Final Total
Forks | 0 |  |  |  | 0
Spoons | 0 |  |  |  | 0
Knives | 0 |  |  |  | 0
 | Total Captured | 0 | 0 | 0 | 0
 | Left Over | 399.3000000000001 | 399.3000000000001 | 399.3000000000001 | 1197.9
 | Add | 39.93000000000006 | 39.93000000000006 | 39.93000000000006
 | Total Left | 439.2300000000001 | 439.2300000000001 | 439.2300000000001
Spreadsheet: 192368d1352389489-exact-all-text-except-last-2-characters-example-problem
Sheet: Sheet1

Customer | Line | Note | Stamp
12345 | 1 |  | 12345   112110615051400001
12345 | 1 |  | 12345   112110615051500001
12345 | 2 |  | 12345   112110615051500002
12345 | 3 |  | 12345   112110615051500003
2345621 | 1 |  | 2345621  112110609311200001
2345621 | 2 |  | 2345621  112110609311200002
564321 | 1 |  | 564321  112110609355700001
564321 | 1 |  | 564321  112110611464700001
564321 | 2 |  | 564321  112110611464700002
564321 | 3 |  | 564321  112110611464700003
564321 | 4 |  | 564321  112110611464700004
564321 | 5 |  | 564321  112110611464700005
564321 | 6 |  | 564321  112110611464700006
564321 | 7 |  | 564321  112110611464700007
564321 | 8 |  | 564321  112110611464700008
564321 | 9 |  | 564321  112110611464700009
564321 | 10 |  | 564321  112110611464700010
564321 | 11 |  | 564321  112110611464700011
564321 | 12 |  | 564321  112110611464700012
Spreadsheet: 1852cafd-3da2-4f59-9edc-afe609fa55c5
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
 | Time Series Workbook
 | 5671.0 Lending Finance, Australia
 | TABLE 33. LEASE FINANCE COMMITMENTS, By Purpose: State (QLD), Original (Number, $000)
Related Information: | Summary Publication | Explanatory Notes | Inquiries
 | Glossary
Data Item Description |  |  | Series Type | Series ID | Series Start | Series End | No. Obs. | Unit | Data Type | [NAME]. | Collection Month
1 . . . [NAME] ; |  |  | Original | A2413943F | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
1.1 . . . . . New cars and station wagons ; |  |  | Original | A2413944J | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
. . . . . . . . [New cars and station wagons (no.)] ; |  |  | Original | A2413945K | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | Number | FLOW | Month | 1
1.2 . . . . . Used cars and station wagons ; |  |  | Original | A2413946L | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
. . . . . . . . [Used cars and station wagons (no.)] ; |  |  | Original | A2413947R | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | Number | FLOW | Month | 1
1.3 . . . . . Other motor vehicles  ; |  |  | Original | A2413948T | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
1.3.1a . . . . . . - new trucks ; |  |  | Original | A2413949V | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
. . . . . . . . . . . . [new trucks (no.)] ; |  |  | Original | A2413950C | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | Number | FLOW | Month | 1
1.3.3 a. . . . . . - used trucks ; |  |  | Original | A2413951F | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
. . . . . . . . . . . . [used trucks (no.)] ; |  |  | Original | A2413952J | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | Number | FLOW | Month | 1
1.3.5 . . . . . . . - trailers, buses, coaches, other MVs ; |  |  | Original | A2413953K | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
2 . . . Other Transport Equipment ; |  |  | Original | A2413954L | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
3 . . . Agricultural, Construction & Manufacturing Equipment ; |  |  | Original | A2413955R | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
4 . . . Office Equipment ; |  |  | Original | A2413956T | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
5 . . . Other ; |  |  | Original | A2413957V | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
TOTAL LEASE FINANCE ; |  |  | Original | A2413958W | 1985-01-01 00:00:00 | 2012-12-01 00:00:00 | 336 | $'000 | FLOW | Month | 1
© Commonwealth of Australia  2013
Spreadsheet: 796081d1663090270-spill-range-with-countifs-of-unique-rows-2022-09-13-oeldere-marbleking-countifs_unique
Sheet: Table1

Date_1 | Date_2 | Date_3
2019-07-30 00:00:00 | 2019-06-25 00:00:00 | 2019-08-01 09:44:12 |  |  | 2019-06-25 00:00:00 | 2019-08-01 09:44:12
2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20 |  | 2019-08-09 00:00:00 | 2019-07-01 00:00:00 | 2019-10-03 13:39:20
2019-08-01 00:00:00 | 2019-07-08 00:00:00 | 2019-08-01 12:19:15 |  | 2019-08-01 00:00:00 | 2019-07-08 00:00:00 | 2019-08-01 12:19:15
2019-08-22 00:00:00 | 2019-07-31 00:00:00 | 2019-09-20 06:54:36 |  | 2019-08-22 00:00:00 | 2019-07-31 00:00:00 | 2019-09-20 06:54:36
2019-09-03 00:00:00 | 2019-08-07 00:00:00 | 2019-09-05 12:57:23 |  | 2019-09-03 00:00:00 | 2019-08-07 00:00:00 | 2019-09-05 12:57:23
2019-09-05 00:00:00 | 2019-08-13 00:00:00 | 2019-09-05 09:55:58 |  | 2019-09-05 00:00:00 | 2019-08-13 00:00:00 | 2019-09-05 09:55:58
Spreadsheet: 888434d1738930254-filter-tocol-dynamic-formula-filterattempt2
Sheet: Data

Fruit | Source | Price
APPLE | BELGIUM | 99
APPLE | FRANCE | 78
APPLE | GERMANY | 71
APPLE | ITALY | 63
APPLE | SPAIN | 84
APPLE | SWITZERLAND | 46
APPLE1 | BELGIUM | 75
APPLE1 | FRANCE | 40
APPLE1 | GERMANY | 92
APPLE1 | SPAIN | 95
APPLE2 | BELGIUM | 10
APPLE2 | FRANCE | 76
APPLE2 | GERMANY | 37
APPLE2 | SPAIN | 65
BANANA | FRANCE | 78
BANANA | SPAIN | 75
BANANA | SWITZERLAND | 89
KIWI | BELGIUM | 66
KIWI | GERMANY | 26
KIWI | SPAIN | 26
KIWI | SWITZERLAND | 92
ORANGE | BELGIUM | 49
ORANGE | FRANCE | 81
ORANGE | GERMANY | 36
ORANGE | ITALY | 32
PEAR | BELGIUM | 48
PEAR | GERMANY | 31
PEAR | SPAIN | 76
PLUM | FRANCE | 15
PLUM | ITALY | 89
PLUM | SPAIN | 34
Spreadsheet: 212406d1360125360-looking-to-count-up-each-time-data-is-presented-copy
Sheet: Sheet1

 | Data | Count | Data | Count | Data | Count | Data | Count | Data | Count
 | 5 |  | 10 |  | 24 |  | 38 |  | 43 | 5
 | 10 |  | 12 |  | 23 |  | 43 | 4 | 47
 | 3 |  | 27 |  | 35 |  | 37 |  | 45
 | 7 |  | 20 | 3 | 43 | 3 | 46 |  | 54
 | 1 |  | 12 |  | 23 |  | 27 |  | 43 | 2
 | 30 |  | 41 |  | 20 | 2 | 51 |  | 53
 | 3 |  | 4 |  | 12 |  | 27 |  | 44
 | 12 |  | 34 |  | 48 |  | 52 |  | 55
 | 6 |  | 20 | 1 | 22 |  | 32 |  | 43 | 1
 | 16 |  | 13 |  | 42 |  | 50 |  | 54
Data will go into columns B,D,F,H,J.
Columns C,E,G,I,K  will count how many times # shows up in B,D,F,H,J.
I have some examples counted in the highlighted areas.
I need this to work for all numbers up to 100 if possible.