tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 707885d1607525196-how-to-assign-a-country-to-a-specific-area-dashboard
Sheet: RUSSIA

Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | Top 5  lowest price | AB | MedEL | Cochlear | OM | Custom label
Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | Top 5  highest price | AB | MedEL | Cochlear | OM | Custom label
Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | Antenna cable | AB | MedEL | Cochlear | OM | Custom label
Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | [NAME] | AB | MedEL | Cochlear | OM | Custom label
Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | Charger | AB | MedEL | Cochlear | OM | Custom label
Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | Recheargable battery | AB | MedEL | Cochlear | OM | Custom label
Country | Category of item | Brands | Name of item | Reference N of the item | End user price in local currency after VAT | GNI per capita | Bundled | End user price in EUR after VAT |  | Full swim kit | AB | MedEL | Cochlear | OM | Custom label
Spreadsheet: 47367d1246395565-fill-cell-w-value-present-in-another-row-if-columns-match-third-smplith-formulas
Sheet: Sheet1

The Specials | The Specials | Blank Expression | The Specials
 | The Specials | Blank Expression | The Specials
 | The Specials | Blank Expression | The Specials
 | The Specials | Blank Expression | The Specials
 | The Specials | Blank Expression | The Specials
Anxiety Always | Adult. | [NAME] | Anxiety Always
Here Come The Warm Jets | [NAME] | [NAME] | Here Come The Warm Jets
 | [NAME] | [NAME] | Here Come The Warm Jets
 | [NAME] | [NAME] | Here Come The Warm Jets
 | [NAME] | [NAME] | Here Come The Warm Jets
 | [NAME] | [NAME] | Here Come The Warm Jets
Adore | [NAME] | Blank Page | Adore
 | [NAME] | Blank Page | Adore
[NAME] | Shuttle 358 | Blast | [NAME]
 | Shuttle 358 | Blast | [NAME]
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Spreadsheet: 51fcb3d9-04d8-441a-af69-6172a9a97adb
Sheet: Frontier Shift

 | This sheet shows the analysis of frontier shift based on the CEPA study.
 | [NAME] - frontier shift
 |  |  |  |  |  | Year: | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10
 | January 2013 FBP Forecast |  |  |  |  |  | Q5 |  |  |  |  | Q5+1 | Q6 |  |  |  |  |  | Q6 Total | CAGR | per year
 | £m 2011/12 prices |  |  |  |  |  | 2008/09 | 2009/10 | 2010/11 | 2011/12 | 2012/13 | 2013/14 | 2014/15 | 2015/16 | 2016/17 | 2017/18 | 2018/19
 | Total FBP
 | Total ABP
 | Airport Efficiency Estimate | Frontier Shift | In Business Plan? | Net
 | Low Efficiency Estimate | 0.009 | 0.0087 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | na
 | Mid Efficiency Estimate | 0.01 | 0.0087 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | na
 | High Efficiency Estimate | 0.01 | 0.0087 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | na
 | End
Spreadsheet: 154039d1336157577-excel-2007-countifs-where-some-data-is-in-columns-and-other-data-is-in-an-array-excel-help
Sheet: Sheet1

 |  |  | Impacts
group | year | feature | system1 | system2 | [NAME] | system4 | system5 |  |  | Group: | IT
finance | 2012 | description… | H |  |  | H
finance | 2013 | description… |  |  |  |  | L |  |  |  | system1 | system4 | system5
finance | 2012 | description… |  | H | M | M |  |  |  | 2012 | =COUNTIFS($A:$A, "="&$L$2,$B:$B, "="&$K$5,(INDEX(D3:H20,0,MATCH(L4,D2:H2,0 ))), <>"")
emerging business | 2013 | description… | L | M |  |  |  |  |  | 2013 | =COUNTIFS($A:$A, "="&$L$2,$B:$B, "="&$K$6,(INDEX(D3:H20,0,MATCH(L4,D2:H2,0 ))), <>"")
emerging business | 2012 | description… |  | x |  |  |  |  |  | 2014 | =COUNTIFS($A:$A, "="&$L$2,$B:$B, "="&$K$7,(INDEX(D3:H20,0,MATCH(L4,D2:H2,0 ))), <>"")
emerging business | 2013 | description…
emerging business | 2013 | description… | L | M
emerging business | 2012 | description… |  | x
emerging business | 2013 | description…
IT | 2014 | description… |  |  | M |  |  |  |  |  | Key
IT | 2012 | description… |  |  |  | H |  |  |  |  |  | represents data validation list
IT | 2013 | description… | H
IT | 2012 | description… | H |  |  | H
IT | 2013 | description… |  |  |  |  | L
IT | 2012 | description… |  | H | M | M
IT | 2014 | description… |  |  | M
IT | 2012 | description… |  |  |  | H
IT | 2013 | description… | H
Spreadsheet: 754305d1636089060-applying-countif-formula-when-counting-values-from-multiple-worksheets-countif-example
Sheet: Music

Name | Staff ID | Staff type | Employed as/student type | Job description
Name 1 | ID 1 | Non-academic | Honorary | Honorary Research Fellow
Name 2 | ID 2 | Non-academic | Honorary | Senior Honorary Research Fellow
Name 3 | ID 3 | Non-academic | Staff | Administrative Assistant
Name 4 | ID 4 | Academic | Teaching & Research | Associate Professor
Name 5 | ID 5 | Non-academic | Staff | Venue Assistant
Name 6 | ID 6 | Academic | Teaching & Research | Lecturer
Name 7 | ID 7 | Academic | Teaching & Research | Senior Lecturer
Name 8 | ID 8 | Academic | Teaching | Lecturer
Name 9 | ID 9 | Academic | Teaching & Research | Senior Lecturer
Name 10 | ID 10 | Academic | Teaching & Research | Lecturer
Name 11 | ID 11 | Non-academic | Honorary | Honorary Research Fellow
Name 12 | ID 12 | Academic | Teaching & Research | Academic Development Officer
Name 13 | ID 13 | Academic | Teaching & Research | Senior Lecturer
Spreadsheet: 218198d1362397725-organising-inventory-upload-for-help_1
Sheet: Inventory Management

 | Total quantity | loan out | maintenance | present remainder | Date |  | Start Date | End Date
Chair | 10 |  |  |  |  |  | 2012-01-01 00:00:00 | 2012-12-31 00:00:00
Table | 10
Lamp | 10
Bottle | 10
[NAME] | 10
Laptop | 10
Spreadsheet: 58451d1258676904-pull-sub-test-scores-from-test-w-best-overall-test-score-psat-test-scores-report-fixed-11-17-09-cv
Sheet: By Wave

 | PSAT |  |  |  |  |  |  | SAT |  |  |  |  |  |  |  | MWEP Math Diagnostics |  |  |  |  |  |  |  |  | RWEP Diagnostics
Test Score ID Reference >> | 215 |  | 216 |  |  | 217 | 382 | 16 |  | 383 |  | 17 |  | 18 |  | 438 | 180 | 441 | 20 | 63 | 67 | 65 | 64 | 66 | 385 | 85 | 83 | 84 | 86
 | Critical Reading |  | Math |  | Writing Skills |  |  | Critical Reading |  | Essay |  | Math |  | Writing |  | 5th Gr. Diagnostic | 6th Gr. Diagnostic | 7th Gr. Diagnostic | Pre-Alg. | Algebra | Alg. II | Geometry | Calculus | Math Analysis | Degrees of Reading Power
Wave-Maker | Number Score | National Percentile | Number Score2 | National Percentile3 | Number Score4 | National Percentile5 | Overall Nat. Percentile | Number Score6 | National Percentile2 | Number Score7 | Nat. Percentile8 | Number Score9 | National Percentile10 | [NAME] | National Percentile12 | Percent Score | Percent Score2 | Percent Score3 | Percent Score4 | Percent Score5 | Percent Score6 | Percent Score7 | Percent Score8 | Percent Score9 | Raw Score | Frustration Reading Lvl | Independent Reading Lvl | Instructional Reading Lvl | Nat. Percentile
Albgal, Hossain
Boles, Adrianna
[NAME], [NAME]
Broussard, Broushon
[NAME], Christian
Cisneros, Cesia E.
[NAME], [NAME]
[NAME], [NAME]
Cowen, [NAME]
Cummings, [NAME]
[NAME], [NAME]
Esquivias, [NAME]
Flores, [NAME]
[NAME], Jemar
Fuentes, [NAME]
Galaviz, Margarita
Godoy, [NAME]
[NAME], Lili
[NAME], [NAME]
Green, [NAME]
Haynes, Dashaela
[NAME], Merced
[NAME], ErnNeshia
[NAME], Izenique
Keobounheung, [NAME]
Keobounheung, [NAME]
[NAME], [NAME]
Macias, Serafin
[NAME], [NAME]
[NAME], Ivon
McDougall, Rosette
McFadden, Devan
Mendez, Miguel
Mendoza, [NAME]
Millan, Viviana
Munguia, [NAME]
Navarro, [NAME]
Ornelas, [NAME]
[NAME], [NAME]
Paasch, [NAME]
Payne, Gina
Pena, [NAME]
Polanco, [NAME]
Ponce, Cristina
[NAME], [NAME]
Quintanilla, [NAME]
Quintanilla, [NAME]
[NAME], [NAME]
Saefong, Samantha
Salas, [NAME]
Sanchez, [NAME]
Sanchez, [NAME]
Silva, Ricardo
Solis, Andres
Souksamphanh, [NAME]
Sterling, Allise
Tooks, [NAME]
Tran, Carol
Walker, Shanika
[NAME], [NAME]
Weston, [NAME]
[NAME], Chara
[NAME], Denzel D.
Spreadsheet: fa968926-0fc8-442d-8cca-5d2caf378a5e
Sheet: Sheet1

[NAME], Maine, by Year, 1999-2009 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
Year | Number of Deaths | Crude Rate |  | Age-adjusted Rate
 |  | Rate | 95% CI | Rate | 95% CI
1999 | 215 | 33 | 28.8 - 37.8 | 27.1 | 23.5 - 31.0 |  | 3 Year Moving Averages
2000 | 197 | 30 | 26.0 - 34.5 | 24.2 | 20.9 - 27.9 |  | Years | Age-Adjusted Rate
2001 | 182 | 27.6 | 23.7 - 31.9 | 22 | 18.9 - 25.5 |  | 99-01 | 24.43333333333333
2002 | 201 | 30.3 | 26.2 - 34.8 | 24 | 20.8 - 27.6 |  | 00-02 | 23.4
2003 | 231 | 34.6 | 30.3 - 39.4 | 27.5 | 24.0 - 31.4 |  | 01-03 | 24.5
2004 | 185 | 27.6 | 23.8 - 31.9 | 21.4 | 18.4 - 24.8 |  | 02-04 | 24.3
2005 | 198 | 29.5 | 25.5 - 33.9 | 22.6 | 19.5 - 26.0 |  | 03-05 | 23.83333333333333
2006 | 193 | 28.7 | 24.8 - 33.0 | 21.4 | 18.4 - 24.7 |  | 04-06 | 21.8
2007 | 184 | 27.3 | 23.5 - 31.5 | 20.3 | 17.4 - 23.5 |  | 05-07 | 21.43333333333333
2008 | 199 | 29.5 | 25.5 - 33.9 | 21.8 | 18.8 - 25.2 |  | 06-08 | 21.16666666666667
US 2009 |  |  |  | 22.5 | 22.3 - 22.7
Data Source: Surveillance, Epidemiology, and End Results SEER Program, National Cancer Institute, Underlying mortality data provided by National Center for Health Statistics. [NAME]: Deaths with malignant cancer as the underlying cause of death. [NAME]: SEER Cause of Death Recode: 26000 (which include 1999-2009: ICD-10 codes C50; 1993-1998: ICD-9 codes 174-175) Crude rates are deaths per 100,000 population. Age-adjusted rates are deaths per 100,000 population age-adjusted to the U.S. 2000 standard population. 95% CI: 95% confidence interval of the rate. Rates are calculated using SEER*Stat Version 7.0.5.
Spreadsheet: 476997d1472099292-how-to-sort-timesheet-from-a-single-column-to-3-different-columns-raw
Sheet: Sheet1

Account No. | Name | Company | ClockTime
32 | [NAME] | Swift | 2016-08-01 08:52:40
32 | [NAME] | Swift | 2016-08-01 18:11:02
32 | [NAME] | Swift | 2016-08-02 08:59:06
32 | [NAME] | Swift | 2016-08-02 18:08:35
32 | [NAME] | Swift | 2016-08-03 08:59:27
32 | [NAME] | Swift | 2016-08-03 18:05:10
32 | [NAME] | Swift | 2016-08-04 09:20:51
32 | [NAME] | Swift | 2016-08-04 18:22:02
32 | [NAME] | Swift | 2016-08-05 09:02:43
32 | [NAME] | Swift | 2016-08-05 18:35:33
32 | [NAME] | Swift | 2016-08-08 09:02:44
32 | [NAME] | Swift | 2016-08-08 18:09:33
32 | [NAME] | Swift | 2016-08-09 08:55:45
32 | [NAME] | Swift | 2016-08-09 18:13:12
32 | [NAME] | Swift | 2016-08-10 08:59:07
32 | [NAME] | Swift | 2016-08-10 18:16:33
32 | [NAME] | Swift | 2016-08-11 09:02:38
32 | [NAME] | Swift | 2016-08-11 18:08:44
32 | [NAME] | Swift | 2016-08-12 08:59:11
32 | [NAME] | Swift | 2016-08-12 18:04:30
32 | [NAME] | Swift | 2016-08-15 08:59:32
32 | [NAME] | Swift | 2016-08-15 18:09:45
32 | [NAME] | Swift | 2016-08-16 08:57:01
32 | [NAME] | Swift | 2016-08-16 18:10:41
32 | [NAME] | Swift | 2016-08-17 08:59:40
32 | [NAME] | Swift | 2016-08-17 18:07:56
32 | [NAME] | Swift | 2016-08-18 08:42:35
32 | [NAME] | Swift | 2016-08-18 18:06:05
32 | [NAME] | Swift | 2016-08-19 08:42:35
32 | [NAME] | Swift | 2016-08-19 18:06:41
32 | [NAME] | Swift | 2016-08-22 08:49:54
32 | [NAME] | Swift | 2016-08-22 18:10:27
32 | [NAME] | Swift | 2016-08-23 08:53:34
Spreadsheet: 780934d1652873272-generating-random-array-with-conditions-random-weights
Sheet: Sheet1

 |  | Example List |  | Conditions
 | 0.02092005660623625 |  |  | 1. Generate 30 weights.
 | 0.03709348467934822 |  |  | 2. Each weight must be less than 10%
 | 0.05847144688689439 |  |  | 3. Sum of all weights must be 100%
 | 0.01960041415196592 |  |  | 4. For weights that are above 5%, sum of them must be not greater than 40%.
 | 0.04621567233992637
 | 0.01133416730281202
 | 0.0320378561195098 |  |  | Condition 1
 | 0.02556246045137877 |  |  | Condition 2
 | 0.02351647362474594 |  |  | Condition 3
 | 0.06804675739146045 |  |  | Condition 4
 | 0.009909331526363318
 | 0.008645657724656622
 | 0.0639556698486989
 | 0.049
 | 0.04214969644853481
 | 0.05837044896057407
 | 0.04329714540041499
 | 0.01246179792804267
 | 0.01303951103344359
 | 0.05014358541913974
 | 0.049
 | 0.01918305355761488
 | 0.001309060460912069
 | 0.0365193252656001
 | 0.01271532300781198
 | 0.05912374943988485
 | 0.0126827219983936
 | 0.03285134429847211
 | 0.04068176213071856
Spreadsheet: 122014d1316551995-indirect-erep_1gb-tigrovi_bkp
Sheet: Friend Freeman

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
Friend [NAME]
offlineFriend [NAME]
Add as a friend Send message Donate
Experience level 30
26,737 / 30,000
Location: CroatiaCroatia, Central Croatia Citizenship: CroatiaCroatia
eRepublik birthday
Dec 11, 2008
National rank: 241
No political activity
HV 1.GB Tigrovi HV 1.GB Tigrovi
Press director
Ljudi Dobre Volje
Friends(707)
[NAME]
Kokach
webstartm
JuniorSoprano
[NAME]
[NAME]
[NAME]
letodred
TerminatorBiH
view all
Land of Friend [NAME]: 17 buildings
Visit
About me
Wiki page
The Sexy Hero achievement is awarded for dealing the highest influence in bed.
Achievements
hard worker
21
Hard Worker
Worked 30 days in a row
congressman
2
Congress Member
Won the Congress elections
president
1
Country President
Won the Presidential elections
media mogul
1
Media Mogul
Reached 1000 subscribers to your newspaper
battle hero
208
Battle Hero
Reach the highest war influence in a battle
campaign hero
14
Campaign Hero
Reach the highest war influence in a campaign
resistance hero
Resistance Hero
Start a resistance war and liberate that region
super soldier
32
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
8,134.39
Super soldier:8,134 / 8,250
Rank
National Force National Force
Rank points:
5,685,046 / 5,800,000
Forum   |   [NAME]   |   Blog   |   Press   |   Contact   |   [NAME]   |   Terms of Service   |   Privacy  |   Affiliates  |   [NAME]
Follow us: FacebookFacebook TwitterTwitter
Copyright © 2007-2011 eRepublik
Spreadsheet: 0abb7b2e-d16f-47ce-959b-ad23839a9bbd
Sheet: Sheet1

Forcible Rape | Unnamed: 1 | Unnamed: 2 | Unnamed: 3
 | 1993
Age Group | Total | Male | Female
12 and under | 1.595418738184365 | 3.01196167134637 | 0.1099484877229392
13-14 | 25.24059431846996 | 48.17454408658649 | 1.155249638800587
15 | 33.87311715162492 | 65.006267823297 | 1.064828537662343
16 | 40.58186022878596 | 77.97753200490169 | 0.9282514927538564
17 | 41.18307025184559 | 79.17948607599563 | 0.7317293746902581
18 | 51.31029177978401 | 98.863625047242 | 1.312985156896005
19 | 44.10557372832896 | 85.11909303943175 | 1.336365952367627
20 | 41.4553457385578 | 80.10815604763891 | 1.108455938378442
21 | 42.44513200691323 | 82.21982744807083 | 0.9327379581921966
22 | 37.52566079837413 | 73.36689887206062 | 0.443530062667134
23 | 36.52306444882433 | 71.0884032268035 | 0.8959044518400376
24 | 36.97933229337163 | 71.56171238969249 | 1.483236958417756
25-29 | 33.41294194576444 | 65.8086330720917 | 0.7774812315692863
30-34 | 26.98487164725568 | 53.43451655053749 | 0.6807350538070934
35-39 | 20.09164657685488 | 39.90193262027596 | 0.4996624297470262
40-44 | 13.22295384588157 | 26.33559694275474 | 0.4220767898961504
45-49 | 9.035499403435477 | 18.20805437468525 | 0.1933710164174631
50-54 | 5.877238575718596 | 12.08875285615406 | b
55-59 | 4.090071211255284 | 8.458533371387986 | 0.06512583223341072
60-64 | 3.499682275411788 | 7.455988389206096 | b
65 and over | 0.9789802087285903 | 2.396752862724653 | a
Spreadsheet: 108722d1305725100-excel-2007-conditional-formatting-book2
Sheet: Sheet1

 |  |  |  | [NAME]
 |  |  |  |  | 0.06599925 | 0.6811 | 0.240489321 | 0.09324854 | 0.353939086
 |  |  |  |  | 0.040773125 | 0.3935 | 0.05892902 | 0.036925933 | 0.119899254
 |  |  |  |  | 0.118105 | 0.9308 | 0.332763483 | 0.063646844 | 0.118227851
 |  |  |  |  | 0.112617143 | 0.8504 | 0.204203711 | 0.1424227 | 0.312127276
 |  |  |  |  | 0.049641667 | 0.8979 | 0.232452073 | 0.149493217 | 0.206853483
 |  |  |  |  | 0 | 0.7479 | 0.253832333 | 0.178153763 | 0.274506057
 |  |  |  |  | 0 | - | 0 | 0 | 0
 |  |  |  |  | 0 | - | 0 | 0 | 0
 |  |  |  |  | 0.07102 | 0.8335 | 0.191312938 | 0.106002664 | 0.286878984
 |  |  |  |  | 0.140734 | 0.7761 | 0.26523732 | 0.118831012 | 0.342513989
 |  |  |  |  |  | 0.0199 | 0.029751316 | 0.018319962 | 0.092635319
 |  |  |  |  | 0.190697222 | 0.8433 | 0.2174195 | 0.127070333 | 0.176693787
 |  |  |  |  | 0.07057013 | 0.9478 | 0.265521613 | 0.162101013 | 0.136596053
 |  |  |  |  | 0.142506 | 0.7653 | 0.257072308 | 0.171838015 | 0.137051958
 |  |  |  |  | 0 | - | 0.188373667 | 0.125032847 | 0.135500357
 |  |  |  |  | 0 | - | 0 | 0 | 0
 |  |  |  |  | 0 | - | 0 | 0 | 0
 |  |  |  |  | 0.112849567 | 0.9607 | 0.270244 | 0.090070645 | 0.22650847
 |  |  |  |  |  | 0.9681 | 0.252185714 | 0.13475009 | 0.098533911
 |  |  |  |  |  | 0.9793 | 0.294029333 | 0.072213195 | 0.176742873
 |  |  |  |  | 0.152794521 | 0.9519 | 0.3539265 | 0.154380718 | 0.184845795
 |  |  |  |  | 0.106051852 | 0.9621 | 0.429925 | 0.11803409 | 0.14253553
 |  |  |  |  | 0.04167 | 0.9461 | 0.38661925 | 0.133416289 | 0.206997743
 |  |  |  |  | 0.058286667 | 0.8855 | 0.3266435 | 0.15938916 | 0.165193965
 |  |  |  |  | 0.097655 | 0.8876 | 0.2630278 | 0.209252984 | 0.141023124
 |  |  |  |  | 0.664333333 | 0.72 | 0.320133333 | 0.14223273 | 0.363574323
 |  |  |  |  | 0.041664465 |  | 0.481937167 | 0.156131138 | 0.051085743
 |  |  |  |  | 0.0992 |  | 0.302085667 | 0.02176217 | 0.19487686
 |  |  |  |  |  |  | 0 | 0 | 0
Spreadsheet: 878559d1725644789-array-cse-formula-help-country-search
Sheet: Sheet1

 | Table with all the Data to look through
Country | [NAME] | Alpha-3 code | Numeric | Ships
Afghanistan | AF | AFG | 4 | No
Albania | AL | ALB | 8 | No
Algeria | DZ | DZA | 12 | Yes
American Samoa | AS | ASM | 16 | No
Andorra | AD | AND | 20 | Yes
Angola | AO | AGO | 24 | Yes
Anguilla | AI | AIA | 660 | No
Antarctica | AQ | ATA | 10 | No
Search
Country | [NAME] | Alpha-3 code | Numeric | Ships
Result below based on Search fields that are above
 | AF | AFG | 4 | No
Albania | AL | ALB | 8 | No
Algeria | DZ | DZA | 12 | Yes
American Samoa | AS | ASM | 16 | No
Andorra | AD | AND | 20 | Yes
Angola | AO | AGO | 24 | Yes
Anguilla | AI | AIA | 660 | No
Antarctica | AQ | ATA | 10 | No
Spreadsheet: 858982d1707468808-no-border-for-empty-cells-excel-border-issue
Sheet: Sheet1

 | DESIRED BORDERS, NO LINES FOR EMPTY CELLS |  |  |  |  |  |  |  | LINES FOR EVERY CELL
 |  |  | 2020 | 2021 | 2022 | 2023 | 2024 |  |  |  | 2020 | 2021 | 2022 | 2023 | 2024
 | North | Q1 |  |  |  |  |  |  | North | Q1
 |  | Q2 |  |  |  |  |  |  |  | Q2
 |  | Q3 |  |  |  |  |  |  |  | Q3
 |  | Q4 |  |  |  |  |  |  |  | Q4
 | South | Q1 |  |  |  |  |  |  | South | Q1
 |  | Q2 |  |  |  |  |  |  |  | Q2
 |  | Q3 |  |  |  |  |  |  |  | Q3
 |  | Q4 |  |  |  |  |  |  |  | Q4
 | West | Q1 |  |  |  |  |  |  | West | Q1
 |  | Q2 |  |  |  |  |  |  |  | Q2
 |  | Q3 |  |  |  |  |  |  |  | Q3
 |  | Q4 |  |  |  |  |  |  |  | Q4
 | East | Q1 |  |  |  |  |  |  | East | Q1
 |  | Q2 |  |  |  |  |  |  |  | Q2
 |  | Q3 |  |  |  |  |  |  |  | Q3
 |  | Q4 |  |  |  |  |  |  |  | Q4
Spreadsheet: 167365d1341963429-how-to-stop-calculating-based-on-criteria-sample1-1-
Sheet: Sheet2

AS400 code | Description of account | Sign
0 |  | 0
A010 | Eng & Tran Labor claim/Allowance | -1
A260 | Advertising/Co-op | -1
A380 | Def. Battery Reserve | -1
A500 | Electronic Media | -1
B210 | Long Term Advertising | -1
B750 | Core Charge | 1
C000 | [NAME] | 1
C310 | End Cap/Wing Panel | -1
C550 | Freight/Backhaul - Allowance/Fuel Surcharge | -1
D240 | Freight Charge -DC & PDQ | 1
E180 | Warr. Claims Labor | 1
E740 | New Store Allowance | -1
F340 | Freight/Backhaul - Allowance/Fuel Surcharge | -1
F800 | Volume Rebate - Volume Allowance | 1
G470 | Freight Charge code | 1
H040 | [NAME] for FDOs | 1
H660 | Pricing account-unit [NAME]. Disc/Florida Pollutant Tax | -1
H700 | Commodity Surcharge/Order Initiation Cost | 1
H740 | Sales tax for store supplies | 1
H760 | [NAME] | 1
H770 | Second Source Allowance | -1
H780 | Freight for Store Supplies | 1
I170 | Trade Discount | -1
I310 | Obsolescence Allowance | -1
I530 | Pricing account-unit [NAME]. Disc/Florida Pollutant Tax | 1
Spreadsheet: 870825d1717263687-how-do-i-calculate-data-from-various-excel-sheets-sample-data1
Sheet: table_1

TABLE 1
Nr | Data col.1 | Data col.2 | Data col.3 | Data col.4
1 | a | 1002 | 10.2
2 | d | 1003 | 10.5
3 |  | 1004 | 10.8
4 | f | 1005 | 11.1
5 |  | 1006 | 11.4
6 | d | 1007 | 11.7
7 |  | 1008 | 12
8 | d | 1009 | 12.3
9 |  | 1010 | 12.6
10 |  | 1011 | 12.9
11 | s | 1012 | 13.2
12 | s | 1013 | 13.5
13 |  | 1014 | 13.8
14 |  | 1015 | 14.1
15 | s | 1016 | 14.4
16 | s | 1017 | 14.7
17 |  | 1018 | 15
18 |  | 1019 | 15.3
19 | s | 1020 | 15.6
20 |  | 1021 | 15.9
21 |  | 1022 | 16.2
22 |  | 1023 | 16.5
23 | sadas | 1024 | 16.8
24 |  | 1025 | 17.1
25 |  | 1026 | 17.4
26 |  | 1027 | 17.7
27 | dasd | 1028 | 18
28 |  | 1029 | 18.3
29 | qweqwe | 1030 | 18.6
30 | qweqweqw | 1031 | 18.9
Spreadsheet: 2c190e4c-7f15-4a7a-ab9e-62a5034011f0
Sheet: Sheet1

GIM Japan/Korea Itinerary
 | Su, 17th | M, 18th | T, 19th | W, 20th | R, 21st | F, 22nd | Sa, 23rd
City | N/A | Chicago | Seoul | Seoul | Seoul | Seoul/Osaka | Osaka
Flights | N/A | D: ORD, 13:30 | A: SEL, 21:10
 | Su, 24th | M, 25th | T, 26th | W, 27th | R, 28th | F, 29th | Sa, 30th
City | Osaka | Osaka | Osaka/Tokyo | Tokyo | Tokyo | Tokyo | Tokyo/Chicago
Flights |  |  | Train |  |  |  | D: TYO, 18:05; A: ORD, 15:40