tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 195675d1353597640-want-to-get-last-5-cell-values-book3
Sheet: NRC

M/C | New Rubber Cots |  | New Rubber Cots |  | New Rubber Cots |  | New Rubber Cots |  | New Rubber Cots |  |  | Second Last |  | Last
 | Date | [NAME] | Date | [NAME] | Date | [NAME] | Date | [NAME] | Date | [NAME] |  | Date | [NAME] | Date | [NAME]
1 | 2009-02-16 00:00:00 | 38 [NAME] | 2011-09-26 00:00:00 | 37 [NAME] | 2012-01-28 00:00:00 | 36 [NAME] | 2012-10-24 00:00:00 | 40 mm
2 | 2009-02-16 00:00:00 | 38 [NAME] | 2011-09-26 00:00:00 | 37 [NAME] | 2012-01-28 00:00:00 | 36 [NAME] | 2012-10-24 00:00:00 | 40 mm
3 | 2009-02-16 00:00:00 | 38 [NAME] | 2011-09-26 00:00:00 | 37 [NAME] | 2012-01-28 00:00:00 | 36 [NAME] | 2012-10-24 00:00:00 | 40 mm
4 | 2009-02-16 00:00:00 | 38 [NAME] | 2011-09-26 00:00:00 | 37 [NAME] | 2012-01-28 00:00:00 | 36 [NAME] | 2012-10-24 00:00:00 | 40 mm
5 | 2009-02-16 00:00:00 | 38 [NAME] | 2011-09-26 00:00:00 | 37 [NAME] | 2012-01-28 00:00:00 | 36 [NAME] | 2012-10-24 00:00:00 | 40 mm
Spreadsheet: 748562d1632217597-populate-dynamic-calendar-with-tasks-based-on-task-frequency-tasks-calendar-ans
Sheet: Sheet1

Sep | Task1 | [NAME] | Task3 | Task4 | Task5 | Task6 | Task7 | Task8
2021-09-01 00:00:00
2021-09-02 00:00:00 |  |  |  |  | Y |  |  |  |  | Example
2021-09-03 00:00:00 | Y |  |  |  |  |  | Y
2021-09-04 00:00:00
2021-09-05 00:00:00 |  |  | Y
2021-09-06 00:00:00
2021-09-07 00:00:00
2021-09-08 00:00:00
2021-09-09 00:00:00
2021-09-10 00:00:00
2021-09-11 00:00:00
2021-09-12 00:00:00
2021-09-13 00:00:00
2021-09-14 00:00:00
2021-09-15 00:00:00
2021-09-16 00:00:00
2021-09-17 00:00:00
2021-09-18 00:00:00
2021-09-19 00:00:00
2021-09-20 00:00:00
2021-09-21 00:00:00
2021-09-22 00:00:00
2021-09-23 00:00:00
2021-09-24 00:00:00
2021-09-25 00:00:00
2021-09-26 00:00:00
2021-09-27 00:00:00
2021-09-28 00:00:00
2021-09-29 00:00:00
2021-09-30 00:00:00
2021-10-01 00:00:00
2021-10-02 00:00:00
2021-10-03 00:00:00
2021-10-04 00:00:00
2021-10-05 00:00:00
2021-10-06 00:00:00
2021-10-07 00:00:00
2021-10-08 00:00:00
2021-10-09 00:00:00
2021-10-10 00:00:00
2021-10-11 00:00:00
2021-10-12 00:00:00
2021-10-13 00:00:00
2021-10-14 00:00:00
2021-10-15 00:00:00
2021-10-16 00:00:00
2021-10-17 00:00:00
2021-10-18 00:00:00
2021-10-19 00:00:00
2021-10-20 00:00:00
2021-10-21 00:00:00
2021-10-22 00:00:00
2021-10-23 00:00:00
2021-10-24 00:00:00
2021-10-25 00:00:00
2021-10-26 00:00:00
2021-10-27 00:00:00
2021-10-28 00:00:00
2021-10-29 00:00:00
2021-10-30 00:00:00
2021-10-31 00:00:00
2021-11-01 00:00:00
2021-11-02 00:00:00
2021-11-03 00:00:00
2021-11-04 00:00:00
2021-11-05 00:00:00
2021-11-06 00:00:00
Spreadsheet: 55825983-100f-47e7-8691-287c69fd1661
Sheet: Quarterly - Long-Term Infl Exp

Quarterly Question: Projecting ahead, to the best of your ability, please assign a percent likelihood to the following changes to unit costs per year over the next FIVE TO 10 years.
Month | Number of Responses | Unit costs down  (<-1%) | Unit costs about unchanged  (-1% to 1%) | Unit costs up somewhat (1.1% to 3%) | Unit costs up significantly (3.1% to 5%) | Unit costs up very significantly  (>5%) | Mean | [NAME]
2012-02-17 00:00:00 | 89 | 0.04078651685393259 | 0.1143820224719101 | 0.3788764044943821 | 0.292134831460674 | 0.1738202247191011 | 0.029 | 0.028
2012-04-13 00:00:00 | 152 | 0.03684210526315786 | 0.1152631578947368 | 0.3626315789473684 | 0.300921052631579 | 0.184342105263158 | 0.03 | 0.026
2012-07-20 00:00:00 | 155 | 0.04006493506493503 | 0.1491558441558442 | 0.3570779220779222 | 0.2640259740259741 | 0.1896753246753247 | 0.028 | 0.029
2012-10-19 00:00:00 | 196 | 0.0387301587301587 | 0.1275661375661376 | 0.3616402116402118 | 0.2974603174603175 | 0.1746031746031747 | 0.029 | 0.027
2013-01-11 00:00:00 | 196 | 0.03195121951219512 | 0.12 | 0.32 | 0.28 | 0.23 | 0.03 | 0.025
2013-04-12 00:00:00 | 189 | 0.03635279463762396 | 0.1247942885739619 | 0.3830080704715921 | 0.2586793008840816 | 0.1971655454327405 | 0.029 | 0.022
2013-07-12 00:00:00 | 209 | 0.04 | 0.14 | 0.37 | 0.28 | 0.15 | 0.028 | 0.024
2013-10-11 00:00:00 | 216 | 0.04 | 0.15 | 0.45 | 0.26 | 0.11 | 0.027 | 0.024
Spreadsheet: 749743d1632990490-how-to-find-top-5-values-from-data-using-function-test-20-
Sheet: Result

 | Top 5 value with name |  |  |  |  |  | output should be the below
 | Name | Value |  |  |  |  | Name | Value
 |  |  |  |  |  |  | England | 14
 |  |  |  |  |  |  | Norfold | 10
 |  |  |  |  |  |  | NZ | 10
 |  |  |  |  |  |  | SA | 9
 |  |  |  |  |  |  | Belgium | 9
Spreadsheet: 09ef0d6c-78eb-4f96-b181-dcb67ab0b2e6
Sheet: Stability

Tune Step | Mass | Name | R | a | b (blank) | DL | BEC
1 | 24 | [NAME] | 0.9998617005759435 | 0.01825018933247337 | 0.01316152334421155 | 0.3766166554375753 | 0.7211718796140197
1 | 39 | K | 0.9998558901727873 | 0.01421654327588255 | 0.5459714367040563 | 13.87330008781096 | 38.40395137615919
1 | 44 | Ca | 0.9999081679614523 | 0.0007266318771534644 | 0.001111776563149657 | 0.5499670698618222 | 1.53004099889613
1 | 55 | Mn | 0.9999411590709434 | 0.1206810109624074 | 0.001233875104999506 | 0.005606441835172287 | 0.01022426888173703
1 | 56 | Fe | 0.9999427126687496 | 0.1824596891907655 | 0.08793938534481228 | 0.1767824607161182 | 0.4819661029503879
1 | 57 | Fe | 0.9999538902752133 | 0.004400002666268353 | 0.002479664069365554 | 0.3156198990637306 | 0.5635596742645977
1 | 63 | Cu | 0.9998128412597762 | 0.2379762471792019 | 0.005629138960984894 | 0.003484637015850321 | 0.02365420510537766
1 | 64 | Zn | 0.9999068518204484 | 0.07016345470184561 | 0.006489952041149325 | 0.03409612474133274 | 0.0924976124497845
1 | 66 | Zn | 0.9999025546673992 | 0.04177420253839002 | 0.003799362562247055 | 0.05172565158062526 | 0.0909499722647125
2 | 78 | Se | 0.9999999570536519 | 0.004595891345112824 | 0.001991161335407424 | 0.04306451117800697 | 0.4332481309691499
1 | 118 | Sn | 0.9999313961538573 | 0.1190260384330566 | 0.006092936828285413 | 0.01922569017091367 | 0.05118994892627834
Spreadsheet: 1025f918-2487-420b-8dd1-e452d17e40e5
Sheet: 1. Fill

 | [NAME] your data |  |  |  |  |  | Learn More
 | Start typing and let Excel finish your work for you
 | [NAME] | First Name
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
 | [EMAIL]
Spreadsheet: 768048d1644812501-transform-raw-data-want-raw-data-to-be-show-as-tableau-transform
Sheet: Sheet1

Raw Data |  |  |  |  |  |  |  | What I wat
Date | Customer | Payment | Deposit |  |  |  |  | Date | Customer | Reference | Payment | Deposit
2022-01-01 00:00:00 | [NAME] | 1000
Edit | 0016RF2032331804
2022-01-01 00:00:00 | [NAME] |  | 3000
Edit | ZZ0016SW282712
2022-01-01 00:00:00 | Crystal | 1100
Edit | 0016SW2208199112111
2022-01-01 00:00:00 | Leiny | 1919
Edit | 0016RF20819MMA
2022-01-02 00:00:00 | Cherbelle |  | 90
Edit | 0016RF2032338881
Spreadsheet: 167045d1341879712-fill-cell-value-based-on-value-from-another-sheet-in-dummy-terms-doc-1-database
Sheet: Sheet1

Restaurant Name | [NAME] | Suburb | Postcode | Phone | Contact First Name | Last Name | Position
[NAME] | [EMAIL] | Blueys Beach | 2428 | (02) 6552 9222
Byblos Restaurant & Bar | [EMAIL] | Gosford | 2250 | (02) 4324 6006
[NAME] | [EMAIL] | [NAME] | 2010 | (02) 9699 8787
[NAME] | [EMAIL] | Tweed Heads | 2485 | (07) 5524 4544
Cove Cafe & Grill | [NAME] | Terrigal | 2260 | 02 4385 3222 | [NAME] | Muir | Accounts Manager
Centennial Parklands Restaurant | [EMAIL] | East Sydney | 2000 | (02) 9380 9350
Spreadsheet: 857342d1706365398-distribute-orders-with-avearge-for-designers-assigning-_2
Sheet: Sheet4

SO number | Order Type | Count# | Customer # | Designer |  |  |  |  | Designers | Assigned Count
SO-2241284 | JXP | 1 | AR-003033 | Designer 1 |  | Count |  |  | Designer 1 |  |  | Row Labels | Min of Count# | [NAME]# | Average of Count#
SO-2242825 | JXP | 1 | AR-000970 | Designer 1 |  | Min | 1 |  | Designer 2 |  |  | Designer 1 | 1 | 1 | 1
SO-2240850 | JX | 32 | AR-005720 | Designer 2 |  | [NAME] | 32 |  | Designer 3 |  |  | Designer 2 | 1 | 32 | 11.33333333333333
[NAME] | JX | 1 | AR-000941 | Designer 2 |  | Avg | 5 |  | Designer 4 |  |  | Designer 3 | 1 | 16 | 7
SO-2240484 | JX | 1 | AR-004628 | Designer 2 |  |  |  |  | Designer 5 |  |  | Designer 4 | 1 | 6 | 2.666666666666667
SO-2242882 | JX | 1 | AR-000883 | Designer 3 |  |  |  |  | Designer 6 |  |  | Designer 5 | 1 | 1 | 1
SO-2242007 | JTS | 16 | AR-000175 | Designer 3 |  |  |  |  |  |  |  | Designer 6 | 1 | 12 | 6.5
SO-2242917 | JTS | 4 | AR-004165 | Designer 3
SO-2242742 | JX | 1 | AR-006882 | Designer 4
SO-2242938 | JX | 6 | AR-000744 | Designer 4
SO-2242630 | JXP | 1 | AR-001426 | Designer 4
SO-2242927 | JX | 1 | AR-001075 | Designer 5
SO-2242869 | JTS | 12 | AR-000175 | Designer 6
SO-2241285 | JX | 1 | AR-004394 | Designer 6
Spreadsheet: 839375d1691908597-summarizing-staff-movement-by-month-staff-movement
Sheet: Sheet1

 | Table 1 |  |  |  |  |  | Table 2
 | Report Date | Staff ID | Name | Type | Branch |  | Report Date | Staff ID | Name | Type | Branch | Hired/Left
 | 2022-12-01 00:00:00 | 123456 | [NAME] | Permanent | Dallas |  | 2023-01-01 00:00:00 | 123461 | Many | Contract | Chicago | Hired
 | 2022-12-01 00:00:00 | 123457 | [NAME] | Permanent | Dallas |  | 2023-02-01 00:00:00 | 123460 | [NAME] | Contract | Chicago | Left
 | 2022-12-01 00:00:00 | 123458 | Nelley | Permanent | Dallas |  | 2023-03-01 00:00:00 | 123459 | Xavier | Contract | New York | Left
 | 2022-12-01 00:00:00 | 123459 | Xavier | Contract | New York |  | 2023-04-01 00:00:00 | 123462 | Maria | Contract | Chicago | Hired
 | 2022-12-01 00:00:00 | 123460 | [NAME] | Contract | Chicago |  | 2023-04-01 00:00:00 | 123463 | [NAME] | Contract | Chicago | Hired
 | 2023-01-01 00:00:00 | 123456 | [NAME] | Permanent | Dallas
 | 2023-01-01 00:00:00 | 123457 | [NAME] | Permanent | Dallas |  |  | Staff ID | Name | Type | Branch | Hired/Left
 | 2023-01-01 00:00:00 | 123458 | Nelley | Permanent | Dallas |  | 2023-01-01 00:00:00 | 123461 | Many | Contract | Chicago | Hired
 | 2023-01-01 00:00:00 | 123459 | Xavier | Contract | New York |  | 2023-02-01 00:00:00 | 123460 | [NAME] | Contract | Chicago | Left
 | 2023-01-01 00:00:00 | 123460 | [NAME] | Contract | Chicago |  | 2023-03-01 00:00:00 | 123459 | Xavier | Contract | New York | Left
 | 2023-01-01 00:00:00 | 123461 | Many | Contract | Chicago |  | 2023-04-01 00:00:00 | 123462 | Maria | Contract | Chicago | Hired
 | 2023-02-01 00:00:00 | 123456 | [NAME] | Permanent | Dallas |  | 2023-04-01 00:00:00 | 123463 | [NAME] | Contract | Chicago | Hired
 | 2023-02-01 00:00:00 | 123457 | [NAME] | Permanent | Dallas
 | 2023-02-01 00:00:00 | 123458 | Nelley | Permanent | Dallas
 | 2023-02-01 00:00:00 | 123459 | Xavier | Contract | New York
 | 2023-02-01 00:00:00 | 123461 | Many | Contract | Chicago
 | 2023-03-01 00:00:00 | 123456 | [NAME] | Permanent | Dallas
 | 2023-03-01 00:00:00 | 123457 | [NAME] | Permanent | Dallas
 | 2023-03-01 00:00:00 | 123458 | Nelley | Permanent | Dallas
 | 2023-03-01 00:00:00 | 123461 | Many | Contract | Chicago
 | 2023-04-01 00:00:00 | 123456 | [NAME] | Permanent | Dallas
 | 2023-04-01 00:00:00 | 123457 | [NAME] | Permanent | Dallas
 | 2023-04-01 00:00:00 | 123458 | Nelley | Permanent | Dallas
 | 2023-04-01 00:00:00 | 123461 | Many | Contract | Chicago
 | 2023-04-01 00:00:00 | 123462 | Maria | Contract | Chicago
 | 2023-04-01 00:00:00 | 123463 | [NAME] | Contract | Chicago
Spreadsheet: 832571d1686443149-how-to-split-cells-into-columns-and-fill-down-help0611
Sheet: Sheet1

A,B,C,D | 10
E,F | 20
G | 30
X
X
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Spreadsheet: 386450d1427800080-dynamic-if-function-query-2-
Sheet: Sheet1

Name | Age |  | Class1 | Name | Age | Class2 | Name | Age | Class3 |  | Class1 | Class2 | Class3
AA | 21 | Business | 1000 | QQ | 34 | 5000 | UU | 43 | 2100
SS | 22 | [NAME] | 2500 | WW | 32 | 3200 | HH | 4 | 2700
DD | 23 | Super | 6000 | EE | 31 | 2300 | GG | 2 | 2800
FF | 24 | Business | 4000 | CC | 35 | 4300 | KK | 41 | 3000
GG | 20 | Super | 1500 | RR | 38 | 4500 | LL | 45 | 3200
Spreadsheet: 141665d1329391875-excel-2007-removing-blanks-from-a-pivot-table-pivot-table-blanks
Sheet: Sheet1

Item 1 | Item 2 | Item 3 |  | Item 1 | Item 2 | Sum of Item 3
a | aa | 151 |  | a | aa | 151
a | bb | 9595 |  |  | bb | 9595
a | cc | 1651 |  |  | cc | 1651
b | aa | 1151 |  | b | aa | 1151
b | bb | 515 |  |  | bb | 515
b | cc | 121 |  |  | cc | 121
c | aa | 846 |  | c | aa | 846
c | bb | 48 |  |  | bb | 48
c | cc | 99 |  |  | cc | 99
 |  |  |  | (blank) | (blank)
 |  |  |  | Grand Total |  | 14177
Spreadsheet: 680479d1591041000-assessment-report-result-formulas-measures-assessment
Sheet: Results_Store Inspection

Audit Report
Audited Store: |  | from: |  |  |  | to:
Scope of audit:
Store contact person:
Store Profile:  [# stores, type certifications, in-store processing]
Audit Conclusion
Best practice | > 92
Good performance | 91.9 - 84%
Acceptable | 83.9 - 76%
Need improv. | < 76%
Detailed Assessment Report: Overview Scoring SHSHS in %
Chapters | HACCP and PRP's | Meat General | Hyg. [NAME] | Meat | Fish &SF | Meat Processing | Bakery General | Bakery Processing | Fruits and Vegetables | Delivery
Achieved  score in % Store Inspections
Achieved  score in % Store Documentation
No. of applicable requirements
Total  No. of points ( for applicable req)
Total No. of achieved points
Detailed Score | req. evaluation | req. evaluation | req. evaluation | req. evaluation | req. evaluation | req. evaluation
3
2
1
Chapters | Achieved  score in % Store Inspections
HACCP
Construction and Facility Management
Human Resources
Personal Hygiene, Infection Control and  Protective Clothing
Cleaning and Sanitation
Waste Management
Pest Control
Callibration
Foreign Body Control
Product Return, Withdrawal and Recall and Food Defence
Dry and [NAME]
Meat General
Meat Processing
Fish
Cheese, [NAME], [NAME], Eggs General
Cheese, [NAME], [NAME], Eggs Processing
Bakery General
Bakery Processing
Fruits and Vegetables
Delivery
Spreadsheet: 113590d1309445169-using-a-drop-down-box-to-activate-a-formula-stock-sheet-experiment-can-capex-be-taken-first
Sheet: Data & Stock Check

STOCK DESCRIPTION, SUPPLIER, ID AND LOCATION |  |  | Running Stock level for All Categories | PERIOD 1 STOCK STATUS |  |  |  |  | PERIOD 1 CAPEX STOCK STATUS
ID No. | Supplier | Item Description | Total Running Stock | Bought / Con Opening Stock Check | Opex Stock In | Opex Stock Out | Running Opex Stock | Category | Opening Capex Stock | Incoming Capex Stock | Issued Capex Stock | Running Opex Stock | Category
001 | [NAME] | 16 watt GLS ES Energy Saver Softone | 250 | 100 | 100 | 100 | 100 | Opex | 200 | 0 | 50 | 150 | Capex
 |  | This sheet is fed from the Stock Movement sheet for incoming and outgoing items
Spreadsheet: 789658d1659276596-adding-black-space-in-a-cell-before-text-or-data-example-17-ans
Sheet: Sheet1

Blank cells before text | 2 | 3 | 4 | 5 | 6 | 2 | 3 | 4
Data/TEXT | 02052022 | CO20 | HKD | USD | 3000 | 22052022 | JournalEntry | YES
Expected Results | '02052022 | CO20 | HKD | USD | 3000 | 22052022 | JournalEntry | YES
FORMULA
Result for verification | 2052022 | CO20 | HKD | USD | 3000 | 22052022 | JournalEntry | YES
Spreadsheet: 684266d1593249321-excel-table-lookup-named-range-book1
Sheet: DCM

Project | Date | Month | Goal | Phase | Threshold | Actual | Difference | Met Obj |  |  | Ref | Project | Goal | Date | Phase | Rule | Threshold
P2 | 2020-06-15 00:00:00 |  | G oal | Phase5 |  | 0.81 |  |  |  |  | P1 | P1 | Goal |  | Phase1 |  | 0.65
P2 | 2020-05-16 00:00:00 |  | G oal | Phase4 |  | 1.81 |  |  |  |  | P2 | P2 | Goal |  | Phase2 |  | 0.89
P2 | 2020-04-15 00:00:00 |  | G oal | Phase3 |  | 0.75 |  |  |  |  | P2 | P2 | Goal |  | Phase3 |  | 1
P2 | 2020-03-15 00:00:00 |  | G oal | Phase3 |  | 0.82 |  |  |  |  | P2 | P2 | Goal |  | Phase4 |  | 0.78
P2 | 2020-02-15 00:00:00 |  | G oal | Phase3 |  | 0.86 |  |  |  |  | P2 | P2 | Goal |  | Phase5 |  | 0.85
P2 | 2020-01-15 00:00:00 |  | G oal | Phase2 |  | 0.86
P1 | 2019-09-15 00:00:00 |  | G oal | Phase1 |  | 0.94
P1 | 2019-08-15 00:00:00 |  | G oal | Phase1 |  | 0.94
P1 | 2019-07-15 00:00:00 |  | G oal | Phase1 |  | 0.95
P1 | 2019-06-15 00:00:00 |  | G oal | Phase1 |  | 0.95
Spreadsheet: 160236d1339014296-excel-2007-multiple-if-statements-in-one-cell-book2
Sheet: Number of Units

3 | 0.45
4 | 0.45 |  | Number of Units | 12
5 | 0.45 |  | Demand Factor
6 | 0.44
7 | 0.44
8 | 0.43
9 | 0.43
10 | 0.43
11 | 0.42
12 | 0.41
13 | 0.41
14 | 0.4
15 | 0.4
16 | 0.39
17 | 0.39
18 | 0.38
19 | 0.38
20 | 0.38
21 | 0.37
22 | 0.36
23 | 0.36
24 | 0.35
25 | 0.35
26 | 0.34
27 | 0.34
28 | 0.33
29 | 0.33
30 | 0.33
31 | 0.32
32 | 0.31
33 | 0.31
34 | 0.3
35 | 0.3
36 | 0.3
37 | 0.29
38 | 0.29
39 | 0.28
40 | 0.28
41 | 0.28
42 | 0.28
43 | 0.27
44 | 0.27
45 | 0.27
46 | 0.26
47 | 0.26
48 | 0.26
49 | 0.26
50 | 0.26
51 | 0.25
52 | 0.25
53 | 0.25
54 | 0.25
55 | 0.25
56 | 0.24
57 | 0.24
58 | 0.24
59 | 0.24
60 | 0.24
61 | 0.24
62 | 0.23
Spreadsheet: 879986d1727598516-using-xlookup-with-2-criteria-to-search-in-table-to-return-results-problem
Sheet: vlookup

[NAME] | Type | Jan | Feb | Mar | Q1 | Payout
[NAME] | Budget | 30 | 40 | 50
Role | Actual | 30 | 50 | 71
Sales | Perf
[NAME] | Budget | 10 | 15 | 20
Role | Actual
Tech | Perf
[NAME] | Budget
Role | Actual
Manager | Perf
Spreadsheet: 837757d1690393153-network-days-with-time-fraction-less-than-full-working-day-network-days
Sheet: Network days

ADP | Full Name | Absence From | Absence To | Duration | Network Days | Expected Result
10906 | A | 2023-06-29 00:00:00 | 2023-06-30 00:00:00 | 2 |  | 2
11073 | B | 2023-07-03 00:00:00 | 2023-07-03 00:00:00 | 1 |  | 1
11430 | C | 2023-07-03 00:00:00 | 2023-07-04 00:00:00 | 2 |  | 2
11566 | D | 2023-07-10 00:00:00 | 2023-07-10 00:00:00 | 1 |  | 1
11590 | E | 2023-06-29 00:00:00 | 2023-06-30 00:00:00 | 2 |  | 2
20053 | F | 2023-06-27 00:00:00 | 2023-07-03 00:00:00 | 5 |  | 5
20074 | G | 2023-07-05 00:00:00 | 2023-07-07 00:00:00 | 3 |  | 3
20175 | H | 2023-07-03 00:00:00 | 2023-07-06 00:00:00 | 4 |  | 4
20176 | I | 2023-06-29 09:00:00 | 2023-06-29 00:00:00 | 0.0625 |  | 0.0625
20197 | J | 2023-07-10 00:00:00 | 2023-07-10 00:00:00 | 1 |  | 1
20698 | K | 2023-07-04 09:00:00 | 2023-07-04 00:00:00 | 0.875 |  | 0.875
20882 | L | 2023-07-11 07:30:00 | 2023-07-11 00:00:00 | 0.8125 |  | 0.8125
20949 | M | 2023-07-07 08:45:00 | 2023-07-07 00:00:00 | 0.6562 |  | 0.6562
20951 | N | 2023-06-19 00:00:00 | 2023-06-20 00:00:00 | 2 |  | 2
20955 | O | 2023-07-11 11:30:00 | 2023-07-11 00:00:00 | 0.375 |  | 0.375
20995 | P | 2023-06-26 00:00:00 | 2023-06-26 00:00:00 | 1 |  | 1
20995 | P | 2023-07-06 10:30:00 | 2023-07-06 00:00:00 | 0.5 |  | 0.5
21006 | q | 2023-07-05 00:00:00 | 2023-07-06 00:00:00 | 0.5 |  | 0.5
21030 | S | 2023-07-10 00:00:00 | 2023-07-10 00:00:00 | 1 |  | 1
20199 | U | 2023-06-16 11:30:00 | 2023-06-17 00:00:00 | 1.5 |  | 1.5
20247 | V | 2023-06-14 06:30:00 | 2023-06-17 00:00:00 | 3.8636 |  | 3.8636
Spreadsheet: 32464d1228651523-stock-list-with-countif-and-autosort-book1
Sheet: Sheet1

 |  | Scapi | -36 | 28 | [NAME] | -17 | 67 | Rome | -5 | 41 | Refresh | 3 | 7 | Surreal | -65 | 7 | Spicy | -10 | 4
 |  | Baby | -106 | 16 | [NAME] | -11 | 65 | Bubbles | -19 | 36 | Hamburg | -73 | 6 | [NAME] | 2 | 6 | Brackets | 1 | 1
 |  |  |  |  | Purple Sea | -8 | 61 | True Blue | -145 | 30 | [NAME] | -108 | 6 | Clearity | -13 | 4 | Tulips | -13 | 1
 |  |  |  |  | Still Waters | -28 | 61 | Blue Planet | -150 | 24 | Brooklyn Bridge | -58 | 5 | Ice | -41 | 4 | Suntree | -120 | 0
 |  |  |  |  | Trippin | 21 | 42 | True Green | -18 | 20 | Gate | -23 | 5 | Mellow | -155 | 4 | Silence | -8 | 0
 |  |  |  |  | Watch | 13 | 40 | [NAME] | -195 | 18 | Fight Club | -23 | 5 | [NAME] | -162 | 1 | Tyrol | -11 | 0
 |  |  |  |  | Red Sea | -72 | 37 | Cellar | -34 | 18 | Brandenburg | -11 | 5 | Height | -75 | 0
 |  |  |  |  | Sunset Beach | -80 | 35 | Wine | -24 | 18 | Bed Me Rose | -70 | 4 | Mood | 0 | 0
 |  |  |  |  | Chinese Wall | -25 | 34 | Run RED | -51 | 16 | Shallow | -86 | 4 | Hong Kong | -104 | 0
 |  |  |  |  | Fire Beach | -69 | 32 | Colosseo | -12 | 16 | [NAME] | -105 | 4 | Bloom | -16 | 0
 |  |  |  |  | [NAME] | -73 | 23 | From Within | -19 | 16 | 3D | -33 | 4
 |  |  |  |  | [NAME] | -30 | 21 | Bombay | -35 | 14 | Smoothin | -58 | 4
 |  |  |  |  | Fresh Water | -45 | 13 | Run | -65 | 13 | Cool | -61 | 4
 |  |  |  |  | Dreamin | -203 | 11 | Times Square | -357 | 12 | New York | -323 | 3
 |  |  |  |  | [NAME] | -45 | 9 | Champagne | -56 | 10 | Waverunner | -34 | 3
 |  |  |  |  |  |  |  | [NAME] | -71 | 10 | River Wash | -14 | 3
 |  |  |  |  |  |  |  | Manhattan Bridge | -152 | 9 | Zebra | -112 | 3
 |  |  |  |  |  |  |  | Lake | -56 | 8 | Crush | -61 | 3
 |  |  |  |  |  |  |  | Fear&Loathin | -17 | 8 | Eiffel | -296 | 2
 |  |  |  |  |  |  |  | Chicago | -157 | 8 | Grand Central | -1 | 2
 |  |  |  |  |  |  |  | Wired | -5 | 8 | Batman | -10 | 1
 |  |  |  |  |  |  |  | Checkers | 6 | 8 | Shanghai | -9 | 1
 |  |  |  |  |  |  |  | Rock | -19 | 8 | Keyboard | -21 | 1
 |  |  |  |  |  |  |  | Behind | -111 | 7 | Paris | -190 | 1
 |  |  |  |  |  |  |  |  |  |  | Spring Garden | -99 | 1
 |  |  |  |  |  |  |  |  |  |  | In Memo | -165 | 0
 |  |  |  |  |  |  |  |  |  |  | Tower | -52 | 0
 |  |  |  |  |  |  |  |  |  |  | Elvis | -50 | 0
 |  |  |  |  |  |  |  |  |  |  | Party | -106 | 0
 |  |  |  |  |  |  |  |  |  |  | Splash | -144 | 0
 |  |  |  |  |  |  |  |  |  |  | Smarties | 0 | 0
 |  |  |  |  |  |  |  |  |  |  | Picadilly | -1 | 0
 |  |  |  |  |  |  |  |  |  |  | Orchid | -2 | 0
 |  |  |  |  |  |  |  |  |  |  | Madrid | -1 | 0
 |  |  |  |  |  |  |  |  |  |  | [NAME] | 0 | 0
 |  |  |  |  |  |  |  |  |  |  | Frisco | 0 | 0
 |  |  |  |  |  |  |  |  |  |  | Cubes | 0 | 0
 |  |  |  |  |  |  |  |  |  |  | Bounce | 0 | 0
 |  |  |  |  |  |  |  |  |  |  | Bottles | -1 | 0
 |  |  |  |  |  |  |  |  |  |  | Boating | -1 | 0
 |  |  |  |  |  |  |  |  |  |  | Pacino | -172 | 0
 |  |  |  |  |  |  |  |  |  |  | [NAME] | -61 | 0
 |  |  |  |  |  |  |  |  |  |  | NYC Day | 0 | 0
 |  |  |  |  |  |  |  |  |  |  | The Strip | -83 | 0
 |  | 7215