tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 885896d1735818814-summing-values-separated-by-marks-summing-values-separated-by-slash-marks
Sheet: Sheet1

Date | data | data
1 | 112/75/60 | 116/75/70
2 | 126/87/65 | 121/75/68
3 | 120/86/72 | 123/80/70
4 | 120/86/72 | 116/71/62
5 | 111/76/66 | 119/78/65
6 | 111/75/62 | 117/76/67
7 | 113/78/57 | 126/74/69
8 | 116/81/60 | 126/77/70
9 | 117/80/64 | 119/72/70
10 | 112/74/56 | 118/77/67
11 | 117/80/62 | 124/76/66
12 | 123/85/58 | 133/78/70
13 | 108/75/58 | 108/67/67
14 | 109/76/65 | 115/74/68
15 | 113/77/62 | 115/72/68
16 | 111/79/61 | 121/79/64
17 | 120/80/63 | 119/76/67
18 | 113/81/59 | 124/72/67
19 | 120/80/66 | 115/75/66
20 | 122/83/64 | 125/74/68
21 | 120/77/61 | 121/76/68
22 | 118/76/72 | 112/70/69
23 | 117/80/65 | 116/74/67
24 | 114/79/59 | 121/78/66
25 | 118/80/59 | 117/76/70
26 | 117/78/66 | 119/77/68
27 | 114/79/62 | 116/70/66
28 | 118/81/59 | 115/70/66
29 | 115/76/60 | 115/68/69
30 | 117/81/67 | 125/78/70
31 | 114/77/57 | 123/78/72
SUM | 3596/2458/1939 | 3700/2313/2100
Spreadsheet: 98cca56e-fa58-40f6-bde9-76ded889665a
Sheet: Weekly Changes

 |  |  | Rail to port--Week to Week Changes |  |  |  |  |  |  |  |  | Rail to port--Changes in 4-week averages
 |  |  | MS | TX | Cross-Border-2 | Cross-Border | PNW | East coast | Total |  |  | MS | TX | Cross-Border-2 | Cross | PNW | East coast | Total
% chg from prior week |  |  |  |  |  | n/a |  |  |  |  | % chg from prior week |  |  |  | n/a
% chg from prior year |  |  |  |  |  | n/a |  |  |  |  | % chg from prior year |  |  |  | n/a
% chg from 4-yr avg. |  |  |  |  |  | n/a |  |  |  |  | % chg from 4-yr avg. |  |  |  | n/a
 |  |  | 4-yr avg |  |  |  |  |  | 4-yr avg |  |  | 4-yr avg |  |  |  |  |  | 4-yr avg
1st Quarter 2013 |  |  |  |  |  | n/a
1st Quarter 2012 |  |  |  |  |  | n/a
Change |  |  |  |  |  | n/a
Spreadsheet: 61797d1262723962-bonus-calculation-bonus-calc
Sheet: Sheet1

Actual Results | 1295000 |  | This Number is input and can change
Original  Base | 1033568
Increase
 | Gross DNI < | Percentage Bonus | Percentage
Base Line | 1033568 | 0
Level 1 | 1292000 | 0.1
Level 2 | 1550350 | 0.3
Level 3 | 2067100 | 0.6
Level 4 | 3100700 | 1
 | Bonus | Level 1 Achieved
Employee | 50000 | 0.1
 | Employee Gets 10% Bonus
 | I need a formula that would pick the correct bonus % based upon the actual Results (cell b1)
 | and place it in cell c14
Spreadsheet: 698341d1601933150-formula-rule-to-highlight-mistake-entry-conditional
Sheet: Sheet1

 | IS NOT 8 NUMBERS | IS NOT TWO CHAR | IS NOT NUMBERS |  |  |  | 00:01:50
1 | abcdefgh
2 |  | C5
3 | 12345678 |  | 5646465
4 |  | CC | 65415613146
5 | 154897 |  | 645312
6 | FB12345678 | 55 | 6541JJ54F1
7 | 165564498 | PS | GK54512H
8 | DFBF | FSDF | DVFD
9 | 546GFF5D5 | 6551
10
 |  |  |  | 10
 | I want use conditonal formatting for 3 separate columns , I explain the rule in headers, if not like headers then fill red and white
 |  | C5
 | 12345678 |  | 5646465
 |  | CC | 65415613146
 | 154897 |  | 645312
 | FB12345678 | 55 | 6541JJ54F1
 | 165564498 | PS | GK54512H
 | DFBF | FSDF | DVFD
 | 546GFF5D5 | 6551
Spreadsheet: 786433d1657192520-using-filter-to-copy-relevant-data-from-one-excel-workbook-to-another-excel-help-1
Sheet: Sheet1

Name | Position | State | Entity
NAME 1 | Manager | NSW | 2
[NAME] 2 | Employee | TAS | 3
NAME 3 | BDM | TAS | 3
NAME 4 | MR | WA | 2
NAME 5 | Manager | WA | 1
NAME 6 | Employee | SA | 2
NAME 7 | Employee | WA | 2
[NAME] 8 | BDM | TAS | 3
NAME 9 | Employee | SA | 5
NAME 10 | MR | SA | 4
Spreadsheet: 855501d1705046122-match-lookup-functions-module-mark-analysis-aligw
Sheet: Sheet1

Modules | Mark | Status
Module 1 | 70 |  |  |  |  |  |  |  |  |  |  | List of Electives (Students can study any two)
Module 2 | 37 |  |  |  |  | Semester 1 | Status | Semester 2 | Status
Module 3 | 79 |  |  |  |  | Module 1 |  | Module 7 |  |  |  | Elective 1
Module 4 | 45 |  |  |  |  | Module 2 |  | Module 8 |  |  |  | Elective 2
Module 5 | 20 |  |  |  |  | Module 3 |  | Module 9 |  |  |  | Elective 3
Module 6 | 20 |  |  |  |  | Module 4 |  | Module 10 |  |  |  | Elective 4
Module 2 | 38 |  |  |  |  | Module 5 |  | Module 11 |  |  |  | Elective 5
Elective 1 | 20 |  |  |  |  | Module 6 |  | Module 12 |  |  |  | Elective 6
Module 7 | 53 |  |  |  |  |  |  |  |  |  |  | Elective 7
Module 8 | 52 |  |  |  |  |  |  |  |  |  |  | Elective 8
Elective 2 | 26
Module 9 | 75
Module 10 | 48
Module 11 | 10
Module 12 | 50
Elective 2 | 55
Elective 3 | 56
Table 1
 |  |  |  |  |  |  | H4:H10 | H4
 |  |  |  |  |  |  | J4:J10 | J4
Spreadsheet: 244656d1371803936-vlookup-subtraction-from-a-cell-sample2
Sheet: Stock

Bag Code | Stock | Stock After Process | Box Code | Stock | Stock After Process
HOL  Bacon Fingers | 35000 |  | HOL Display | 793
HOL Chicken Fingers | 41500 |  | HOL 3 kg | 3500
HOL 200g sausages | 23500 |  | HOL 1kg | 0
HOL Instore sausage 750g | 9750 |  | [NAME] | 4025
HOL 3kg sausages | 0 |  | Armitage | 1300
HOL 1kg sausages | 33150 |  | Disney | 3784
HOL Instore sausage 150g | 31500 |  | BHJ Natural Bites | 10000
HOL Petface 10pk | 12000 |  | BHJ Racinel | 1211
HOL Winners 6pk sausage | 37500 |  | Olivers | 4650
HOL Armitage 10pk sausage | 0 |  | 24 kg | 1670
CD [NAME] 150g | 33060 |  | M&J Ham | 1834
CD Pork sausage 150g | 840 |  | M&J Chicken | 1240
BHJ [NAME] 150g | 9524 |  | [NAME] | 1211
BHJ Beef Bones 150g | 48240 |  | Natures Harvest | 4650
[NAME] sausage 150g | 4020 |  | Chub | 0
BHJ Beef Fingers | 2500 |  | Plain 3 kg | 1220
BHJ Ham Fingers | 5500 |  | [NAME] | 0
BHJ Chicken Fingers | 2000 |  | [NAME] | 510
BHJ Chicken Chunks 120g | 2000 |  | Royce | 0
BHJ Salmon Nuggets 120g | 2000
BHJ Primal Beef Bones | 2000
BHJ Primal Pork Sausages | 2000
Mutt & Jeff Sausage | 17500
Mutt & Jeff Chicken | 25000
Mutt & Jeff Ham | 13000
3 kg | 10500
NH Salmon Nuggets 250g | 2118
NH Beef Nuggets 250g | 2074
NH Chicken Nuggets 250g | 1987
NH Ham Nuggets 250g | 2016
Spreadsheet: 725923d1616969437-combine-text-from-multiple-cells-in-one-cell-example
Sheet: Sheet1

Mon 22 March | [NAME] 23 March | Wed 24 March | Thur 25 March | Fri 26 March | Sat 27 March | Sun 28 March | Mon 29 March | [NAME] 30 March | Wed 31 March
 |  |  | 0800-1700 | 0800-1400 |  |  | 0800-1700 | 0800-1700
09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30 | 09.30-17.30
 |  |  | 1200-1800 | 1200-1800 | 1200-1800 | 0900-1200
1200-2000 | 1200-2000 | 1200-2000 | 1200-2000 | 1200-2000 |  |  | 1200-2000 | 1200-2000 | 1200-2000
Spreadsheet: rick_buy__32857__DOUG
Sheet: 1001

4
POWER PLANTS  ACCOUNTS RECEIVABLE AGING
AS OF OCTOBER 31, 2001
 |  |  | CURRENT |  | 1-30 |  | 31-60 |  | 61-90 |  | OVER 90 |  | TOTAL | COMMENTS
SMITH ENRON | A/R |  | 0 |  | 0 |  | 3119556.94 |  | 5122056.38 |  |  |  |  | THIS MONTH TOTAL PAYMENTS
 | PER CENT |  |  |  |  |  | 0 |  | 0 |  |  |  |  | 0
PUERTO QUETZAL | A/R |  | 0 |  | 0 |  | 0 |  | 0 |  | 361082.48 |  |  | THIS MONTH TOTAL PAYMENTS
 | PER CENT
DABHOL POWER CO | A/R |  | 222042.77 |  | 222042.77 |  | 222042.77 |  | 222042.41 |  |  |  |  | THIS MONTH TOTAL PAYMENTS
 | PER CENT |  |  |  |  |  |  |  |  |  |  |  |  | 0
EMPRESA ENERGETICA | A/R |  | 1065593.95 |  | 1847003.65 |  | 0 |  | 1395232.05 |  | 74964.58 |  |  | THIS MONTH TOTAL PAYMENTS
 | PER CENT |  |  |  |  |  |  |  |  |  |  |  |  | 0
EGEMINSA | A/R |  | 6666416.18 |  | 4365995.86 |  | 0 |  | 36113.98 |  |  |  |  | THIS MONTH TOTAL PAYMENTS
 | PER CENT
TOTALS | A/R
 | PER CENT |  |  |  |  |  |  |  |  |  |  |  |  | TOTAL RECEIPTS
Spreadsheet: 216093d1361578676-vlookup-formula-issue-fishing-orders
Sheet: Ship

Ship Table 1 - Regular Customer Orders $[NAME]
Region | Truck | Rail | Air
1 | 2.3 | 2.2 | 30
2 | 2.55 | 2.4 | 32
3 | 3.05 | 2.8 | 34
4 | 3.55 | 3.2 | 35
5 | 4.05 | 3.5 | 36
Ship Table 2 - Preferred Customer Orders $[NAME]
Region | Truck | Rail | Air
1 |  |  | 27
2 |  |  | 30
3 |  |  | 32
4 |  |  | 33
5 |  |  | 34
Spreadsheet: 587715d1535198081-find-the-sum-from-certain-name-and-year-no-pivot-excelforum-sumtot
Sheet: Blad1

NAME | QTY | YEAR |  |  | RESULT SHOULD LOOK LIKE
alfa | 12 | 2018 |  |  |  | 2018 |  | 2019 |  | 2020 |  | etc | etc
alfa | 23 | 2019 |  |  |  |  | tot qty |  | tot qty |  | tot qty
alfa | 45 | 2023 |  |  | ALFA
alfa | 76 | 2019 |  |  |  |  | 24 |  | 99 |  | 78
alfa | 12 | 2018 |  |  |  | Help to make a formula in yellow
alfa | 78 | 2020
alfa | 34 | 2031
alfa | 13 | 2021
NO PIVOT
I will continue a list of names like above that I want to sort out
Spreadsheet: d3c8f62c-356b-475a-aeec-f7fa1fbaafc7
Sheet: Sheet1

PROG ID | ATHLETE ID | ATHLETE FIRST | ATHLETE LAST | NATIONALITY | START NUMBER | SWIM | T1 | BIKE | T2 | RUN | POSITION | TOTAL TIME
6770 | 51453 | Ana Maria | Martinez | PAN | 0 | 00:33:02 | 00:01:15 | 03:09:39 | 00:01:14 | 01:52:10 | 1 | 05:37:22
6770 | 34939 | [NAME] | Torres | COL | 0 | 00:27:50 | 00:01:16 | 03:25:04 | 00:03:00 | 01:49:13 | 2 | 05:46:25
Spreadsheet: 01e118d2-4d57-43b6-b1bf-5ad2f5dedb28
Sheet: Electronics Tech 3

ELECTRONICS
[NAME]
Student Name:
ID #
Communications
General Education | Semester | Grade
Area 1:  Written Communication or Oral Communication (3)
Area 2:  ___ MAT 150 (3) College Algebra
OR ___ MAT 126 (3) Technical Algebra and Trigonometry
Core
___ ELT 110 (5) Circuits I
___ ELT 114 (5) Circuits II
___ ELT 210 (4) Devices I
___ ELT 120 (3) Digital I
___ CAD 100 (3) Introduction to Computer Aided Design
OR Equivalent course with consent of Program Coordinator (3-4)
___ CIT 105 (3) Introduction to Computers
___ ELT 289 (1) Engineering and Electronics Technology Capstone Course
___ COED 198 (1-2) Practicum
OR ___ COE 199 (1-2) Cooperative Education
OR ___ Equivalent course with consent of Program Coordinator (1-2)
Technical Courses
___ ELT 214 (4) Devices II
___ ELT 220 (3) Digital II
___ ELT 240 (6) Communication Electronics
Technical Electives (11)
Technical Electives: Any EET, ET, ELT, IMT, CIS, CIT, NIS, IT, ISM, CAD, ICT, MFG or any other
course as approved by the Program Coordinator.
Southeast Kentucky Community & Technical College | Updated Spring 2013
Spreadsheet: 872697d1719059648-using-large-match-and-index-but-not-finding-second-duplicate-score-match-nigel-balchin-example-v4-njb-phuocam-aligw
Sheet: Scores

 |  | 100 |  | [NAME]
 |  | 104 |  | [NAME]
 |  | 134 |  | [NAME]
 |  | 112 |  | [NAME]
 |  | 123 |  | [NAME]
 |  | 87 |  | [NAME]
 |  | 143 |  | [NAME]
 |  | 116 |  | [NAME]
 |  | 123 |  | [NAME]
 |  | 112 |  | [NAME]
 |  | 120 |  | [NAME]
 |  | 126 |  | [NAME]
 | Pos | Sc | position in list
 | 1 |  |  |  |  | 1st
 | 2 |  |  |  |  | 2nd
 | 3 |  |  |  |  | 3rd
 | 4 |  |  |  |  | 4th
 | 5 |  |  |  |  | 5th
 | 6
 | 7
 | 8
 | 9
 | 10
 | 11
 | 12
Spreadsheet: michelle_lokay__26570__imbalsumm0012
Sheet: Amoco

 | Florida Plant
Day | Measured | Scheduled | Imbal
1 | 93344 | 93623
2 | 90757 | 82485
3 | 79881 | 83564
4 | 86932 | 85573
5 | 91421 | 89951
6 | 93012 | 90323
7 | 112781 | 112264
8 | 107002 | 105320
9 | 103512 | 98386
10 | 106623 | 104979
11 | 95291 | 93974
12 | 91874 | 89099
13 | 105714 | 103835
14 | 101750 | 100162
15 | 109775 | 109693
16 | 87524 | 86423
17 | 98132 | 96808
18 | 101493 | 99961
19 | 134960 | 143957
20 | 123614 | 121696
21 | 113423 | 111901
22 | 122997 | 120814
23 | 95797 | 94551
24 | 86651 | 84733
25 | 91545 | 90433
26
27
28
29
30
31
2000-11-30 00:00:00 |  |  | -15891
2000-12-25 00:00:00
Spreadsheet: 0fda912a-6dbb-487d-8837-aca41cd5ef49
Sheet: 15a

Product1 | Cleared2 | Uncleared | TOTAL
Index Tranche | - | 1117 | 1117
Index | 132826 | 112288 | 245114
Europe | 53151 | 53248 | 106399
North America/Asia | 78914 | 57780 | 136694
Other | 761 | 1260 | 2021
OTHER* | 3580 | 29107 | 32687
TOTAL | 136406 | 142512 | 278918
*OTHER variable includes exotic credit products, swaptions, and total return swaps.
Spreadsheet: 849769d1700161046-night-shift-calculation-error-display-value-night-shift-ot-computation
Sheet: Night Shift 

 | EMPLOYEE NAME |  |  | EMPLOYEE ID | DEPARTMENT |  | MANAGER
 | [NAME] |  |  | c753951 | Accounting
 | Select date from drop-down menus for Year, Month, Date, and  Weekend fields. |  | YEAR | MONTH | DATE | [NAME] | Check box if Weekends          are paid at overtime rate
 |  |  | 2023 | November | 1 | Fri & Sat | <--- Select designated Weekend Days
 | Enter data for Start Time, Regular Hours, Regular Pay, and Overtime Pay. |  | START  TIME | REGULAR  HOURS* | REGULAR PAY hourly rate | OVERTIME PAY hourly rate
 |  |  | 21:00:00 | 8 |  | 75
 | Enter Start, End, and Break  Times, below.    Day and Date and Calculations will automatically populate. |  |  | *When designating "Night Shift Hours," build in standard break times. For example, if a night shift begins at 9pm and ends at 5:30am with a half-hour break, set hours to: 8.5 if a night shift begins at 9pm and ends at 5am with an hour break, set hours to: 9.0
 |  |  |  |  |  | C A L C U L A T I O N S do not alter fields
 | DAY | DATE | START  TIME | END  TIME | BREAK TIME in hours | REGULAR  HOURS | OVERTIME  HOURS | TOTAL  PAY
 |  |  | 21:00:00 | 07:00:00
 |  |  |  |  | BREAK TIME in hours | REGULAR  HOURS | OVERTIME  HOURS | TOTAL  PAY
 |  |  |  | OVERVIEW
Spreadsheet: 881235d1729191842-using-isnumber-with-and-or-multiple-conditions-book2
Sheet: Sheet1

Main Data | Data Check 1 | Data Check 2 | Data Check 3 | Data Check 4 |  | Cats | Dogs | Mice | Pigs | Sheep
Cats Dogs Mice Sheep | Cats Dogs | Cats Dogs | Pigs Cats | Mice Sheep Pigs |  | Main Data & Data Check 1-4
Pigs Cats | Pigs Cats | Mice Sheep Pigs | Cats Dogs | Cats Sheep Dogs |  | Not in Main Data
Mice Sheep Pigs Cats | Mice Sheep Pigs | Cats Sheep Dogs | Cats Sheep Dogs | Cats Dogs |  | Main Data & Data Check 1-4
Dogs Pigs | Cats Sheep Dogs | Pigs Cats | Pigs Cats | Mice Sheep Pigs |  | Not in Main Data
Mice Cats Sheep | Pigs Dogs | Cats Dogs | Mice Sheep Pigs | Mice Sheep |  | Main Data & Data Check 1-4
Sheep Dogs Cats Mice | Mice Sheep | Mice Sheep | Pigs | Dogs |  | Main Data & Not in Data Check 1-4
Spreadsheet: 294463d1391395784-extracting-data-from-large-spreadsheet-mock-spreadsheet-and-data-needs-for-gloria
Sheet: Charges by Funding Source

Funding Source | Protocol | Sum of Payment Amount
CNI | Field Trial | 30000
 | field work | 21800
 | Lab Work | 15000
 | None | 84770
 | Random | 5500
 | Testing | 112890
CNI Total |  | 269960
SAC | field work | 27370
 | None | 86159
 | Store Sales | 34670
 | Testing | 91570
SAC Total |  | 239769
Grand Total |  | 509729
Spreadsheet: 231393d1367034311-need-help-with-data-summary-based-on-a-daily-basis-salesman-performance_solution
Sheet: Data

 |  |  | 20 |  | 30 |  | 40 |  | 50 |  | 60 |  | 70 |  | 80
 | Driver | Sale Day | Cash | Credit | Cash | Credit | Cash | Credit | Cash | Credit | Cash | Credit | Cash | Credit | Cash | Credit
 | Salesman 1 | 2013-04-26 00:00:00 | 54 | 87 | 59 | 119 | 11 | 74 | 57 | 89 | 114 | 2 | 56 | 15 | 117 | 58
 | Salesman 2 | 2013-04-26 00:00:00 | 37 | 116 | 100 | 100 | 26 | 107 | 47 | 101 | 116 | 9 | 17 | 107 | 36 | 59
 | Salesman 3 | 2013-04-26 00:00:00 | 96 | 78 | 71 | 50 | 4 | 8 | 43 | 62 | 35 | 56 | 19 | 53 | 35 | 112
 | Salesman 4 | 2013-04-26 00:00:00 | 79 | 87 | 83 | 1 | 65 | 59 | 37 | 11 | 35 | 34 | 95 | 119 | 4 | 101
 | Salesman 1 | 2013-04-27 00:00:00 | 54 | 49 | 31 | 59 | 100 | 18 | 50 | 1 | 3 | 84 | 97 | 14 | 83 | 10
 | Salesman 2 | 2013-04-27 00:00:00 | 44 | 73 | 116 | 65 | 29 | 89 | 25 | 9 | 58 | 77 | 25 | 6 | 109 | 99
 | Salesman 3 | 2013-04-27 00:00:00 | 34 | 34 | 2 | 116 | 30 | 21 | 64 | 27 | 31 | 27 | 99 | 18 | 86 | 7
 | Salesman 5 | 2013-04-27 00:00:00 | 57 | 97 | 106 | 34 | 18 | 2 | 6 | 40 | 67 | 57 | 75 | 118 | 85 | 77
 | Salesman 1 | 2013-04-28 00:00:00 | 16 | 9 | 25 | 119 | 27 | 67 | 36 | 113 | 100 | 26 | 6 | 63 | 43 | 12
 | Salesman 2 | 2013-04-28 00:00:00 | 15 | 90 | 108 | 26 | 108 | 60 | 54 | 50 | 50 | 103 | 42 | 72 | 97 | 91
 | Salesman 3 | 2013-04-28 00:00:00 | 23 | 66 | 75 | 18 | 79 | 55 | 87 | 36 | 50 | 62 | 62 | 97 | 67 | 16
 | Salesman 7 | 2013-04-28 00:00:00 | 53 | 116 | 108 | 68 | 36 | 1 | 101 | 72 | 101 | 36 | 79 | 15 | 68 | 7
Spreadsheet: 22854d1212007757-search-for-a-file-and-bring-back-data-to-master-spreadsheet-4875
Sheet: Sheet1

05/14/2008 07:57:57 AM |  |  | Dennis Steel, Inc. |  |  |  |  |  | Page 1 of 1
 |  |  | Cost Summary
 |  |  | 4875  - Leander HS Weight Room Addtn
 |  |  | to 05/15/08
Cost | Cost Code |  | Matl Lbs | Labor Hours |  |  | Actual Cost | Income | Profit/Loss
Code | Description |  |  |  |  |  | to Date | to Date | before OH
100 | Fabrication Labor |  |  |  |  | 408.5 | 7800
101 | Erection Labor |  |  |  | 1532.5 |  | 33085
200 | Materials-Steel & Misc |  | 35660 |  |  |  | 24393
210 | Materials-Joist & Deck |  |  |  |  |  | 50880
500 | Equipment Rental |  |  |  |  |  | 29770
700 | Detailing |  |  |  |  | 94 | 2878
** Leander HS Weight Room Addtn Totals **
 |  |  | 35660 |  | 2035 |  | 148805 | 211603 | 62798
 |  |  | Client Name:  111 - Brath, Inc.
 |  |  | Original Contract Amount: |  |  |  | 220603
 |  |  | Change Orders to Date:
 |  | Total Revised Contract Amount: |  |  |  |  | 220603
 |  |  | Billed To Date: |  |  |  | 211603
 |  |  | Left To Bill On Contract: |  |  |  | 9000
Spreadsheet: 37289d1235250227-need-a-formula-to-populate-cells-with-lists-dependentlists
Sheet: Choices

On this page we use Validation List of |  |  |  |  |  | Sample Lists
Allow: =Animals
for both H5 and H19 versions. |  |  |  |  |  | Problematic
 |  |  |  |  |  |  | Classes | Types | Animals
Then, the validation list for I5 uses an INDIRECT formula |  |  |  |  |  |  | Canine | Tigers | [NAME]
Allow:  =INDIRECT(H5)
so the word chosen becomes the active "list" and the animal
names are brought over. The same thing is used in the |  |  |  |  |  |  | NOTE: Problem if you make selections in the boxes above, and then go back and change an earlier box
validation list for J5: |  |  |  |  |  |  | it does not change the others, so you could end up with Canine - Tiger - Bald Eagle.
Allow:  =INDIRECT(I5)
This technique could go on indefinitely. |  |  |  |  |  |  | SOLUTION: A WorkSheet_change macro can be used to watch for changes in the earliest boxes and then
 |  |  |  |  |  |  | clear the previous made in later boxes that are now no longer valid.
The "LISTS" are on the next sheet.
 |  |  |  |  |  |  | Right-click on the sheetname tab and VIEW CODE to see the macro.
 |  |  |  |  |  | Better
 |  |  |  |  |  |  | Classes | Types | Animals
 |  |  |  |  |  |  | Feline | [NAME] | Can't Afford
Spreadsheet: 52207d1251908192-if-formula-dummy-workbook
Sheet: Summary

 |  |  | Person A | Person B | Person C | Person D | Person E
 |  | Question | Score | Score | Score | Score | Score | TOTAL
[NAME] | XX | 1
 |  | 6
 |  | 14
 |  | 21
 |  | 28
 | XX | 4
 |  | 11
 |  | 18
 |  | 26
 | XX | 8
 |  | 16
 |  | 24
[NAME] | XX | 2
 |  | 9
 |  | 15
 |  | 22
 |  | 29
 | XX | 5
 |  | 19
 | XX | 12
 |  | 25
[NAME] | XX | 3
 |  | 13
 |  | 20
 |  | 30
 | XX | 7
 |  | 17
 |  | 23
 | XX | 10
 |  | 27
 |  | INSPIRE
 |  | CREATE
 |  | CONNECT
 |  | TOTAL
 |  | AVERAGE
Spreadsheet: 680707d1591152436-summing-by-matching-parts-of-a-value-to-a-matrix-sum-or-sumif
Sheet: OS

MODEL/SZ | Total Plan
SSS333-02 |  |  | Need advise for sum or sumif formula
SSS333-03
SSS333-04
SSS333-05
SSS333-06
SSS333-07
SSS333-08
SSS333-09
SSS333-10
SSS333-11
SSS333-12
SSS333-13
DDD4444-02
DDD4444-03
DDD4444-04
DDD4444-05
DDD4444-06
DDD4444-07
DDD4444-08
DDD4444-09
DDD4444-10
DDD4444-11
DDD4444-12
DDD4444-13
WWW999DW-02
WWW999DW-03
[NAME]
WWW999DW-05
WWW999DW-06
WWW999DW-07
WWW999DW-08
WWW999DW-09
WWW999DW-10
WWW999DW-11
WWW999DW-12
WWW999DW-13
Spreadsheet: 7c4683e7-4d3e-4987-b0cb-545a1c94460b
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
PROT | Test | PROT | Protamine, IgE | Protamine, IgE | Fluorescence Enzyme Immunoassay (FEIA) | Serum Gel Tube: SGT |  |  | 0.5 | mL | Container/Tube:  Preferred: Red top Acceptable: Serum gel [NAME]: 0.5 mL for each 5 allergens requested Additional Information: Designate specific allergens from the list in Allergens-IgE Antibodies in Special Instructions. Forms: If not ordering electronically, submit an Allergen Request Form (Supply T236) with the specimen. | For 1 allergen: 0.3 mL/For more | Hemolysis	Mild OK; Gross OK Thawing	Warm reject; Cold OK Lipemia	Mild OK; [NAME] OK Icterus	NA Other	NA | Class	IgE kU/L	Interpretation 0	<0.35	Negative 1	0.35-0.69	Equivocal 2	0.70-3.49	Positive 3	3.50-17.4	Positive 4	17.5-49.9	Strongly positive 5	50.0-99.9	Strongly positive 6	> or =100	Strongly positive Reference values apply to all ages. | Monday through Friday; 9 a.m.-8 p.m., Saturday; 8 a.m.-3 p.m. | Same day/1 day | 3 days | 1 | 86003 |  |  |  |  | Rochester
PROT | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 14 days
PROT | Result | PROT | Protamine, IgE | Protamine, IgE | Numeric |  |  |  |  | kU/L |  |  |  |  |  |  |  |  |  | 11192-2 | [NAME].IgE:ACnc:Pt:Ser:Qn:
Spreadsheet: 792108d1660742844-determine-how-many-times-a-value-occurs-in-a-specific-time-range-test
Sheet: Sheet1

[NAME] | Data | Recurent - 6 or more than 6 orders in January - June 2022 | Ideal - 2 or more than 2 orders in June 2022
[EMAIL] | 01.01.2022
[EMAIL] | 07.03.2022
[EMAIL] | 07.03.2022
[EMAIL] | 07.03.2022
[EMAIL] | 07.03.2022
[EMAIL] | 20.06.2022
[EMAIL] | 20.06.2022
[EMAIL] | 31.05.2022
[EMAIL] | 31.05.2022
[EMAIL] | 31.05.2022
[EMAIL] | 13.06.2022
[EMAIL] | 17.06.2022
Spreadsheet: 117393d1312768995-linking-cells-draft
Sheet: TE

 | Rank | Player | Team | Bye | Age | [NAME]. | Projected | Available
 | 1 | [NAME] | SD | 6 | 31 | 8 | 176 | YES
 | 2 | [NAME] | DAL | 5 | 29 | 8 | 138 | YES
 | 3 | [NAME] | GB | 8 | 24 | 3 | 138 | YES
 | 4 | [NAME] | SF | 7 | 27 | 5 | 134.5 | YES
 | 5 | Dallas Clark | IND | 11 | 32 | 8 | 132 | YES
 | 6 | [NAME] | NO | 11 | 24 | 1 | 122 | YES
 | 7 | Marcedes Lewis | JAX | 9 | 27 | 5 | 114 | YES
 | 8 | [NAME] | HOU | 11 | 28 | 5 | 110 | YES
 | 9 | [NAME] | NYJ | 8 | 26 | 3 | 100 | YES
 | 10 | [NAME] | WAS | 5 | 29 | 7 | 96.2 | YES
 | 11 | [NAME] | DET | 9 | 26 | 2 | 94.1 | YES
 | 12 | [NAME] | NE | 7 | 22 | 1 | 92.5 | YES
 | 13 | [NAME] | ATL | 8 | 35 | 14 | 90 | YES
 | 14 | [NAME] | SEA | 8 | 25 | 4 | 90 | YES
 | 15 | [NAME] | TB | 8 | 28 | 7 | 89.5 | YES
 | 16 | [NAME] | TEN | 6 | 24 | 2 | 89 | YES
 | 17 | Jermaine [NAME] | CIN | 7 | 23 | 1 | 87.6 | YES
 | 18 | [NAME] | NE | 7 | 21 | 1 | 82 | YES
 | 19 | [NAME] | CAR | 8 | 26 | 4 | 80 | YES
 | 20 | [NAME] | ARI | 5 | 31 | 10 | 79 | YES
 | 21 | [NAME] | IND | 11 | 26 | 3 | 76 | YES
 | 22 | [NAME] | STL | 5 | 23 | R | 74 | YES
 | 23 | [NAME] | KC | 6 | 24 | 1 | 71 | YES
 | 24 | Visanthe Shiancoe | MIN | 9 | 31 | 8 | 68.5 | YES
 | 25 | [NAME] | PHI | 7 | 26 | 4 | 68 | YES
 | 26 | [NAME] | PIT | 11 | 28 | 6 | 67.7 | YES
 | 27 | [NAME] | CLE | 5 | 30 | 7 | 61.9 | YES
 | 28 | [NAME] | MIA | 5 | 27 | 5 | 58 | YES
 | 29 | [NAME] | OAK | 7 | 27 | 4 | 55.6 | YES
 | 30 | [NAME] | HOU | 11 | 29 | 6 | 55.2 | YES
 | 31 | [NAME] | MIN | 9 | 21 | R | 52 | YES
 | 32 | [NAME] | JAX | 9 | 26 | 2 | 51.7 | YES
 | 33 | [NAME] | CLE | 5 | 26 | 3 | 48.2 | YES
 | 34 | [NAME] | TB | 8 | 23 | R | 48 | YES
 | 35 | [NAME] | BUF | 7 | 25 | 2 | 47.5 | YES
 | 36 | [NAME] | CHI | 8 | 34 | 12 | 47 | YES
 | 37 | [NAME] | DEN | 5 | 27 | 5 | 43.4 | YES
 | 38 | [NAME] | BAL | 5 | 24 | 1 | 41.6 | YES
 | 39 | [NAME] | WAS | 5 | 25 | 3 | 39.5 | YES
 | 40 | [NAME] | PIT | 8 | 31 | 9 | 38.9 | YES
 | 41 | [NAME] | ATL | 8 | 32 | 9 | 36.2 | YES
 | 42 | [NAME] | SEA | 6 | 27 | 3 | 36 | YES
 | 43 | Bo Scaife | CIN | 6 | 30 | 6 | 30.7 | YES
 | 44 | Delanie Walker | SF | 7 | 26 | 5 | 29.7 | YES
 | 45 | [NAME] | GB | 8 | 22 | R | 26 | YES
 | 46 | [NAME] | CAR | 9 | 30 | 9 | 26 | YES
 | 47 | [NAME] | DET | 9 | 28 | 5 | 22.8 | YES
 | 48 | [NAME] | SD | 6 | 32 | 9 | 17.5 | YES
 | 49 | [NAME] | ARI | 6 | 23 | R | 16 | YES
 | 50 | [NAME] | KC | 6 | 27 | 5 | 11 | YES
 | 51 | [NAME] | IND | 11 | 26 | 4 | 6.6 | YES
 | 52 | [NAME] | GB | 8 | 22 | 1 | 3 | YES