tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 86951d1286898009-pivot-tables-adjacent-formulas-book1
Sheet: Sheet3

Age | (All) |  |  |  |  |  |  |  |  |  | 3
Sum of Amount | MOS2
Name | Beginning Weight | Ending Weight |  | Difference in Weight
[NAME] | 187 | 185 |  | #N/A
Barack | 178 | 181 |  | -3
Barney | 98 | 101 |  | -3
Dopey | 42 | 40 |  | 2
Droopy | 58 | 61 |  | -3
[NAME] | 185 | 183 |  | 2
Homer | 245 | 243 |  | 2
Jethro | 210 | 213 |  | -3
Sad Sack | 114 | 112 |  | 2
Grand Total | 1317 | 1319 |  | -2
Spreadsheet: kate_symes__18249__DJ Index 3-30
Sheet: Sheet1

Electricity Price Index Report
Rep. [NAME]: | 2001-03-30 00:00:00
Flow Date: | 2001-03-30 00:00:00
From: | Enron Power Marketing Inc. - Kate Symes
Phone: | (800) 464-7486
Fax: | (503) 464-3740
To: | [NAME] or [NAME]
Phone: | (609) 520-4452 ([NAME])
Phone: | (609) 520-4663 (Earnest Onukogu)
Fax: | (609) 452-3531
COB
Designation | Type | Weighted Avg. Price | MWH Vol.
On [NAME] | Firm Trades Sales | 186.25 | 1600
 | Firm Trades Purchases | 178.3333333333333 | 1200
[NAME] | Firm Trades Sales | 119.2897727272727 | 1408
 | Firm Trades Purchases | #[NAME]! | 0
MID COLUMBIA
Designation | Type | Weighted Avg. Price | MWH Vol.
On [NAME] | Firm Trades Sales | 178 | 2000
 | Firm Trades Purchases | 178 | 400
[NAME] | Firm Trades Sales | 125.8333333333333 | 1200
 | Firm Trades Purchases | 125 | 200
PALO VERDE
Designation | Type | Weighted Avg. Price | MWH Vol.
On [NAME] | Firm Trades Sales | 155.7826086956522 | 9200
 | Firm Trades Purchases | 155 | 2400
[NAME] | Firm Trades Sales | 77.55555555555554 | 1800
 | Firm Trades Purchases | #[NAME]! | 0
MEAD
Designation | Type | Weighted Avg. Price | MWH Vol.
On [NAME] | Firm Trades Sales | 160 | 400
 | Firm Trades Purchases | 145 | 160
[NAME] | Firm Trades Sales | 90 | 400
 | Firm Trades Purchases | #[NAME]! | 0
NP-15
Designation | Type | Weighted Avg. Price | MWH Vol.
On [NAME] | Firm Trades Sales | 149.3 | 4000
 | Firm Trades Purchases | 163.5 | 800
[NAME] | Firm Trades Sales | 93.4 | 1000
 | Firm Trades Purchases | 92.11538461538461 | 1040
SP-15
Designation | Type | Weighted Avg. Price | MWH Vol.
On [NAME] | Firm Trades Sales | 164.375 | 3200
 | Firm Trades Purchases | 162.764705882353 | 1360
[NAME] | Firm Trades Sales | 93.88524590163932 | 2440
 | Firm Trades Purchases | 91.13333333333333 | 600
Spreadsheet: 215860d1361523541-searching-for-a-value-in-multiple-sheets-fame1
Sheet: SN5(040912-24)

3.017 | 3.01 | 3.023 | TIC | 863 | 0.02 | 1107 | 0.06 | 0.78 |  | Cycloheptanone, 4-acetyl-7,7-dimethyl-2-(2-oxopropyl)-
3.064 | 3.023 | 3.1 | TIC | 29236 | 0.51 | 12575 | 0.63 | 2.32 | V | Cyclohexane, 1,1'-[1-(2,2-dimethylbutyl)-1,3-propanediyl]bis- (CAS) HEPTAN, 1,3-DICYCLOHEXYL-5,5-DIMETHYL-
3.107 | 3.1 | 3.143 | TIC | 3327 | 0.06 | 2521 | 0.13 | 1.32 |  | 1-Naphthalenemethanol, decahydro-5-(5-hydroxy-3-methyl-3-pentenyl)-1,4a-dimethyl-6-methylene-, [1S-[1.alpha.,4a.alpha.,5.alpha.
3.199 | 3.143 | 3.227 | TIC | 7746 | 0.14 | 2968 | 0.15 | 2.61 |  | 2,5,9-Trimethyl-12-oxododeca-4,8-dienoic acid, methyl ester
3.353 | 3.337 | 3.39 | TIC | 6901 | 0.12 | 4501 | 0.22 | 1.53 |  | 1-Methyl-4-(2'-methyl-5'-heptyn-2'-yl)-2,3,5-trioxabicyclo[2.2.2]oct-7-ene
Spreadsheet: 08ec3f9c-3f4e-4b06-a7b3-4bd5380d5eb7
Sheet: Sheet1

Table 1--U.S. rice supply and use  1/ | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7
Item | 2005/06 | 2006/07 | 2007/08 | 2008/09 | 2009/10 | 2010/11 | 2011/12
 |  |  |  |  |  |  | 2/
TOTAL RICE |  |  |  | Million acres
Area:
Planted | 3.384 | 2.838 | 2.761 | 2.995 | 3.135 | 3.636 | 2.689
Harvested | 3.364 | 2.821 | 2.748 | 2.976 | 3.103 | 3.615 | 2.618
 |  |  |  | Pounds per harvested acre
Yield | 6624 | 6898 | 7219 | 6846 | 7085 | 6725 | 7067
 |  |  |  | Million cwt
Beginning stocks | 37.71 | 42.992 | 39.315 | 29.492 | 30.419 | 36.499 | 48.467
Production | 222.833 | 194.585 | 198.388 | 203.733 | 219.85 | 243.104 | 185.009
Imports | 17.134 | 20.581 | 23.9 | 19.218 | 19.019 | 18.336 | 19
Total supply | 277.677 | 258.158 | 261.603 | 252.443 | 269.288 | 297.939 | 252.476
Food, industrial,
& residual 3/ | 116.329 | 124.671 | 123.152 | 123.77 | 120.012 | 134.502 | -
Seed | 3.503 | 3.408 | 3.697 | 3.87 | 4.488 | 3.324 | -
Total domestic use | 119.832 | 128.079 | 126.849 | 127.64 | 124.5 | 137.826 | 124
Exports | 114.853 | 90.764 | 105.262 | 94.384 | 108.341 | 111.646 | 90
Rough | 33.449 | 32.112 | 37.663 | 31.633 | 40.351 | 34.896 | 33
Milled 4/ | 81.404 | 58.652 | 67.599 | 62.751 | 67.953 | 76.75 | 57
Total use | 234.685 | 218.843 | 232.111 | 222.024 | 232.841 | 249.472 | 214
Ending stocks | 42.992 | 39.315 | 29.492 | 30.419 | 36.499 | 48.46700000000004 | 38.5
 |  |  |  | Percent
Stocks-to-use ratio | 18.31902337175363 | 17.96493376530206 | 12.70598980660115 | 13.70077108781033 | 15.67550388462513 | 19.42783158029761 | 18
 |  |  |  | $/cwt
Average farm |  |  |  |  |  |  | 13.8
price 5/ | 7.65 | 9.96 | 12.8 | 16.8 | 14.4 | 12.7 | 14.8
 |  |  |  | Percent
Average
milling rate | 70.25 | 71 | 69.88 | 70.83 | 71.53 | 68.86 | 70.75
N/A = not available.  1/ August-July market year; rough equivalent.  2/ Projected.  3/ Residual includes unreported
use, processing losses, and estimating errors.  4/  Rough-rice equivalent.  5/ Market-year weighted average.
Source: World Agricultural Supply and Demand Estimates, WAOB, USDA.
Updated January 12, 2012.
Spreadsheet: darrell_schoolcraft__7735__imball0203
Sheet: mewborne

 | [NAME]
 | 500174 |  | 53888 |  | 78060 |  | 78062
Day | Measured | Scheduled | Measured | Scheduled | Measured | Scheduled | Measured | Scheduled
1 | 5107 | 4944 |  |  | 830 | 901 | 1351 | 1247
2 | 4736 | 4944 |  |  | 173 | 901 | 1282 | 1247
3 | 4732 | 4944 | 1 |  | 1073 | 901 | 1359 | 1247
4 | 5539 | 4944 | 1 |  | 1146 | 901 | 1382 | 1247
5 | 5559 | 6484 |  |  | 902 | 901 | 1409 | 1247
6 | 5635 | 5714 |  |  | 817 | 901 | 1389 | 1247
7 | 5741 | 5714 |  |  | 949 | 854 | 1350 | 1247
8 | 5542 | 4944 |  |  | 919 | 680 | 1368 | 1247
9 | 5518 | 4944 |  |  | 914 | 225 | 1358 | 1247
10 | 5505 | 4944 |  |  | 868 | 8 | 1355 | 1247
11 | 5427 | 4944 |  |  | 877 | 901 | 1379 | 1247
12 | 5555 | 4941 |  |  | 843 | 901 | 1351 | 1247
13 | 4841 | 4944 |  |  | 916 | 901 | 1349 | 1247
14 | 5472 | 4944 |  |  | 903 | 901 | 1347 | 1247
15 | 5321 | 4944 | 2 |  | 803 | 901 | 1328 | 1247
16 | 5319 | 4944 |  |  | 880 | 901 | 1314 | 1247
17 | 5104 | 4944 |  |  | 887 | 901 | 1317 | 1247
18 | 5295 | 4944 |  |  | 866 | 901 | 1328 | 1247
19 | 5291 | 4944 |  |  | 483 | 901 | 1285 | 1247
20
21
22
23
24 |  |  |  |  |  |  |  |  |  |  | 377
25 |  |  |  |  |  |  |  |  |  |  | 725
26
27
28
29
30
31
2002-02-28 00:00:00 |  |  |  |  |  |  |  |  | 326187.28
2002-03-19 00:00:00
CBS Volume
 |  |  | 128267
Spreadsheet: 732512d1621001177-calculate-and-return-decimal-value-between-range-new-microsoft-excel-worksheet
Sheet: Sheet1

 |  |  |  | Enter Load | 170
 |  |  |  | Hours [NAME]. |  |  |  | Hours | 1 | 2 | 3 | 4 | 6 | 8 | 10 | 15 | 30
 |  |  |  |  |  |  |  | Mod calcs
 |  |  |  | Enter Total mods | 64
 |  |  |  |  |  |  |  | VPC | 5.7 | 4 | 2.95 | 2.33 | 1.58 | 1.19 | 0.94 | 0.6 | 0.25
Spreadsheet: 90534d1290256976-using-solver-function-solver_solution_books
Sheet: Book Boxes

 | BOOK BOXES
 | Title | Weight | Cost | Sale Price | Number of authors per [NAME] | Books per author | Numbers of books per box | Profit per book | Total Profit | Total Weight
 | [NAME], JK Rowling | 5 | 9 | 17 | 0 | 0 | 0 | 8 | 0 | 0
 | The Lord of the Rings, JRR Tolkien | 4 | 8 | 13 | 0 | 0 | 0 | 5 | 0 | 0
 | Chronicles of Narnia, CS Lewis | 3.5 | 7 | 11 | 0 | 0 | 0 | 4 | 0 | 0
 | A Series of Unfortunate Events, [NAME] | 3 | 6 | 9 | 0 | 0 | 0 | 3 | 0 | 0
 | [NAME] and the Chocolate Factory, [NAME] | 2.5 | 5 | 7 | 0 | 0 | 0 | 2 | 0 | 0
 | A Wrinkle in Time, [NAME] | 1 | 4 | 6 | 0 | 0 | 0 | 2 | 0 | 0
 | Total |  |  |  | 0 |  | 0 |  | 0 | 0
 |  |  |  |  | ***20 books or less per box
 |  |  |  |  | ***Three different authors must be in the box
 |  |  |  |  | ***Between 4 and 8 from each author must be in the box
 |  |  |  |  | ***Total weight must be equal to or less than 50 pounds
Spreadsheet: 77517d1277978542-countif-with-multiple-criteria-function-analysis-of-dome-spec
Sheet: Sheet1

 |  |  |  |  |  | Spec (mm)
Dome | Spec |  |  |  |  | 95 | 100 | 105 | 110 | 115 | 120 | 125 | 130
(kg) | ([NAME])
1.73 | 105 |  |  | Dome (kg) | 1.00>1.25
1.76 | 105 |  |  |  | 1.25>1.5
1.775 | 105 |  |  |  | 1.50>1.75
1.785 | 110 |  |  |  | 1.75>2.00
1.835 | 95 |  |  |  | 2.00>2.25
1.84 | 120 |  |  |  | 2.25>2.50
1.88 | 105 |  |  |  | 2.50>2.75
1.88 | 100
1.9 | 120
1.915 | 105
1.87 | 105
1.79 | 105
Spreadsheet: benjamin_rogers__1039__Consolidated 6 Peaker-051800
Sheet: Brownsville

INCOME STATEMENT - BROWNSVILLE
('000 $) | 2001
Revenue
Fixed Price Period: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0
Demand Payment
Energy Payment
Block Payment
Amortization of Contract
Market Price & Price Extension Period:
Demand Payment | 0 | 0 | 0
Variable Revenue | 0 | 0 | 0
Energy Margin | 0 | 0 | 0
Interest Income
Total Revenue
Expense
Fixed O&M
Variable O&M
Major Maintenance & Ongoing Capex
O&M Management Fee
Owner's Expense
Property Taxes Liability | 325 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 375 | 427.6483011796236 | 436.201267203216 | 444.9252925472804 | 453.823798398226 | 462.9002743661905
Franchise Tax
Total Expense
EBITDA
Depreciation & Amortization
EBIT
Interest Expense
EBT
Book State Tax Benefit / (Expense)
Shareholder Fed. Tax Benefit / (Expense)
After Tax Book Income
CASH FLOW - BROWNSVILLE
('000 $) | 2001 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Check
EBITDA less Contract Amortization
Plus Property Tax Liability
Less Property Tax Expense | -250
Debt Service
Pre Tax Cash Flow
State Cash Taxes Benefit (Expense)
Federal Cash Taxes Benefit (Expense)
After Tax Cash Flow
STATE TAX & FRANCHISE TAX - BROWNSVILLE
 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22
('000 $) | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020
FRANCHISE TAX
Book Value of Assets
Paid-In-Capital
[NAME]
Outstanding Debt
Total Capitalization
Greater of Book Value or Capitalization
State Franchise Tax Rate
State Franchise Tax Liability | 454.2454129454724 | 440.1965857409733 | 426.1477585364741 | 412.0989313319749 | 398.0501041274757 | 384.0012769229766 | 369.9524497184774 | 355.9036225139782 | 341.854795309479 | 327.8059681049799 | 313.7571409004807 | 299.7083136959816 | 285.6594864914824 | 271.6106592869833 | 257.5618320824842 | 243.513004877985 | 229.4641776734859 | 215.4153504689867 | 201.3665232644876 | 187.3176960599885
STATE TAXES
Pretax Book Income less Contract Amortization
Plus Book Depreciation & Amortization
Less Tax Depreciation
State Taxable Income
State Income Tax Rate
Current State Income Tax Expense (Benefit)
Beginning NOL's | 0 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0
New NOL's
Expired NOL's | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
NOL Utilization
Ending NOL's
Total State Taxes Utilizing NOLs
Spreadsheet: 79811d1280045813-transposing-multiple-rows-example
Sheet: Sheet1

Want to know how to get from this….. |  |  |  |  | To this……. (but with a much LARGER dataset)
 |  |  |  |  |  | Distance (m)
Distance (m) | Depth (m) | Value |  |  | Depth (m) | 1 | 2 | 3 | 4
1 | 1.11 | 0.72 |  |  | 1.11 | 0.72 | 8.58 | 2.98 | 3.98
1 | 1.36 | 1.89 |  |  | 1.36 | 1.89 | 9.32 | 6.9 | 4.25
1 | 1.61 | 7.54 |  |  | 1.61 | 7.54 | 11.96 | 10.67 | 3.24
1 | 1.86 | 3.72 |  |  | 1.86 | 3.72 | 7.48 | 14.41 | 2.95
2 | 1.11 | 8.58
2 | 1.36 | 9.32 |  |  | Can do minor editing
2 | 1.61 | 11.96
2 | 1.86 | 7.48
3 | 1.11 | 2.98
3 | 1.36 | 6.9
3 | 1.61 | 10.67
3 | 1.86 | 14.41
4 | 1.11 | 3.98
4 | 1.36 | 4.25
4 | 1.61 | 3.24
4 | 1.86 | 2.95
Spreadsheet: 107424d1304599166-need-formula-for-a-macro-function-example
Sheet: 15

1288
Name | Amount
Name 2 | 143
Name 2 | 174
Name 1 | 174
Name 3 | 143
Name 3 | 137
Name 3 | 116
Name 1 | 114
Name 1 | 103
Name 1 | 109
Name 3 | 119
Name 2 | 114
Name 2 | 124
Name 3 | 119
Name 3 | 168
Name 1 | 160
Name 2 | 198
Name 2 | 187
Name 3 | 194
Name 2 | 155
Name 1 | 151
Name 1 | 154
Name 1 | 141
Name 1 | 182
Name 2 | 162
Name 3 | 169
Spreadsheet: 09f64a8b-b58c-4687-8a87-8f175a4c2cb5
Sheet: Sheet1

Engineering Technology* | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
Associate of Applied Science Degree
Name |  |  | Student ID Number |  |  |  | Date Entered:
Address |  |  | Phone: |  |  |  | Proposed Graduation Date:
 |  |  | [NAME]:
 |  |  | Student Signature: |  |  |  |  | Date:
 |  |  | Advisor Signature: |  |  |  |  | Date:
 |  |  | Authorizing Signature: |  |  |  |  | Date:
Remedial Courses As Needed |  |  |  | Grade | Semester Taken
010 RDG + 12 DRE - Intro. to [NAME]
020 RDG + 101 GE - Improved College Reading
030 RDG + 101 GE (if not already completed)
090 ENC - Foundations of College Writing I
091 ENC - Foundations of College Writing II
055 MT - Pre-Algebra
065 MT - Elemtary Algebra
120 MT - Intermediate Algebra
General Education Courses (Core Curiculum) |  |  |  |  | Credit  Hours | Grade | Semester Taken | Note
ENG101 - Writing I |  |  |  |  | 3
Communications Course |  |  |  |  | 3
Mathematics Course (MT 150 or MT 125) |  |  |  |  | 3
Heritage/Humanities Course |  |  |  |  | 3
Social Science Course |  |  |  |  | 3
Physics Course (PHY 171 or higher level) |  |  |  |  | 3-4
Total Gen. [NAME]. Semester Hours |  |  |  |  | 18-19
Technical Core Courses |  |  |  |  | Credit  Hours | Grade | Semester Taken | Note
ENGT 110 | Circuits I |  |  |  | 5
ENGT 114 | Circuits II |  |  |  | 5
ENGT 210 | Devices I |  |  |  | 5
ENGT 120 | Digital Logic Circuits |  |  |  | 3
CAD 100 | Introduction to Computer Aided Design OR |  |  |  | 3
BRX 120 | Basic Blueprint Reading OR |  |  |  | 3
EET  148 | Electronic Drafting |  |  |  | 3
 | Computer Literacy Course |  |  |  | 3
ET 234 | Computer Hardware Maintenance OR |  |  |  | 3
ET 250 | Programmable Logic Controllers OR |  |  |  | 4
ET 256 | Microprocessors Fundamentals |  |  |  | 4
Total Technical Core Hours |  |  |  |  | 27-29
Mechanical Specialization Courses |  |  |  |  | Credit Hours | Grade | Semester Taken | Note
CHE 105 | General College Chemistry I |  |  |  | 3 |  |  | Technical Electives:
ET 201 | Statics and Strengths of Materials |  |  |  | 4 |  |  | ET 185
ET 210 | Thermodynamics Applications |  |  |  | 3 |  |  | ET 122
ET 264 | Mechanical Design |  |  |  | 4 |  |  | ET 290
Technical Electives - see program coordinator |  |  |  |  | 10 |  |  | ET 295
Total Specialization Hours |  |  |  |  | 24 |  |  | Courses under other
 |  |  |  |  |  |  |  | specializations
*This curriculum is to be followed by students entering this program beginning Fall 2005 or after.
Spreadsheet: 08cae973-a59a-40cd-8bd1-14481440a549
Sheet: 11d

Product | 0-3** | 3-6 | 6-12 | 12-24 | 24-60 | 60-120 | 120+ | TOTAL
Basis* |  | <100 | <100 | <100 | 226 | 206 | 180 | 612
FRA | 5560 | 5696 | 3384 | 4265 | <100 |  |  | 18905
IRS- [NAME] | <100 | 132 | 228 | 1566 | 6956 | 9763 | 11437 | 30082
OIS | 352 | 370 | 336 | 902 | 244 |  |  | 2204
VNS |  |  |  |  | <100 |  | <100 | <100
Zero Coupon | <100 |  | <100 | <100 | <100 | <100 | <100 | <100
TOTAL | 5912 | 6198 | 3948 | 6733 | 7426 | 9969 | 11617 | 51803
Estimated swap transaction volumes, January 18 weekly snapshot, by product type and tenor (millions of USD), all participant types and currencies.
Total(s) may be less than total shown for this asset class in the All Swaps reports and/or other CFTC Swaps Report tables if products were excluded from this table that (a) presented disclosure risk or (b) did not belong in the categories shown.
*See Data Dictionary for product descriptions.
**See Data Dictionary for tenor bucket descriptions.
***N/A indicates that data are not currently available.
Note: Transaction volumes currently include house and client trades by FCMs in the interest rate asset class.
The Commission requests feedback on the format and content of this CFTC Swaps Report table. Submit comments to [EMAIL].
Spreadsheet: 809521d1671125357-use-comma-separated-values-in-a-cell-as-source-for-lookups-iterateovercommaseperateddatainacell-1-
Sheet: Sheet1

Server | APPS |  |  | Expected result | Enhanced result | Enhanced result sorted by earliest date
S1 | app1 |  |  | 2021-12-10 00:00:00 | App1:10/12/21 | App1:10/12/21
[NAME] | app2,app10 |  |  | 17/03/2022, 10/12/21 | App2:17/03/2022, app10:10/12/21 | App10:10/12/21, App2:17/03/2022
S2
S6 | app6 |  |  | 2022-02-14 00:00:00 | App6:14/02/22 | App6:14/02/22
APPS | date
app1 | 2021-12-10 00:00:00 |  |  | Each server only appears once but and app can be on multiple servers.
app2 | 2022-03-17 00:00:00 |  |  | The removal date for an app is the same for all instances
app10 | 2021-12-10 00:00:00 |  |  | The server data will be on one worksheet and the app data on another
app6 | 2022-02-14 00:00:00 |  |  | Effectively I am looking for how to lookup things based on a previously textjoined list and possibly put in some extra data.
 |  |  |  | Office 365
Spreadsheet: e29af379-f527-47ff-8072-c2b34aedce61
Sheet: Revenues

Yes
No |  | Game Assumptions
 |  | CPI |  |  | 1.5
 |  | ARPDAU |  |  | 0.1
 |  | K-factor |  |  | 0.15
 |  | Monthly [NAME] |  |  | 5000
 |  | Monthly Acquisition Budget |  |  | 0
 |  | Net Revenue Reinvestment |  |  | 0.25
 |  | Publishing Agreement Assumptions
 |  | Publishing Agreement? |  |  | Yes
 |  | Revenue Split |  |  | 0.5
 |  | Acquisition spend per month |  |  | 20000
 |  | Revenue split until acquisition recoup |  |  | 0.8
 |  |  |  |  |  |  |  |  | Month 1 | Month 2 | Month 3 | Month 4 | Month 5 | Month 6 | Month 7 | Month 8 | Month 9 | Month 10 | Month 11 | Month 12
 |  |  | Total Acquisition Budget
 |  |  |  | From Developer Monthly Acquisition Budget
 |  |  |  | From Developer Reinvestment |  |  |  |  | 0
 |  |  |  | From Publisher
 |  |  | [NAME]
 |  |  | Organic Installs
 |  |  | Viral Installs
 |  |  | Total Users
 |  |  | Total Revenue
 |  |  | Total Expenses
 |  |  |  | Additional Expenses |  |  |  |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 |  |  | Total Revenue
 |  |  |  | Net of Expenses
 |  |  |  | Net of Platform Fee
 |  |  | Net of Publishing Agreement
 |  | 52-Week Total Revenue
 |  |  | Net of Expenses
 |  |  | Net of Platform Fees
 |  |  | Less half of net revenue | Net of Publishing Agreement
Spreadsheet: 807920d1670169699-mortgage-calculator-p-and-i-repayments-calculator-with-offset-account-loan-with-offset-acct
Sheet: Sheet1

 |  |  |  | regular loan |  |  |  |  | loan with offset account
loan | 300000 |  |  | pmt# | prin | int | end bal |  | pmt# | prin | int | end bal
term |  | months
int rate |  | monthly
loan pmt
offset bal | 20000
 |  |  |  |  |  |  | total int |  |  |  |  | total int
 |  |  |  |  |  |  |  |  |  |  |  | savings
Spreadsheet: 455999d1460591607-formula-to-combine-text-from-various-date-entries-manager-notebook
Sheet: Sheet1

Created By | Team | Date | Time Off Options | Hours missed/adjusted | Comments/Notes |  | Outcome Expected
[NAME] | Eligibility - In Training | 2016-04-08 00:00:00 | Special Projects | 0.75 | Indexing |  | 2016-04-04 00:00:00 | Indexing, QC, SOP Creation - Missing EDIs
[NAME] | Eligibility - In Training | 2016-04-07 00:00:00 | Special Projects | 0.75 | Indexing |  | 2016-04-05 00:00:00 | Indexing, QC
[NAME] | Eligibility - In Training | 2016-04-06 00:00:00 | Special Projects | 0.25 | Indexing |  | 2016-04-06 00:00:00 | Indexing, QC
[NAME] | Eligibility - In Training | 2016-04-06 00:00:00 | Special Projects | 4.00 | QC |  | 2016-04-07 00:00:00 | Indexing
[NAME] | Eligibility - In Training | 2016-04-05 00:00:00 | Special Projects | 0.25 | Indexing |  | 2016-04-08 00:00:00 | Indexing
[NAME] | Eligibility - In Training | 2016-04-05 00:00:00 | Special Projects | 4.00 | QC |  | ^^ Need a Formula that can combine the text with commas with all the notes that coincide with the date
[NAME] | Eligibility - In Training | 2016-04-04 00:00:00 | Special Projects | 0.25 | Indexing
[NAME] | Eligibility - In Training | 2016-04-04 00:00:00 | Special Projects | 2.00 | QC
[NAME] | Eligibility - In Training | 2016-04-04 00:00:00 | Manager Projects | 2.00 | SOP Creation - Missing EDIs
Spreadsheet: 804356d1668014285-sumif-and-vlookup-together-vlookup-and-sumif-help
Sheet: Bank

Bank |  |  |  |  |  | Lookup from GL
Type | Date | Ck# | Amount |  |  | Ck# | [NAME] | Amt | Src Code
Check | 2022-10-27 00:00:00 | 12345 | 644.56 | Debit |  |  | 0 | 0 | 0
Check | 2022-10-31 00:00:00 | 456 | 27900.64 | Debit |  |  | 0 | 0 | 0
Check | 2022-10-12 00:00:00 | 789 | 1399.98 | Debit |  |  | 0 | 0 | 0 | Why is the formula not returning the data from GL TAB from column A, B, C and D column?
Spreadsheet: 64349d1265217378-sumproduct-formula-not-working-sumproducthelp
Sheet: Sheet1

 | Date Received | Blue Cars | Red Cars | Yellow Cars | Total Cars |  |  |  | Jan | Feb
 | 2009-01-15 00:00:00 | 21 | 5 | 9 | 35 |  |  | Blue Cars Received
 | 2009-01-18 00:00:00 | 2 | 19 | 5 | 26 |  |  | Red Cars Received
 | 2009-01-30 00:00:00 | 15 | 20 | 0 | 35 |  |  | Yellow Cars Received
 | 2009-02-05 00:00:00 | 3 | 8 | 4 | 15
 | 2009-02-21 00:00:00 | 6 | 2 | 12 | 20
 |  |  |  |  |  | Question:  How is the best way to sum all blue, red, and yellow cars received in the month of January?
Spreadsheet: 77759d1278230484-excel-2007-lookup-across-multiple-sheets-forum-eample
Sheet: Main Sheet

Food Technology |  |  |  |  |  |  | Maths
Student ID Number | Surname | [NAME] | Exam Grade | Total Mark | Grade |  | Student ID | Surname | cwrk Grade | Exam Grade | Total Mark | Grade
1233 | A S M Shamshear |  |  |  |  |  | 1233 | A S M Shamshear
2444 | [NAME] |  |  |  |  |  | 2444 | [NAME]
Spreadsheet: 715169d1611591344-comparing-values-in-2-4-columns-example_formula
Sheet: Formula Jungle

Obs. 1 | Obs. 2 | Obs. 3 | Obs. 4 | if >1 apart |  |  |  |  | Obs. 1 | Obs. 2 | Obs. 3 | Obs. 4
1 | 2 | 3 | 3 |  | (1 and 3 are more than 1 apart) |  |  |  | 1 | 2 | 5 | 2
3 | 2 | 3 | 2 |  |  |  |  |  | 4 | 3 | 4
3 | 4 | 2 |  |  | <- without formula |  |  |  | 3 | 5 | 4 | 5 |  | <- Formula can be placed here :)
4 | 2 |  |  |  | (4 >1 apart from 2) |  |  |  | 2 | 4 | 3
5 | 4 |  |  |  |  |  |  |  | 4 | 3
 |  |  |  |  |  |  | 1. It does not have to be an exclamation point but some elegant way to signal, that the values are more than 1 value apart. 2. The table if possible should be dynamic so that if I have values for 2 then it will only look at those two, for 3 then all three, etc. 3. Reason being, that sometimes only 2 observations are recorded while other times I have 4. The values always range from 1-5.
My Attempt for 2 Columns:
1 | 2
4 | 3
2 | 4 |  | <- with formula
1 | 2
2 | 4
My bad Attempt for 3 Columns:
1 | 2 | 3
2 | 5 | 3
4 | 4 | 4 |  | <- with formula
2 | 4 | 2
3 | 4 | 3
Spreadsheet: 231316d1367005551-need-help-getting-started-on-a-hw-assignment-kjdeutinassign10
Sheet: countries

Country | Author
Albania | Kadare
Australia | Scott
Australia | [NAME]
Australia | [NAME]
Canada | [NAME]
Colombia | [NAME]
Cuba | [NAME]
Cuba | Somoza
Czechoslovakia | Hašek
Czechoslovakia | Monika
Dominican Republic | [NAME]
England | [NAME]
England | [NAME]
England | Christie
England | Dahl
England | Evaristo
England | Potter
England | [NAME]
England | Appiah
England | Mccoy
England | [NAME]
England | Hollinghurst
England | Phillips
England | [NAME]
France | [NAME]
Germany | Schatzing
Germany | Franck
Greece | [NAME]
Haiti | Cadet
Ireland | Welch
Ireland | Stack
Ireland | Trevor
Israel | Oz
Japan | Yamashita
North Wales | Bell
Russia | Brosgol
Scotland | Kelman
Serbia | Obreht
South Africa | Coetzee
Sweden | [NAME]
Trinidad | Naipaul