tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 884698d1733942690-search-and-identy-user-name-from-description-example-data
Sheet: Sheet1

Master data |  |  |  |  |  |  | Formulae to write here
Section | Division | Emp name |  | Section | Division | Description | Identify | Comments
ABC | 123 | Sunil |  | ABC | 123 | TP2018 [PHONE] [NAME] NOV23 7359.16 | [NAME]
ABC | 123 | [NAME] |  | ABC | 123 | Sunil Sustain charge for Application | Sunil
ABC | 123 | Dharshik |  | ABC | 123 | I  SWISS [PHONE] Divya DEC'23 | [NAME]
BCD | 234 | Rehanshi |  | ABC | 123 | Sunil. UK | Sunil
BCD | 234 | Vijaya |  | ABC | 123 | Dharshik UK | Dharshik | Dharshik is not part of L1 - ABC and CC - 123
BCD | 234 | Venki |  | ABC | 123 | Vijaya UK |  | Vijaya is not part of L1 - ABC and CC - 123
DCF | 345 | Divyaja |  | ABC | 123 | Divya UK | [NAME]
DCF | 345 | Sunita |  | ABC | 123 | Rehanshi Colombia |  | Rehanshi is not part of L1 - ABC and CC - 123
DCF | 345 | Sunit |  | ABC | 123 | M Vijaya |  | Vijaya is not part of L1 - ABC and CC - 123
 |  |  |  | BCD | 234 | I  DUBAI 12 Rehanshi DEC'23 | Rehanshi
 |  |  |  | BCD | 234 | I  AUS 24-01-US050A Vijaya JAN'24 | Vijaya
 |  |  |  | BCD | 234 | P01 2024 FLUS 3.2 Sunil |  | Sunil not part of L1 - BCD and CC 234
 |  |  |  | BCD | 234 | I  USA -VB0124NASS000 Venki | Venki
 |  |  |  | BCD | 234 | I  UK [PHONE] Divya DEC'23 | [NAME]
 |  |  |  | BCD | 234 | I  UK [PHONE] Dharshik DEC'23 |  | Dharshik is not part of L1 - BCD and CC - 234
 |  |  |  | DCF | 345 | I  UK [PHONE] Sunit JAN'24 | Sunit
 |  |  |  | DCF | 345 | I  UK [PHONE] Sunita JAN'24 | Sunita
 |  |  |  | DCF | 345 | I  Colombia 3003-1547 Vijaya JAN'24 |  | Vijaya is not part of L1 - DCF and CC - 345
 |  |  |  | DCF | 345 | I  UK [PHONE] Sunita DEC'23 | Sunita
 |  |  |  | DCF | 345 | I  Sunil JAN'24 |  | Sunil not part of L1 - DCF and CC 345
Spreadsheet: 770378d1646042190-calculate-how-many-days-people-have-from-start-date-until-end-date-from-month-to-month-enddate-aligw
Sheet: English (3)

September |  |  |  |  | Calculation date
 |  | Start date | End date |  | 2021-02-28 00:00:00 | I want to get | AliGW
 | Anne | 2021-01-01 00:00:00 |  |  |  | 30
 | Nina |  | 2021-09-30 00:00:00 |  |  | 30
 | [NAME] | 2021-03-01 00:00:00 | 2021-08-01 00:00:00 |  |  | 0
 | [NAME] | 2021-02-03 00:00:00 | 2021-10-31 00:00:00 |  |  | 28
 | [NAME] |  |  |  |  | 0
 | Sigrid | 2021-09-09 00:00:00 | 2021-11-30 00:00:00 |  |  | 0
 | [NAME] | 2019-03-31 00:00:00 | 2021-09-02 00:00:00 |  |  | 30
 | Heida | 2021-02-03 00:00:00 | 2021-02-18 00:00:00
 | Sandra | 2021-02-28 00:00:00 | 2021-12-31 00:00:00
 | Eva | 2022-11-03 00:00:00 |  |  |  | 0
Oktobere
 |  | Upphafsdagur | Lokadagur |  | 2021-10-31 00:00:00 | The correct answer would be
 | Anne | 2021-01-01 00:00:00 |  |  |  |  | [NAME]=MAX(MIN(IF(OR(D3="";AND(D3<=Calcul_9;D3-Calcul_9>30));30;-((Calcul_9-30)-D3));30);0)
 | Nina |  | 2021-09-30 00:00:00 | 0 |  |  | =MIN(30;MAX(0;1+MIN(Calcul_9;$D3)-MAX($C3;EOMONTH(Calcul_9;-1)+1))*SIGN(COUNT($C3:$D3)))
 | [NAME] | 2021-03-01 00:00:00 | 2021-08-01 00:00:00 | 0
 | [NAME] | 2021-08-07 00:00:00 | 2021-10-31 00:00:00 | 30 |  |  |  | 1. If a start date has started the take it in the calculation
 | [NAME] |  |  | 0 |  |  |  | 2. If neither [NAME] date nor End date is available  then =0
 | Sigrid | 2021-09-09 00:00:00 | 2021-11-30 00:00:00 | 30 |  |  |  | 3. If there is a Start date that has not started then =0
 | [NAME] | 2019-03-31 00:00:00 | 2021-09-02 00:00:00 | 0 |  |  |  | 4. If there is no [NAME] date but only End date then only consider End date
 | Heida | 2021-09-02 00:00:00 |  | 30
 | Sandra | 2021-10-03 00:00:00 | 2021-12-31 00:00:00 | 28
 | Eva | 2022-11-03 00:00:00 |  | 0
November
 |  | Upphafsdagur | Lokadagur |  | 2021-11-30 00:00:00 | The correct answer would be
 | Anne | 2021-01-01 00:00:00
 | Nina |  | 2021-09-30 00:00:00
 | [NAME] | 2021-03-01 00:00:00 | 2021-08-01 00:00:00
 | [NAME] | 2021-08-07 00:00:00 | 2021-10-31 00:00:00
 | [NAME]
 | Sigrid | 2021-09-09 00:00:00 | 2021-11-30 00:00:00
 | [NAME] | 2019-03-31 00:00:00 | 2021-09-02 00:00:00
 | Heida | 2021-09-02 00:00:00
 | Sandra | 2021-10-03 00:00:00 | 2021-12-31 00:00:00
 | Eva | 2021-11-03 00:00:00
Spreadsheet: sara_shackleton__36426__southern12
Sheet: Ticket

Paper/Pulp Deal Ticket
ERMS Deal Ticket Number: |  |  |  | EZ3059 | (to be completed by [NAME])
File: Southern9.xls
 |  | Month |  | Day |  | Year
Deal Date:
ECT B/S
ECT Trader |  |  |  |  | Other:
Counterparty |  |  |  |  |  |  | Other:
Counterparty Contact |  | [NAME] |  |  |  |  | Phone | [PHONE] |  |  | Fax | [PHONE]
Broker |  |  |  |  |  | Commission
Deal Type
Transaction Type |  |  |  |  | Other: |  |  |  |  |  | Linked trade
Option Style |  |  |  |  | Other:
 |  |  |  |  |  | Physical Prem |  |  |  | (ex: OCC11 - Official Board Markets)
Commodity |  |  |  |  |  | Storage
 |  |  |  |  |  | Other
 |  |  |  |  |  | Total
Pricing Reference | Commodity |  |  |  |  | Location |  | Low/High/Avg |  |  |  | Publication
Other:
Calculation Period |  |  |  |  |  |  | Payment/Settlement Date
 |  |  |  |  |  |  |  | Business Days After Price is Known
Other: |  |  |  |  |  | Note: | Provide for 90 day true-up provision instead of the 40 day in our ISDA.
Fall Back Pricing:
 | Commodity |  |  |  |  | Location |  | Low/High/Avg |  |  |  | Publication |  |  |  |  | Spread
Other:
Trade Terms |  |  |  |  |  |  |  |  |  |  |  |  |  | Conditional
 |  |  |  |  |  |  |  |  |  | Option only |  |  |  | Swap Only |  |  | Physical Only
Short/Metric | Monthly Vol. |  |  | Start Date |  | End Date |  | Fixed Price |  | Strike |  | Premium |  | [NAME] |  |  | Storage | Transport
 |  | 250 |  | 2000-04-01 00:00:00 |  | 2000-09-30 00:00:00 |  | 1020
Currency
Note:
Note:
Spreadsheet: 155038d1336658218-multiple-excel-sheets-into-one-with-different-cell-numbers-sampleworkbook2
Sheet: Sheet3

status | avail | dept | brand | [NAME] | decription | sub class | sub class name | capacity | cycles | color | E-star | exclusive | pedistals | stacking | hoses | upgrade | vent | attach
CLR | In Store | 50 | Samsung | 10142009 | WF350ANR Steam | Washer | Front Load Full Size | 4.3 | 12 | Red | Y - Tier 3 | No |  |  | na | 10154208 | NA | 10099456
CLR | In Store | 51 | Samsung | 10142010 | DV350AER Steam | Dryer | Front Load Full Size | 7.3 | 9 | Red | NA | No |  |  | na | na | 10063889 | NA
CLR | In Store | 58 | Samsung | 10088622 | WE357A7R | Pedestal | Accessory | NA | NA | Red | NA | No | na | na | na | na | NA | NA
CLR | In Store | 58 | Samsung | 10160725 | WE357A0R | Pedestal | Accessory | NA | NA | Red | NA | No | na | na | na | na | NA | NA
ACTIVE | [NAME] | 50 | Samsung | 10142013 | WF350ANG Steam | Washer | Front Load Full Size | 4.3 | 12 | Grey | Y - Tier 3 | No |  |  | na | 10154208 | NA | 10099456
ACTIVE | [NAME] | 51 | Samsung | 10142011 | DV350AEG Steam | Dryer | Front Load Full Size | 7.3 | 9 | Grey | NA | No |  |  | na | na | 10063889 | NA
ACTIVE | In Store | 58 | Samsung | 10160920 | WE357A0G/XAC | Pedestal | Accessory | NA | NA | Red | NA | No | na | na | na | na | NA | NA
ACTIVE | In Store | 58 | Samsung | 10110309 | SK-5A | Stacking Kit | Accessory | NA | NA | Chrome | NA | No | na | na | na | na | NA | NA
ACTIVE | In Store | 50 | Samsung | 10171314 | WF350ANP Steam | Washer | Front Load Full Size | 4.3 | 12 | Platinum | Y - Tier 3 | No |  |  | na | 10154208 | NA | 10099456
ACTIVE | In Store | 51 | Samsung | 10171318 | DV350AEP Steam | Dryer | Front Load Full Size | 7.3 | 9 | Platinum | NA | No |  |  | na | na | 10063889 | NA
ACTIVE | [NAME] | 58 | Samsung | 10160723 | WE357A0P | Pedestal | Accessory | NA | NA | Platinum | NA | No | na | na | na | na | NA | NA
Spreadsheet: 145490d1331614255-average-if-book1
Sheet: Sheet1

my data looks like below and I have like this 2500 rows
Type | Area | Rent
1 Bed | New York | 200
2 Bed | Delhi | 100
3 Bed | New York | 500
4 Bed | Delhi | 300
2 Bed | Tokyo | 150
1 Bed | Delhi | 80
4 Bed | Tokyo | 300
1 Bed | New York | 175
2 Bed | Delhi | 125
below is what I'm looking for
Average Rent | 1 Bed | 2 Bed | 3 Bed | 4 Bed
New York
Delhi
Tokyo
Maximum Rent | 1 Bed | 2 Bed | 3 Bed | 4 Bed
New York
Delhi
Tokyo
Minimum Rent | 1 Bed | 2 Bed | 3 Bed | 4 Bed
New York
Delhi
Tokyo
Spreadsheet: 168911d1342628261-cell-automation-sheet-1-
Sheet: Sheet1

 |  |  | 1 |  |  |  |  |  |  |  | 2
 |  |  | DATE | ITEM | PRIZE |  |  |  |  |  | DATE | ITEM | PRIZE
 |  |  | 2012-07-21 00:00:00 | chettigari | 4 |  |  |  |  |  | 2012-07-21 00:00:00 | chettigari | 4
 |  |  | 2012-07-20 00:00:00 | Deepakaaa | 3
 |  |  | 2012-07-20 00:00:00 | Gunturu | 1
 |  |  | 2012-07-20 00:00:00 | ABC | 2
Spreadsheet: 834087d1687439147-formula-to-create-a-automating-a-template-from-a-data-set-in-a-second-sheet-sample-book-2
Sheet: Upload

 |  |  |  | Date | Nominal Code | Amount
 |  |  |  |  |  |  |  |  | 7500 | 7.983333333333333
 |  |  |  |  |  |  |  | 2023-05-17 00:00:00 | 2300 | 1.596666666666667
 |  |  |  |  |  |  |  | 2023-05-17 00:00:00 | 7502 | 40
 |  |  |  |  |  |  |  | 2023-05-17 00:00:00 | 2300 | 8
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 6900 | 8.333333333333334
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 2300 | 1.666666666666666
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7500 | 69.4
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7403 | 49.66666666666667
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 2300 | 9.93333333333333
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7300 | -100
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 2300 | -20
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7401 | 100
` |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7403 | 49.67
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 2300 | 9.93
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7200 | 100
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7405 | 49.67
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 2300 | 9.93
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7200 | 100
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 7405 | 41.66666666666667
 |  |  |  |  |  |  |  | 2023-05-18 00:00:00 | 2300 | 8.333333333333329
Spreadsheet: 71524d1272299841-excel-2007-sorting-rows-of-data-into-one-column-example2
Sheet: Sheet1

Data now…
X | Y | P0110 | P0210 | P0310 | P0410 | P0510 | P0610 | P0710 | P0810 | P0910 | P1010 | P1110 | P1210
410 | 590000 | 8541 | 8541 | 8541 | 50 | 8541 | 8541 | 40 | 8541 | 50 | 8541 | 8541 | 8541
410 | 591000 | 4401 | 30 | 4401 | 4401 | 33 | 4401 | 4401 | 51 | 4401 | 4401 | 85 | 4401
410 | 590001
410 | 591001
410 | 593000
410 | 594000
410 | 595000
410 | 599000
410 | 601000 | 45 | 5 | 5 | 65 | 57 | 23 | 55 | 5554 | 11 | 5554 | 85 | 85
410 | 601500 | 497 | 529 | 629 | 550 | 517 | 654 | 517 | 517 | 654 | 550 | 550 | 589
410 | 602000
410 | 603000
410 | 603001
410 | 603009
410 | 604000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
410 | 604001 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
410 | 604009 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
410 | 605000
410 | 606000
410 | 606001 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Need….
410 | 590000 | P0110 | 8541
410 | 590000 | P0210 | 8541
410 | 590000 | P0310 | 8541
410 | 590000 | P0410 | 50
410 | 590000 | P0510 | 8541
410 | 590000 | P0610 | 8541
410 | 590000 | P0710 | 40
410 | 590000 | P0810 | 8541
410 | 590000 | P0910 | 50
410 | 590000 | P1010 | 8541
410 | 590000 | P1110 | 8541
410 | 590000 | P1210 | 8541
410 | 591000 | P0110 | 4401
410 | 591000 | P0210 | 30
410 | 591000 | P0310 | 4401
410 | 591000 | P0410 | 4401
410 | 591000 | P0510 | 33
410 | 591000 | P0610 | 4401
410 | 591000 | P0710 | 4401
410 | 591000 | P0810 | 51
410 | 591000 | P0910 | 4401
410 | 591000 | P1010 | 4401
410 | 591000 | P1110 | 85
410 | 591000 | P1210 | 4401
410 | 590001 | P0110
410 | 590001 | P0210
410 | 590001 | P0310
410 | 590001 | P0410
410 | 590001 | P0510
410 | 590001 | P0610
410 | 590001 | P0710
410 | 590001 | P0810
410 | 590001 | P0910
410 | 590001 | P1010
410 | 590001 | P1110
410 | 590001 | P1210
So on, and so on…..Need blanks to show as well
Spreadsheet: 860779d1708772923-how-can-we-bring-max-and-second-max-values-to-mixed-table-on-different-sheet-example-data-v4-ans
Sheet: Data

Product Code | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15
a123 | 139 | 24 | 101 | 75 | 13 | 20 | 142 | 147 | 25 | 141 | 242 | 227 | 145 | 219 | 42
a124 | 214 | 191 | 206 | 163 | 95 | 219 | 184 | 179 | 39 | 123 | 166 | 168 | 244 | 79 | 114
a125 | 129 | 194 | 28 | 155 | 190 | 183 | 43 | 74 | 224 | 112 | 188 | 84 | 117 | 97 | 104
a126 | 229 | 57 | 103 | 78 | 65 | 166 | 174 | 169 | 235 | 51 | 85 | 132 | 19 | 173 | 166
a127 | 243 | 29 | 52 | 44 | 20 | 193 | 86 | 190 | 178 | 96 | 42 | 223 | 47 | 100 | 155
a128 | 48 | 207 | 13 | 111 | 96 | 40 | 154 | 140 | 140 | 156 | 159 | 102 | 112 | 67 | 168
a129 | 86 | 29 | 243 | 227 | 25 | 111 | 105 | 74 | 50 | 94 | 232 | 96 | 90 | 82 | 115
a130 | 162 | 90 | 59 | 193 | 173 | 115 | 52 | 240 | 250 | 138 | 161 | 148 | 54 | 35 | 99
Spreadsheet: 864800d1711949502-from-static-to-dynamic-cell-reference-via-indirect-function-raw-materials-record-aligw
Sheet: SBO

Raw Material |  | SBO
Date | Description | Batch Processed Quantity |  | Quantity Stored ([NAME]'s) | Quantity Issued ([NAME]'s) | Total Quantity Remaining ([NAME]'s) | Bilty or Batch (Description)
 |  | Qty | [NAME]'s
Column1 | Column2 | Column3 | Column4 | Column5 | Column6 | Column7 | Column8
2023-09-30 00:00:00 |  |  |  |  |  | 722
Total
Spreadsheet: 850291d1700660991-help-with-vlookup-from-2-columns-to-2-columns-if-possible-excel-workbook-help
Sheet: Formulas

NAME | NUMBER
Abby A | 70244
[NAME] | 71444
[NAME] | 5915
[NAME] | 70289
[NAME] | 76873
[NAME] | 76881
[NAME] | 12279
[NAME] | 3184
[NAME] | 12292
[NAME] | 10343
[NAME] | 2618
[NAME] R | 12215
[NAME] | 25641
[NAME] | 73078
Spreadsheet: 17cbb32e-ec8c-4f2e-84a8-3a1c20adbec4
Sheet: Sheet1

OPERATING/PROGRAMMATIC | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11
Legislative Fiscal Note |  |  |  |  |  |  | Ordinance Number
Ordinance Title (in Brief)
 | VariousTraffic Signal Modifications
 | [NAME]
Does this Legislation Estimate New or Additional Revenues to the City? |  |  |  |  |  |  |  | No |  | x | Yes
 | If yes, please identify in  which Fund these revenues will be deposited (e.g. General, Sales Tax) |  |  |  |  |  |  |  |  |  | General
 | and provide the following revenue information:
 | Revenue Detail |  |  |  | FY 2004-05 |  |  | FY 2005-06
 | General Fund |  |  |  | 599800 |  |  | 0
 | Special Revenue
 | Enterprise
 |  |  | Total: | $ | 599800 |  | $ | 0
 | (Please detail type of revenue (fees, grants, tax) and change that will occur as a result of this legislation.  Provide multi-year
 | estimates if known, or if grant revenue please identify source of funds (federal or state) and duration of grant support)
Does this Legislation increase appropriations in the current budget? |  |  |  |  |  |  |  | No |  | x | Yes
 | If Yes, please complete the following budget information:
 | Expense Detail |  |  |  | FY 2004-05 |  |  | FY 2005-06
 | General Fund |  |  |  | 599800 |  |  | 0
 | Special Revenue
 | Enterprise/Other
 |  |  | Total: | $ | 599800 |  | $ | 0
 | Please detail the extent to which these increased appropriations will be of a permanent nature (e.g. number of
 | additional staff, facilities, long-term contracts)
Does this Legislation expand the scope of current city services? |  |  |  |  |  |  | x | No |  |  | Yes
 | (Please detail estimate number of people to be served, who is delivering services currently to that population, service
 | performance expectations, and if grant supported, provisions for support if grant support ends.
Is this legislation the result of a federal or state legislative mandate? |  |  |  |  |  |  | x | No |  |  | Yes
 | (If yes, please detail the purpose and source for that mandate).
Reviewed by:
 | 0ffice of Management and Budget |  |  | OMB Approval Date
Spreadsheet: 845341d1696872515-advice-on-sumifs-with-choosecol-looking-for-ways-to-shorten-my-formula-sumifs-choosecol
Sheet: Sheet2

Received Pocket | Header 1 | Code | Type | [NAME] | Currency | Value USD
YYY | Useless info | Useless info | Deposit | Useless info | RMB | 2000
[NAME] | Useless info | Useless info | Withdraw | Useless info | [NAME] | 10000
[NAME] | Useless info | Useless info | Deposit | Useless info | [NAME] | 10000
YYY | Useless info | Useless info | Deposit | Useless info | USD | 5000
[NAME] | Useless info | Useless info | Withdraw | Useless info | USD | 10000
AAA | Useless info | Useless info | Withdraw | Useless info | RMB | 1000
WWW | Useless info | Useless info | Withdraw | Useless info | IND | 20000
WWW | Useless info | Useless info | Withdraw | Useless info | EUR | 3000
WWW | Useless info | Useless info | Deposit | Useless info | EUR | 10000
WWW | Useless info | Useless info | Deposit | Useless info | EUR | 20000
AAA | Useless info | Useless info | Withdraw | Useless info | [NAME] | 1000
AAA | Useless info | Useless info | Withdraw | Useless info | CNY | 500
AAA | Useless info | Useless info | Withdraw | Useless info | USD | 900
AAA | Useless info | Useless info | Deposit | Useless info | [NAME] | 9000
YYY | Useless info | Useless info | Deposit | Useless info | IND | 10000
My formula as below
LET(x,UNIQUE(SORT(CHOOSECOLS(Table1,1,4,6),1,1)),HSTACK(x,SUMIFS(Table1[Value USD],Table1[Received Pocket],CHOOSECOLS(x,1),Table1[Type],CHOOSECOLS(x,2),Table1[Currency],CHOOSECOLS(x,3))))
Question, is there a way to write the Red Portion in a shorter way? It work but somehow I don't think it’s the best way
Also, how do I make it if its Withdraw, then negative while Deposit is positive?
Received Pocket | Type | Currency | Value USD
 | Withdraw | RMB | 1000
AAA | Withdraw | [NAME] | 1000
AAA | Withdraw | CNY | 500
AAA | Withdraw | USD | 900
AAA | Deposit | [NAME] | 9000
WWW | Withdraw | IND | 20000
WWW | Withdraw | EUR | 3000
WWW | Deposit | EUR | 30000
[NAME] | Withdraw | [NAME] | 10000
[NAME] | Deposit | [NAME] | 10000
[NAME] | Withdraw | USD | 10000
YYY | Deposit | RMB | 2000
YYY | Deposit | USD | 5000
YYY | Deposit | IND | 10000
Spreadsheet: 0b96aac2-f1d3-4282-bd5a-79db5a58dd04
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11
 | Time Series Workbook
 | 6202.0 Labour Force, Australia
 | Table 10. Labour force status by Sex - Northern Territory - Trend and Original
Related Information: | Summary Publication | Explanatory Notes | Inquiries
Data Item Description |  |  | Series Type | Series ID | Series Start | Series End | No. Obs. | Unit | Data Type | [NAME]. | Collection Month
Employed - full-time ;  [NAME] ; |  |  | Trend | A184131L | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Employed - full-time ;  Females ; |  |  | Trend | A184148J | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Employed - full-time ;  Persons ; |  |  | Trend | A184165K | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Employed - total ;  [NAME] ; |  |  | Trend | A184133T | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Employed - total ;  Females ; |  |  | Trend | A184150V | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Employed - total ;  Persons ; |  |  | Trend | [NAME] | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Unemployed - total ;  [NAME] ; |  |  | Trend | A184136X | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Unemployed - total ;  Females ; |  |  | Trend | A184153A | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Unemployed - total ;  Persons ; |  |  | Trend | A184170C | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Unemployment rate ;  [NAME] ; |  |  | Trend | A184143W | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | Percent | PERCENT | Month | 1
Unemployment rate ;  Females ; |  |  | Trend | A184160X | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | Percent | PERCENT | Month | 1
Unemployment rate ;  Persons ; |  |  | Trend | A184177V | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | Percent | PERCENT | Month | 1
Participation rate ;  [NAME] ; |  |  | Trend | A184142V | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | Percent | PERCENT | Month | 1
Participation rate ;  Females ; |  |  | Trend | A184159R | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | Percent | PERCENT | Month | 1
Participation rate ;  Persons ; |  |  | Trend | A184176T | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | Percent | PERCENT | Month | 1
Civilian population ;  [NAME] ; |  |  | Original | A163486J | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Civilian population ;  Females ; |  |  | Original | A163503X | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
Civilian population ;  Persons ; |  |  | Original | A163520A | 1978-02-01 00:00:00 | 2013-01-01 00:00:00 | 420 | 000 | STOCK | Month | 1
© Commonwealth of Australia  2013
Spreadsheet: 814749d1674574690-need-help-in-excel-formulae-book3
Sheet: Sheet1

Counter | Exp In
0 | 14
0 | 16
0 | 0
0 | 17
0 | 16
0 | 15
0 | 14
1 | -4
2 | -3
3 | 2
4 | 1
5 | 78
6 | -79
Spreadsheet: 773202d1647689002-budget-account-formula-required-if-possible-budget-table
Sheet: Account 2

Year | Month | Date | Description | Category | Income | Debits | Balance
 |  | 2019-02-01 00:00:00 | Opening Balance |  | 1000 |  | 1000
 |  | 2019-02-02 00:00:00 | Gas [NAME] (Waiting on new card) | Utilities |  | 150
 |  | 2019-02-03 00:00:00 | Shopping | Food & Drinks |  | 100
 |  | 2019-02-05 00:00:00 | Fuel | Transport
 |  | 2019-02-06 00:00:00 | Transfer | Account 1 |  | 100
 |  | 2019-02-06 00:00:00 | [NAME] | Entertainment |  | 120
 |  | 2019-03-01 00:00:00 | Weekend Away | Spendings |  | 260
 |  | 2019-03-05 00:00:00 | Transfer | Account 1 |  | 50
 |  | 2019-03-07 00:00:00 | Coffee | Food & Drinks |  | 6
 |  | 2019-03-08 00:00:00 | Dinner | Food & Drinks |  | 36
Spreadsheet: benjamin_rogers__1034__Shortlist2
Sheet: NRG NE Facilities-Project

NRG NORTHEAST FACILITIES
Summary of Projects:
Operation (North America, Northeast)
 | Plants | Location | MW | Fuel | Technology/Type | Grid | Ownership | Partner | Power Purchaser | Net
1 | [NAME]: Conemaugh | New Florence, PA | 1711 | Coal, gas, oil | Steam | WPJM | 0.0755113968439509
2 | [NAME]: [NAME] | Shelocta, PA | 1711 | Coal, oil | Steam | WPJM | 0.06171829339567504
3 | Oswego (2 units) | Oswego, NY | 1700 | Oil, natural gas | 2 Steam (unit 5,6) | NYPP | 1 |  | [NAME] 4 yr contract
4 | Middletown | Middletown, CT | 856.2 | Natural gas, oil, jet | 3 Steam/1 Gas Turbine | NEPOOL | 1 | Bilateral contracts, NEPOOL
5 | [NAME] (3 units) | Staten Island, NY | 842 | Gas/oil | 2 Steam Turbines(unit 2,3)/ 1Combustion | NYPP, NYC | 1 |  | Consolidated Edison 2 yr contract
6 | [NAME]: Indian River | Millsboro, DE | 784 | Coal, oil | Steam/Gas | EPJM | 1
7 | Huntley | Buffalo, NY | 760 | Bituminous coal | 6 Steam Units | NYPP | 1 |  | [NAME] 4 yr contract
8 | Astoria Gas Turbines (20 units) | Queens, NY | 614 | Gas/kerosene/oil | Combustion | NYPP, NYC | 1 |  | [NAME] 2 yr contract
9 | Dunkirk (4 units) | Dunkirk, NY | 600 | Bituminous coal | 4 Steam Units | NYPP | 1 |  | 4 yr contract
10 | Montville | Uncasville, CT | 497.6 | Natural gas, oil, diesel | 2 Steam (unit1,2) /1 Diesel engine (unit 10,11) | NEPOOL | 1 | Bilateral contracts, NEPOOL
11 | [NAME]: BL England | Mamora, NJ | 447 | Coal, oil, TDF | Steam | EPJM | 1
12 | [NAME] | Milford, CT | 400.5 | Natural gas, oil, jet fuel | 2 Steam/5 Combustion-gas GE LM6000 in '96 | NEPOOL | 1 | Bilateral contracts, NEPOOL
13 | Norwalk Harbor | S. Norwalk, CT | 353 | Oil | 2 Steam (unit 1,2)/Gas Turbine (unit 10) | NEPOOL | 1 | Bilateral contracts, NEPOOL
14 | [NAME]: Deepwater | Pensville, NJ | 239 | Coal, gas, oil | Steam/Jet Eng | EPJM | 1
15 | Somerset (4 units) | Somerset, Mass | 229 | Bituminous coal, gas oil, jet fuel | 1 Steam (unit 6), [NAME] (J-1,J-2) | NEPOOL | 1 |  | Eastern Utilities & NEPOOL
16 | [NAME]: Vienna | Vienna,MD | 170 | Oil | Steam/Gas | EPJM | 1
17 | Connecticut Jet Power | Branford, CT | 110 | Oil | 7 Combustion | NEPOOL | 1