tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 99700d1298301160-a-list-of-days-by-date-to-the-end-of-the-next-month-then-the-list-turns-to-months-excel-file
Sheet: What I Would Like to See

2011-03-21 00:00:00
2011-03-21 00:00:00 | 2011-03-22 00:00:00 | 2011-03-23 00:00:00 | 2011-03-24 00:00:00 | 2011-03-25 00:00:00 | 2011-03-26 00:00:00 | 2011-03-27 00:00:00 | 2011-03-28 00:00:00 | 2011-03-29 00:00:00 | 2011-03-30 00:00:00 | 2011-03-31 00:00:00 | 2011-04-01 00:00:00 | 2011-04-02 00:00:00 | 2011-04-03 00:00:00 | 2011-04-04 00:00:00 | 2011-04-05 00:00:00 | 2011-04-06 00:00:00 | 2011-04-07 00:00:00 | 2011-04-08 00:00:00 | 2011-04-09 00:00:00 | 2011-04-10 00:00:00 | 2011-04-11 00:00:00 | 2011-04-12 00:00:00 | 2011-04-13 00:00:00 | 2011-04-14 00:00:00 | 2011-04-15 00:00:00 | 2011-04-16 00:00:00 | 2011-04-17 00:00:00 | 2011-04-18 00:00:00 | 2011-04-19 00:00:00 | 2011-04-20 00:00:00 | 2011-04-21 00:00:00 | 2011-04-22 00:00:00 | 2011-04-23 00:00:00 | 2011-04-24 00:00:00 | 2011-04-25 00:00:00 | 2011-04-26 00:00:00 | 2011-04-27 00:00:00 | 2011-04-28 00:00:00 | 2011-04-29 00:00:00 | 2011-04-30 00:00:00 | 2011-05-30 00:00:00 | 2011-06-29 00:00:00 | 2011-07-29 00:00:00 | 2011-08-28 00:00:00
Spreadsheet: 2c5696b3-4e32-428a-bb72-a607aee9d743
Sheet: Sheet1

Table 9--U.S. cotton textile exports, by destination | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
 | Oct. | Nov. | Dec. |  | Dec.
Region/country | 2012 | 2012 | 2012 |  | 2011
 | 1,000 pounds 1/
North America | 120071.334 | 112835.016 | 103380.355 |  | 87950.605
Bahamas | 98.368 | 161.439 | 57.859 |  | 98.627
Canada | 9679.422 | 9367.475 | 8358.346 |  | 9691.865
Costa Rica | 342.498 | 367.286 | 286.206 |  | 261.792
Dominican Republic | 20584.63 | 17776.751 | 18562.024 |  | 11010.487
El Salvador | 10278.917 | 10480.039 | 10688.493 |  | 9406.705
Guatemala | 2553.092 | 2136.458 | 2848.481 |  | 2088.943
Haiti | 760.656 | 613.142 | 798.881 |  | 375.105
Honduras | 46161.496 | 44932.29 | 37882.982 |  | 31956.136
Jamaica | 80.226 | 128.301 | 101.137 |  | 90.872
Mexico | 26662.816 | 24194.962 | 22000.268 |  | 21179.906
Nicaragua | 1931.183 | 2095.935 | 1463.009 |  | 1269.447
Panama | 345.54 | 153.012 | 137.605 |  | 262.625
South America | 3656.46 | 3206.975 | 2511.706 |  | 3225.197
Brazil | 463.066 | 425.806 | 361.374 |  | 715.862
Chile | 439.573 | 210.527 | 222.51 |  | 219.056
Colombia | 1456.87 | 1234.797 | 1128.324 |  | 1677.824
Peru | 383.755 | 498.989 | 222.155 |  | 178.089
Venezuela | 541.479 | 544.51 | 277.823 |  | 192.048
Europe | 2855.253 | 2883.105 | 3417.723 |  | 3261.747
Belgium | 209 | 353.987 | 334.63 |  | 470.046
France | 107.226 | 96.021 | 130.204 |  | 117.32
Germany | 475.489 | 286.109 | 472.819 |  | 601.336
Italy | 168.088 | 178.84 | 129.888 |  | 250.401
Netherlands | 394.127 | 354.607 | 533.971 |  | 311.247
Russia | 51.147 | 52.627 | 74.132 |  | 97.16
Turkey | 79.297 | 83.662 | 119.876 |  | 75.464
United Kingdom | 989.202 | 1029.687 | 1120.926 |  | 835.589
Asia | 12590.661 | 10109.917 | 10792.065 |  | 7657.762
Bangladesh | 7 | 30.61 | 20.944 |  | 0
China | 8898.187 | 7442.319 | 6930.867 |  | 3624.351
Hong Kong | 343.725 | 439.15 | 520.275 |  | 660.812
India | 162.409 | 130.338 | 135.783 |  | 162.194
Israel | 143.091 | 79.427 | 175.541 |  | 168.242
Japan | 843.813 | 717.875 | 1040.988 |  | 910.597
Pakistan | 61 | 5 | 35.828 |  | 47.079
Saudi Arabia | 140.761 | 96.528 | 101.335 |  | 145.446
Singapore | 283.04 | 158.496 | 183.751 |  | 150.603
South Korea | 426.993 | 306.026 | 488.719 |  | 672.779
Taiwan | 138.774 | 85.89 | 77.245 |  | 152.559
United Arab Emirates | 328.956 | 282.496 | 418.993 |  | 349.463
Oceania | 783.027 | 729.303 | 733.369 |  | 887.932
Australia | 632.442 | 584.553 | 532.78 |  | 771.751
Africa | 375.696 | 243.207 | 334.838 |  | 259.123
South Africa | 59.221 | 76.859 | 56.192 |  | 77.87
World 2/ | 140332.432 | 130007.524 | 121170.056 |  | 103289.754
1/ Raw-fiber equivalent.  2/ Totals may not add due to rounding.
Sources: USDA, Economic Research Service; and
U.S. Dept. of Commerce, U.S. Census Bureau.
Last update: 03/12/13.
Spreadsheet: darrell_schoolcraft__7818__imbalsumm0109
Sheet: Calpine

 | Calpine So. Point Power Del
 | 78113
Day | Measured | Scheduled
1 | -78239 | -85300
2 | -74222 | -85101
3 | -78756 | -71658
4 | -82484 | -65890
5 | -72415 | -62441
6 | -77980 | -71332
7 | -76345 | -81863
8 | -78285 | -81938
9 | -79383 | -81100
10 | -80612 | -80889
11 | -77102 | -79550
12 | -80401 | -81880
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
2001-08-31 00:00:00 |  |  | 81630
2001-09-12 00:00:00
CBS Volume
 |  |  | 130472
Spreadsheet: 216792d1361890475-use-several-cells-from-differnt-areas-as-one-row-or-column-book1
Sheet: Hárok1

numbers are  in various cells  from different areas
 | 12 | 5
 |  |  | 2 | -7 |  |  |  | Maybe just use [NAME]()?
wanted - one compact row formula
wanted - one compact column formula
another example - broken row |  |  | 12 | 34
 | 11 | 8
one-row formula:
another example - broken row |  |  |  | 34
 | 11 | 8
 |  |  |  |  | 9
 |  |  | 12
Spreadsheet: 123693d1317811511-day-of-week-calc-dayadder
Sheet: Sheet1

Sunday | 2012-01-01 00:00:00
Monday | 2012-01-02 00:00:00 |  |  |  |  | 1 | Sunday
Tuesday | 2012-01-03 00:00:00 |  |  |  |  | 2 | Monday
Wednesday | 2012-01-04 00:00:00 |  |  |  |  | 3 | Tuesday
Thursday | 2012-01-05 00:00:00 |  |  |  |  | 4 | Wednesday
Friday | 2012-01-06 00:00:00 |  |  |  |  | 5 | Thursday
Saturday | 2012-01-07 00:00:00 |  |  |  |  | 6 | Friday
Sunday | 2012-01-08 00:00:00 |  |  |  |  | 7 | Saturday
Monday | 2012-01-09 00:00:00
Tuesday | 2012-01-10 00:00:00
Wednesday | 2012-01-11 00:00:00
Thursday | 2012-01-12 00:00:00
Friday | 2012-01-13 00:00:00
Saturday | 2012-01-14 00:00:00
Sunday | 2012-01-15 00:00:00
Monday | 2012-01-16 00:00:00
Tuesday | 2012-01-17 00:00:00
Wednesday | 2012-01-18 00:00:00
Thursday | 2012-01-19 00:00:00
Friday | 2012-01-20 00:00:00
Saturday | 2012-01-21 00:00:00
Sunday | 2012-01-22 00:00:00
Monday | 2012-01-23 00:00:00
Tuesday | 2012-01-24 00:00:00
Wednesday | 2012-01-25 00:00:00
Thursday | 2012-01-26 00:00:00
Friday | 2012-01-27 00:00:00
Saturday | 2012-01-28 00:00:00
Sunday | 2012-01-29 00:00:00
Monday | 2012-01-30 00:00:00
Tuesday | 2012-01-31 00:00:00
sub-total
FEB
 | 2011-02-01 00:00:00
 | 2011-02-02 00:00:00
 | 2011-02-03 00:00:00
 | 2011-02-04 00:00:00
 | 2011-02-05 00:00:00
 | 2011-02-06 00:00:00
 | 2011-02-07 00:00:00
 | 2011-02-08 00:00:00
 | 2011-02-09 00:00:00
 | 2011-02-10 00:00:00
 | 2011-02-11 00:00:00
 | 2011-02-12 00:00:00
 | 2011-02-13 00:00:00
 | 2011-02-14 00:00:00
 | 2011-02-15 00:00:00
 | 2011-02-16 00:00:00
 | 2011-02-17 00:00:00
 | 2011-02-18 00:00:00
 | 2011-02-19 00:00:00
 | 2011-02-20 00:00:00
 | 2011-02-21 00:00:00
 | 2011-02-22 00:00:00
 | 2011-02-23 00:00:00
 | 2011-02-24 00:00:00
 | 2011-02-25 00:00:00
 | 2011-02-26 00:00:00
 | 2011-02-27 00:00:00
 | 2011-02-28 00:00:00
sub-total
[NAME]
Tuesday | 2011-03-01 00:00:00
Wednesday | 2011-03-02 00:00:00
Thursday | 2011-03-03 00:00:00
Friday | 2011-03-04 00:00:00
Spreadsheet: 220094d1363053092-sum-using-vlookup-adding-numbers-in-vlookup
Sheet: Sheet2

 | Data
 | [NAME] | No. Customers | Net Sales | Profit / Loss
 | [NAME] | 6 | 726 | 235.8774
 | [NAME] | 6 | 714 | 220.983
 | [NAME] | 7 | 1316 | 427.5684000000001
 | Jagjit | 7 | 1799 | 708.806
 | [NAME] | 8 | 1592 | 562.7719999999999
 | [NAME] | 8 | 1088 | 396.9024
 | [NAME] | 8 | 1680 | 752.64
 | [NAME] | 8 | 1624 | 621.3424
 | [NAME] | 9 | 2133 | 922.7357999999999
 | Javed | 9 | 2277 | 965.6756999999999
 | [NAME] | 9 | 2682 | 1023.183
 | [NAME] | 10 | 1610 | 579.1170000000001 |  | Questions | Your Answer
 | [NAME] | 10 | 1540 | 569.8 |  | What is the netsales for the persons who had 6 customers?
 |  |  |  |  |  |  | 1440
Spreadsheet: 742238d1627612776-trying-to-interpolate-a-table-help-please-curry-v2
Sheet: Sheet1

Altitude (1,000ft) | Weight (tonnes)
 | 85 | 80 | 75 | 70 | 65 | 60 | 55 | 50 | 45 | 40
41 |  |  |  |  | 30 | 7 | 0 | 4 | 16 | 33
 |  |  |  | 22 | 4 | 0 | 4 | 15 | 30 | 45
 |  | 37 | 14 | 2 | 0 | 5 | 15 | 28 | 43 | 56
 | 23 | 7 | 0 | 0 | 6 | 16 | 28 | 41 | 54 | 64
 | 2 | 0 | 2 | 8 | 18 | 29 | 41 | 53 | 62 | 68
 | 0 | 4 | 11 | 21 | 31 | 42 | 52 | 61 | 67 | 70
 | 7 | 15 | 24 | 34 | 43 | 53 | 61 | 67 | 70 | 70
 | 19 | 27 | 36 | 45 | 54 | 61 | 66 | 70 | 70 | 68
 | 31 | 40 | 48 | 55 | 62 | 67 | 70 | 70 | 69 | 64
 | Question
 | What value is obtained from the table for a aircraft weight of 58 tonnes at a altitude of 32,000ft?
 | Manual caluclation
 | - Interpolate between 60 & 55 tonnes for both 33,000 and 31,000ft.
 | - copying data from the table and interpolating for 58 tonnes on the x axis |  |  |  |  |  |  | How do I build a formula for these input fields
 |  | 60 | 55 | 58
 | 33 | 29 | 41 |  |  |  |  |  | Weight =
 | 31 | 42 | 52 |  |  |  |  |  | Altitude =
 | - now interpolating the 58 tonne data in the Y axis
 |  | 58 |  |  |  |  |  |  | Answer =
 | 33
 | 32
 | 31
 | - Answer is 42.1
Spreadsheet: 148384d1333380384-multi-worksheet-2-dimensional-lookups-help-appreciated-sample_slar
Sheet: April 2012

 |  |  |  |  | SLA's & Client Specific Notes
 | Month |  |  | April
 | Week |  |  | Week 1 |  |  |  |  |  |  | Week 2 |  |  |  |  |  |  | Week 3 |  |  |  |  |  |  | Week 4 |  |  |  |  |  |  | Week 5
 | Day |  |  | Monday | Tuesday | Wednesday | Thursday | Friday |  |  | Monday | Tuesday | Wednesday | Thursday | Friday |  |  | Monday | Tuesday | Wednesday | Thursday | Friday |  |  | Monday | Tuesday | Wednesday | Thursday | Friday |  |  | Monday | Tuesday | Wednesday | Thursday | Friday
Mailing Code | Date | Column1 | 01/04/2012 | 02/04/2012 | 03/04/2012 | 04/04/2012 | 05/04/2012 | 06/04/2012 | [NAME] | 08/04/2012 | 09/04/2012 | 10/04/2012 | 11/04/2012 | 12/04/2012 | 13/04/2012 | 14/04/2012 | 15/04/2012 | 16/04/2012 | 17/04/2012 | 18/04/2012 | 19/04/2012 | 20/04/2012 | 21/04/2012 | 22/04/2012 | 23/04/2012 | 24/04/2012 | [NAME] | 26/04/2012 | 27/04/2012 | 28/04/2012 | 29/04/2012 | 30/04/2012 | [NAME] | [NAME] | 03/05/2012 | 04/05/2012
BG36 |  |  |  | Text |  |  |  |  |  |  |  |  |  | Text
CH96 |  |  |  |  | Text | Agree Offers | Agree Contact Strategy | [NAME] |  |  |  | [NAME] | Order Source Codes |  |  |  |  |  |  | Text | Selections |  |  |  |  | Artwork Delivered | Data Cleanse | Data Coded | Text
CH97 |  |  |  | Text | Agree Offers | Agree Contact Strategy | Order Prospect Modelling Data | [NAME] by 10am |  |  | [NAME] |  |  |  |  |  |  |  |  |  | Order Source Codes |  |  |  | Artwork Delivered |  |  | Text | Selections |  |  |  | Data Cleanse | Data Code | Text
HH81 |  |  |  | Internal Strategy Meeting |  |  |  |  |  |  |  |  |  |  |  |  |  | Text | Agree Offers | Agree Contact Strategy |  | [NAME] |  |  |  | [NAME] |  |  | Order Source Codes |  |  |  |  |  | RFM Segmentation | Selections
BG37 |  |  |  |  |  |  |  |  |  |  | Internal Strategy Meeting |  |  |  |  |  |  |  |  |  |  | Text |  |  | Text |  |  | Text | Agree Contact Strategies |  |  |  | [NAME] |  | [NAME]
CH98 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Internal Strategy Meeting |  |  |  |  |  |  |  |  | Text | Text |  |  |  | [NAME] | Agree Contact Strategies |  | [NAME]
CH99 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Internal Strategy Meeting
Spreadsheet: 94932d1294685508-separate-comma-delimited-values-to-rows-example_data
Sheet: Source

ABC, ABC, ABC | TABLE_BUS_ORG, TABLE_CONTACT, TABLE_CONTACT | PHONE, X_BUSINESS_PHONE, X_HOME_PHONE | Address | T1 | C1
ABC, ABC, ABC | TABLE_BUS_ORG, TABLE_CONTACT, TABLE_CONTACT | PHONE, X_BUSINESS_PHONE, X_HOME_PHONE | Address | T1 | C2
DEF, ABC | EC_ADDRESS, TABLE_CONTACT | ADDR_TEL_EXTN, X_EXTENSION | Address | T1 | [NAME]
ABC, ABC | TABLE_CASE, TABLE_CASE | X_OTHER_SYS_TCK_ID, [NAME] | Call Centre | T2 | C1
XYZ | DIGITALTV | ENDTIME | Call Centre | T2 | C2
XYZ | VIEWAUDITLOGGING | TICKETID | Call Centre | T3 | C1
XYZ | VIEWAUDITLOGGING | TIMESTAMP | Call Centre | T3 | C2
Spreadsheet: 165368d1341201136-counting-number-of-people-by-time-schedule_need_count_people_by_hour
Sheet: Sheet1

 | mon |  |  |  | tues |  |  |  | wed |  |  |  | [NAME] |  |  |  | fri |  |  |  | sat |  |  |  | [NAME]
Calculated | Lunch |  | Dinner |  | Lunch |  | Dinner |  | Lunch |  | Dinner |  | Lunch |  | Dinner |  | Lunch |  | Dinner |  | Lunch |  | Dinner |  | Lunch |  | Dinner
 | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | In | Out | Total
a |  |  | 18:00:00 | 22:30:00 |  |  | 18:00:00 | 22:30:00 |  |  |  |  |  |  |  |  |  |  |  |  | 11:00:00 | 15:00:00
b | 09:00:00 | 15:00:00 |  |  | 09:00:00 | 15:00:00 |  |  | 09:00:00 | 15:00:00 |  |  | 09:00:00 | 16:00:00 |  |  | 09:00:00 | 16:00:00
c |  |  | 17:00:00 | 22:30:00 |  |  |  |  |  |  |  |  |  |  | 18:00:00 | 22:30:00 |  |  | 18:00:00 | 22:30:00 | 09:00:00 | 15:00:00
d |  |  |  |  |  |  | 17:00:00 | 22:30:00 |  |  | 17:00:00 | 22:30:00 |  |  | 17:00:00 | 22:30:00 |  |  | 17:00:00 | 22:30:00 |  |  | 17:00:00 | 22:30:00 | 09:00:00 | 16:00:00
e |  |  |  |  |  |  | 17:00:00 | 21:00:00 |  |  | 18:00:00 | 22:30:00 |  |  | 18:00:00 | 22:30:00 |  |  | 18:00:00 | 22:30:00 |  |  | 17:00:00 | 22:30:00
f
g | 12:00:00 | 17:00:00 |  |  |  |  | 15:00:00 | 22:30:00 | 09:00:00 | 15:00:00 |  |  | 09:00:00 | 15:00:00 |  |  |  |  | 17:00:00 | 22:30:00 | 09:00:00 | 16:00:00
h | 09:00:00 | 15:00:00 |  |  | 09:00:00 | 15:00:00 |  |  | 10:00:00 | 16:00:00 |  |  | 10:00:00 | 16:00:00 |  |  | 09:00:00 | 16:00:00 |  |  |  |  |  |  |  |  | 17:00:00 | 22:30:00
i |  |  |  |  | 10:00:00 | 16:00:00 |  |  |  |  |  |  |  |  | 16:00:00 | 21:00:00 |  |  | 18:00:00 | 22:30:00 | 10:00:00 | 15:00:00 |  |  |  |  | 17:00:00 | 22:30:00
 | Monday
07:00:00 | 0
08:00:00 | 0
09:00:00 | 2
09:30:00 | 2
10:00:00 | 2
10:30:00 | 2
11:00:00 | 2
12:00:00 | 3
13:00:00 | 3
14:00:00 | 3
15:00:00 | 1
16:00:00 | 1
17:00:00 | 1
18:00:00 | 2
19:00:00 | 2
20:00:00 | 2
21:00:00 | 2
22:00:00 | 2
22:30:00 | 0
23:00:00
Spreadsheet: 484888d1476541928-count-number-of-calls-between-dates-calls
Sheet: count

WK-1 | 2016-07-03 00:00:00
WK-2
WK-3
WK-4
WK-5
WK-6
WK-7
WK-8
WK-9
WK-10
WK-11
WK-12
WK-13
WK-14
WK-15
[NAME]
WK-17
WK-18
WK-19
WK-20
WK-21
WK-22
WK-23
WK-24
WK-25
WK-26
[NAME]
WK-28
WK-29
WK-30
WK-31
WK-32
WK-33
WK-34
WK-35
WK-36
WK-37
WK-38
WK-39
WK-40
WK-41
WK-42
WK-43
WK-44
WK-45
WK-46
WK-47
WK-48
WK-49
WK-50
WK-51
WK-52
Spreadsheet: 38314d1236441311-displaying-multiple-leaders-in-a-score-sheet-book2
Sheet: Sheet1

A Grade | HandiCap | Scratch Score | Net-Score
[NAME] | 5 | 65 | 60
[NAME] | 20 | 70 | 50
[NAME] | 17 | 117 | 100
[NAME] | 6 | 106 | 100
[NAME] | 7 | 69 | 62
Jhon | 6 | 77 | 71
[NAME] | 19 | 118 | 99
Trent
[NAME]
[NAME]
[NAME] | 5 | 65 | 60
Net Leader | [NAME]
Leading NetScore | 50
Scratch Leader | [NAME]
Leading Scratch Score | 65
Spreadsheet: 99451d1298060357-if-statement-calendar-issue
Sheet: Mapping table 

 |  | 2011-02-18 00:00:00 |  | February
 |  | 2011 |  |  |  |  |  | 1 | January | 1
 |  |  |  |  |  |  |  | 2 | February | 2
 |  |  |  |  |  |  |  | 3 | March | 3
 |  |  |  |  |  |  |  | 4 | April | 4
 |  |  |  |  |  |  |  | 5 | May | 5
 |  |  |  |  |  |  |  | 6 | June | 6
 |  |  |  |  |  |  |  | 7 | July | 7
 | 2012 | 8 | 8 | August |  |  |  | 8 | August | 8
 | 2012 | 7 | 7 | July |  |  |  | 9 | September | 9
 | 2012 | 6 | 6 | June |  |  |  | 10 | October | 10
 | 2012 | 5 | 5 | May |  |  |  | 11 | November | 11
 | 2012 | 4 | 4 | April |  |  |  | 12 | December | 12
2012 | 2012 | 3 | 3 | March
 | 2011 | 2 | 2 | February | February2011
 | 2011 | 1 | 1 | January | January2011
 | 2010 | 12 | 0 | December | December2010
 | 2010 | 11 | 11 | November | November2010
 | 2010 | 10 | 10 | October | October2010
 | 2010 | 9 | 9 | September | September2010
 | 2010 | 8 | 8 | August | August2010
 | 2010 | 7 | 7 | July | [NAME]
 | 2010 | 6 | 6 | June | [NAME]
 | 2010 | 5 | 5 | May | May2010
 | 2010 | 4 | 4 | April | April2010
 | 2010 | 3 | 3 | March | March2010
 | 2010 | 2 | 2 | February | February2010
Spreadsheet: mike_grigsby__27674__New_Gen_Sheet_ver2
Sheet: PIRA Summary

WSCC Capacity Additions (000 MW)
 |  | 1999-07-01 00:00:00 | 2000-07-01 00:00:00 | 2001-07-01 00:00:00
 |  | 2000-06-30 00:00:00 | 2001-06-30 00:00:00 | 2002-06-30 00:00:00
CA |  | 0 | 1.6 | 1.6
AZ/NM/NV |  | 0.6 | 1.1 | 0.7
RMPA |  | 0.4 | 0.3 | 0.6
[NAME] |  | 0 | 0.5 | 0.5
US
CFE |  | 0 | 0.5 | 0
BC |  | 0.1 | 0.2 | 0.1
AB |  | 0.8 | 0.3 | 0.2
Total
Available Resources (000 MW)
 | 1999-07-01 00:00:00 | 2000-07-01 00:00:00 | 2001-07-01 00:00:00 | 2002-07-01 00:00:00
CA | 54
AZ/NM/NV | 20.1
RMPA | 10.3
[NAME] | 46.4
WSCC US
CFE | 1.5
BC | 11.8
AB | 8
Total
Summer Peak Demand (000 MW)
 | 1999 | 2000 | 2001 | 2002
CA | 53 | 54.7 | 56 | 56.8
AZ/NM/NV | 20.5 | 21.4 | 22.2 | 22.9
RMPA | 8.1 | 8.4 | 8.7 | 8.9
[NAME] | 34 | 35 | 35.7 | 36.3
WSCC US
CFE | 1.5 | 1.6 | 1.7 | 1.8
BC | 7.5 | 7.7 | 7.9 | 8.1
AB | 6.8 | 7 | 7.2 | 7.4
Total
Average Energy Demand (000 MW)
 | 1999 | 2000 | 2001 | 2002
CA | 31.6 | 33.1 | 34.1 | 35
AZ/NM/NV | 11.8 | 12.4 | 12.9 | 13.3
RMPA | 5.5 | 5.8 | 6 | 6.2
[NAME] | 27.3 | 27.9 | 28.4 | 28.8
WSCC US
CFE | 0.8 | 0.9 | 1 | 1.1
BC | 6.8 | 7 | 7.2 | 7.4
AB | 5.8 | 6 | 6.2 | 6.4
Total
Spreadsheet: 26012d1217876506-column-total-contingent-upon-another-column-totals-exforum
Sheet: Sheet1

Qty | Cost | Total
1 | 10 | 10
2 | 10.01 | 20.02
3 | 10.02 | 30.06
4 | 10.03 | 40.12
5 | 10.04 | 50.2
6 | 10.05 | 60.3
7 | 10.06 | 70.42
8 | 10.07 | 80.56
9 | 10.08 | 90.72
10 | 10.09 | 100.9
11 | 10.1 | 111.1
12 | 10.11 | 121.32
13 | 10.12 | 131.56
14 | 10.13 | 141.82
15 | 10.14 | 152.1
16 | 10.15 | 162.4
Total |  | 1373.6
Spreadsheet: 98130c5b-3d59-40ab-abb0-028c585af7a6
Sheet: ER - Schedule 1

Kraft Foods Inc. and Subsidiaries
Condensed Consolidated Statements of Earnings
For the Three Months Ended March 31,
(in millions of dollars, except per share data)  ([NAME])
 |  |  | As Reported (GAAP)
 |  |  | 2011 |  | 2010 |  | % Change Fav / (Unfav)
Net revenues |  |  | 12573 |  | 11318 |  | 0.111
Cost of sales |  |  | 7937 |  | 7229 |  | -0.098
 | Gross profit |  | 4636 |  | 4089 |  | 0.134
 | Gross profit margin |  | 0.369 |  | 0.361
Selling, general and administrative expenses |  |  | 2933 |  | 2850 |  | -0.029
Amortization of intangibles |  |  | 57 |  | 33 |  | -0.727
 | Operating income |  | 1646 |  | 1206 |  | 0.365
 | Operating income margin |  | 0.131 |  | 0.107
Interest and other expense, net |  |  | 446 |  | 624 |  | 0.285
 | Earnings from continuing operations before income taxes |  | 1200 |  | 582 |  | 100.0+%
Provision for income taxes |  |  | 398 |  | 333 |  | -0.195
Effective tax rate |  |  | 0.332 |  | 0.572
 | Earnings from continuing operations |  | 802 |  | 249 |  | 100.0+%
Earnings from discontinued operations, net of income taxes |  |  | 0 |  | 48 |  | (100.0)%
Gain on divestiture of discontinued operations, net of income taxes |  |  | 0 |  | 1596 |  | (100.0)%
 | Net earnings |  | 802 |  | 1893 |  | -0.576
Noncontrolling interest |  |  | 3 |  | 10 |  | 0.7
 | Net earnings attributable to Kraft Foods |  | 799 |  | 1883 |  | -0.576
Per share data:
 | Basic earnings per share attributable to Kraft Foods:
 | -  Continuing operations |  | 0.46 |  | 0.15 |  | 100.0+%
 | -  Discontinued operations |  | 0 |  | 1.02 |  | (100.0)%
 | -  Net earnings attributable to Kraft Foods |  | 0.46 |  | 1.17 |  | -0.607
 | Diluted earnings per share attributable to Kraft Foods:
 | -  Continuing operations |  | 0.45 |  | 0.15 |  | 100.0+%
 | -  Discontinued operations |  | 0 |  | 1.01 |  | (100.0)%
 | -  Net earnings attributable to Kraft Foods |  | 0.45 |  | 1.16 |  | -0.612
Average shares outstanding:
 | Basic |  | 1754 |  | 1614 |  | -0.087
 | Diluted |  | 1760 |  | 1620 |  | -0.086
Spreadsheet: 91979d1291665542-display-only-blank-cells-book1
Sheet: Sheet1

7064753361 | 12 | Simpson,[NAME]
7064753361 | 18 | Jacobs, [NAME]
7064753361 | 28 | Jones, [NAME]
7064753361 | 14 | Sims, [NAME]
7064753362 | 2 | Franks, Harold
7064753362 | 5 | Bum, Lazy
7064753362 | 4 | [NAME], [NAME]
Spreadsheet: 763165d1642014088-combining-different-if-fuctions-based-on-multiple-criterias-in-different-tabs-example-pl-act-bud-ly-and-departments
Sheet: P&L

Month: | December
Department: | Department 1 |  |  |  |  |  |  |  |  |  |  |  |  |  | January | Department 1
 | MTD |  |  | YTD |  |  |  |  |  |  |  |  |  |  | February | Department 2
Category | Actual | Budget | 2020 | Actual | Budget | 2020 |  |  |  |  |  |  |  |  | March | Department 3
Revenue 1 |  |  |  |  | ? | ? |  |  |  |  |  |  |  |  | April
Revenue 2 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | May
Total revenue |  |  |  |  |  |  |  |  |  |  |  |  |  |  | June
Cost 1 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | July
Cost 2 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | August
Total costs |  |  |  |  |  |  |  |  |  |  |  |  |  |  | September
Profit |  |  |  |  |  |  |  |  |  |  |  |  |  |  | October
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | November
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | December
1. I want a formula that returns values based on Month (B1), Department (B2), Actual/Budget/2020 on MTD and YTD and the categories (A5,A6,A8 and A9). So when I change the month and department, the values in my MTD and YTD table will change according to this.
2. In this example I have created 3 departments in 3 different tabs with unique values in actual, budget and 2020 numbers (the set up is the same in all tabs).
3. In the D1,D2 and [NAME] tabs I have set different categories (column A in each tab).
4. The formulas I have put in this tab (P&L) in cell B5, C5 and D5 is the correct numbers, and somehow how I want it, but the problem is that if i change Month and Department in Cell B1 and B2, the whole table wont update.
5. I also have an issue figuring out how I can get the Year-to-date numbers based on Month and Department.
Spreadsheet: 726010d1617016940-how-to-categorize-using-multiple-currency-rate-multiple-currency-rev2
Sheet: Sheet2

Team | Request Ticket | Item | Category | Case code | Total Value | Currency | USD | Threshold
 | 12580243 | 10 | X |  | 15000 | USD
 | 17185628 | 10 | X |  | 100000 | USD
 | 55723648 | 40 | X |  | 2300000 | EUR
 | 51858337 | 30 | X |  | 1700 | USD
 | 11467077 | 10 | X |  | 70000 | [NAME]
 | 4420109 | 10 |  | ABC54656 | 170.14 | EUR
 | 11518185 | 10 |  |  | 2920 | AUD
 | 11518185 | 20 |  |  | 5920 | USD
 | 11467077 | 20 |  |  | 1000000 | [NAME]
 | 4420109 | 20 |  |  | 50000 | EUR
Spreadsheet: 217677d1362150320-creating-list-based-on-several-criteria-on-another-sheet-sal1check_new
Sheet: Sheet3

Sum of TOTAL HNA |  |  | year | month
 |  |  | 2012 |  |  |  |  |  |  |  |  |  |  |  | 2013 | Total Geral
PS BY JAN 2013 | O_code | O_Name | Jan | Feb | Mar | Apr | [NAME] | Jun | Jul | Agust | Sep | Okt | Nop | Des | Jan
DENI JULIANA SARAGI |  |  | 15996000 | 6751500 | 12277000 | 7400000 | 34658500 | 936000 | 16128000 | 10242000 | 15834000 | 8317000 | 6552500 | 3134000 | 5028000 | 143254500
HARLEN |  |  | 18735000 | 20645000 | 27900000 | 16340000 | 18930000 | 34685000 | 30170000 | 50580000 | 93110000 | 17720000 | 15820000 | 87880000 | 94870000 | 527385000
MANSON PP |  |  | 25833500 | 5202500 | 10487000 | 12571000 | 23288000 | 25273000 | 16232000 | 30158000 | 13028000 | 32445000 | 53533000 | 15470000 | 31126000 | 294647000
NELSY |  |  |  |  |  |  |  |  |  | 5814000 | 25299000 | 13116000 | 34235000 | 36114000 | 44043000 | 158621000
PUSPA SARI |  |  | 33624000 | 6262000 | 81564000 | 90735000 | 45396000 | 5184000 | 15732000 | 95184000 | 78004000 | 72475000 | 77834000 | 105606000 | 125189000 | 832789000
Total Geral |  |  | 94188500 | 38861000 | 132228000 | 127046000 | 122272500 | 66078000 | 78262000 | 191978000 | 225275000 | 144073000 | 187974500 | 248204000 | 300256000 | 1956696500