tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 89554d1289337910-dependent-percentile-formula-in-table-with-nested-lookup-or-index-match-benchmark-help2
Sheet: Sheet3

 | Benchmark Calculator
 |  | 1 - select industry:
 |  | Engineering and Construction
 |  | 2 - select sub-industry
 |  | BUILDING CONSTRUCTION-GENERAL CONTRACTORS AND OPERATIVE BUILDERS
 |  | benchmark results
 |  | No. | Benchmark | Format | 1st Quartile | Average | 4th Quartile
 |  | 1 | Revenue per Employee | In Thousands of $
 |  | 2 | Revenue Growth | Percentage of Year/Year growth
 |  | 3 | Cost of Goods Sold | As a % of Revenue
 |  | 4 | Selling, General, and [NAME] (SG&A) | As a % of Revenue
 |  | 5 | Days Sales Outstanding (DSO) | No. of days
 |  | 6 | Days in Inventory (DII) | No. of days
 |  | 7 | Days Payable Outstanding (DPO) | No. of days
 |  | 8 | Operating Profit | As a % of Revenue
 |  | 9 | Return on Capital (ROIC) | As a % of Return
 |  | 10 | Operational Profit per Employee | In Thousands of $
Spreadsheet: 686929d1594879808-dertemine-which-months-there-are-between-two-dates-example
Sheet: Sheet1

Begindatum | Einddatum
2019-03-01 00:00:00 | 2020-04-01 00:00:00
2019-03-01 00:00:00 | 2020-04-02 00:00:00
2019-03-01 00:00:00 | 2020-04-03 00:00:00
2020-04-01 00:00:00 | 2020-04-04 00:00:00
2020-04-01 00:00:00 | 2020-04-05 00:00:00
2020-04-01 00:00:00 | 2020-04-06 00:00:00
2020-05-01 00:00:00 | 2020-07-01 00:00:00
2020-05-01 00:00:00 | 2020-08-01 00:00:00
2020-06-01 00:00:00 | 2020-10-09 00:00:00
2020-06-02 00:00:00 | 2020-10-10 00:00:00
2020-06-03 00:00:00 | 2020-10-11 00:00:00
2020-08-01 00:00:00 | 2020-10-12 00:00:00
2020-08-01 00:00:00 | 2020-10-13 00:00:00
2020-10-01 00:00:00 | 2020-10-14 00:00:00
2020-10-01 00:00:00 | 2020-10-15 00:00:00
2020-10-01 00:00:00 | 2020-10-16 00:00:00
2020-10-01 00:00:00 | 2020-10-17 00:00:00
2020-10-01 00:00:00 | 2020-10-18 00:00:00
2020-11-01 00:00:00 | 2020-12-01 00:00:00
2020-11-01 00:00:00 | 2020-12-02 00:00:00
2020-11-01 00:00:00 | 2020-12-03 00:00:00
2020-12-01 00:00:00 | 2020-12-04 00:00:00
2020-11-01 00:00:00 | 2020-12-05 00:00:00
2020-01-01 00:00:00 | 2020-01-02 00:00:00
2020-01-01 00:00:00 | 2020-01-03 00:00:00
2020-01-01 00:00:00 | 2020-01-08 00:00:00
2020-01-01 00:00:00 | 2020-01-10 00:00:00
2020-01-01 00:00:00 | 2020-02-09 00:00:00
2019-02-01 00:00:00 | 2020-02-10 00:00:00
2019-02-01 00:00:00 | 2020-02-11 00:00:00
2019-02-01 00:00:00 | 2020-02-12 00:00:00
2019-03-01 00:00:00 | 2020-03-12 00:00:00
2020-04-01 00:00:00 | 2020-04-03 00:00:00
2020-05-01 00:00:00 | 2020-05-01 00:00:00
2019-02-01 00:00:00 | 2020-06-05 00:00:00
2020-02-01 00:00:00 | 2020-06-05 00:00:00
2020-02-01 00:00:00 | 2020-06-05 00:00:00
2020-01-01 00:00:00 | 2020-06-15 00:00:00
2020-06-01 00:00:00 | 2020-08-01 00:00:00
2020-06-01 00:00:00 | 2020-08-02 00:00:00
2020-06-01 00:00:00 | 2020-09-01 00:00:00
2020-06-01 00:00:00 | 2020-09-02 00:00:00
2020-06-01 00:00:00 | 2020-09-03 00:00:00
2020-06-01 00:00:00 | 2020-09-04 00:00:00
2020-06-01 00:00:00 | 2020-09-05 00:00:00
2020-06-01 00:00:00 | 2020-12-01 00:00:00
2020-06-01 00:00:00 | 2020-12-02 00:00:00
2020-06-01 00:00:00 | 2020-12-03 00:00:00
2020-01-01 00:00:00 | 2020-12-10 00:00:00
Spreadsheet: 858554d1707204738-calculate-number-of-months-datedif-2-aligw
Sheet: Sheet1

Start | End | Manual |  | Period |  |  | [NAME] |  |  | AliGW |  | Start | Finish
2023-01-01 00:00:00 | 2023-12-14 00:00:00 | 11 |  | Jan 23 | Nov 23
2022-12-01 00:00:00 | 2023-12-14 00:00:00 | 12 |  | Dec 22 | Nov 23
2023-07-01 00:00:00 | 2024-07-28 00:00:00 | 13 |  | Jul 23 | Jul 24
2021-02-28 00:00:00 | 2024-04-27 00:00:00 | 38 |  | Mar 21 | Apr 24
2023-03-01 00:00:00 | 2024-02-29 00:00:00 | 12 |  | Mar23 | Feb 24
2023-07-01 00:00:00 | 2024-06-30 00:00:00 | 12 |  | Jul 23 | Jun 24
Spreadsheet: 759931d1639824054-maximum-average-for-dataset-with-defined-sample-size-running-
Sheet: Sheet1

 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |  | Size of sample | No.of samples | [NAME] | Months
 | 0.02840000000000004 | 0.02659999999999996 | 0.0227 | 0.03184999999999993 | 0.03185000000000004 | 0.03580000000000005 | 0.03869999999999996 | 0.04020000000000001 | 0.04080000000000006 | 0.03289999999999993 |  | 1 | 10 | 0.0408 | 9
 |  |  |  |  |  |  |  |  |  |  |  | 2 | 9 | 0.0405 | 8,9
 |  |  |  |  |  |  |  |  |  |  |  | 3 | 8 | 0.0399 | 7,8,9
 |  |  |  |  |  |  |  |  |  |  |  | 4 | 7 | 0.0389 | 6,7,8,9
 |  |  |  |  |  |  |  |  |  |  |  | 5 | 6 | 0.0377 | 6,7,8,9,10
Spreadsheet: 455348d1460269253-formula-based-on-total-new-100-excel-weight-adjustment-1-
Sheet: Sheet1

S.NO. | CONTAINER NOS. |  | SEAL NOS. |  | NET WT | ADJUSTED WT |  |  | SLABS
1 | ABCD | 123456 | 56789 |  | 26.86 |  |  | 1 | below 23.7
 |  |  |  |  | 25.57 |  |  | 2 | below 27.7
 |  |  |  |  | 25.78
 |  |  |  |  | 24.89
 |  |  |  |  | 22.15
 |  |  |  |  | 22.68
 |  |  |  |  | 23.95
 |  |  |  |  | 27.65
 |  |  |  |  | 27.44
 |  |  |  |  | 22.38
 |  |  |  |  | 25.98
 |  |  |  |  | 24.73
 |  |  |  |  | 23.24
 |  |  |  |  | 23.72
 |  |  |  |  | 25.91
 |  |  |  |  | 25.86
 |  |  |  |  | 22.27
 |  |  |  |  | 23.82
 |  |  |  |  | 26.68
 |  |  |  |  | 27.15
 |  |  |  |  | 26.34
 |  |  |  |  | 23.11
 |  |  |  |  | 22.43
 |  |  |  |  | 27.56
 |  |  |  |  | 22.36
 |  |  |  |  | 23.91
 |  |  |  |  | 24.82
 |  |  |  |  | 24.91
 |  |  |  |  | 24.33
 |  |  |  |  | 27.68
 |  |  |  |  | 27.19
 |  |  |  |  | 22.19
 |  |  |  |  | 24.72
 |  |  |  |  | 25.99
 |  |  |  |  | 21.12
 |  |  |  |  | 20.18
 |  |  |  |  | 19.9
 |  |  |  |  | 23.72
 |  |  |  |  | 23.9
 |  |  |  |  | 24.82
 |  |  |  |  | 27.23
 |  |  |  |  | 22.81
 |  |  |  |  | 23.91
 |  |  |  |  | 24.99
 |  |  |  |  | 25.72
 |  |  |  |  | 24.55
 |  |  |  |  | 21.76
 |  |  |  |  | 27.69
 |  |  |  |  | 23.9
 |  |  |  |  | 25.87
 |  |  |  |  | 25.88
 |  |  |  |  | 24.9
 |  |  |  |  | 25.91
 |  |  |  |  | 26.91
 |  |  |  |  | 25.9
 |  |  |  |  | 27.65
 |  |  |  |  | 24.91
 |  |  |  |  | 23.89
 |  |  |  |  | 22.1
 |  |  |  |  | 21.9
 |  |  |  |  | 21
 |  |  |  |  | 22.71
 |  |  |  |  | 24.78
 |  |  |  |  | 22.65
 |  |  |  |  | 22.34
 |  |  |  |  | 26.98
 |  |  |  |  | 26.93
 |  |  |  |  | 23.33
 |  |  |  |  | 21.88
 |  |  |  |  | 21.98
 |  |  |  |  | 19.88
 |  |  |  |  | 20.81
 |  |  |  |  | 21.89
 |  |  |  |  | 20.33
 |  |  |  |  | 27.67
 |  |  |  |  | 25.98
 |  |  |  |  | 22.77
 |  |  |  |  | 21.98
 |  |  |  |  | 21.76
 |  |  |  |  | 24.56
 |  |  |  |  | 20.59
 |  |  |  |  | 21.5
 |  |  |  |  | 25.39
 |  |  |  |  | 22.48
 |  |  |  |  | 21.72
 |  |  |  |  | 21.89
 |  |  |  |  | 25.77
 |  |  |  |  | 26.33
 |  |  |  |  | 21.82
 |  |  |  |  | 25.99
 |  |  |  |  | 27.5
 |  |  |  |  | 26.37
 |  |  |  |  | 26.62
 |  |  |  |  | 25.46
 |  |  |  |  | 24.22
 |  |  |  |  | 26.18
 |  |  |  |  | 24.89
 |  |  |  |  | 25.88
 |  |  |  |  | 24.44
 |  |  |  |  | 28
Spreadsheet: 163376d1340287668-how-to-prevent-excel-from-copying-conditional-formatting-rules-ezell-usa-unit-1-and-1a
Sheet: APRIL 2012

<HOME> | Field:  [NAME]: G.A. Carter #1          Lease No:  9024368 |  |  |  |  |  |  |  |  |  | SALES
 |  | ttotal sales: |  |  |  |  |  | Avg. Prod: |  |  | ALL INFORMATION FOR THIS TABLE MUST BE ENTERED FROM TICKETS
APRIL | Tank | 5664 | Tank | 5665 | 5664 | 5665 | Total | Downtime | Downtime Description |  | Tank | 5664 | Tank | 5665 | Plains | Ticket | BS&W | OBS | OBS | Durango | Corrected
2012 | Ft. | In. | Ft. | In. | Prod. | Prod. | (BPD) | Hours | or Comments |  | Ft. | In. | Ft. | In. | Bought | No. | % | Grav. | Temp. | Sold | Sales
Prev. Gauge: | 1 | 5.5 | 5 | 9.25
1 | 1 | 5.5 | 5 | 11
2 | 1 | 5.5 | 6 | 1.75
3 | 1 | 7 | 6 | 1.75
4 | 1 | 9.25 | 6 | 1.75
5 | 1 | 11.5 | 6 | 1.75
6 | 2 | 1 | 6 | 1.75
7 | 2 | 3.25 | 6 | 1.75 |  |  |  |  |  |  |  |  | 6 | 1
8 | 2 | 6.5 | 1 | 4.5 |  |  |  |  |  |  |  |  | 1 | 4 |  | 3830197 | 0.1 | 26 | 62
9 | 2 | 8.25 | 1 | 4.5
10 | 2 | 10.75 | 1 | 4.5
11 | 3 | 0.75 | 1 | 4.5
12 | 3 | 2.75 | 1 | 4.5
13 | 3 | 5 | 1 | 4.5
14 | 3 | 6.5 | 1 | 4.5
15 | 3 | 8.75 | 1 | 4.5
16 | 3 | 11.75 | 1 | 4.5
17 | 4 | 1.75 | 1 | 4.5
18 | 4 | 3.5 | 1 | 4.5
19 | 4 | 6 | 1 | 4.5
20 | 4 | 8.5 | 1 | 4.5
21 | 4 | 10.5 | 1 | 4.5
22 | 5 | 0.5 | 1 | 4.5
23 | 5 | 2.5 | 1 | 4.5
24 | 5 | 5 | 1 | 4.5
25 | 5 | 6.5 | 1 | 4.5 |  |  |  | 5 | DOA reason unknown went back online with no prob.
26 | 5 | 8.75 | 1 | 4.5
27 | 5 | 10.75 | 1 | 4.5
28 | 6 | 1.25 | 1 | 4.5
29 | 6 | 1.25 | 1 | 5.75
30 | 6 | 1.25 | 1 | 8.25 |  |  |  |  | END OF MONTH TANK READING
31
1 | 6 | 1.25 | 1 | 10.5
 | Tank 64 |  | 33.11
 | Tank 65 |  | 33.11
 | Load ready |  | 6
Spreadsheet: 052e3933-573e-4dc7-ab53-6d0d00969c3c
Sheet: Sheet1

Samenstelling bodemlaag 1 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Conclusies bodemlaag 1: | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13 | Unnamed: 14 | Unnamed: 15 | Unnamed: 16 | Unnamed: 17 | Unnamed: 18 | Unnamed: 19
 |  |  |  | Saneren niet zinvol, gehalten in laag < MWW
Bovenzijde (m -mv.) |  | 0
Onderzijde (m -mv.) |  | 0
[NAME] laag 1 in (m) |  | 0
Bodemmonster | Koper | Zink | Cadmium | Lood | Arseen | Kwik | [NAME] | Chroom | Barium | Kobalt | Molybdeen | PAK | [NAME] | PCB's | [NAME] | lutum |  | [NAME] in bodemmonster < MWW+ | [NAME] in bodemmonster < MWW
1
2
3
4
5
6
7
8
9
10
Gemiddelde | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 2 |  | niets ingevuld | concl.
Variantiecoëfficiënt |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | True | False
MWW | 26.1 | 84.28571428571429 | 0.6970700636942674 | 44.47058823529412 | 15.4551724137931 | 0.5777019867549668 | 13.37142857142857 | 33.48 | 142.4516129032258 | 9.955555555555556 | 54 | 6.8 | 38 | 0.004
MWW+ | 26.1 | 84.28571428571429 | 0.6970700636942674 | 44.47058823529412 | 15.4551724137931 | 0.5777019867549668 | 13.37142857142857 | 33.48 | 142.4516129032258 | 9.955555555555556 | 54 | 6.8 | 38 | 0.004
[NAME] |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 4
laag > MWW I | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False
laag > MWW+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False
1 of meer monsters > MWW+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
1 of meer monsters < MWW+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
1 of meer monsters > MWW | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
1 of meer monsters < MWW | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False | Let op deelgebieden, een of meer monster(s)/gehalte(n) in de laag < MWW
monster>MWW laag<MWW | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False | Let op deelgebieden, een of meer monster(s)/gehalte(n) in de laag < MWW
monster>MWW+ laag<MWW+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False | Let op deelgebieden, een of meer gehalte(n) in de laag overschrijden de MWW+
monster<MWW+ laag>MWW+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False | Let op deelgebieden, een of meer gehalte(n) in de laag overschrijden de MWW+
alle monsters<MWWI + laag<MWWI | True | True | True | True | True | True | True | True | True | True | True | True | True | True |  | True | Saneren niet zinvol, gehalten in laag < MWW
alle monsters>MWW+ laag>MWW+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |  | False | Saneren noodzakelijk, gehalten in laag > MWW+
bodemmonster >MWW+ |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | False
Spreadsheet: 166644d1341681304-averageif-statement-for-excel-2003-example
Sheet: Sheet1

Criteria | Number to average
A | 1
B | 2
C | 3
A | 4
A | 5
B | 6
B | 7
B | 8
B | 9
C | 10
C | 11
C | 12
C | 13
C | 14
Spreadsheet: 2e48a8d8-c031-4580-9841-9e25995c8e38
Sheet: By State

[NAME] | NPA | 2014.1 FCST |  | 2013.2 FCST |  | Change | Notes Comments
 |  | Year | Quarter | Year | Quarter | 2013.2 to 2014.1
California | 209 | 2027 | 2Q | 2027 | 4Q | -2Q
California | 213
California | 323 | 2018 | 1Q | 2018 | 1Q | N/C
California | 415 | 2015 | 3Q | 2015 | 3Q | N/C
California | 510 | 2020 | 4Q | 2021 | 2Q | -2Q
California | 530 | 2023 | 1Q | 2023 | 1Q | N/C
California | 559 | 2033 | 1Q | 2032 | 4Q | +1Q
California | 562 | 2033 | 4Q | 2034 | 3Q | -3Q | Increased historical and projected demand.
California | 619 | 2021 | 4Q | 2022 | 3Q | -3Q | Increased historical and projected demand.
California | 626 | 2030 | 1Q | 2032 | 2Q | -9Q | Increased historical and projected demand.
California | 650 | 2026 | 1Q | 2024 | 4Q | +5Q | Reduced historical and projected demand.
California | 661 | 2026 | 4Q | 2030 | 1Q | -13Q | Increased historical and projected demand.
California | 707 | 2019 | 2Q | 2019 | 3Q | -1Q
California | 805 | 2018 | 3Q | 2019 | 1Q | -2Q
California | 831
California | 858 | 2033 | 4Q | 2034 | 1Q | -1Q
California | 909 | 2019 | 3Q | 2020 | 1Q | -2Q
California | 916 | 2019 | 4Q | 2021 | 1Q | -5Q | Increased historical and projected demand.
California | 925 | 2027 | 2Q | 2031 | 1Q | -15Q | Increased historical and projected demand.
California | 949 | 2032 | 2Q | 2030 | 2Q | +8Q | Reduced historical and projected demand.
California | 951 | 2024 | 3Q | 2025 | 4Q | -5Q | Increased historical and projected demand.
California | 310/424 | 2028 | 4Q | 2028 | 2Q | +2Q
California | 408/669 | 2043 | 4Q | 2040 | 3Q | +13Q | Reduced historical and projected demand.
California | 442/760 | 2034 | 2Q | 2034 | 2Q | N/C
California | 657/714 |  |  | 2038 | 4Q
California | 747/818 |  |  | 2043 | 4Q
Spreadsheet: 5692f0bb-864e-4b81-b005-67d532a14a87
Sheet: Sheet1

Adresseliste fra www.proff.no | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7
[NAME]:Oppføringer fra [NAME]
FIRMANAVN | ADRESSE | POSTNR. | POSTSTED | TELEFON | TELEFAKS
Metall Fasader Terje Trondsen |  | 3092 | Sundbyfoss
Hetronic Norge AS | Hanekleiva 161 | 3090 | Hof
Tre & Kabelservice AS Tvangsavviklingsbo | Gutua 5A | 3090 | Hof
Tre & Kabelservice AS | Gutua 5A | 3090 | Hof
Trenger du oppdaterte adresselister til DM /TM? [NAME] (www.forvalt.no) tilbyr ett segmenterings- og uttekksverktøy hvor du [NAME] frem til din målgruppe og eksportere lister til Excel. Du kan gjøre oppslag så ofte du vil, med en begrensning på 3500 selskap per søk. Våre telefonnummere er hentet fra Telefonkatalogen og [NAME].  Med segmenteringsverktøy kan du: - Hente ut adresseliste før en DM utsendelse - Lage ringelister - Hente ut bransjestatistikker - Oppdatere din kundedatabase  Se http://forvalt.no/segmenteringsverktoy/
Spreadsheet: 716052d1612001278-formula-to-extract-records-with-indirect-and-multiple-criteria-sample-file-for-forum-ans1
Sheet: Result

 | Classification | Kabaddi | Select Game Name |  | Sheet Name | GAme1 | <<< Select Sheet Name
 | No. of Records
Sr. No. | Product Code | Game Name | Rate
 | =IF(ROWS($B$5:B5)>$O$1,"",INDEX((INDIRECT("'"&$G$1&"'!"&"A$2:A$500")),SMALL(IF((INDIRECT("'"&$G$1&"'!"&"B$4:B$500"))<>,ROW((INDIRECT("'"&$G$1&"'!"&"B$4:B$500")))-ROW((INDIRECT("'"&$G$1&"'!"&"$B$4"))+1),ROWS($B$5:B5)))
 | ^ the above formula couldn't work
 |  |  |  |  |  |  |  |  |  |  |  |  |  | Sheet Name |  | Game name
 |  | ProductCode | Game Name | Rate |  | I want this result |  |  |  |  |  |  |  | GAme1 |  | KhoKho
 |  |  |  |  |  | 9 | KhoKho | 195 |  |  |  |  |  | GAme2 |  | Kabaddi
 |  |  |  |  |  | 27 | Cricket | 620 |  |  |  |  |  | GAme3 |  | Cricket
 |  |  |  |  |  | 32 | Carrom | 1665 |  |  |  |  |  |  |  | Carrom
 |  |  |  |  |  | 2 | Tennis | 1015 |  |  |  |  |  |  |  | Tennis
 |  |  |  |  |  | 48 | Cricket | 1840 |  |  |  |  |  |  |  | [NAME]
 |  |  |  |  |  | 53 | Carrom | 585 |  |  |  |  |  |  |  | Basket Ball
 |  |  |  |  |  | 64 | [NAME] | 950
 |  |  |  |  |  | 138 | [NAME] | 2465
 |  |  |  |  |  | 7 | Cricket | 3740
 |  |  |  |  |  | 7 | [NAME] | 9170
 |  |  |  |  |  | 24 | KhoKho | 138
 |  |  |  |  |  | 38 | Carrom | 155
 |  |  |  |  |  | 9 | [NAME] | 122
 |  |  |  |  | NOTE: To avoid 0 [NAME] cells
 |  |  |  |  | [NAME]#
Spreadsheet: tracy_geaccone__40152__2001_Q1_Negotiated Deals
Sheet: Summary

JANUARY
 |  |  | VOLUME |  | REVENUE
Deal | Reliant |  | 310000 |  | 155000
[NAME] | Reliant |  | 310000 |  | 68634
Difference
JANUARY TOTAL
FEBRUARY
 |  |  | VOLUME |  | REVENUE
Deal | Sempra |  | 420000 |  | 4441744
[NAME] | Sempra |  | 420000 |  | 159207
Difference
Deal | Richardson |  |  |  | 1480810
[NAME] | Richardson |  |  |  | 99600
Difference
FEBRUARY TOTAL
[NAME]
 |  |  | VOLUME |  | REVENUE
Deal | Astra |  | 1550000 |  | 355603
[NAME] | Astra |  | 1550000
Difference
Deal | Reliant |  | 930000 |  | 495219
[NAME] | Reliant |  | 930000
Difference
Deal | Sempra |  | 465000 |  | 1827947
[NAME] | Sempra |  | 465000
Difference
Deal | Richardson |  | 310000 |  | 1299622
[NAME] | Richardson |  | 310000
Difference
[NAME] TOTAL
TOTAL Q1
Spreadsheet: 4cf237e8-994d-4474-8b37-5eebc857bff3
Sheet: 2015-2016

2015-2016 Class Schedule |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | You may select up to three classroom attributes.  Select only course requirements, as the number of available classrooms will be reduced with each attribute selected.
Communication Studies
Spring 2016
Subject | Course and Title | Subtitle/Alternate Title | Days | Times | Sec | Part of Term | Credits | Hamline Plan | Instructor(s) | Instructor ID | FT or Adj | [NAME] | Registration Approval Required? | [NAME] | Seats to be Saved | Saved Seats Type | Campus: [NAME], [NAME], Online, Blended |  |  |  | Cross list? SUBJ CRSE SEC | XLST total enrl | Areas of Study | Comments
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Classroom Attribute A | Classroom Attribute B | Classroom Attribute C
Spreadsheet: 684215d1593194137-arranging-the-data-pq-rearranging-aligw
Sheet: question

Particulars | List | Units
25 | USA 2 | a
25 | USA,2 | b
45 | UK | a
45 | UK Ltd | b
45 | UK,Ltd | c
45 | UK,West | d
21 | RAM | a
37 | [NAME] | b
37 | [NAME] | a
12 | [NAME] | b
12 | [NAME] | a
12 | [NAME] | d
7 | Kapil | c
Spreadsheet: 6056386e-812b-4265-b629-c0f41506e9f5
Sheet: Sheet1

Table 10--Global rice exporters, calendar years; monthly revisions and annual changes | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11 | Unnamed: 12 | Unnamed: 13
 | 2011 |  |  |  | 2012 |  |  |  |  |  | 2013 1/
 | February |  | January | February |  | Monthly | Annual |  | January | February |  | Monthly | Annual
 | 2013 |  | 2013 | 2013 |  | revisions | changes |  | 2013 | 2013 |  | revisions | changes
 |  |  |  |  |  |  | 1,000 metric tons (milled basis)
Argentina | 732 |  | 675 | 608 |  | -67 | -124 |  | 650 | 625 |  | -25 | 17
Australia | 311 |  | 450 | 450 |  | 0 | 139 |  | 500 | 500 |  | 0 | 50
Brazil | 1296 |  | 1200 | 1105 |  | -95 | -191 |  | 800 | 800 |  | 0 | -305
Burma | 778 |  | 700 | 700 |  | 0 | -78 |  | 600 | 600 |  | 0 | -100
Cambodia | 860 |  | 800 | 800 |  | 0 | -60 |  | 825 | 825 |  | 0 | 25
China | 487 |  | 260 | 267 |  | 7 | -220 |  | 500 | 300 |  | -200 | 33
Ecuador | 70 |  | 30 | 30 |  | 0 | -40 |  | 15 | 15 |  | 0 | -15
Egypt | 320 |  | 600 | 600 |  | 0 | 280 |  | 850 | 850 |  | 0 | 250
European Union-27 | 241 |  | 210 | 210 |  | 0 | -31 |  | 235 | 235 |  | 0 | 25
Guinea | 80 |  | 80 | 80 |  | 0 | 0 |  | 80 | 80 |  | 0 | 0
Guyana | 257 |  | 285 | 285 |  | 0 | 28 |  | 300 | 300 |  | 0 | 15
India | 4637 |  | 10250 | 10250 |  | 0 | 5613 |  | 7500 | 7500 |  | 0 | -2750
Japan | 200 |  | 200 | 200 |  | 0 | 0 |  | 200 | 200 |  | 0 | 0
Korea, South | 4 |  | 5 | 2 |  | -3 | -2 |  | 5 | 5 |  | 0 | 3
Pakistan | 3414 |  | 3500 | 3500 |  | 0 | 86 |  | 3800 | 3800 |  | 0 | 300
Paraguay | 208 |  | 250 | 250 |  | 0 | 42 |  | 200 | 200 |  | 0 | -50
Peru | 50 |  | 30 | 30 |  | 0 | -20 |  | 60 | 60 |  | 0 | 30
Russia | 142 |  | 220 | 282 |  | 62 | 140 |  | 170 | 160 |  | -10 | -122
Thailand | 10647 |  | 6900 | 6945 |  | 45 | -3702 |  | 8000 | 8000 |  | 0 | 1055
Turkey | 90 |  | 75 | 75 |  | 0 | -15 |  | 80 | 80 |  | 0 | 5
Uganda | 40 |  | 35 | 35 |  | 0 | -5 |  | 35 | 35 |  | 0 | 0
United States | 3247 |  | 3300 | 3300 |  | 0 | 53 |  | 3450 | 3450 |  | 0 | 150
Uruguay | 841 |  | 1056 | 1056 |  | 0 | 215 |  | 850 | 850 |  | 0 | -206
Vietnam | 7000 |  | 7700 | 7717 |  | 17 | 717 |  | 7400 | 7400 |  | 0 | -317
Subtotal | 35952 |  | 38811 | 38777 |  | -34 | 2825 |  | 37105 | 36870 |  | -235 | -1907
Other | 269 |  | 254 | 250 |  | -4 | -20 |  | 260 | 260 |  | 0 | 10
 |  |  |  |  |  |  |  |  |  |  |  | 0
World total | 36221 |  | 39065 | 39027 |  | -38 | 2806 |  | 37365 | 37130 |  | -235 | -1897
U.S. Share | 0.08964412909638056 |  | 0.08447459362600794 | 0.08455684526097318 |  | -- | -- |  | 0.0923323966278603 | 0.09291677888499865 |  | -- | --
-- Not available.  Note: All trade data are reported on a calendar-year basis.
1/ Projected.
Source: Production, Supply, & Distribution Online Data Base, FAS/USDA, http://www.fas.usda.gov/psdonline/psdHome.aspx.
Last updated February 8, 2013.
Spreadsheet: 771490d1646696657-rank-and-provide-best-matches-between-two-tables-excel-forum-ranking
Sheet: Request

ID | Tableu | Sharepoint | Power BI | Smartsheet | MS Excel | MS Word | MS Powerpoint | MS Project | Best Matches
1 | Novice | Expert | Expert | Intermediate | Novice | NA | NA | NA
2 | Novice | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate
3 | Expert | Intermediate | Novice | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate
4 | Novice | Intermediate | Intermediate | Intermediate | Novice | Novice | NA | NA
5 | Novice | NA | Intermediate | Novice | Intermediate | Intermediate | Intermediate | Intermediate
6 | Novice | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate | NA | NA
7 | Novice | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate | Intermediate
8 | Intermediate | Novice | Intermediate | Intermediate | Novice | Novice | Expert | Expert
Spreadsheet: 851eb6f5-e273-47fc-857a-2d54b65a7bda
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Win by Pin | Unnamed: 3 | Unnamed: 4 | Win By DQ | Unnamed: 6 | Unnamed: 7 | DRAW | Unnamed: 9 | Unnamed: 10 | DRAW.1 | Unnamed: 12
 |  | or Submission |  |  | or Count Out |  |  | Time Limit or No C |  |  | Double CO or DQ
 | Favorite | 1000 | 0 |  | 1000 | 0 |  | 1000 | 0 |  | 1000 | 0
 | Underdog | 1000 | 0 |  | 1000 | 0 |  | 1000 | 0 |  | 1000 | 0
 | K factor = | 20 |  |  | 10 |  |  | 20 |  |  | 10
 | P(1) win chance = | 0.5 |  |  | 0.5 |  |  | 0.5 |  |  | 0.5
 | P(2) win chance = | 0.5 |  |  | 0.5 |  |  | 0.5 |  |  | 0.5
 |  | IF Fav wins |  |  | IF Fav wins
 | New Fav rank | 1010 | 10 |  | 1005 | 5
 | New Und rank | 990 | -10 |  | 995 | -5
 |  | IF Und wins |  |  | IF Und wins |  |  | DRAW |  |  | DRAW
 | New Fav rank | 990 | -10 |  | 995 | -5 |  | 999.99999998 | -2.000001586566214e-08 |  | 999.99999999 | -1.000000793283107e-08
 | New Und rank | 1010 | 10 |  | 1005 | 5 |  | 1000.00000002 | 2.000001586566214e-08 |  | 1000.00000001 | 1.000000793283107e-08
 |  | Input the two fighter's prematch ELO rating - Not their wrestling rating. I started everyone at 1000.
 |  | The K-Factor is how much you want the ratings to swing for the match. I use 20 for Pins/Submissions
 |  | and 10 for Count out or Disqualification
Spreadsheet: 785986d1656900479-how-to-transpose-a-complex-table-book1-excelletor-
Sheet: Sheet1

ID | Language | Term |  |  | ID | EN | FR | ES | DE
1 | EN | Term 1 |  |  | 1
1 | EN | Synonym to term 1 |  |  | 2
1 | FR | Term 1 |  |  | 3
2 | EN | Term 2 |  |  | 4