tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 12bb6687-7689-4eb9-8c6c-eefe7e914d08
Sheet: Sheet1

 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9
 |  |  |  |  |  |  | [NAME], Form CCHE-C-6
UTILIZATION REPORT
Due: November 15 Due: April 15
 | INSTITUTION: |  |  |  | FINANCIAL AID DIRECTOR:
 |  |  | CSG | [NAME] | Work Study | GOS | CLEAP | SLEAP | TOTAL
 | 1 | Original Offical Allocation Notice |  |  |  |  |  |  | 0
 | 2 | Additional Funds Allocated by CCHE |  |  |  |  |  |  | 0
 | 3 | Funds Released to CCHE |  |  |  |  |  |  | 0
 | 4 | Total Available | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | 5 | Total Amount Expended to Date |  |  |  |  |  |  | 0
 | 6 | Total Amount Committed to Date |  |  |  |  |  |  | 0
 | 7 | Percent Utilized | 0% | 0% | 0% | 0% | 0% | 0% | 0%
 | 8 | Funds to be Released to CCHE
 |  | CCHE Use Only
Financial Aid Director Signature:   ____________________________________ |  |  |  |  |  |  | Date:   __________________________
DIRECTIONS: |  | 1.  Complete Lines 1, 5, 6 8 2.  Enter Name of Institution and Name of Financial Aid Director 3.  Sign and Date Form 4.  Return to Celina Duran, [NAME] ([EMAIL]) or fax to [PHONE]
Institutions that do not use (i.e., award) 80% of Colorado student Aid funds by November 15 may have the under-utilized funds reallocated.
Spreadsheet: 711466d1609738846-subtotal-not-working-in-array-extracted-database-export-performance-reg-2021
Sheet: PROOF SHEET-LOCAL

 | PROOF SHEET LOCAL EXPORT-2021
EXPORTER | BILL NUMBER | DATE | BILL AMOUNT IN FC | BILL AMOUNT IN BDT | OD SIGHT/ TT DOC RATE | EXPORT LC/SC | APPLICANT NAME | ISSUING BANK/DOC. SENT TO | TENOR | LDBP/IBP NO. | LDBP/IBP DATE | PURCHASE AMOUNT OUTSTANDING BDT | DATE OF ACCPTNCE RECEIVED | MATURITY DATE | LDBC OUTSTANDING IN FC | LDBC OUTSTANDING IN BDT
TOTAL
Spreadsheet: 330727d1404836852-formula-help-if-and-or-vlookup-effective-rate
Sheet: Effective Rate

Sales Range |  | Base | Effective | Incemental | Net
0 | 25000 | 0.6 | 0.6 |  | 15000
25001 | 50000 | 0.61 | 0.605
50001 | 75000 | 0.61 | 0.6067
75001 | 100000 | 0.62 | 0.61
100001 | 150000 | 0.72 | 0.6466
150001 | 200000 | 0.735 | 0.6687
200001 | 250000 | 0.7425 | 0.6835
250001 | 300000 | 0.7425 | 0.6933
300001 | 400000 | 0.7475 | 0.7069
400001 | 500000 | 0.7475 | 0.715
Sales | 166314.18
Effective
Spreadsheet: 869669d1716280940-help-with-selecting-volleyball-or-any-sport-teams-with-equal-skill-divide-players-into-teams-of-equal-skill
Sheet: Coach 2

Volleyball Evaluation Form
 |  | Serving | Passing | Setting | Hitting | Teamwork | Blocking U18 only |  | Overall
 |  | 4 | 5 | 5 | 4.5 | 5 | 4.5
 |  | 1 | 5 | 1 | 3 | 5 | 3
 |  | 4 | 2 | 2 | 2 | 1 | 1
 |  | 4 | 3 | 2 | 1 | 2 | 5
 |  | 2 | 4 | 5 | 1 | 3 | 1
 |  | 4 | 3 | 4 | 5 | 2 | 2
 |  | 1 | 3 | 3 | 2 | 3 | 3
 |  | 3 | 2 | 1 | 4 | 3 | 1
 |  | 4 | 4 | 4.5 | 4.5 | 4.5 | 4.5
 |  | 2 | 4 | 1 | 2 | 4 | 2
 |  | 5 | 2 | 1 | 1 | 5 | 4
 |  | 4 | 5 | 5 | 2 | 1 | 1
 |  | 1 | 3 | 1 | 1 | 1 | 2
Spreadsheet: 215243d1361311639-merging-spreadsheet-data-ats-example
Sheet: Manufacturing

Item Code | Qty | Due Date | Comments
KI4D----RK2-X20 | 10601.00 | 04/02/13
KN02----4S2BS21 | 4316.00 | 03/07/13
KN0205004S2-S21 | 4535.00 | 03/07/13 | No Inserts
KN04----K4DBN21 | 2092.00 | 02/27/13 | No Inserts
KN100625K2BXNC1 | 78871.00 | 02/19/13
KN100625K2BXNC1 | 78871.00 | 03/27/13 | No Inserts
[NAME] | 4999.00 | 03/22/13
[NAME] | 4999.00 | 04/12/13
KN2416704S4X553 | 20.00 | 01/09/13
KN4A----F6---90 | 1680.00 | 03/18/13 | No Inserts
KN4A----F6---90 | 1680.00 | 03/25/13
KN4A----F6---90 | 1680.00 | 04/01/13
KN4C----3P1C-21 | 2285.00 | 02/20/13
[NAME] | 6417.00 | 03/01/13 | No Inserts
[NAME] | 6417.00 | 03/08/13
[NAME] | 6417.00 | 04/10/13 | No Inserts
Spreadsheet: 81979d1282066007-inventory-database-lookup-book5
Sheet: Sheet1

Item1 | 1 | 10 | 100
Item2 | 2 | 20 | 200
Item3 | 3 | 30 | 300
Item4 | 4 | 40 | 400
Item5 | 5 | 50 | 500
Item6 | 6 | 60 | 600
Item7 | 7 | 70 | 700
Item8 | 8 | 80 | 800
Item9 | 9 | 90 | 900
Item10 | 10 | 100 | 1000
Item11 | 11 | 110 | 1100
Item12 | 12 | 120 | 1200
Item13 | 13 | 130 | 1300
Item14 | 14 | 140 | 1400
Item15 | 15 | 150 | 1500
Item16 | 16 | 160 | 1600
Item17 | 17 | 170 | 1700
Item18 | 18 | 180 | 1800
Item19 | 19 | 190 | 1900
Item20 | 20 | 200 | 2000
Item10 | 10 | 100 | 1000
Spreadsheet: 688889d1596005418-help-sorting-apartments-2020-07-29-oeldere-csgrey-688869d1595988776-help-sorting-apartments-go-advanced
Sheet: Sheet1

 | Apt # | BDRMS | floor | Room
 | 2B | 1 |  |  |  |  |  |  |  | need to sort apartments by the number of bedrooms they have in a 26 story apartment building w 12 apartments on each floor. They are numbered 1A,1B,1C...etc...to 1L.
 | 3B | 1 |  |  |  |  |  |  |  | The i and c lines are 3 bedrooms and the b and h lines are 1 bedroom...every other apt is 2 bedroom.
 | 2H | 1 |  |  |  |  |  |  |  | I think it's a IF function I am after but I don't know how to build the formula...
 | 3H | 1 |  |  |  |  |  |  |  | It might go something like this....=if(*cell*=(number)A,2,if *cell*=(number)B,1,if *cell*=(number)c,3...etc...with the (number) being some kind of super secret universal symbol for number that will deal with apt 3B as well as apt 26B
 | 2A | 2 |  |  |  |  |  |  |  | I could probably manually fill in 312 apartments except that's the easy way out.
 | 3A | 2 |  |  |  |  |  |  |  | Any help would be appreciated.
 | 2D | 2 |  |  |  |  |  |  | Pivot table
 | 3D | 2
 | 2E | 2 |  |  |  |  |  |  | Som [NAME] | Kolomlabels
 | 3E | 2 |  |  |  |  |  |  | Rijlabels | 2 | 3
 | 2F | 2 |  |  |  |  |  |  | 1 | 2 | 2
 | 3F | 2 |  |  |  |  |  |  | B | 1 | 1
 | 2G | 2 |  |  |  |  |  |  | H | 1 | 1
 | 3G | 2 |  |  |  |  |  |  | 2 | 16 | 16
 | 2J | 2 |  |  |  |  |  |  | A | 2 | 2
 | 3J | 2 |  |  |  |  |  |  | D | 2 | 2
 | 2K | 2 |  |  |  |  |  |  | E | 2 | 2
 | 3K | 2 |  |  |  |  |  |  | F | 2 | 2
 | 2L | 2 |  |  |  |  |  |  | G | 2 | 2
 | 3L | 2 |  |  |  |  |  |  | J | 2 | 2
 | 2C | 3 |  |  |  |  |  |  | K | 2 | 2
 | 3C | 3 |  |  |  |  |  |  | L | 2 | 2
 | 2I | 3 |  |  |  |  |  |  | 3 | 6 | 6
 | 3I | 3 |  |  |  |  |  |  | C | 3 | 3
 |  |  |  |  |  |  |  |  | I | 3 | 3
 |  |  |  |  |  |  |  |  | Eindtotaal | 24 | 24
Spreadsheet: 76979d1277425849-using-the-index-and-match-functions-with-a-like-function-timequestion
Sheet: Data

Agent Name | Extn |  | [NAME] |  | Logout Time | Logout Date | [NAME] | Skill 1 | Skill 2 | Skill 3 | Skill 4 | Time
Smith, Jill | 7651 |  | 05:01:00 |  | 06:05:00 | 2010-06-01 00:00:00 | 0 | 11 | 2 | 3 | 1
Smith, Jill | 7650 |  | 06:06:00 |  | 08:40:00 | 2010-06-01 00:00:00 | 0 | 11 | 2 | 3 | 1
Smith, Jill | 7650 |  | 08:40:00 |  | 09:24:00 | 2010-06-01 00:00:00 | 0 | 11 | 2 | 3 | 1
Smith, Jill | 7650 |  | 09:37:00 |  | 10:06:00 | 2010-06-01 00:00:00 | 0 | 11 | 2 | 3 | 1
Smith, Jill | 7650 |  | 10:36:00 |  | 12:00:00
Smith, Jill | 7650
Spreadsheet: 724436d1616159399-making-zebra-rows-that-you-can-still-highlight-mock_data
Sheet: MOCK_DATA

id | first_name | last_name | email | gender | ip_address
1 | Stillmann | Annell | [EMAIL] | Genderqueer | 165.9.243.10
2 | [NAME] | LeEstut | [EMAIL] | Genderqueer | 162.242.80.87
3 | Velvet | Hiscoe | [EMAIL] | Polygender | 202.2.191.42
4 | [NAME] | Maywood | [EMAIL] | Genderqueer | 0.10.250.79
5 | Charmain | Bellringer | [EMAIL] | Genderqueer | 5.102.144.35
6 | Llewellyn | Sebrens | [EMAIL] | Genderqueer | 99.69.50.66
7 | Brett | [NAME] | [EMAIL] | Polygender | 44.84.253.8
8 | Fay | Marcus | [EMAIL] | Polygender | 48.255.242.49
9 | [NAME] | Josefsohn | [EMAIL] | Polygender | 164.143.28.198
10 | Pandora | Kisting | [EMAIL] | Genderqueer | 131.45.245.46
11 | Norton | Niaves | [EMAIL] | Male | 35.236.219.118
12 | Desiree | Drust | [EMAIL] | Genderfluid | 5.247.56.122
13 | Fritz | [NAME] | [EMAIL] | Male | 142.190.208.78
14 | [NAME] | Greensite | [EMAIL] | Bigender | 10.19.88.239
15 | [NAME] | Weyland | [EMAIL] | Female | 198.202.45.66
16 | Brennen | Deal | [EMAIL] | Genderfluid | 111.112.183.30
17 | Jordan | [NAME] | [EMAIL] | Polygender | 148.24.132.101
18 | [NAME] | Norcott | [EMAIL] | Agender | 57.40.174.18
19 | Morly | [NAME] | [EMAIL] | Genderqueer | 100.125.78.114
20 | Randa | [NAME] | [EMAIL] | Non-binary | 151.118.253.91
21 | Izaak | Cawthorn | [EMAIL] | Polygender | 16.234.39.224
22 | Ferdinand | Semkins | [EMAIL] | Male | 44.148.38.74
23 | Junette | MacFarland | [EMAIL] | Non-binary | 102.20.93.65
24 | [NAME] | [NAME] | [EMAIL] | Genderqueer | 219.234.102.150
25 | [NAME] | [NAME] | [EMAIL] | Polygender | 202.47.79.128
26 | Clair | Beldom | [EMAIL] | Non-binary | 138.236.33.137
27 | Margarethe | Brewers | [EMAIL] | Non-binary | 144.59.171.161
28 | Torey | Crimpe | [EMAIL] | Genderfluid | 241.190.104.173
29 | [NAME] | Adshead | [EMAIL] | Genderfluid | 163.175.196.224
30 | [NAME] | McFetridge | [EMAIL] | Genderfluid | 238.116.132.123
31 | [NAME] | Baress | [EMAIL] | Non-binary | 55.218.13.107
32 | [NAME] | Burgane | [EMAIL] | Agender | 137.10.226.232
33 | [NAME] | Labb | [EMAIL] | Agender | 137.34.199.149
34 | [NAME] | Dobbs | [EMAIL] | Female | 131.78.250.186
35 | Aline | Beecker | [EMAIL] | Genderfluid | 209.120.83.50
36 | Daren | Hardaway | [EMAIL] | Non-binary | 153.75.250.240
37 | [NAME] | Fells | [EMAIL] | Polygender | 61.244.144.33
38 | Menard | Grcic | [EMAIL] | Agender | 169.146.52.10
39 | Llewellyn | Shearer | [EMAIL] | Agender | 143.224.151.240
40 | [NAME] | [NAME] | [EMAIL] | Agender | 107.182.11.175
41 | [NAME] | [NAME] | [EMAIL] | Male | 214.59.237.99
42 | Shandee | McNamee | [NAME] | Male | 80.57.177.245
43 | Clarice | Duckels | [EMAIL] | Female | 184.86.142.72
44 | Will | Bothie | [EMAIL] | Genderfluid | 105.42.156.48
45 | Cristiano | Pedersen | [EMAIL] | Genderqueer | 0.50.188.120
46 | Burnard | Verrillo | [EMAIL] | Genderqueer | 15.128.99.0
47 | [NAME] | Churly | [EMAIL] | Male | 143.21.184.241
48 | Kris | Craft | [EMAIL] | Female | 216.26.75.161
49 | [NAME] | Gommery | [EMAIL] | Male | 241.85.83.102
50 | Kessiah | Hardaway | [EMAIL] | Male | 7.173.36.166
Spreadsheet: 127579d1320416707-if-hired-before-a-particular-date-if-hired-before-october-2001
Sheet: Sheet1

 |  |  | 2010 Wage | 2011 Increase | 2011 Wage
EE# | Employee Name | Hired | Hourly | Hourly | Hourly
12345 | Polo, [NAME] | 2008-02-15 00:00:00 | 9.65 | 0.2 | 9.85
67891 | Smith, [NAME] | 2001-10-01 00:00:00 | 9.65 | 0.44 | 10.09
41356 | Virgo, Lugo | 2009-08-23 00:00:00 | 9.65 | 0.2 | 9.85
Spreadsheet: 750414d1633443988-automating-color-coding-and-trend-help-needed-jlausier-data-color-coding-request
Sheet: 12-2-2016

 | ServiceNow Data Accuracy
 | Computers
 |  | Assigned to | Asset Function | [NAME] | Model | Acquisition Method | Computers not reporting Inventory | Cost
 | Total Records | 49323 | 49323 | 49323 | 49323 | 49323 | 49323 | 49323
 | Missing Records | 810 | 0 | 4031 | 526 | 1050 | 1325 | 942
 | Percentage of Missing Data
 | Server-(ESX, HPUX, Windows, Storage, Zone)
 |  | Serial Number | State | [NAME] | Model | Acquisition Method | Cost
 | Total Records | 2125 | 2125 | 2125 | 2125 | 2125 | 2125
 | Missing Records | 114 | 0 | 1613 | 236 | 907 | 1848
 | Percentage of Missing Data
 | Network Gear
 |  | Serial Number | State | [NAME] | Model | Acquisition Method | Cost
 | Total Records | 4407 | 4407 | 4407 | 4407 | 4407 | 4407
 | Missing Records | 188 | 100 | 4187 | 7 | 2000 | 4131
 | Percentage of Missing Data
 | US Cycle Count 12-2-2016
 | State | In transit available | In stock available | In stock used | Pending repair | Data Retention
 | Total Records | 328 | 282 | 1067 | 52 | 284
 | Matching Records | 328 | 282 | 1067 | 52 | 284
 | [NAME]
 | Asset Reconciliation 2016 |  | Remediated Records |  |  | Less than 5% Accuracy
 | 30+ Day Audits/Site Asset Reconciliation |  | 7104 |  |  | Less than 10% Accuracy
 |  |  |  |  |  | Greater than 50%
 | VMware
 | Network Gear |  | 2997
 | WebServer, AppServer, Disk, ETC |  | 5812
 | Total Infrastructure Asset Record Clean up
 | Duplicates based on Serial Number | 2016-06-22 00:00:00 | 2016-12-02 00:00:00
 | Computers | 187 | 0
 | Servers | 7225 | 212
 | Network Gear | 600 | 407
Spreadsheet: 153815d1336062709-crunching-down-years-2001-2002-2003-2005-to-2001-2005-book1_garu
Sheet: Sheet1

Volvo C30 | 2008-2012 | 2008 | 2009 | 2010 | 2011 | 2012
Volvo C70 Convertible | 1998-2004 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004
Volvo C70 Convertible | 2006-2010 | 2006 | 2007 | 2008 | 2009 | 2010
Spreadsheet: a2bb9df0-0812-422e-aaed-ae653b196494
Sheet: Report

Unit | Unit Priority | [NAME] | Objective Id | Objective Name | Objective Priority | Strategic Direction | Impact Type
Distance Education | 1 | Provide infrastructure to support DE courses and services | 1.1 | Integrate online student services into DE and traditional courses | 3 | None | -- Pick One --
Distance Education | 2 | Expand DE services offerings | 2.1 | Identify potential services that can meet the DE constituents' needs | 4 | None | -- Pick One --
Distance Education | 2 | Expand DE services offerings | 2.2 | Integrate technology that support DE strategic vision | 5 | None | -- Pick One --
Distance Education | 3 | Faculty/Staff Training | 3.1 | Identify training opportunities for DE Faculty and Staff | 6 | None | -- Pick One --
Distance Education | 3 | Faculty/Staff Training | 3.2 | Develop web-based training modules | 7 | None | -- Pick One --
Spreadsheet: 79cc519d-477e-4d75-985c-6bf95817d379
Sheet: MARCH

SEATTLE UNIVERSITY
NON-EXEMPT EMPLOYEE TIME REPORT
NAME: |  |  |  |  | DEPT: |  |  | (Use 4 letter-code as shown on paystub under DEPT)
Datatel ID Number or SSN:
PE: |  | 2015-03-01 00:00:00 | TO | 2015-03-31 00:00:00 |  | MO. NO.: |  | 3
Holiday Pay |  |  |  | HP
Sick Pay |  |  |  | SP
Vacation Pay |  |  |  | VP
[NAME] |  |  |  | BR |  | (up to 5 days of paid leave)
Jury Duty Leave |  |  |  | JL
[NAME] |  |  |  | DP
 |  |  |  |  |  |  |  |  | Employee Signature |  |  |  | Date
Regular Pay |  |  |  | RP
SUB-TOTAL |  |  |  |  | 165 |  |  |  | Supervisor Signature |  |  |  | Date
Overtime (1.0 rate) |  |  |  |  |  | (If total hours worked (Sunday-Saturday) is between 37.50 and 40)
Overtime (1.5 rate) |  |  |  |  |  | (If total hours worked (Sunday-Saturday) is above 40)
TOTAL
Sunday |  | Monday |  | Tuesday |  | Wednesday |  | Thursday |  | Friday |  | Saturday
 |  |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5
 | 1 |  | 2 |  | 3 |  | 4 |  | 5 |  | 6 |  | 7
 |  |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5
 | 8 |  | 9 |  | 10 |  | 11 |  | 12 |  | 13 |  | 14
 |  |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5
 | 15 |  | 16 |  | 17 | Time sheets due | 18 |  | 19 |  | 20 |  | 21
 |  |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5 |  | 7.5
 | 22 |  | 23 |  | 24 |  | 25 |  | 26 |  | 27 |  | 28
 |  |  | 7.5 |  | 7.5
 | 29 |  | 30 | pay day | 31
REMEMBER: Adjustment from Prior Month!! INCLUDE PRIOR MONTH ADJ HOURS IN THE ABOVE CALCULATION!
Spreadsheet: 128330d1320918955-locking-date-order-dummy-template
Sheet: Order Sheet

 | ORDER FOR: |  |  |  |  |  |  |  | supplier 1
 | ORDER TYPE:
 | Order No: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Date:
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Rep Name:
 | Delivery Address |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Invoice Address
 | Type 1
 | BARCODE |  |  |  | 1st Desc |  |  |  |  |  |  |  | 2nd Desc |  |  |  |  |  |  |  | Stock Code |  |  |  |  | Cost |  |  | Qty
1
 | Type 2
 | BARCODE |  |  |  | 1st Desc |  |  |  |  |  |  |  | 2nd Desc |  |  |  |  |  |  |  | Stock Code |  |  |  |  | Cost |  |  | Qty
2
 | Type 3
 | BARCODE |  |  |  | 1st Desc |  |  |  |  |  |  |  | 2nd Desc |  |  |  |  |  |  |  | Stock Code |  |  |  |  | Cost |  |  | Qty
3
Spreadsheet: 716476d1612224931-personal-budget-tracker-help-needed-sumif-newbudget-tracker-2021-sumproduct
Sheet: PERSONAL BUDGET

Create a Simple Personal Budget in this worksheet. Helpful instructions on how to use this worksheet are in cells in this column. Arrow down to get started.
Title of this worksheet is in cell at right. Enter year in cell Q2. Next instruction is in cell A4. | PERSONAL BUDGET
[NAME] are in cells C4 through P4. |  | REVENUE | JAN | FEB | MAR | APR | MAY | JUN | JUL | AUG | SEP | OCT | NOV | DEC | YEAR
Enter details in Income table starting in cell C5. Next instruction is in cell A11. |  | INCOME | January | February | March | April | May | June | July | August | September | October | November | December | Year | Sparkline
 |  | Wages | 4500 | 4500 | 4500 | 4500 | 4500 | 4500 | 4500 | 4500 | 4500 | 4500 | 4500 | 4500
 |  | Interest/Dividends | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 |  | Miscellaneous | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 |  | Total
 |  | Total Expenses
 |  | [NAME]
[NAME] are in cells C11 through P11. |  | EXPENSES | JAN | FEB | MAR | APR | MAY | JUN | JUL | AUG | SEP | OCT | NOV | DEC | YEAR
Enter Home expenses in table starting in cell C12. Next instruction is in cell A20. |  | HOME | January | February | March | April | May | June | July | August | September | October | November | December | Year | Sparkline
 |  | Electric
 |  | Internet
 |  | Cable
 |  | Water
 |  | Planet Fitness
 |  | Car Payment
 |  | Car Insurance
 |  | Groceries
 |  | Optavia
 |  | Dining out
Enter Daily expenses in table starting in cell C20. Next instruction is in cell A29. |  | Total
 |  | DEBT | January | February | March | April | May | June | July | August | September | October | November | December | Year | Sparkline
 |  | WGU - Tuition
 |  | 401K Loan
 |  | Student Loans
Enter Transportation expenses in table starting in cell C29. Next instruction is in cell A38. |  | Total
 |  | WEDDING | January | February | March | April | May | June | July | August | September | October | November | December | Year | Sparkline
 |  | Flights
 |  | VRBO
 |  | Cake
 |  | Flowers
 |  | Suit
 |  | Dress
Enter Entertainment expenses in table starting in cell C38. Next instruction is in cell A45. |  | Reception Dinner
 |  | Photographer
 |  | Transporation to airport
 |  | Car rental
 |  | Officiant
 |  | Hair/Makeup
 |  | Nails
 |  | Total
Enter Health expenses in table starting in cell C45. Next instruction is in cell A55.
 |  | TOTALS | JAN | FEB | MAR | APR | MAY | JUN | JUL | AUG | SEP | OCT | NOV | DEC | YEAR | SPARKLINE
 |  | Total expenses
 |  | Cash short/extra
Spreadsheet: 342836d1409696050-event-calendar-with-recurring-event-140902_-calendar-of-events-2014-_-test
Sheet: Event Calendar - MAR 15

 |  |  |  | EVENT CALENDAR
 |  |  |  |  |  | ENTER MONTH: | March
 |  |  |  |  |  | ENTER YEAR: | 2015
 |  |  |  |  |  | ENTER START DAY: | Sunday
 | TO EVENT LIST >>
Spreadsheet: 100820d1299058560-speed-up-max-if-array-sample-1-
Sheet: Sheet1

ID | Value | [NAME]
1 | 1 | 1
1 | 1 | 1 |  |  | Max of Value
2 | 1 | 2 |  |  | ID | Total
2 | 2 | 2 |  |  | 1 | 1
3 | 2 | 2 |  |  | 2 | 2
3 | 2 | 2 |  |  | 3 | 2
3 | 1 | 2 |  |  | 4 | 3
4 | 1 | 3 |  |  | 5 | 2
4 | 2 | 3 |  |  | 6 | 3
4 | 3 | 3 |  |  | Grand Total | 3
5 | 1 | 2
5 | 2 | 2
5 | 2 | 2
5 | 1 | 2
5 | 2 | 2
6 | 1 | 3
6 | 3 | 3
6 | 2 | 3
6 | 3 | 3
Spreadsheet: 16ae589b-8303-486f-82e9-e1fb4e09ca6e
Sheet: Figure 5.3

Figure 5.3 Trend in average annual SO2 concentrations (2001-2010) per station type
Note: All stations in EU Member States, with at least 75 % data coverage for at least 8 years were included in the analysis. Concentrations per station type (T= traffic, U=Urban/Suburban, R=Rural) are given in µg/m3. In the diagram a geographical bias exists towards central Europe where there is a higher density of stations.
Source: ETC/ACM
The layout version will use colors consistently in the figures, consistent with the color used in Figure 5.3 in the 2011 Report.
Annual mean/day
all | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010
N | 768 | 822 | 912 | 887 | 908 | 913 | 908 | 914 | 858 | 814
aver | 8.06307161458333 | 7.607160583941599 | 7.728529605263159 | 6.699406989853435 | 6.469593612334807 | 6.165773274917854 | 5.65379845814978 | 4.699029540481403 | 4.250078088578086 | 4.085224815724812
U | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010
N | 303 | 321 | 359 | 350 | 353 | 357 | 355 | 359 | 339 | 322
aver | 7.805095709570953 | 7.168274143302177 | 8.03229526462395 | 6.381805714285713 | 6.231798866855524 | 5.948453781512607 | 5.224019718309854 | 4.372303621169916 | 4.159247787610622 | 4.182959627329197
T | 2001.1 | 2002.1 | 2003.1 | 2004.1 | 2005.1 | 2006.1 | 2007.1 | 2008.1 | 2009.1 | 2010.1
N | 106 | 121 | 148 | 144 | 151 | 149 | 149 | 150 | 138 | 120
aver | 9.615481132075473 | 8.249280991735537 | 7.388317567567566 | 6.630458333333333 | 6.550271523178805 | 6.362852348993293 | 5.946986577181207 | 5.322286666666665 | 4.930905797101448 | 4.440283333333331
RL | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010
N | 96 | 102 | 107 | 100 | 110 | 107 | 106 | 106 | 99 | 96
aver | 4.070489583333332 | 3.998588235294118 | 3.958635514018691 | 3.395560000000001 | 3.362381818181818 | 3.442084112149533 | 2.823754716981133 | 2.48929245283019 | 2.244353535353536 | 2.439916666666666
RH | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010
N | 63 | 63 | 63 | 61 | 60 | 62 | 62 | 63 | 61 | 54
aver | 3.488666666666667 | 3.613412698412697 | 3.642650793650794 | 3.031459016393443 | 3.213616666666667 | 3.033451612903225 | 2.589806451612903 | 2.026412698412699 | 2.077967213114754 | 2.31112962962963
R | 2000.9 | 2001.9 | 2002.9 | 2003.9 | 2004.9 | 2005.9 | 2006.9 | 2007.9 | 2008.9 | 2009.9
N | 159 | 165 | 170 | 161 | 170 | 169 | 168 | 169 | 160 | 150
aver | 3.839955974842768 | 3.851521212121212 | 3.841535294117649 | 3.257608695652174 | 3.309876470588236 | 3.292171597633136 | 2.737416666666667 | 2.316739644970415 | 2.180918749999999 | 2.393553333333334
O | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010
N | 200 | 215 | 235 | 232 | 234 | 238 | 236 | 236 | 221 | 222
aver | 10.988505 | 10.78328372093023 | 10.29060851063829 | 9.609831896551727 | 9.071777777777774 | 8.408869747899159 | 8.19125 | 6.505864406779657 | 5.462307692307691 | 4.894563063063067
Spreadsheet: phillip_m_love__30150__9907_OA
Sheet: TOTAL

ENRON CAPITAL & TRADE RESOURCES
OPERATIONAL ANALYSIS - CONSOLIDATED VARIANCE
COMPANY:  ALL
REGION: ALL
 |  |  | Reported |  | Actuals |  | [NAME]
 |  |  | Volume | $'s | Volume | $'s | Volume | $'s
 | Sales:
1 |  | 3rd Party / Inter Enron
2 |  | Liquidations
3 |  | Interdesk
4 |  | Option Premiums
5 |  | Dmd Reimbursements
 | Total Sales:
 | Purchases:
6 |  | 3rd Party / Inter Enron
7 |  | Liquidations
8 |  | Interdesk
9 |  | Option Premiums
10 |  | [NAME]
 | Total Purchases:
 | Intra CTS (EGM / HPL / LRC):
11 |  | Sales
12 |  | Purchases
 | Total Intra CTS Sales / Purchases
 | Imbalances:
13 |  | In Kind
14 |  | Cash Out
15 |  | Cash In
16 |  | Synthetic Storage
 | Total Imbalances:
 | Storage:
17 |  | Injection (Sales to Stg)
18 |  | W/D (Purchase from Stg)
19 |  | Inventory Profit
 |  | Total W/D
 | Total Storage:
20 | Linepack:
21 | Shrinkage:
22 | UA4:
23 | Fuel:
 | Transport Expense:
24 |  | Commodity
25 |  | Demand
 | Total Transport Expense:
 | Transport Revenue:
26 |  | Interstate
27 |  | Intrastate
 | Total Transport Revenue:
 | Intra CTS (EGM / HPL / LRC):
28 |  | Transport Expense
29 |  | Transport Revenue
 | Total Intra CTS Transport
 | Tie Out Schedule Items:
 |  | MTM Income:
30 |  | Current Gross Book Balance
31 |  | Prior Month Book Balance
 |  | Total MTM Income
32 |  | Prudency
33 |  | Financial Liquidations
34 |  | Originations
35 |  | Broker Fees
36 |  | Asset Group Demand Charges
37 |  | [NAME]
38 |  | Interdesk Charges
39 |  | Canada
40 |  | Miscellaneous
 |  | TOTAL
FT-Ontario
 |  | Current Month MTM
 |  | Financial Liquidations
 |  | Originations
 |  | TOTAL FIRM TRADING
 |  | TOTAL GL