tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: c663f84c-f97b-47b6-b0dc-1429be955887
Sheet: Sheet1

Bevölkerung des Freistaates Sachsen nach ausgewählten Altersgruppen | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Wilkau-Haßlau, Stadt - Variante 1
Alter von ... bis                     unter ... Jahren | 2011 | 2015 | 2020 | 2025
1 000
unter 15 | 1139 | 1174 | 1115 | 1012
15 - 65 | 6499 | 6232 | 5672 | 5232
65 und mehr | 3136 | 3059 | 3129 | 3100
Insgesamt | 10774 | 10465 | 9916 | 9344
%
unter 15 | 10.57174679784667 | 11.21834687052078 | 11.24445340863251 | 10.83047945205479
15 - 65 | 60.3211434935957 | 59.55088389870998 | 57.20048406615571 | 55.9931506849315
65 und mehr | 29.10710970855764 | 29.23076923076923 | 31.55506252521178 | 33.1763698630137
Insgesamt | 100 | 100 | 100 | 100
Abhängigkeitsquotient
Jugendquotient | 17.52577319587629 | 18.8382541720154 | 19.65796897038082 | 19.34250764525994
Altenquotient | 48.25357747345745 | 49.08536585365854 | 55.16572637517631 | 59.25076452599388
Gesamtquotient | 65.77935066933375 | 67.92362002567394 | 74.82369534555711 | 78.59327217125383
Gebietsstand: | 1. Januar 2012
Quelle: | 2011 Bevölkerungsfortschreibung auf Basis der [NAME] vom 03. Oktober 1990
 | 2012 - 2025 Bevölkerungsprognose
Bevölkerung jeweils am 31. Dezember
Prognoseergebnisse werden bei der Veröffentlichung immer auf volle [NAME] gerundet. [NAME] basieren [NAME] ungerundeten Werten. Beim [NAME] der [NAME] werden Ihnen die ungerundeten [NAME] zur Verfügung gestellt, damit [NAME] eigenen Berechnungen genauer durchführen können. Die Darstellung der Ergebnisse sollte dann aber wieder gerundet erfolgen.
Spreadsheet: 525325d1498667695-mathmatical-issue-need-solution-and-need-formula-to-calculate-number-of-working-shift-shift-calculation-trials
Sheet: Sheet1

Product Name |  | DDDD |  |  |  | Number | Time | working hours | Total hours / operator/ Day | No. / 1 Hour | Average operator | No. Of hours / all operator/ Day | No. / shift/ all operator
Batch No. |  | 1222 |  |  | Shift 1 | 300 | 09-12 | 3 |  |  | 10
[NAME] |  | 1000 |  |  | Shift 2 | 200 | 13-15 | 2 |  |  | 10
[NAME] |  | 1000000 |  |  | Shift 3 | 300 | 15-18 | 3 |  |  | 10
[NAME] |  | 9523.809523809523
Expected No. of hours taken |  |  |  | Hours
Inspection Start Day |  | 2017-06-28 00:00:00 |  |  | Day | 1 | 1 | 1 | 2 | 2 | 2 | 3 | 3 | 3
Inspection Start Time |  | 13:00:00 |  |  |  | Shift 1 | Shift 2 | Shift 3 | Shift 1 | Shift 2 | Shift 3 | Shift 1 | Shift 2 | Shift 3
Expected Finished date & time |  | 2017-06-29 00:00:00 |  | 14:30:00
Expected No. of shift taken |  | 3.5 shift |  |  | Hours
Starting Shift No. |  | shift 2 |  |  | Finish Time
 |  |  |  |  | Finish Date
Spreadsheet: 540548d1506768631-how-to-use-multiple-ifs-excel-forum
Sheet: before

 | scenario 1 |  |  | scenario 2 |  |  | scenario 3 |  |  | scenario 4
 | base | 3000 |  | base | 3000 |  | base | 3000 |  | base | 3000
 | result 1 | 3220 |  | result 1 | 4500 |  | result 1 | 3300 |  | result 1 | 2600
 | result 2 | 3000 |  | result 2 | 2600 |  | result 2 | 2700 |  | result 2 | 2700
 | average |  |  | average |  |  | average |  |  | average
 | remarks |  |  | remarks |  |  | remarks |  |  | remarks
 | scenario 5 |  |  | scenario 6 |  |  | scenario 7
 | base | 2130 |  | base | 2130 |  | base | 2130
 | result 1 | 2500 |  | result 1 | 2000 |  | result 1 | 2130
 | result 2 | n/a |  | result 2 | n/a |  | result 2 | n/a
 | average | 2500 |  | average | 2000 |  | average | 2130
 | remarks |  |  | remarks |  |  | remarks
Spreadsheet: 771723d1646816110-why-column-with-address-in-side-can-not-work-and-substitute-can-not-remove-the-quote-how-to-put-a-name-into-columns-formula-and-make-it-draggable-tms
Sheet: Sheet1

 |  |  |  | AA | BB | CC | DD | EE
 |  |  |  |  |  | DNR: | ABCD2 | =Sheet1!$E$3:E$3
 |  |  |  | =COLUMNS(ABCD2)
 |  |  |  |  |  |  |  |  |  |  | =COLUMNS($E$3:$L$3)
 |  |  |  |  |  |  |  |  |  |  | (using Evaluate Formula)
 |  |  |  | =COLUMNS(ABCD2:ABCD2)
Spreadsheet: louise_kitchen__23837__2QYTD Orig w notes
Sheet: Canada Power

Canada Power
Mid Year 2001
Originator |  | Commodity |  | Team |  | Total |  | %Total
Biever* |  | Power |  | Canada |  | 2283200
Devries |  | Power |  | Canada |  | 500000
[NAME] |  | Power |  | Canada |  | 2127333
Law |  | Power |  | Canada |  | 138233
Davies |  | Power |  | Canada
Total
*Enron Retail Number
Spreadsheet: 170076d1343153779-need-help-to-create-sales-register-with-automatic-update-my-data-sample1
Sheet: Sheet1

sales Register
sr. no. | date | invoice no | cstomer name | sales amount
1 | 2012-01-01 00:00:00 | INV001 | AAAAAAAAAAA | 158
2 | 2012-01-02 00:00:00 | INV002 | WWWWWWWWWWWW | 158
3 | 2012-01-03 00:00:00 | INV003 | AAAAAAAAAAA | 1254
4 | 2012-01-04 00:00:00 | INV004 | [NAME] | 665
5 | 2012-01-05 00:00:00 | INV005 | FFFFFFFFFFFFFFFF | 3659
6 | 2012-01-15 00:00:00 | INV006 | EEEEEEEEEEEE | 2668
7 | 2012-01-16 00:00:00 | INV007 | RRRRRRRRRR | 265
8 | 2012-01-18 00:00:00 | INV008 | TTTTTTTTTTTT | 154
9 | 2012-01-19 00:00:00 | INV009 | FFFFFFFFFFFFFFFF | 2668
10 | 2012-01-20 00:00:00 | INV010 | AAAAAAAAAAA | 246
11 | 2012-01-25 00:00:00 | INV011 | WWWWWWWWWWWW | 2658
12 | 2012-01-27 00:00:00 | INV012 | TTTTTTTTTTTT | 36
13 | 2012-01-30 00:00:00 | INV013 | [NAME] | 258
14 | 2012-02-01 00:00:00 | INV014 | HHHHHHHHHHHHHHHHHHH | 25
15 | 2012-02-03 00:00:00 | INV015 | JJJJJJJJJJJJJJJJJ | 25
16 | 2012-02-05 00:00:00 | INV016 | [NAME] | 21
17 | 2012-02-10 00:00:00 | INV017 | UUUUUUUUUUUUU | 1245
18 | 2012-02-15 00:00:00 | INV018 | WWWWWWWWWWWW | 1245
19 | 2012-02-22 00:00:00 | INV019 | RRRRRRRRRR | 365
20 | 2012-02-23 00:00:00 | INV020 | TTTTTTTTTTTT | 3695
21 | 2012-02-25 00:00:00 | INV021 | AAAAAAAAAAA | 68
22 | 2012-02-28 00:00:00 | INV022 | BBBBBBBBBBBBBB | 6889
23 | 2012-03-01 00:00:00 | INV023 | HHHHHHHHHHHHHHHHHHH | 68
24 | 2012-03-04 00:00:00 | INV024 | KKKKKKKKKKKKKKK | 21
25 | 2012-03-05 00:00:00 | INV025 | MMMMMMMMMMMMMMM | 255
26 | 2012-03-06 00:00:00 | INV026 | KKKKKKKKKKKKKKK | 3336
27 | 2012-03-12 00:00:00 | INV027 | WWWWWWWWWWWW | 658
28 | 2012-03-15 00:00:00 | INV028 | FFFFFFFFFFFFFFFF | 3658
29 | 2012-03-18 00:00:00 | INV029 | FFFFFFFFFFFFFFFF | 3659
30 | 2012-03-20 00:00:00 | [NAME] | FFFFFFFFFFFFFFFF | 3658
31 | 2012-03-21 00:00:00 | INV031 | WWWWWWWWWWWW | 3658
32 | 2012-03-23 00:00:00 | INV032 | [NAME] | 316
33 | 2012-03-24 00:00:00 | INV033 | GGGGGGGGGG | 315
34 | 2012-03-27 00:00:00 | INV034 | BBBBBBBBBBBBBB | 468
35 | 2012-03-29 00:00:00 | INV035 | EEEEEEEEEEEE | 658
36 | 2012-04-01 00:00:00 | INV036 | TTTTTTTTTTTT | 365
37 | 2012-04-03 00:00:00 | INV037 | [NAME] | 658
38 | 2012-04-06 00:00:00 | INV038 | UUUUUUUUUUUUU | 658
39 | 2012-04-08 00:00:00 | INV039 | KKKKKKKKKKKKKKK | 658
40 | 2012-04-12 00:00:00 | INV040 | LLLLLLLLLLLLLLL | 69
41 | 2012-04-13 00:00:00 | INV041 | PPPPPPPPPPP | 98
42 | 2012-04-16 00:00:00 | INV042 | LLLLLLLLLLLLLLL | 48
43 | 2012-04-19 00:00:00 | INV043 | PPPPPPPPPPP | 98
44 | 2012-04-21 00:00:00 | INV044 | WWWWWWWWWWWW | 989
45 | 2012-04-23 00:00:00 | INV045 | [NAME] | 659
46 | 2012-04-27 00:00:00 | INV046 | QQQQQQQQQQ | 659
47 | 2012-04-28 00:00:00 | INV047 | SSSSSSSSSS | 656
Spreadsheet: 691736d1597847847-vlookup-and-count-excel
Sheet: Sheet1

 |  | firsttry |  | secondtry |  | thirdtry
name | colour | grade1 | total1 | grade2 | total2 | grade3 | total3
a | blue | pass | 90 | pass | 90 | fail | 43
b | blue | pass | 70 | pass | 94 | fail | 66
c | blue | pass | 80 | pass | 91 | fail | 1
d | red | pass | 90 | pass | 95 | fail | 0
e | red | pass | 90 | pass | 99 | fail | 5
f | red | fail | 40 | pass | 100 | fail | 4
g | red | fail | 33 | pass | 153 | pass | 90
h | red | fail | 55 | pass | 98 | pass | 100
i | green | fail | 11 | fail | 40 | pass | 120
j | red | pass | 98 | fail | 0 | pass | 900
k | green | fail | 20 | fail | 0 | pass | 1000
Spreadsheet: 472439d1469600792-how-to-search-filter-data-by-various-basis-from-other-sheets-syllabus-book
Sheet: EEE DEPT

Department | EEE | Course Content
Level | 1
Term | 1
Subject | Physics
Subject Code | Phy 121
[NAME] | Structure of Matter
Credit Hour | 3
Contact Hour | 3
Department | EEE | Course Content
Level | 1
Term | 1
Subject | Chemistry
Subject Code | Chem 123
[NAME] | Inorganic Quantitative Analysis
Credit Hour | 2
Contact Hour | 2 |  |  |  | Waves and oscillations: differential equation of a simple harmonic oscillator, total energy and average energy, combination of simple harmonic oscillations, Lissajous figures, spring-mass system, calculation of time period of torsional pendulum, damped oscillation, determination of damping co-efficient; forced oscillation, resonance, two-body oscillations, reduced mass, differential equation of a progressive wave, power and intensity of wave motion, stationary wave, group velocity and phase velocity, architectural acoustics, reverberation and Sabine's formula.
Department | EEE | Course Content
Level | 1
Term | 2
Subject | Accounting
Subject Code | Acc 125
[NAME] | Principles of Accounting
Credit Hour | 3
Contact Hour | 3
Department | EEE | Course Content
Level | 1
Term | 2
Subject | Economics
Subject Code | Eco 127
[NAME] | Engineering Economics
Credit Hour | 2
Contact Hour | 2
Spreadsheet: 171060d1343607565-match-and-determine-frequency-match-and-frequency
Sheet: Sheet1

 | Sample Table
 | Table / File 1 |  | Table / File 2 |  | Table / File 3 |  | Table / File 4
 | MNDJ17 |  | 769503 |  | 704706 |  | 769503
 | [NAME] |  | 769301 |  | 704747 |  | 769403
 | MNDJ17 |  | 711100 |  | 711100 |  | 769303
 | 769311 |  | 704747 |  | 769301 |  | MNDJ17
 | 769303 |  | 704706 |  | 769303 |  | [NAME]
 | 769403 |  |  |  | 769403 |  | MNDJ17
 | 769503 |  |  |  | 769503 |  | 704706
 | Scenario or Situation
 | I have 4 Excel files with a large list of IDs in them   -- Table 1 is organized by sales   -- Table 2 is organized by known products   -- Table 3 is QAs list of known product IDs   -- Table 4 is table that a department is working  I need to compare these files, match up product IDs & verify which list is more valid or confirm the product IDs that are in actual used
 | After verifying Product IDs usage, looking to do the following: -- Develop some type of "Match" verifification between 2 or all the    columns or files, which will be compliled into 1 worksheet -- Determine frequency of how many times an ID matches between    all fo the tables or files -- Perhaps, priortize product IDs by the frequency that the IDs     shows up
Spreadsheet: 866207d1713180168-calculate-completion-date-and-time-with-conditions-and-exclusions-estimated-date-and-time-example-sheet
Sheet: Lead Times

Product | Product No. | Quantity | Total Time To Complete | Average Time to [NAME]
Product A | 1 | 35 | 01:30:00
Product B | 2 | 20 | 00:34:00
Product C | 3 | 15 | 01:20:00
Product D | 4 | 40 | 02:20:00
Product E | 5 | 50 | 04:05:00
Spreadsheet: 151e5902-ceed-4a39-a1a3-add7807b2c23
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
 | 6302.0 Average Weekly Earnings, Australia
 | TABLE 8. Average Weekly Earnings, Public Sector - Australia (Dollars) - Seasonally Adjusted
Related Information: | Summary Publication | Explanatory Notes | Inquiries
 | Glossary
Data Item Description |  |  | Series Type | Series ID | Series Start | Series End | No. Obs. | Unit | Data Type | [NAME]. | Collection Month
Earnings; [NAME]; Full Time; Adult; Ordinary time earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773696V | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; [NAME]; Full Time; Adult; Total earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773699A | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; [NAME]; Total earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773705K | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; Females; Full Time; Adult; Ordinary time earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773697W | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; Females; Full Time; Adult; Total earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773700X | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; Females; Total earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773706L | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; Persons; Full Time; Adult; Ordinary time earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773698X | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; Persons; Full Time; Adult; Total earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773701A | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
Earnings; Persons; Total earnings ;  Public sector ; |  |  | Seasonally Adjusted | A2773707R | 2012-05-15 00:00:00 | 2012-11-15 00:00:00 | 3 | $ | RATIO | Quarter | 2
© Commonwealth of Australia  2013
Spreadsheet: 270129d1381395838-multiple-if-functions-excel-forum
Sheet: Sheet1

Date | Invoice/Account # | Supplier | Description | Code | Cash In | GST on Income
Opening Balance
2013-02-28 00:00:00 |  | x | item | 100 | 100
2013-03-01 00:00:00 |  | x | item | 3 | 50
2013-03-03 00:00:00 |  | x | item | 5 | 200
Closing Balance
Spreadsheet: 888455d1738941378-please-help-with-results-table-vlookup-match-index-functions-or-a-table-gymnastics-results-forum
Sheet: individuals & overall

RESULTS KEY STEPS 1 GYMNASTICS DEC 2024
TEAMS
SCHOOL |  | SCORE
1st
2nd
3rd
4th
5th
6th
7th
8th
9th
10th
11th
INDIVIDUALS
FLOOR Competitor / School |  | SCORE |  | BENCH Competitor / School |  | SCORE
1st |  |  |  | 1st
2nd |  |  |  | 2nd
3rd |  |  |  | 3rd
Spreadsheet: 742082d1627506729-extract-text-form-text-string-extract-5-charactors-in-front-of-all-left-parenthese-dataset
Sheet: TEST 

xxxxxx
crossmatches are negative and B Cell Flow crossmatches are positive with 2/15/2031 and 4/22/2061 sera are negative vs ZZZZZZ. Concurrent crossmatches with the same sera are negative. IgG antibody screens with the same sera detect DSA to DR53 (MFI= 2051 and 2518) and DQ6 (MFI= 20484 and 23931) respectively; in adfdition, the tests with 4/22/2061 serum detect DSA in possible range to DQ2 (MFI= 822).zxxx has preformed DSA.
crossmatches with 03/01/40 and 12/19/50 sera are negative vs AAA0. Concurrent T and B cell Flow Auto crossmatches with the same sera are negative. IgG antibody screens with 3/01/40 serum show no detectable antibodies to donor and with 12/19/50 serum detect DSA in possible range to DR13 (MFI=660). C1q antibody screens with 3/01/50 serum detect DSA in possible range to Cw6 (MFI=690); C1q antibody screens were not performed with 12/19/50 serum. IgG DSA to [NAME] (MFI=1047 to 1459) and DQ6 (MFI=1060 to 1623).
crossmatches are negative and B cell Flow crossmatches with 3/4/50 and 10/23/51 sera are positive vs [NAME]. T and B cell Flow Auto crossmatches with both sera are negative. IgG antibody screens with the same sera detect DSA to DQ7 (MFI=30607 and 29189, respectively). C1q antibody screens were not performed with 3/4/50 serum. C1q antibody screens with 10/23/51 serum detect DSA to DQ7 (MFI=42412). xxx has IgG DSA to A2 (MFI=1345) and DR52 (MFI=1343). Incompatible donor.
crossmatches with 4/16/29 and 7/11/26 sera are negative vs YYYYYYY. Concurrent T and B cell Flow Auto crossmatches with the same sera are negative. antibody screens with4/16/29 serum show no detectable antibodies to donor and with 7/11/26 serum detect DSA to A1. C1q antibody screens with 4/16/29 are invalid due to high background that could not be removed after adsorption; antibody screens with 7/11/26 serum were not performed. Historically, xxx has IgG DSA to [NAME] (MFI=1392), [NAME] (MFI=1730), [NAME] (MFI=2348), Cw6 (MFI=2084) and DR7 (MFI=1262). xxx also has DSA to DQ2 (MFI=1499).
Spreadsheet: 867507d1714381260-using-array-formula-and-relative-referencing-most-efficiently-map-for-array-aligw
Sheet: Sheet1

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 |  | 4
 |  | 5
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Spreadsheet: 741337d1626976901-count-items-based-on-various-criteria-including-date-sample
Sheet: Sheet1

My Report
Date | Total Surveys Conducted that Month | Sum of reponses that state [NAME] | % Customers Satisfied
2021-08-01 00:00:00
2021-09-01 00:00:00
2021-10-01 00:00:00
2021-11-01 00:00:00
2021-12-01 00:00:00
2022-01-01 00:00:00
2022-02-01 00:00:00
2022-03-01 00:00:00
Spreadsheet: 02fb5f3f-56a6-4818-807b-8cd4ac3cad3e
Sheet: Sheet1

Number of Land Trusts and Acres Protected by Local and State Land Trusts as of December 31, 2010 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
State | Number of Land Trusts | Acres Owned | Acres Under Easement | Acres Acquired and [NAME] by Other Means | Total Acres Conserved
AK | 8 | 1644.29 | 7135.94 | 33769 | 42549
AL | 8 | 8571.35 | 97034.78 | 55409.45 | 161015
AR | 4 | 928 | 12731 | 414 | 14073
AZ | 22 | 1144.44 | 45707.53 | 482959 | 529811
CA | 197 | 538681.93 | 651270.013 | 1113490.54 | 2303442
CO | 38 | 5916 | 1141097.92 | 78036 | 1225050
CT | 137 | 56530.84 | 36053.64 | 6964 | 99549
DC | 3 | 1 | 6 | 0 | 7
DE | 6 | 21709 | 2588 | 79000 | 103297
FL | 33 | 11447.25 | 45164 | 114168 | 170779
GA | 22 | 3155 | 223652.75 | 19216 | 246024
HI | 13 | 496.4 | 17150 | 2853 | 20499
IA | 5 | 6394 | 12346 | 88491 | 107231
ID | 12 | 6297 | 52478.76 | 26061 | 84837
IL | 41 | 12464.42 | 14856.52 | 64202.89 | 91524
IN | 27 | 14386 | 18321 | 4549 | 37256
KS | 8 | 624 | 19924 | 0 | 20548
KY | 13 | 2572.15 | 14527.87 | 6876 | 23976
LA | 4 | 7 | 29232.6 | 533 | 29773
MA | 159 | 129451.93 | 80344.75 | 123536.75 | 333334
MD | 56 | 4537.231999999996 | 167395.1528 | 18707.88 | 190640
ME | 88 | 115698.11 | 1577299.06 | 103390 | 1796387
MI | 43 | 45209.78 | 86354.7 | 30254 | 161819
MN | 7 | 4021 | 37741 | 9010 | 50772
MO | 14 | 150775 | 17438 | 2897 | 171110
MS | 6 | 2207.37 | 88931 | 2761 | 93899
MT | 15 | 41287.1 | 977339.8 | 112181 | 1130808
NC | 35 | 36474.57 | 154391.88 | 148802.46 | 339669
ND | 0 | 0 | 0 | 0 | 0
NE | 5 | 16143 | 10867 | 45 | 27055
NH | 34 | 94527.6 | 200725.82 | 53019.8 | 348274
NJ | 37 | 62058.56 | 14607.93 | 156911 | 233578
NM | 8 | 322032 | 281816 | 17203 | 621051
NV | 5 | 492 | 750 | 43770 | 45012
NY | 97 | 169887.45 | 281991.786 | 521927.5 | 973807
OH | 44 | 22039.38 | 78684.15 | 12423 | 113146
OK | 3 | 91 | 18199 | 1 | 18291
OR | 23 | 11084 | 36851 | 5451 | 53386
PA | 103 | 46048.24500000002 | 188944.273 | 267251.35 | 502243
RI | 47 | 18051.554 | 9918.668000000001 | 1961.32 | 29932
SC | 24 | 8065.9 | 216337.7 | 21172 | 245576
SD | 2 | 280 | 1171 | 5361 | 6812
TN | 20 | 10829.75 | 58480.6 | 67569.79999999999 | 136881
TX | 36 | 31060 | 300754 | 43446.88 | 375261
UT | 8 | 1082.67 | 47075.47 | 17559.86 | 65718
VA | 36 | 8075.45 | 642945.603 | 478766 | 1129787
VT | 35 | 39040.8 | 463061.75 | 111868 | 613971
WA | 37 | 32852.29 | 60169.08 | 186456.6 | 279478
WI | 58 | 27595.89 | 68797.96 | 23565.5 | 119960
WV | 8 | 243 | 24453 | 7000 | 31696
WY | 5 | 498 | 198248 | 326521 | 525267
Totals | 1699 | 2144709 | 8833368 | 5097783 | 16075860
Spreadsheet: frank_ermis__11217__West NatGas Prices 1119
Sheet: Gas Average FinIdx

FinIdx Curves
 |  | WEST NATURAL GAS PRICES- Fin Idx
 |  | AS OF
 |  |  |  |  |  |  |  |  |  | Last-Day | Cash | Cash | Change | BOM | BOM | Change | Prompt Month | Change | Q4 | Change | Winter 2001-02 | Change | Q1 | Change | Q2 | Change | Summer 2002 | Change | Q3 | Change | Q4 | Change | Winter 2002-03 | Change
 |  |  |  |  |  |  |  |  |  | Cash Settle | Price | Spread |  | Price | Spread |  |  |  | 2001 |  | Nov-01/Mar-02 |  | 2002 |  | 2002 |  | Apr-02/Oct-02 |  | 2002 |  | 2002 |  | Nov-02/Mar-03
 |  | California Region Notional
 |  |  |  |  | Sheet Name | Row Num for CurveName | Column Letter for Date
 |  |  |  | Basis | IndexCurves | 13 | B
 |  | Gas Trading |  | IntraMonth | CurveFetch | 4 | D
 |  |  |  |  |  |  |  |  | IntraMonth
 |  |  |  | IntraMonth Hub Curve | IF-HEHUB
 |  |  |  | IntraMonth Month
 |  |  |  |  |  |  |  |  | Date Start |  |  |  |  |  |  |  |  |  | 2001-10-01 00:00:00 |  |  |  | 2002-01-01 00:00:00 |  | 2002-04-01 00:00:00 |  | 2002-04-01 00:00:00 |  | 2002-07-01 00:00:00 |  | 2002-10-01 00:00:00 |  | 2002-11-01 00:00:00
 |  |  |  |  |  |  |  |  | Date End |  |  |  |  |  |  |  |  |  | 2001-12-01 00:00:00 |  | 2002-03-01 00:00:00 |  | 2002-03-01 00:00:00 |  | 2002-06-01 00:00:00 |  | 2002-10-01 00:00:00 |  | 2002-09-01 00:00:00 |  | 2002-12-01 00:00:00 |  | 2003-03-01 00:00:00
 |  | WEST REGION BASIS NOTIONAL |  | Intra-Month | Basis |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | IntraMonth Match |  | Basis Match
 |  | NGI-PGE/CG |  | NGI-PGE/CG | GD-PG&E/CITIGAT |  |  |  |  |  |  |  |  |  |  |  |  |  |  | -0.043 |  |  |  | -0.0483 |  | -0.01 |  |  |  | -0.045 |  | -0.03
 |  | NGI-PGE/TOPOCK |  | NGI-PGE/TOPOCK | GDP-PGE/TOPOCK
 |  | NGI-MALIN |  | NGI-MALIN | GDP-MALIN-CTYGA
 |  | NGI-SOCAL |  | NGI-SOCAL | GDP-CAL BORDER
 |  | Southwest Region Notional
 |  | SAN JUAN |  | IF-ELPO/SJ | GDP-ELPO/SANJUA
 |  | ELPO/PERMIAN |  | IF-ELPO/PERMIAN | GDP-ELPO/PERM2
 |  | WAHA |  | IF-WAHA-TX | GDP-WAHA
 |  | NGPL/MIDCON |  | IF-NGPL/MIDCON | GDP-NGPL/OK
 |  | Northwest Region Notional
 |  | OPAL |  | IF-NWPL_ROCKY_M | GDP-KERN/OPAL
 |  | STANFIELD |  | NW-STANFIELD | GD-NW STANFIELD
 |  | SUMAS |  | IF-NWPL/CNBR-US | GDP-NTHWST/CANB
 |  | AECO |  | CGPR-AECO/USIM | [NAME]
 |  | CIG |  | IF-CIG/RKYMTN | GDP-CIG/RKYMTN
 |  | Ontario Region Notional
 |  | Central Region Notional
 |  | East & Texas Region Notional
 |  | Nymex
 |  | Nymex |  | GDP-HEHUB | NG
Spreadsheet: c1f1e2a5-250b-4256-aaf6-65bf1d953ba9
Sheet: Sheet1

Announcement of Class and Component Prices for March 2008 1/ | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
Release date: April 4, 2008
Class II Price: 2/ |  |  |  | 15.63 | (per hundredweight)
Class II Butterfat Price: |  |  |  | 1.3674 | (per pound)
Class III Price: |  |  |  | 18 | (per hundredweight)
Class III Skim Milk Price: |  |  |  | 13.72 | (per hundredweight)
Class IV Price: |  |  |  | 14.17 | (per hundredweight)
Class IV Skim Milk Price: |  |  |  | 9.75 | (per hundredweight)
Butterfat Price: |  |  |  | 1.3604 | (per pound)
Nonfat Solids Price: |  |  |  | 1.0833 | (per pound)
Protein Price: |  |  |  | 4.3331 | (per pound)
Other Solids Price: |  |  |  | 0.0493 | (per pound)
Somatic Cell Adjustment Rate: |  |  |  | 0.00098 | (per 1,000 somatic cell count)
Product Price Averages:
Butter |  |  |  | 1.2539 | (per pound)
Nonfat Dry Milk |  |  |  | 1.2512 | (per pound)
Cheese |  |  |  | 1.9575 | (per pound)
Dry Whey |  |  |  | 0.2435 | (per pound)
1/ See Price [NAME] at www.ams.usda.gov/dyfmos/mib/price_form_2008.htm
2/ The Class II skim milk price is $11.24; this was announced on 2/22/08.
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send a message to "[EMAIL]"
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subscribe MilkOrderPrice YourFirstName YourLastName
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send a message to "[EMAIL]"
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Spreadsheet: 736718d1623832894-transpose-formula-error-transpose
Sheet: Sheet1

 | CODE | A | B | C | D | E |  |  |  | NUMBER
 | NUMBER | 50 | 65 | 12 | 145 | 65 |  |  | A | 50
 |  |  |  |  |  |  |  |  | B | 65
 |  |  |  |  |  |  |  |  | C | 12
 |  |  |  |  |  |  |  |  | D | 145
 |  |  |  |  |  |  |  |  | E | 65
 |  |  |  |  |  |  |  |  | #N/A | #N/A
 |  |  |  |  |  |  |  |  | #N/A | #N/A