tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 485953d1477211147-moving-every-second-row-into-the-row-above-book1
Sheet: Sheet1

Column A | Column B |  |  |  | Column A | Column B |  | Column A | Column B | Column C
2015-09-19 00:00:00 | [NAME], [NAME]
2015-09-25 00:00:00 | [NAME], [NAME]
 | 51.78 Regular
2016-09-08 00:00:00 | Ngapuhi Service Station, Kaikohe
 | 27.46 Regular
2015-08-02 00:00:00 | BP 2GO WAIPAPA
2015-08-20 00:00:00 | BP 2GO WAIPAPA
 | 32.71 Unleaded
2015-07-31 00:00:00 | [NAME], [NAME]
 | 26.49 Regular
2015-08-22 00:00:00 | Caltex Western Hills Drive, [NAME]
 | 32.37 Regular
2015-08-26 00:00:00 | Ngapuhi Service Station, Kaikohe
 | 24.73 Regular
Spreadsheet: 0d9394d6-138d-40d5-9334-c35304de69dd
Sheet: Sheet1

UTAH STATE OFFICE OF EDUCATION | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10
District Pupil Transportation
Annual Statistical Report Form "C" ([NAME])
District: |  |  |  | Date: |  |  |  |  | Year:
 |  | Annual Activity Trip Statistics |  |  |  |  |  |  |  | Instructions:
 | Elementary |  |  |  |  | Secondary |  |  |  | For Activity & Field Trips, supply current year summary statistics from activity and field trip reports. For Additional Mileage Summary Statistics, supply current year summary statistics from other mileage reports as needed.
 | [NAME] | Pupils | Trips |  | [NAME] | Pupils | Trips
Prior Year
Current Year
 |  | Annual Field Trip Statistics
 | Elementary |  |  |  |  | Secondary
 | [NAME] | Pupils | Trips |  | [NAME] | Pupils | Trips
Prior Year
Current Year
 |  | Annual Mileage Summary Statistics |  |  |  |  |  |  | Total [NAME]
 | Summer Program Miles | Other Program [NAME]: ______________________ | Repair Dead Miles | Training Miles | Total "To & From" Miles from A1 Report | Other Miles Unaccounted for. | Total miles from "all" mileage report forms. |  |  | Instructions: Total miles from beginning & ending odometer reports of all buses in fleet. If an odometer was down for a period of time, best estimate of total miles should be used for that bus.
Prior Year
Current Year
Note: The total miles from "all" mileage forms will not match with total odometer miles unless the "other miles" are used to make up the differences. A high percentage of "unaccounted" other miles may indicate a problem with reporting methods, or may indicate unaccounted miles due to unauthorized use by drivers. Changes in this annual Statistics Report have been made in an effort to meet the needs of current standards, pages 139, 140, and 141. The final paragraph on page 141 outlines the importance of complete, accurate data, and also outlines that the value of the data more than offsets the effort expended in accumulating and maintaining the required records.
Spreadsheet: 805662d1668810338-return-array-with-values-repeated-n-times-based-on-another-criteria-book2-2-2-
Sheet: Sheet1

allo_id | allo_wh_n |  | OUTPUT
allo-750-001 | 1
allo-750-002 | 1 |  |  |  |  | allo-750-002
allo-750-003 | 1 |  |  |  |  | allo-750-003
allo-750-004 | 2 |  |  |  |  | allo-750-004
allo-750-005 | 3 |  |  |  |  | allo-750-004
allo-750-006 | 4 |  |  |  |  | allo-750-005
 |  |  |  |  |  | allo-750-005
 |  |  |  |  |  | allo-750-005
 |  |  |  |  |  | allo-750-006
 |  |  |  |  |  | allo-750-006
 |  |  |  |  |  | allo-750-006
 |  |  |  |  |  | allo-750-006
Spreadsheet: cca7042f-3164-4be2-9e01-3aa47c6695ee
Sheet: Sheet1

Test Referenced | Entry Type | Mayo ID | Description | Reporting Description | Method | Collection Container | Temperature | Stability | [NAME] | Unit of Measure | [NAME] | Minimum Volume | Reject Due To | Reference Values | Days/Times Performed | Analytic Time | Maximum Lab Time | CPT Units | CPT Code | LOINC® Code | LOINC® Attributes | Always Performed | Orderable Separately | Performing Location
PF199 | Test | PF199 | Carbohydrate Antigen 19-9 (CA 19-9), Pleural Fluid | CA 19-9, Pleural Fluid | Immunoenzymatic Assay |  |  |  | 2 | mL | Container/Tube: Plain, plastic, screw-top tube [NAME]: 2 mL | 0.5 mL (Samples <0.5 mL may be r | Hemolysis	Mild OK; Gross reject Thawing	Warm Reject; Cold OK Lipemia	NA Icterus	NA Other	NA | An interpretive report will be provided. | Monday through Friday; Varies | Same day/1 day | 3 days | 1 | 86301 |  |  |  |  | Rochester
PF199 | [NAME] | PLRFLD | Pleural Fluid |  |  |  | Frozen | 30 days
PF199 | Result | P199 | CA 19-9, Pleural Fluid | CA 19-9, Pleural Fluid | Numeric |  |  |  |  | U/mL |  |  |  |  |  |  |  |  |  | 19163-5 | [NAME] 19-9:ACnc:Pt:Plr fld:Qn:
PF199 | Result | SITE8 | Site | Site | Numeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 39111-0 | Body site:[NAME]:Pt:^Patient:Nom:
Spreadsheet: mary_hain__25859__IOU04
Sheet: Rate Case Assumptions

How the rate case assumed loads and market forcast distributed the benefits.
 |  | Load | Price | Market | Benefit in Millions
IOU
 | Exchange | 900
 | RL | 1000 | 19.25 | 28.1
Public
 | PF | 4225 | 19.25 | 28.1
 | FPS I&S | 125 | 14.25 | 28.1
DSI
 | IPTAC | 1490 | 23 | 28.1
Spreadsheet: 46387d1245261631-if-and-vlookup-formula-order-form
Sheet: Order Form

ORDER FORM
[NAME] To: | SAME | Ship To:
 |  |  |  |  |  |  |  | Terms: Open-60 days
 |  |  |  |  |  |  | Taken By:
Order Date: |  |  | P.O. #:
Product   No. | Description | Quantity | Cost/Bottle | Total | Serial No. | Expiration Date
1CL | MS | 250 | 14.55 | 3637.5
12Cl | ERS | 1200 | TBD
 |  |  | Subtotal | 3637.5
 |  |  | Freight
 |  |  | Total
 | Delivery Date:
 | SAP Due Date: | 1900-04-29 00:00:00
 | Date Wanted:
Labeling Information
Product No. | Description | Full Shippers/ Cases | Btls/Shipper | Partial Shippers/ Cases | Btls/Partial Shippers/ Cases | Total Btls
1CL | MS | 154 | 1.62 | 1 | 0.5199999999999818 | 250
12Cl | ERS | 8 | 150 | 0 | 0 | 1200
Gaylord | Product | GLB11A's
Cooler
Spreadsheet: 50953d1250542185-understanding-lookup-formula-example
Sheet: Sheet1

AAA-001 | AAA BBB 002 | BBB 003 | AAA-004 | AAA BBB | BBB | AAA
 |  |  |  | X | X |  | AAA BBB
 | X | X |  |  |  |  | AAA BBB 002
 |  |  |  | X |  |  | AAA BBB
 |  |  |  |  |  | X | AAA
X |  |  |  |  |  |  | AAA-001
 | X | X | X | X | X |  | AAA BBB
 |  |  |  | X |  |  | AAA BBB
 | X | X |  |  |  |  | AAA BBB 002
 | X |  |  |  |  |  | AAA BBB 002
 |  |  | X |  |  |  | AAA-004
Spreadsheet: 784542d1655817386-lookup-previous-price-in-price-list-previous-price
Sheet: Price List

Date | Site | Supplier | P/N | MOQ | Price | Previous price
2022-06-21 00:00:00 | Paris | S1 | 123 | 10 | 12 |  |  |  |  |  | Task:
2022-06-21 00:00:00 | Paris | S1 | 258 | 30 | 16.5 |  |  |  |  |  | Lookup previous price matching with Site, [NAME], P/N and MOQ. If MOQ does not match, look for the closest value instead.
2022-06-21 00:00:00 | Paris | S1 | 258 | 60 | 12.6 |  |  |  |  |  | If the previous price does not exist for the criteria above, show "-".
2022-06-21 00:00:00 | Prague | S1 | 456 | 100 | 6.8 |  |  |  |  |  | Data may not be sorted
2022-06-21 00:00:00 | Prague | S1 | 456 | 1000 | 4.5
2022-06-21 00:00:00 | Prague | S1 | 456 | 10000 | 3.8
2022-06-18 00:00:00 | London | S2 | 147 | 100 | 15
2022-06-18 00:00:00 | Paris | S2 | 123 | 20 | 10.6
2022-06-18 00:00:00 | Paris | S2 | 159 | 1000 | 14
2022-06-18 00:00:00 | Prague | S2 | 369 | 4500 | 13
2022-06-18 00:00:00 | Prague | S2 | 369 | 13500 | 10.1
2022-06-18 00:00:00 | Prague | S2 | 369 | 26000 | 8.2
2022-05-15 00:00:00 | Prague | S3 | 369 | 4500 | 12
2022-05-15 00:00:00 | Prague | S3 | 369 | 26000 | 7.4
2022-04-18 00:00:00 | Paris | S1 | 123 | 10 | 14
2022-04-18 00:00:00 | Paris | S1 | 258 | 30 | 17
2022-04-18 00:00:00 | Paris | S1 | 258 | 60 | 13
2022-04-18 00:00:00 | Prague | S1 | 456 | 100 | 6.8
2022-04-18 00:00:00 | Prague | S1 | 456 | 1000 | 4.2
2022-04-18 00:00:00 | Prague | S1 | 456 | 10000 | 3.8
2022-03-30 00:00:00 | Prague | S3 | 369 | 4500 | 13
2022-03-30 00:00:00 | Prague | S3 | 369 | 26000 | 6.5
2022-03-05 00:00:00 | London | S2 | 147 | 100 | 14
2022-03-05 00:00:00 | Paris | S2 | 123 | 20 | 14.3
2022-03-05 00:00:00 | Paris | S2 | 159 | 1000 | 13
2022-03-05 00:00:00 | Prague | S2 | 369 | 4500 | 12
2022-03-05 00:00:00 | Prague | S2 | 369 | 13500 | 9.9
2022-03-05 00:00:00 | Prague | S2 | 369 | 26000 | 7.2
2022-03-04 00:00:00 | Paris | S2 | 159 | 100 | 20
2022-01-14 00:00:00 | Paris | S1 | 123 | 10 | 13
2022-01-14 00:00:00 | Paris | S1 | 258 | 30 | 16.5
2022-01-14 00:00:00 | Paris | S1 | 258 | 60 | 11.2
2022-01-14 00:00:00 | Prague | S1 | 159 | 200 | 17
2022-01-14 00:00:00 | Prague | S1 | 456 | 100 | 7
2022-01-14 00:00:00 | Prague | S1 | 456 | 1000 | 4.5
2022-01-14 00:00:00 | Prague | S1 | 456 | 10000 | 2.1
2021-12-22 00:00:00 | Prague | S3 | 369 | 4500 | 11
2021-12-22 00:00:00 | Prague | S3 | 369 | 26000 | 6.2
2021-12-19 00:00:00 | London | S2 | 147 | 100 | 16
2021-12-19 00:00:00 | Paris | S2 | 123 | 20 | 10.6
2021-12-19 00:00:00 | Paris | S2 | 159 | 1000 | 13
2021-12-19 00:00:00 | Prague | S2 | 369 | 4500 | 11
2021-12-19 00:00:00 | Prague | S2 | 369 | 13500 | 9.1
2021-12-19 00:00:00 | Prague | S2 | 369 | 26000 | 8.2
2021-12-18 00:00:00 | Paris | S2 | 159 | 200 | 16.5
Spreadsheet: 698642d1602091638-nested-vlookup-with-indirect-function-sample
Sheet: 2017

Number | Name | Combo
433356 | bob |  |  | Need a formula to check if these combos exist in any of the previous year tabs
32323 | [NAME] |  |  | If it isnt I want it to show the [NAME] field, if it is present in any of the previous tabs I want to show "previous"
677 | [NAME]
98 | lpo
1267 | wedc
876554 | [NAME]
6576 | ssaa
456 | wqadf
357 | [NAME]
33222 | djfhj
5678 | lshdj
2346 | loasd
7 | pool
6443 | aws
126788 | fhnsk
1244566 | alkdk
Spreadsheet: 842309d1694429691-dynamic-array-formula-needed-for-irregular-data-book1a
Sheet: Sheet1

 | Source: | Dynamic Array formula needed for irregular data
 |  |  |  |  | 1-Col |  |  |  |  |  |  |  |  |  |  | Dyn.Arr. Cell
 |  |  |  |  | Dyn.Arr. | Expected values |  |  | Dyn.Arr. Multi-Col - [NAME]
 | [NAME] | Dataset | Product | Channel | Division | Type | A-Code | X-Code | Division | Type | A-Code | X-Code |  |  | Dataset | unique id | Division | Type | A-Code | Colour | X-Code
 | 1 | [NAME] |  |  |  |  |  |  |  |  |  |  |  |  | 1 | [NAME] | North | A | A01 | Grey | X01
 |  |  | Product X | EU | North | A | A01 | X01 | North | A | A01 | X01 |  |  | 2 | XEFGH | South | B | A02 | Black | X02
 |  |  | Product X | UK | North | A | A01 | X01 | North | A | A01 | X01 |  |  | 3 | XIJKL | West | C | A03 | White | X03
 |  |  | Product X | AU | North | A | A01 | X01 | North | A | A01 | X01 |  |  | 4 | XMNOP | North | D | A04 | Green | [NAME]
 |  |  | Product X | US | North | A | A01 | X01 | North | A | A01 | X01 |  |  | 5 | XQRST | East | E | A05 | Blue | X05
 | 2 | XEFGH |  |  |  |  |  |  |  |  |  |  |  |  | 6 | XUVWX | West | F | A06 | Red | X06
 |  |  | Product Y | EU | South | B | A02 | X02 | South | B | A02 | X02
 |  |  | Product Y | UK | South | B | A02 | X02 | South | B | A02 | X02
 |  |  | Product Y | AU | South | B | A02 | X02 | South | B | A02 | X02
 |  |  | Product Y | US | South | B | A02 | X02 | South | B | A02 | X02
 | 3 | XIJKL
 |  |  | Product Z | EU | West | C | A03 | X03 | West | C | A03 | X03
 |  |  | Product Z | UK | West | C | A03 | X03 | West | C | A03 | X03
 |  |  | Product Z | AU | West | C | A03 | X03 | West | C | A03 | X03
 |  |  | Product Z | US | West | C | A03 | X03 | West | C | A03 | X03
 | 4 |  |  |  | West
 |  |  |  |  | West
 |  |  |  |  | West
 |  |  |  |  | West
 |  |  |  |  | West
 | 5 | XMNOP
 |  |  | Product A |  | North | D | A04 | [NAME] | North | D | A04 | [NAME]
 |  |  | Product A |  | North | D | A04 | [NAME] | North | D | A04 | [NAME]
 |  |  | Product A |  | North | D | A04 | [NAME] | North | D | A04 | [NAME]
 |  |  | Product A |  | North | D | A04 | [NAME] | North | D | A04 | [NAME]
Spreadsheet: b24b99e2-6c2f-406f-b737-428f288c17d0
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
 | Table S1. SFPs between Col and Van.
 | Table S1A. SFPs detected at different [NAME].
 | [NAME] | Calleda | [NAME] | Sig-c | Sig+c
 | 13.05% | 211220 | 29007 | 58628 | 152592
 | 6.22% | 173611 | 11363 | 33227 | 140384
 | 2.74% | 153401 | 4431 | 23326 | 130075
 | 1.16% | 138552 | 1698 | 17742 | 120810
 | 0.51% | 126499 | 678 | 14131 | 112368
 | 0.22% | 116122 | 272 | 11448 | 104674
 | 0.09% | 106817 | 104 | 9347 | 97470
 | aThe number of features called significant.
 | bThe number of features determined as false positives based on permutation.
 | cThe number of features called significant with either greater Van signals (Sig-) or greater Col signals (Sig+).
 | Table S1B. Genic distribution of 120,810 SFPs detected at 1% FDR with greater Col signal.
 |  | CD | Intron | UTRs | Promoter | Downstream | Intergenic | Total
 | SFPa | 23180 | 19806 | 5130 | 30190 | 32158 | 50539 | 161003
 | Featureb | 526407 | 301947 | 105260 | 429585 | 452681 | 593757 | 2409637
 | Percentage | 0.044 | 0.0656 | 0.0487 | 0.0703 | 0.071 | 0.0851 | 0.0668
 | aThe number of SFPs within each annotation category.
 | The annotation categories analyzed included coding sequences (CD), intron, UTRs, transcriptional start to upstream 1kb (promoter), transcriptional stop to downstream 1kb (downstream) and inter-genic regions.
 | As genes on forward and reverse direction could overlap, the total number of SFPs mapped to these annotation categories was more than 120,810.
 | bThe number of features within each annotation category. The total number of features mapped to annotation categories was more than 1,683,620 due to overlap between two strands.
Spreadsheet: 764985d1643108161-generating-random-names-and-comparing-to-existing-list-badmintonschedulertesting
Sheet: Players

 |  | Size of Team | 4
 | S No | Player | Random | Rank | Game | Present
 | 1 | A |  |  |  | Y
 | 2 | B |  |  |  | Y
 | 3 | C |  |  |  | Y
 | 4 | D |  |  |  | Y
 | 5 | E |  |  |  | Y
 | 6 | F |  |  |  | Y
 | 7 | G |  |  |  | Y
 | 8 | H |  |  |  | Y
 | 9 | I |  |  |  | Y
 | 10 | J |  |  |  | Y
 | 11 | K |  |  |  | Y
 | 12 | L |  |  |  | Y
 | 13 | M |  |  |  | Y
 | 14 | N |  |  |  | Y
 | 15 | O |  |  |  | Y
 | 16 | P |  |  |  | Y
 | 17 | Q |  |  |  | Y
 | 18 | R |  |  |  | Y
 | 19 | S |  |  |  | Y
 | 20 | T |  |  |  | Y
 | 21 | U |  |  |  | Y
 | 22 | V |  |  |  | Y
 | 23 | W |  |  |  | Y
Spreadsheet: 672343d1586834201-how-to-get-data-based-on-date-criteria-excel-solution
Sheet: Sticker

Period : | 2020-03-20 00:00:00 |  | 2020-04-20 00:00:00
Type | Start | Finish
abc | 2020-04-12 00:00:00 | 2020-04-13 00:00:00
lalal | 2020-04-12 00:00:00 | 2020-04-15 00:00:00
ZZZ | 2020-04-12 00:00:00 | 2020-04-15 00:00:00
[NAME] | 2020-04-13 00:00:00 | 2020-04-15 00:00:00
sss | 2020-04-14 00:00:00 | 2020-04-15 00:00:00
Update production
Date | Type
2020-04-12 00:00:00 | abc
2020-04-12 00:00:00 | lalal
2020-04-12 00:00:00 | ZZZ
2020-04-13 00:00:00 | abc
2020-04-13 00:00:00 | lalal
2020-04-13 00:00:00 | ZZZ
2020-04-13 00:00:00 | [NAME]
2020-04-14 00:00:00 | lalal
2020-04-14 00:00:00 | ZZZ
2020-04-14 00:00:00 | [NAME]
2020-04-14 00:00:00 | sss
Spreadsheet: 481713d1474613394-match-dates-and-sum-values-match-dates-and-sum-values-match-dates-and-sum-values-example
Sheet: Venue2

START DATE | FLT OPERATORS | TELE | # CREWS | # LABOUR PER CREW
2018-03-14 08:00:00 | 4 |  | 2 | 6
2018-03-15 08:00:00 | 4 |  | 2 | 6
2018-03-16 08:00:00 | 4 |  | 2 | 6
2018-03-17 08:00:00 | 4 |  | 2 | 6
2018-03-18 08:00:00 | 4 |  | 2 | 6
2018-03-19 08:00:00 | 4 |  | 2 | 6
2018-03-20 08:00:00 | 4 |  | 1 | 8
2018-03-21 08:00:00 | 4 |  | 1 | 8
2018-03-22 08:00:00 | 4 |  | 1 | 8
2018-03-23 08:00:00 | 4 |  | 1 | 8
2018-03-24 08:00:00 | 4 |  | 1 | 8
2018-03-25 08:00:00 | 4 | 2 | 1 | 8
2018-03-26 08:00:00 | 4 | 2 | 1 | 8
2018-03-27 08:00:00 | 4 | 2 | 1 | 8
2018-03-28 08:00:00 | 4 | 2 | 1 | 8
2018-03-29 08:00:00 | 4 | 2 | 1 | 8
2018-03-30 08:00:00 | 4 | 2 | 1 | 8
2018-03-31 08:00:00 | 4 | 2 | 1 | 8
2018-04-01 08:00:00 |  |  | 1 | 8
2018-04-02 08:00:00 |  |  | 1 | 8
2018-04-03 08:00:00 |  |  | 1 | 8
2018-04-04 08:00:00 |  |  | 1 | 8
2018-04-05 08:00:00 |  |  | 1 | 8
2018-04-06 08:00:00 | 4 |  | 1 | 8
2018-04-07 08:00:00 | 4 |  | 1 | 8
2018-04-08 08:00:00 | 4 |  | 1 | 8
2018-04-09 08:00:00 | 4 |  | 1 | 8
2018-04-10 08:00:00 | 4 |  | 1 | 8
2018-04-11 08:00:00 | 4 |  | 1 | 8
2018-04-12 08:00:00 | 4 |  | 1 | 8
2018-04-13 08:00:00 | 4 |  | 1 | 8
2018-04-14 08:00:00 | 4 |  | 1 | 8
2018-04-15 08:00:00 | 4 |  | 1 | 8
2018-04-16 08:00:00 | 4 |  | 1 | 8
2018-04-17 08:00:00 | 4 |  | 1 | 8
2018-04-18 08:00:00 | 4 |  | 1 | 8
2018-04-19 08:00:00 | 4 |  | 1 | 8
2018-04-20 08:00:00 | 4 |  | 1 | 8
2018-04-21 08:00:00 | 4 |  | 1 | 8
2018-04-22 08:00:00 | 4 |  | 1 | 8
Spreadsheet: stacey_white__39194__UBS curves
Sheet: By Curve Code

Power East and West Primary Curves and Basis Mappings
Sorted by Curve Code
Curve Code | Curve Name | Dependency
PWCN | Cinergy Futures | R4
PWQJ | PJM Futures | R1E
R1 | [NAME]
R1A | PJM West | R1E
R1B | Nepool
R1C | NY Zone A
R1D | PJM Eastern Hub | R1E
R1E | PJM Western Hub
R1Z | NY Zone J | R1
R3 | SOCO
R3B | TVA | R4
R4 | Cinergy
R4C | Comed | R4
R5 | Entergy | R4
R6 | South Texas
R6A | North Texas | R6
R20 | Ontario
Spreadsheet: 122262d1316700814-convert-text-to-formula-indirect
Sheet: Data

 |  |  | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28
SUM(LINEST(D7:O7, $D$4:$O$4)*{13,1}) | <- Text Construct |  | 1 | 2 | 1 | 5 | 2 | 4 | 3 | 1 | 3 | 1 | 2 | 2
2.181818181818182 | <- Working formular
#N/A | <- INDIRECT, not working
Spreadsheet: 784599d1655844942-filter-by-several-values-filter-by-value
Sheet: DATA

From here we read the data. |  |  | These serials contains at least one of the looking codes
Serial number | Codes |  | Serial number |  | The look up values are these
NL17011072 | NESTC03 - Other Complaint |  | NL16264216
NL16292014 | NESTC10 - Battery Issue |  | NL17227332 |  | Codes
NL16292014 | [NAME] |  | N018106166 |  | NESTC13 - Front Housing Issue
NL16264216 | NESTC03 - Other Complaint |  |  |  | NESTC14 - Rear housing
NL16264216 | [NAME] |  |  |  | [NAME]
NL16264216 | NESTC13 - Front Housing Issue
NL17227332 | NESTC06 - Error Code Issue
NL17227332 | [NAME]
N018129146 | NESTC03 - Other Complaint
NL17212292 | NESTC06 - Error Code Issue
N018106166 | NESTC06 - Error Code Issue
N018106166 | [NAME]
N018106166 | NESTC14 - Rear housing
Spreadsheet: 03c4f140-a3e4-41bc-8f33-b721362f8fef
Sheet: Fish Example

Modeling the growth of fish in a lake using the logistic growth model
[NAME]
The initial term is 1.00
r = .000025
K = 90,000
50 periods are examined
 |  |  | t | Nt
 |  |  | 1 | 1
 |  |  | 2
 |  |  | 3
 |  |  | 4
 |  |  | 5
 |  |  | 6
 |  |  | 7
 |  |  | 8
 |  |  | 9
 |  |  | 10
 |  |  | 11
 |  |  | 12
 |  |  | 13
 |  |  | 14
 |  |  | 15
 |  |  | 16
 |  |  | 17
 |  |  | 18
 |  |  | 19
 |  |  | 20
 |  |  | 21
 |  |  | 22
 |  |  | 23
 |  |  | 24
 |  |  | 25
 |  |  | 26
 |  |  | 27
 |  |  | 28
 |  |  | 29
 |  |  | 30
 |  |  | 31
 |  |  | 32
 |  |  | 33
 |  |  | 34
 |  |  | 35
 |  |  | 36
 |  |  | 37
 |  |  | 38
 |  |  | 39
 |  |  | 40
 |  |  | 41
 |  |  | 42
 |  |  | 43
 |  |  | 44
 |  |  | 45
 |  |  | 46
 |  |  | 47
 |  |  | 48
 |  |  | 49
 |  |  | 50
Spreadsheet: 220151d1363084935-if-if-greater-not-working-staff-requirements
Sheet: Formula

Order Reference | Qty | [NAME] | Tool | Machine | Customer | Product | Start Date | End Date |  |  |  | Machine 1 | Machine 2 | Machine 3 | Machine 4 | Machine 5 | Machine 6 | Machine 7 |  | Start time
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | SHIFT 1 | 06:00:00
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | SHIFT 2 | 14:00:00
Spreadsheet: phillip_m_love__30713__200009_OA
Sheet: EAST-EGM-VAR

ENRON CAPITAL & TRADE RESOURCES
OPERATIONAL ANALYSIS - VARIANCE
COMPANY:  ECTR (EGM)
REGION: NORTHEAST
 |  |  | 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
Transport
 |  | Current Month MTM
 |  | Financial Liquidations
 |  | Originations
 |  | TOTAL FIRM TRADING
Spreadsheet: michelle_lokay__26699__imball0112
Sheet: summary

TRANSWESTERN  PIPELINE -   SUMMARY OF OBA BALANCES |  |  |  |  |  | index
 |  |  |  |  |  | SJ
Positive=due [NAME] |  | Negative = due operator |  |  |  | AVG
 |  |  |  |  |  | NTXPH
Operator | Dollars | Volume | Date | Imbal Type | MS rep | Comments
Duke Energy Field Service SW |  |  | 2001-11-30 00:00:00 | Dollar Valued | [NAME]
Duke Energy Trading &Mktg |  |  |  | Dollar Valued | [NAME]
NNG |  |  |  | Dollar Valued | [NAME]
PNM |  |  |  | Dollar Valued | [NAME]
Mewborne |  |  |  | Dollar Valued | [NAME]
Amoco Abo |  |  |  | Dollar Valued | [NAME]
[NAME] |  |  |  | Dollar Valued | [NAME]
Conoco |  |  |  | Dollar Valued | [NAME] | [NAME] and Maljamar
Mojave Pipeline |  |  |  | Volumetric | [NAME]
SoCal |  |  |  | Volumetric | [NAME]
NGPL |  |  |  | Volumetric | [NAME]
[NAME] |  |  |  | Volumetric | [NAME]
Dominion Gas Ventures |  |  |  | Dollar Valued | [NAME]
[NAME] |  |  |  | Dollar Valued | [NAME]
Red Cedar |  |  |  | Volumetric | [NAME] |  |  |  |  |  | DEFS,LP | 23995 | -1023166 | Hobbs plant
PG&E Topock |  |  |  | Volumetric | [NAME] |  |  |  |  |  | DEFS,LP | 22051 | -527215 | Artesia plant
Amarillo Nat Gas |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DEFS,LP | 22864 | -58339.66 | inactive
Calpine |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DEFS,LP | 20379 | -51695.87 | inactive
El Paso Field Services |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DEFS,LP | 26357 | 44144.84 | inactive
Agave |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DEFS,LP | 21544 | 61340.16 | inactive
Citizens-Griffith |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DEFS,LP | 24532 | -956477
Northwest |  |  |  | Volumetric | [NAME] |  |  |  |  |  | DEFSSW | 24268 | 1481856.66
[NAME] |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DE T&M | 24693 | 275313.72
CIG |  |  |  | Volumetric | [NAME] |  |  |  |  |  | DE T&M | 24361 | 811179.69
Continental |  |  |  | Dollar Valued | [NAME] |  |  |  |  |  | DE T&M | 21665 | 73449
Lonestar |  |  |  | Volumetric | [NAME] |  |  |  |  |  | DE T&M | 22664 | 23612
TransColorado |  |  |  | Dollar Valued | [NAME]
Receivable imbalances
Operator | Dollars | Volume | Date | Imbal Type | MS rep | Comments
Duke Energy Field Services LP |  |  | 2001-11-30 00:00:00 | Dollar Valued | [NAME]
Citizens Communications |  |  |  | Dollar Valued | [NAME]
North Star Steel |  |  |  | Dollar Valued | [NAME]
Crosstex Energy Serv |  |  |  | Dollar Valued | [NAME]
EPFS / PG&E TX |  |  |  | Dollar Valued | [NAME]
El Paso |  |  |  | Volumetric | [NAME]
Amoco |  |  |  | Volumetric | [NAME]
EOG |  |  |  | Dollar Valued | [NAME]
Panhandle Eastern |  |  |  | Volumetric | [NAME]
Burlington |  |  |  | Dollar Valued | [NAME]
Oasis |  |  |  | Volumetric | [NAME]
WTG Gas Marketing |  |  |  | Dollar Valued | [NAME]
Payable imbalances
Net imbals
Note -  This report does not represent the total population of imbalances on Transwestern.