tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 823391d1679940336-call-function-of-a-total-column-test3
Sheet: Sheet2

 |  |  |  |  | 2023-02-18 00:00:00 |  |  |  | 23:08:17 |  | Store: |  |  |  | 26049 |  |  |  |  |  |  | page: |  |  |  | 1 / 1
 | Date: 18.02.2023
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Customers (Tickets) |  |  |  | Check average
 |  | Type |  |  |  | Description |  |  |  |  |  |  | Gross |  |  |  | Net
 |  | 1 |  |  |  | Counter
 |  |  |  |  |  |  | In House |  |  |  |  |  |  | 1 |  |  |  | 1 |  |  | 1 |  |  |  | 1
 |  |  |  |  |  |  | Take Away |  |  |  |  |  |  | 1 |  |  |  | 1 |  |  | 1 |  |  |  | 1
 |  |  |  |  |  |  |  |  |  |  |  |  | 1 |  |  |  | 1 |  |  | 1 |  |  |  | 1
 |  |  |  |  |  |  |  |  |  |  |  |  | 1 |  |  |  | 1 |  |  | 1 |  |  |  | 1
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Customers (Tickets) |  |  |  | Check average
 |  | Type |  |  |  | Description |  |  |  |  |  |  | Gross |  |  |  | Net
 |  | 0 |  |  |  | In House |  |  |  |  |  |  | 5 |  |  |  | 4 |  |  | 416 |  |  |  | 5.627908653846173
 |  | 1 |  |  |  | Take Away |  |  |  |  |  |  | 5 |  |  |  | 4 |  |  | 62 |  |  |  | 4.724032258064516
 |  |  |  |  |  |  |  |  |  |  |  |  | 5 |  |  |  | 4 |  |  | 478 |  |  |  | 5.510669456066963
 |  |  |  |  |  |  |  | 544 / 3
Spreadsheet: 48305d1247545326-calculate-retrospectively-book5
Sheet: Sheet1

 |  |  |  | Lbs | Unit Price$ | Value
 |  | Receipt | 21 | 5000 | 100 | 500000
 |  |  | 25 | 5000 | 100 | 500000
 |  |  | 28 | 7500 | 102 | 765000
 |  |  | 31 | 7500 | 102 | 765000
 |  |  | 35 | 10000 | 100 | 1000000
 |  |  | 48 | 5000 | 103 | 515000
 |  |  | 51 | 7000 | 103 | 721000
 |  |  | 52 | 6000 | 100 | 600000
 |  |  | 56 | 2000 | 105 | 210000
 |  |  |  | 55000 |  | 5576000
 |  | Closing |  | 18750 |  | ?
 |  |  |  |  |  | Calculate the closing value on First In First Out basis which in this case would be | 1917250
Spreadsheet: 083fb4a6-e343-4139-b1f5-81f6174f748a
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6
Announcement of Advanced Prices and Pricing Factors for December 2007 1/
 |  | Release Date: November 23, 2007
Base Skim Milk Price for Class I 2/: |  |  |  |  | 15.65 | (per hundredweight)
Advanced Class III Skim Milk Pricing Factor: |  |  |  |  | 14.81 | (per hundredweight)
Advanced Class IV Skim Milk Pricing Factor: |  |  |  |  | 15.65 | (per hundredweight)
Advanced Butterfat Pricing Factor 3/: |  |  |  |  | 1.412 | (per pound)
Class II Skim Milk Price: |  |  |  |  | 16.35 | (per hundredweight)
Class II Nonfat Solids Price: |  |  |  |  | 1.8167 | (per pound)
Two-week Product Price Averages:
 | Butter |  |  |  | 1.2969 | (per pound)
 | Nonfat Dry Milk |  |  |  | 1.9131 | (per pound)
 | Cheese |  |  |  | 1.9648 | (per pound)
 | Dry Whey |  |  |  | 0.4385 | (per pound)
Special information for Appalachian and Southeast:
 | Diesel Fuel Price |  |  |  | 3.25 | (per gallon)
 | Mileage Rate Factor |  |  |  | 0.00467 | (per cwt. [NAME])
1/ See Price [NAME] at www.ams.usda.gov/dyfmos/mib/price_form_2007.htm
2/ Higher of advanced Class III or IV skim milk pricing factors. The Class I skim milk
price equals this price plus applicable Class I differential.
3/ The Class I butterfat price equals this price plus (applicable Class I differential divided
by 100).
Note: The Class I price equals ( Class I skim milk price times 0.965 ) plus ( Class I
butterfat price times 3.5 ), rounded to the nearest cent.
For information only: The Class I base price is: |  |  |  |  | 20.04
(Sometimes referred to as the Class I mover, it equals (base skim milk price for Class I
times 0.965) plus (advanced butterfat pricing factor times 3.5).)
Spreadsheet: 875637d1722240109-count-unique-values-from-multile-entries-help2
Sheet: Sheet1

Enrolment ID | Enrolment Type | Customer # | Company Name | [NAME]
1120517 | Indigo | 129999 | Kamala  Trump Co. | TDX911 |  |  | Manual Answer
1121003 | Indigo | 129999 | Kamala  Trump Co. | TDX911
1128856 | Turquoise | 129999 | Kamala  Trump Co. | TDX911 |  |  |  | Unique Vehicles |  |  | Indigo & Turqoise
5435104 | Indigo | 129999 | Kamala  Trump Co. | WQB922 |  |  | Customer # | Indigo | Turquoise | Red
5933105 | Indigo | 129999 | Kamala  Trump Co. | WQB922 |  |  | 129999 | 1 | 2 | 0 | 3
11312 | Indigo | 129999 | Kamala  Trump Co. | WQB922
11313 | Indigo | 129999 | Kamala  Trump Co. | WQB922
TTD000114 | Turquoise | 129999 | Kamala  Trump Co. | XQ04YES
TTD000113 | Turquoise | 129999 | Kamala  Trump Co. | XQ04YES |  |  | [NAME]?
11318 | Indigo | 129999 | Kamala  Trump Co. | XQ4USA
11319 | Turquoise | 129999 | Kamala  Trump Co. | XQ4USA |  |  |  | [NAME] |  |  | Indigo & Turqoise
TTD000324 | Turquoise | 129999 | Kamala  Trump Co. | XQ4USA |  |  | [NAME] | Indigo | Turquoise | Red
345235 | Turquoise | 129999 | Kamala  Trump Co. | BFF123 |  |  | 129999
325552 | Turquoise | 129999 | Kamala  Trump Co. | BFF123
11327 | Red | 129999 | Kamala  Trump Co. | [NAME] |  |  | Find H14 in column C, and I13 (Indigo) in column B. Uniquely count how many vehicles are "Indigo" ONLY, and don’t have another colour associated to the REGO.
11329 | Turquoise | 129999 | Kamala  Trump Co. | [NAME]
11324 | Indigo | 129999 | Kamala  Trump Co. | [NAME]
 |  |  |  |  |  |  | Find H14 in Column C. Count how many vehicles have a "Indigo" and "Turqoise" enrolment only.
Spreadsheet: 297394d1392379686-show-values-in-the-list-book2
Sheet: Sheet1

80 | Ø88,9
100 | Ø114,3 x 6,3
110 | 0
150 | 0
160 | 0
200 | Ø 219,1 x 6
250 | Ø 273
300 | Ø323
350 | Ø355,6
400 | 0
450 | Ø 457
500 | Ø 508
600 | 0
800 | Ø 813 x 8
Spreadsheet: 728965d1618838110-formula-for-percentage-reduction-of-numbers-from-new-base-number-question
Sheet: Sheet1

[NAME] of quantities |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 0.18
No | Position | Unit | Quality | Single Price-no Vat | Total Price- no Vat | Single price-with [NAME] | Total Price-with [NAME] | New Single Price | New Total Price |  | 1. Our predicted prices are F12 cell ([NAME]) without VAT or H12 cell(1066838 EU) with [NAME].
1 | Excavation of earth from 3 and 4 category for pillars and with dimensions of foundation 0.8 * 0.8 * 1.3 | m3 | 20.8 | 500 |  |  |  |  |  |  | 2. After auction the prices are reduced F12=803090 and H12=947646,20
2 | Excavation of earth of 3 and 4 category with dimensions 0.4 * 0.8 for laying supply distribution cables | m3 | 320 | 280 |  |  |  |  |  |  | 3.Problem: How to reduce single prices according the after action total price, is there a excel formula for that?
3 | Procurement and installation of fine sand 10 cm below and 10 cm above the cable | m3 | 80 | 490
4 | Re-burial of the excavated soil in the ditch | m3 | 240 | 30
5 | Loading and transport of surplus land in the length of 5 km | m3 | 100.8 | 600
6 | Steel pillar with a height of 10m | No. | 25 | 15000
7 | Construction of concrete foundation with concrete brand MB 20 for columns, with built-in anchor plate and pipe Ф50 mm for input-output of cables: -0.8 * 0.8 * 1.3 | No. | 25 | 4500
8 | Procurement and laying of cable in an already excavated trench | m | 1070 | 98
9 | Procurement and installation of galvanized steel strip FeZn 30x4mm in an already excavated trench with power lines and its connection with appropriate cross plates and screws for grounding the columns | m | 1070 | 98
 |  |  |  | Total
 |  |  |  |  | 803090 |  | 947646
Spreadsheet: 856992d1706107898-sortby-in-filter-sorby-function
Sheet: TR-Vaxo

 | I need to sort firstly by : Reference and then by date
 | Acc.# | NLI_Joined | FSLI_ENG | FSLI_GEO | BS/IS | Date | Month | Reference | Description | Debit | Credit
3502 |  | 2110 3500 | Trade Receivables | 0 | BS | 2023-02-15 00:00:00 | 2 | 3500 | CLOSING FEE 1412 | 3540.42 | 0
3501 | 2110 | 2110 3500 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3500 | PMT CLOSING FEE 1412 | 0 | 3477.5
3503 | 2110 | 2110 3500 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3500 | LEX AT CLOSING FEE 1412 | 0 | 62.92
3500 | 2110 | 2110 3501 | Trade Receivables | 0 | BS | 2023-02-07 00:00:00 | 2 | 3501 | CLOSING FEE 1411 | 1421.6 | 0
 | 2110 | 2110 3501 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3501 | PMT CLOSING FEE 1411 | 0 | 1403.85
 | 2110 | 2110 3501 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3501 | LEX AT CLOSING FEE 1411 | 0 | 17.75
 | 2110 | 2110 3502 | Trade Receivables | 0 | BS | 2023-02-02 00:00:00 | 2 | 3502 | CLOSING FEE 1416 | 8125.26 | 0
 | 2110 | 2110 3502 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3502 | PMT CLOSING FEE 1416 | 0 | 7890.59
 | 2110 | 2110 3502 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3502 | LEX AT CLOSING FEE 1416 | 0 | 234.67
 | 2110 | 2110 3503 | Trade Receivables | 0 | BS | 2023-02-15 00:00:00 | 2 | 3503 | CLOSING FEE 1414 | 1936.69 | 0
 | 2110 | 2110 3503 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3503 | PMT OF CLOSING FEE 1414 | 0 | 1902.27
 | 2110 | 2110 3503 | Trade Receivables | 0 | BS | 2023-02-20 00:00:00 | 2 | 3503 | LEX AT CLOSING FEE 1414 | 0 | 34.42
Spreadsheet: 174045d1344896238-remove-column-restrictions-121-schedule1
Sheet: Class List

 | CLASS LIST
 | CLASS | ID | DAY | [NAME] | START TIME | END TIME | UNIQUE
 | RF & Microwave Transcievers Design and Analysis | EE441 | SUNDAY | Building 59 - 2004 | 10:00:00 | 11:15:00
 | RF & Microwave Transcievers Design and Analysis | EE441 | TUESDAY | Building 59 - 2004 | 10:00:00 | 11:15:00
 | Microwave Measurements | EE631 | SUNDAY | Building 59 - 1005 | 20:00:00 | 20:15:00
 | Microwave Measurements | EE631 | TUESDAY | Building 59 - 1005 | 20:00:00 | 20:15:00
 | Digital Logic Circuit Design | EE200 | TUESDAY | Building 59 - 0000 | 14:10:00 | 16:50:00
 | Independent Research OR M.S Thesis | EE606
Spreadsheet: 101805d1299850927-extracting-specifics-from-xls-file-excel-2003-pl-replacements-1100-and-1200
Sheet: 1209-DFM 0403-10

Phase | Project No. | Segment ID (GIE) | Route No. | Facility Type | Pipe O.D., in. | Segment Length, ft | Proposed [NAME] | Proposed End M.P. | Proposed total length, ft. | Proposed [NAME], in. | Segment Length per Construction Classification, ft |  |  | Bored Crossings |  | HDDs |  | Potential Re-route | Move-arounds | Comments, notes, assumptions
 |  |  |  |  |  |  |  |  |  |  | Non-cong. | Semi-cong. | High-cong. | Q-ty | Length, Feet | Q-ty | Length, Feet | Yes/No | Q-ty |  | [NAME] | MP1 | MP2 | JNTEFF | GIRTH_WELD | LONG_SEAM | JOINT_TYPE | [NAME] | W_THICK | TEST_DATE | TEST_PRESS | [NAME] | TEST_DUR | MAOP | SMYS_MAOP | MOP | SMYS_MOP | YR_INSTALL | CLASSESENT | HCA_ID | SCC_THREAT | MANU_HREAT | CONSTHREAT | OF_THREAT | HS_THREAT | Legend Name | PerSMYS | TestPer | Sub_J | Fab_Note | Threat | Seismic | Object_ID | Shape_Length
1 | 1209 | 1413 | 0403-10 | DFM | 8.625 | 16 | 0 | 0 | 16 | 8.625 |  | 16 |  |  |  |  |  |  |  |  | 201 | 0 | 0 | -0.800 |  |  |  | -24000 | -0.141 |  | 0 |  | 0 | 0 | -9 | -250 | -39.8244 |  | 3 | N1 |  |  |  |  |  | ManuNoTestHCA | -39.82 | 0 | N |  |  |  | 4491 | 4.87553299782045
Spreadsheet: 121038d1315788139-converting-column-info-to-row-info-equipmentlist2
Sheet: Sheet1

Customer # | Equipment 1 | Equipment 2 | Equipment 3 | Equipment 4 |  |  | Helper2 | Helper | Customer Number | Equipment Type
AM100 |  |  |  |  |  |  |  |  | AM100 | Computer
[NAME] |  |  |  |  |  |  |  |  | AM100 | Cell Phone
AM102 |  |  |  |  |  |  |  |  | AM100 | [NAME]
AM103 |  |  |  |  |  |  |  |  | [NAME] | Computer
AM104 |  |  |  |  |  |  |  |  | AM102 | [NAME]
 |  |  |  |  |  |  |  |  | AM102 | Cup
 |  |  |  |  |  |  |  |  | AM102 | Computer
 |  |  |  |  |  |  |  |  | AM102 | Remote
 |  |  |  |  |  |  |  |  | AM103 | [NAME]
 |  |  |  |  |  |  |  |  | AM103 | Cell Phone
 |  |  |  |  |  |  |  |  | AM104 | Cup
Result I need |  |  |  |  |  | Basically I have a bunch of equipment in one column and I need to match it with a customer number and cascade it in a row. Is this possible?
Customer # | Equipment 1 | Equipment 2 | Equipment 3 | Equipment 4
AM100 | Computer | Cell Phone | [NAME]
[NAME] | Computer
AM102 | [NAME] | Cup | Computer | Remote
AM103 | [NAME] | Cell Phone
AM104 | Cup
Customer | 1 | 2 | 3 | 4
AM100
[NAME]
AM102
AM103
AM104
Spreadsheet: 03928b0c-5c77-41f1-a4ed-22bbc69a8f70
Sheet: French

French - Lesson Planning
 | Fall 2011 | Sp 2012 | Fall 2012 | Sp 2013 | Fall 2013
Curriculum and Standards | 4.4 | 4.8 | 5 | N/A | 5
Objectives should define what students will know and be able to do.) | 4.5 | 4.8 | 5 | N/A | 5
Introductory activities set the stage for learning by providing background information about the topic to help orient investigations | 4.7 | 4.8 | 5 | N/A | 5
All activities are aligned with the objective(s), build upon each other, are appropriately paced, and developmentally appropriate. | 4.6 | 5 | 5 | N/A | 5
The course of instruction responds to student needs and interests, and students can make key decisions regarding their learning | 4.4 | 5 | 5 | N/A | 5
Collaborative learning allows all students opportunities to develop teamwork, communication, problem-solving skills, and reflection | 4.5 | 5 | 5 | N/A | 5
Concluding activities re-examine the important points of the lesson | 4.5 | 5 | 5 | N/A | 5
A variety of technology is integrated appropriately throughout the lesson in a manner that enhances the effectiveness of the lesson and the learning of the student. | 4.4 | 4.8 | 5 | N/A | 5
Emphasis on the technology standards and performance indicators are clearly seen through the major components of the lesson plan | 4.6 | 4.8 | 5 | N/A | 5
Assessment opportunities are ongoing and inform students | 4.7 | 4.7 | 5 | N/A | 5
Methods should include both formal and informal tools | 4.5 | 4.5 | 5 | N/A | 5
Materials and resources—exclusive of technology tool—that are needed by the student or the teacher to execute the lesson.) | 4.6 | 4.5 | 5 | N/A | 5
Accommodations do not change lesson or criteria. | 4.7 | 4.7 | 5 | N/A | 5
Modifications change lesson and criteria | 4.6 | 4.5 | 5 | N/A | 5
Explorations identify further study activities; extensions identify bridge activities | 4.7 | 4.7 | 5 | N/A | 5
Resources used by the teacher to create this lesson, i.e. books, journals, magazines, web sites, school/public library resources, outside experts, etc.) | 4.5 | 4.6 | 5 | N/A | 5
 |  |  |  |  |  | Sp 2014
Professional Writing |  |  |  |  |  | 3.8
Essential Question |  |  |  |  |  | 3.5
Standards and Benchmarks |  |  |  |  |  | 3.7
Student Outcomes |  |  |  |  |  | 3.8
Materials/Technology |  |  |  |  |  | 3.9
Procedures |  |  |  |  |  | 3.5
[NAME] “Hook” |  |  |  |  |  | 3.6
Pre-planned (seed) Questions |  |  |  |  |  | 3.8
Modeling, guided, collaborative and independent practice |  |  |  |  |  | 3.7
Formative/Summative |  |  |  |  |  | 3.8
Assessment |  |  |  |  |  | 3.9
Closure |  |  |  |  |  | 3.8
Differentiation |  |  |  |  |  | 3.7
Post-Lesson Reflection/Analysis |  |  |  |  |  | 3.6
Spreadsheet: 703891d1605211164-match-criteria-and-return-earliest-date-formula-help-sample
Sheet: Sheet1

 |  |  |  | [NAME]
19910031531 | 9103683380 |  | 2005-07-20 00:00:00
19910032291 | 1100054070 |  | 2009-03-04 00:00:00
19910032291 | 1100054070 |  | 2006-11-05 00:00:00
19910032291 | 1100054070 |  | 2008-12-18 00:00:00
19910032301 | 9103649720 |  | 2008-03-22 00:00:00
19910032301 | 9103649720 |  | 2006-01-22 00:00:00
19910032661 | 9103649940 |  | 2013-04-07 00:00:00
19910032661 | 9103649940 |  | 2009-05-27 00:00:00
19910032891 | 9103434660
19910033241 | 1100096270 |  | 2008-05-22 00:00:00
19910033241 | 1100096270 |  | 2010-12-13 00:00:00
19910033241 | 1100096270 |  | 2008-04-01 00:00:00
19910033271 | 9103410290 |  | 2009-10-30 00:00:00
19910033271 | 9119652940 |  | 2009-12-25 00:00:00
19910033931 | 9103532270 |  | 1993-06-24 00:00:00
19910034021 | 9103661910 |  | 2009-01-06 00:00:00
Spreadsheet: 159599d1338770751-find-corresponding-values-from-different-cells-find-corresponding-values-from-different-cells
Sheet: Sheet1

 |  | Count | Cumulative | Total |  | Col_A | Col_B
1 mg  in 1 mL;10 mg  in 1 mL;0.10 mL  in 1 mL;9 mg  in 1 mL;15 mg  in 1 mL | 51688-6257-2;0409-7241-61;0409-4713-65;52380-0001-3;65282-1510-1;0409-1209-65 |  | 0
10 mg  in 1 mL;0.10 mL  in 1 mL;9 mg  in 1 mL;15 mg  in 1 mL | 51688-6256-2;0409-4713-65;52380-0001-3;65282-1510-1;0409-1209-65
10 mg  in 1 mL;0.10 mL  in 1 mL;9 mg  in 1 mL;15 mg  in 1 mL | 51688-6255-2;0409-4713-65;52380-0001-3;65282-1510-1;0409-1209-65
1;2 | 1;2;3;4
11;12;13;14;15;16;17;18;19;20 | 11;12;13;14
21;22;23 | 21;22;23
Spreadsheet: 68366d1268901056-skip-repeats-without-deleting-w-multi-criteria-involved-722176_powerschooldude
Sheet: Grades

PowerSchool Dude
5th Grade | T1 | T2 | T3 | T4 | T5 |  |  | Row
 |  |  |  |  |  |  |  |  |  | PowerSchool Dude
 |  |  |  |  |  |  |  |  |  | PowerSchool Gal
6th Grade | T1 | T2 | T3 | T4 | T5 |  |  | Row
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | << What I would like for it to display, but also base it on the student selected in cell [NAME]. So if the student selected changes, it would display the other students info. See rows in the first column when you switch the name in A1 as an example.
7th Grade | T1 | T2 | T3 | T4 | T5 |  |  | Row
8th Grade | T1 | T2 | T3 | T4 | T5 |  |  | Row
Spreadsheet: 677305d1589299920-formula-to-duplicate-row-references-test
Sheet: Sheet4

Cat | 10 |  | 170040
Dog | 15 |  | 544110
Cow | 12 |  | 170040
 |  |  | 544110
 |  |  | 170040
 |  |  | 544110
Spreadsheet: 87901d1287761303-lock-unlock-rows-based-on-values-in-cell-protect-unprotect
Sheet: Sheet1

Work? | Name | Age | Salary | DOJ
OK | [NAME] | 18 | 1000 | 2010-10-22 00:00:00
OK | [NAME] | 20 | 2000 | 2019-10-22 00:00:00
Amendment | [NAME] | 20 | 2000 | 2019-10-22 00:00:00
requirements
I will enter all the details and send to my colligue
I need a macro to protect all the rows of Column B,C & E( from row 2)
If anything has to be changed in any of the rows in Column B,C & E, the values in column A has to be changed to "Amendment" only then that particular rows should be unlocked
again the value is changed to OK, then lock the cells back.
** cells marked in yellow are always to be protected if values in column A is "OK" & should be unlocked if values in Column A is "Amendment"
Spreadsheet: mary_fischer__25615__32L
Sheet: E18YTD.XLS

ENRON CORP AND CONSOLIDTED SUBSIDIARIES
COMPANY # 032L
COMPANY NAME   Jovinole Associates
ANALYSIS OF RESERVE ITEMS
FOR THE YEAR ENDED 12-31-2001
 |  |  |  |  |  |  |  |  |  |  |  |  |  | E-18
 |  | 12-31-2000 Balance |  | ADDITIONS  DR (CR) |  |  |  | DEDUCTIONS  DR (CR)
 |  | DR. (CR) |  | RECORDED TO |  | RECORDED TO |  | RECORDED TO |  | RECORDED TO |  | DR. (CR)
[NAME] |  | BEGINNING BALANCE |  | INCOME STATEMENT |  | OTHER ACCOUNTS |  | INCOME STATEMENT |  | OTHER ACCOUNTS |  | ENDING BALANCE |  | COMMENTS/EXPLANATIONS
Allowance for Doubtful Accounts
(MUST TIE TO HYPERION LINE 0065)
Asset/Expense Accts:  DR/(CR)  Same signs as Hyperion
Reserve for Regulatory Issues - Current
(MUST TIE TO HYPERION LINE 0641)
Income Accts:  DR/(CR)  Reverse signs from Hyperion
Reserve for Regulatory Issues - Long Term
(MUST TIE TO HYPERION LINE 0815)
Income Accts: DR/(CR)  Reverse signs from Hyperion
Other Reserves - Other
(PROVIDE DETAIL OF INDIVIDUAL ITEMS
IN EXCESS OF $200,000.)
(MUST TIE TO HYPERION LINE 0840)
Income Accts: DR/(CR)  Reverse signs from Hyperion
Hyperion Line #   and Description of Other Reserves   (not listed above)
Total Other Reserves  DR/(CR)
 |  |  |  |  |  |  |  |  |  |  |  |  |  | E-18
Spreadsheet: 677711d1589479642-uk-telephone-numbers-selecting-sorting-and-formatting-2020-05-14-oeldere-kevlee-677704d1589477493-format-for-uk-phone-numbers-sample-of-number-form
Sheet: Sheet1

Home Phone | Business Phone | Home Fax | Business Fax | Pager | [NAME] | mobiles | Homefones |  |  | UK landlines |  |  |  |  |  |  | 01xxx xxxxxx
 |  |  |  |  | 07766 731871 |  |  |  |  | UK citis |  |  |  |  |  |  | 01xx xxx xxxx
 |  |  |  |  | 07971 601972 |  |  |  |  | Mobiles |  |  |  |  |  |  | 07xxx xxxxxx
 |  |  |  |  | 07825 045119
01937 845040 |  |  |  |  |  |  |  |  |  | g2 = IF($F2="","",IF(AND(LEFT($F2,2)="07",LEN($F2)=12),"","invaled mobile number")) and drag down
 |  |  |  |  | 07720 771237 |  |  |  |  | H2  =IF($A2="","",IF(AND(LEFT($A2,2)="01,;OR(LEN($A2)=12,LEN($A2)=13)),"","invaled home number")) and drag down
[PHONE]
 |  |  |  |  | 07927 327043
 |  |  |  |  | 07590 467070
[PHONE]
 |  |  |  |  | 07717 574470 |  |  |  |  | The UK has landlines in the format 01xxx xxxxxx and citys have 01xx xxx xxxx
 |  |  |  |  | 07831 184928 |  |  |  |  | Mobiles are always 07xxx xxxxxx
 |  |  |  |  | 07713 244301
01937 586639 |  |  |  |  |  |  |  |  |  | I have a corrupted csv from my iphone and the numbers are sometimes in the wrong format or the wrong column ie mobiles in home number and landlines in mobile number.
 |  |  |  |  | 07791 316609
 |  |  |  |  | 07927 260174 |  |  |  |  | I have over 1000 contacts and I'm doing this manually.
07807Â 887399
01757 212120 |  |  |  |  | 07788 450853 |  |  |  |  | There must be a better way???
01924 277902
7748123172
 |  |  |  |  | 07802 647475
 |  |  |  |  | 7806739874
07775Â 350332
01937 573512
07547Â 522030
Spreadsheet: 584640d1533303281-show-where-max-value-came-from-example
Sheet: Sheet1

ASC Price | AMZ Fee | ASC Cost Gound | total cost | ASC GM $ | GM % | ASC Cost Smart Post | total cost | ASC SP GM $ | GM % |  | Sugested FBA Price | FBA FEES | FBA Ship cost | FBA Cost - landed cost | FBA GM $ | GM % |  | SFP Price | SFP Shipping Cost | SFP GM $ | GM % |  | [NAME] | [NAME] | DS GM $ | GM % |  | VC Direct Price | VC Direct Cost | VC GM $ | GM % | Most Profit | service
16.95 | 2.54 | 9.79 | 15.8 | 1.15 | 0.07 | 5.8 | 11.81 | 5.14 | 0.3 |  | 16.95 | 2.54 | 5.64 | 11.65 | 5.3 | 0.31 |  | 15.95 | 9.79 | 6.16 | 0.39 |  | 9.04 | 0 | 5.57 | 0.62 |  | 3.8 | 2.8 | 1 | 0.26 |  | SFP GM $
14.95 | 2.24 | 9.79 | 15.2 | -0.25 | -0.02 | 5.8 | 11.21 | 3.74 | 0.25 |  | 14.95 | 2.24 |  | 5.41 | 9.54 | 0.64 |  | 14.95 | 9.79 | 5.16 | 0.35 |  | 12 | 0 | 8.83 | 0.74 |  |  |  | 0 | #[NAME]! |  | FBA GM $
17.99 | 2.7 | 9.79 | 15.91 | 2.08 | 0.12 | 5.2 | 11.32 | 6.67 | 0.37 |  | 17.99 | 2.7 | 5.24 | 11.36 | 6.63 | 0.37 |  | 15.95 | 9.79 | 6.16 | 0.39 |  | 11.5 | 0 | 8.08 | 0.7 |  |  |  | 0 | #[NAME]! |  | DS GM $
19.99 | 3 | 9.79 | 15.96 | 4.03 | 0.2 | 5.2 | 11.37 | 8.62 | 0.43 |  | 19.99 | 3 | 5.67 | 11.84 | 8.15 | 0.41 |  | 15.95 | 9.79 | 6.16 | 0.39 |  | 9.97 | 0 | 6.8 | 0.68 |  |  |  | 0 | #[NAME]! |  | ASC SP GM $
Spreadsheet: sally_beck__33957__Weekly Operating Report 2-22
Sheet: EIM New Deals

New Deals for | JANUARY |  |  |  |  |  |  |  | FEBRUARY
 | Week Ending 4 |  | Week Ending 11 |  | Week Ending 18 |  | Week Ending 25 |  | Week Ending 1 |  | Week Ending 8 |  | Week Ending 16 |  | Week Ending 22
 | EOL | Non-EOL | EOL | Non-EOL | EOL | Non-EOL | EOL | Non-EOL | EOL | Non-EOL | EOL | Non-EOL | EOL | Non-EOL | EOL | Non-EOL
Financial
ENA
Gas (Calgary)
Gas (Houston)
Power (Houston)
Power (Calgary)
EIM
Lumber | 0 | 23 | 0 | 7 | 0 | 10 | 0 | 19 | 0 | 19 | 0 | 24 | 0 | 8 | 0 | 9
Newsprint | 0 | 2 | 2 | 0 | 0 | 2 | 0 | 2 | 0 | 0 | 0 | 10 | 0 | 12 | 0 | 0
Pulp (recycled paper) | 0 | 1 | 0 | 4 | 0 | 12 | 0 | 10 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 2
Steel | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0
EGM
IR/FX
Weather
Liquids
Emissions
Physical
ENA
Gas (Houston)
Gas (Calgary)
Power (Houston)
Power (Calgary)
EIM
Lumber | 1 | 62 | 12 | 107 | 10 | 83 | 2 | 103 | 5 | 62 | 7 | 38 | 4 | 26 | 2 | 30
Newsprint | 0 | 3 | 0 | 15 | 1 | 6 | 0 | 22 | 0 | 4 | 0 | 2 | 0 | 18 | 0 | 17
Pulp (recycled paper) | 4 | 1 | 3 | 10 | 0 | 12 | 0 | 9 | 2 | 23 | 4 | 13 | 3 | 12 | 3 | 18
Steel | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 0 | 0
EGM
Liquids
Coal