tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 02d1dae1-973a-43a7-8632-adf467bd0460
Sheet: SV

Table | El Salvador |  | Latin America and the Caribbean
 | Grain | Root | Commercial | Food aid |  | Aggregate
Year | production | production | imports | receipts |  | availability
 |  | (grain equiv.) | (grains) | (grain equiv.) |  | of all food
 |  |  | ---1,000 tons ---
2002 | 804.534 | 20.22263752132273 | 688.286695 | 91.774205 |  | 1760.991881528018
2003 | 783.961 | 21.27011193061771 | 799.157784 | 11.542731 |  | 1731.857419872055
2004 | 813.364 | 18.9585746714384 | 826.576363 | 12.175193 |  | 1716.469032483478
2005 | 886.322 | 19.88226705566508 | 778.031695 | 66.68124300000001 |  | 1716.94311982616
2006 | 926.758 | 18.75989392012447 | 937.846708 | 19.048876 |  | 1722.480114754936
2007 | 1039.426 | 19.59821650853267 | 947.674047 | 3.938951 |  | 1732.934930110407
2008 | 1194.3101 | 20.83977677937558 | 589.86876 | 1.09424 |  | 2061.749119370761
2009 | 982.2029 | 20.22769651753609 | 732.00189 | 0.808698 |  | 2087.431311539289
2010(e) | 898.7627 | 19.93584953895915 | 766.0778075276656 | 1.947296333333333 |  | 2039.293464724947
Projections |  |  |  | Food gaps*
 |  |  |  | NG | DG
2011 | 1086.599600017736 | 20.1402636311013 | 710.3349605164019 | 0 | 38.49180760997766 | 2041.098518655473
2016 | 1143.854409471415 | 21.16893746841934 | 787.2336980249894 | 0 | 18.51168055882044 | 2223.042245916085
2021 | 1197.570213793129 | 22.20850891184893 | 831.1362735395151 | 0 | 16.28733782560067 | 2345.047944568088
Source: Economic Research Service, using data from FAOSTAT (grain and root and tuber production and imports), and the World Food Program (food aid).
*NR stands for nutritional requirements and describes the amount of grain equivalent needed to support nutritional standards on
*NG stands for nutritional gap and describes the amount of grain equivalent needed to support nutritional standards on
income quintile to reach the nutrional requirement.
Spreadsheet: 841380d1693564331-countifs-not-counting-correctly-help
Sheet: DROPDOWN

Completed |  |  | ACTON
Unable to [NAME] |  |  | BRENT
Moved to Another Office |  |  | EALING
 |  |  | EalingReep
 |  |  | FULHAM
 |  |  | HAMMERSMITH
 |  |  | Harlesden
 |  |  | QUEENSPARK
WC (NAME) |  |  | HARROW
TEAM LEADER (NAME) |  |  | HAYES |  |  |  |  |  | 2023-06-01 00:00:00
 |  |  | VALIANTHOUSE |  |  |  |  |  | 2023-06-30 00:00:00
 |  |  | HOUNSLOW
 |  |  | HOUNSLOWREEP
 |  |  | KINGSTON
 |  |  | SHEPHERDSBUSH
 |  |  | TWICKENHAM
 |  |  | UXBRIDGE
 |  |  | WANDSWORTH
Spreadsheet: 475e6472-785b-41fd-961b-d2f47d1afb1f
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
FIMM | Test | FIMM | Immunofixation, CSF | Immunofixation, CSF | Immunofixation | [NAME], sterile container: SrwStlCont |  |  | 3 | mL | Collect 3 mL of spinal fluid. Send specimen frozen. | 2.5 mL | Specimens other than	CSF Anticoagulants other than	NA Hemolysis	NA Thawing	Warm reject; Cold OK Lipemia	NA Icteric	NA | Reference Range: No monoclonal proteins added.      This test was developed and its performance characteristics determined by Quest Diagnostics Nichols Institute. It has not been cleared or approved by the U.S. Food and Drug Administration. The FDA has determined that such clearance or approval is not necessary. Performance characteristics refer to the analytical performance of the test.    Test Performed By:  Quest Diagnostics Nichols Institute                                           33608 [NAME]San Juan Capistrano, CA  92690-6130 | Monday through Saturday | 2-3 days, depending on repeat status | 3-5 days, depending on repeat status | 1 | 86335 |  |  |  |  | Quest Diagnostics/Nichols Institute
FIMM | [NAME] | CSF | CSF |  |  |  | Frozen | 30 days
FIMM | Result | Z1570 | Interpretation: | Interpretation: | Alphanumeric |  |  |  |  |  |  |  |  |  |  |  |  |  |  | In Process
Spreadsheet: lisa_gang__22270__ENA_PGE_APRIL_24_2002
Sheet: JD-MAL OR CPTJK TRANS

From: | EPMI
To: | PGE System Transactions
Date: | 2002-04-24 00:00:00
Total Transmission
HE
ENDING | PGE TRANNY | PGE TRANNY | TOTAL
Pacific Prevailing
Time | NOT FOR TOM, ET AL | NOT FOR TOM, ET AL | [NAME] USED
(PPT) |  |  | Total In To PGE Trans
0100 |  | 0
0200 | 0 | 0
0300 | 0 | 0
0400 | 0 | 0
0500 | 0 | 0
0600 | 0 | 0
0700 | 75 | 75
0800 | 75 | 75
0900 | 75 | 75
1000 | 75 | 75
1100 | 75 | 75
1200 | 75 | 75
1300 | 75 | 75
1400 | 75 | 75
1500 | 75 | 75
1600 | 75 | 75
1700 | 75 | 75
1800 | 75 | 75
1900 | 75 | 75
2000 | 75 | 75
2100 | 75 | 75
2200 | 75 | 75
2300 | 0 | 0
2400 | 0 | 0
 | BPA(G) | BPA(G)
 | BPA(T)SYS/JD | BPA(T)SYS/JD
 | AVISTA(PSE) | AVISTA(PSE)
 | EPMI(PSE) | EPMI(PSE)
 | PGE(T)JD/MAL5 | PGE(T)JD/MAL5
 | EPMI(PSE) | EPMI(PSE)
 | AVISTA(PSE) | AVISTA(PSE)
 | TEMU | PGE
 | WAPA | MORGAN
 | CISO(T)MAL5/NP15 | APX
 | WAPA(L,FS) CISO (CA) | ISO(T)MALIN/NP15
 |  | APX(L,FS) CISOI (CA)
Spreadsheet: 800827d1665913322-count-sessions-if-a-date-time-falls-within-a-specific-range-sample-session-workbook
Sheet: Sheet5

Day of Month | Shift 1 | Shift 2 | Shift 3 |  |  |  |  | Start Shifttimes
1 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59 |  | Start | 2022-07-08 05:59:00 |  | 06:00:00
2 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59 |  | Finish | 2022-07-21 14:00:00 |  | 14:00:00
3 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59 |  |  |  | [NAME] | 21:00:00
4 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59 |  | Total Sessions | 42
5 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
6 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
7 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
8 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
9 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
10 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
11 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
12 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
13 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
14 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
15 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
16 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
17 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
18 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
19 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
20 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
21 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
22 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
23 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
24 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
25 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
26 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
27 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
28 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
29 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
30 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
31 | 06:00 - 13:59 | 14:00 - 20:59 | 21:00 - 05:59
Spreadsheet: 141084d1329079873-excel-2007-how-to-grab-information-from-other-sheets-and-place-it-in-the-main-sheet-fulllist
Sheet: Running

 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Accounts (see 'EventList' Worksheet for Entry Fees)
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Insert $ pd in appropriate
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Pymt Method
Event & Age Category (use dropdown list) | Team Name (if applicable) | Level of Play | First Name | Last Name | Capt(*) | Sex | Date of Birth | Address | Suburb | State(abbr) | Postcode | Phone # | [NAME] | [NAME] | Golf Club | Squash Grade | Tenpin Average | Bowling Centre | Preferred Day | Time | Rego/Soc | Business Unit | Employee# | T-Shirt Size | Cheque | Cash | Direct Deb | Total |  | Notes
4604 Road Running 5K Women -30 |  |  | Rebecca | Morgan | Morgan | F | 1984-07-30 00:00:00 | Lvl 7, 68 York St | Sydney | NSW | 2000 | 93202200 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | 8 |  |  | 50
4607 Road Running 5K Men 30-39 |  |  | [NAME] | Lay | Lay | M | 1981-09-23 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | M |  |  | 50
4607 Road Running 5K Men 30-39 |  |  | Jorge | Moreno | Moreno | M | 1980-11-29 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | L |  |  | 50
4607 Road Running 5K Men 30-39 |  |  | Adam | Persen | Persen | M | 1981-03-06 00:00:00 | Quad 1, 8 Parkview Road | [NAME] | NSW | 2117 |  | [EMAIL] |  |  |  |  |  |  |  |  |  |  | L |  |  | 50
4609 Road Running 5K Men 40-49 |  |  | [NAME] | Tolhurst | Tolhurst | M | 1966-10-30 00:00:00 | Quad 1, 8 Parkview Road | [NAME] | NSW | 2117 |  | [EMAIL] |  |  |  |  |  |  |  |  |  |  | XL |  |  | 50
4609 Road Running 5K Men 40-49 |  |  | [NAME] | Varaprasad | Varaprasad | M | 1963-02-01 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | S |  |  | 50
4612 Road Running 5K Women 50-59 |  |  | [NAME] | Utterson | Utterson | F | 1960-11-18 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | 14 |  |  | 50
4613 Road Running 5K Men 50-59 |  |  | [NAME] | Costa | Costa | M | 1956-12-22 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | L |  |  | 50
4623 Road Running 10K Men 30-39 |  |  | Jeremy | Hill | Hill | M | 1978-10-01 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | M |  |  | 50
4623 Road Running 10K Men 30-39 |  |  | Nick | [NAME] | [NAME] | M | 1978-03-22 00:00:00 | Lvl 7, 68 York St | Sydney | NSW | 2000 | 93202200 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | S |  |  | 50
4627 Road Running 10K Men 50+ |  |  | [NAME] | Olmos | Olmos | M | 1953-10-29 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 | 96479647 | [EMAIL] |  |  |  |  |  |  |  |  |  |  | XL |  |  | 50
4627 Road Running 10K Men 50+ |  |  | Derek | Liebenberg |  | M | 1954-05-03 00:00:00 | 29 Nyrang St | Lidcombe | NSW | 2141 |  |  |  |  |  |  |  |  |  |  |  |  | L |  |  | 50
Spreadsheet: 155506d1336904001-arrays-question-anotherwa2doit2
Sheet: Sheet2

 | [NAME] | coef | Inga | coef | Alise | coef | today()
[NAME] | 2012-01-01 00:00:00 | 1.688710444469143 | 2012-01-06 00:00:00 | 1.371252155020653 | 2012-01-03 00:00:00 | 1.040553926723608 | 2012-02-14 00:00:00
Alise | 2012-02-15 00:00:00 | 0.9871740102151009 | 2012-02-02 00:00:00 | 0.8076068832731258 | 2012-02-04 00:00:00 | 0.6022022025140813
 | 2012-03-25 00:00:00 | 0.07976106303538122 | 2012-03-31 00:00:00 | 0.1160746904611686 | 2012-03-15 00:00:00 | 0.5758473982879398
1. Getting coef knowing raws |  |  |  |  | 4. Maybe the future index solution
 |  |  | 0.9871740102151009
 |  |  | 0.5758473982879398 |  | index
 |  |  |  |  | Array | C1:Q1
2. Getting coef per one column |  |  |  |  | Row number | MATCH(SMALL(IF($C$2:$C$4>A13,$C$2:$C$4),1),$C$2:$C$4,0)
 |  | a | 0.9871740102151009 |  |  | MATCH(A13,$C$2:$C$4,1)+1
 |  | b | 0.9871740102151009 |  | Col number | match(A3:A5,C1:Q1)+2
3.Getting right columns
 |  |  | 1 |  | [NAME] | Alise
 |  |  | 5 |  | 2012-01-01 00:00:00 | 2012-01-03 00:00:00 |  |  | 0 | 0 | #N/A
 |  |  |  |  | 2012-02-15 00:00:00 | 2012-02-04 00:00:00 |  |  | 17 | 0 | #N/A
4. Two dimensional lookup |  |  |  |  | 2012-03-25 00:00:00 | 2012-03-15 00:00:00 |  |  | 18 | 18 | #N/A
 |  |  | #N/A |  |  |  |  |  | #N/A | #N/A | #N/A
 |  |  | #N/A |  |  |  |  |  | #N/A | #N/A | #N/A
 |  |  | 3
Spreadsheet: 738848d1625282273-predict-future-re-orders-of-a-product-product-repurchase-model-template
Sheet: CarinaC21

Product Repurchase Estimates
 |  | REPURCHASE ASSUMPTIONS
 |  | Product |  | 1st Re Order |  | 2nd Re Order |  | 3rd Re Order |  | 4th Re Order |  | 5th Re Order |  | 6th Re Order
 |  |  |  | % | Time Lag (Months) | % | Time Lag (Months) | % | Time Lag (Months) | % | Time Lag (Months) | % | Time Lag (Months) | % | Time Lag (Months)
 |  | Product 1 | Serum | 0.2 | 2 | 0.35 | 2 | 0.5 | 2 | 0.5 | 2 | 0.5 | 2 | 0.5 | 2
 |  | Product 2 | Serum | 0.2 | 2 | 0.35 | 2 | 0.5 | 2 | 0.5 | 2 | 0.5 | 2 | 0.5 | 2
 |  | Product 3 | Serum | 0.2 | 2 | 0.35 | 2 | 0.5 | 2 | 0.5 | 2 | 0.5 | 2 | 0.5 | 2
 |  | Product 4
 |  | Product 5
 |  | Product 6
 |  | Product 7
 |  | Product 8
 |  | Month 1 | Month 2 | Month 3 | Month 4 | Month 5 | Month 6 | Month 7 | Month 8 | Month 9 | Month 10 | Month 11 | Month 12 | Month 13 | Month 14 | Month 15 | Month 16 | Month 17 | Month 18 | Month 19 | Month 20 | Month 21 | Month 22 | Month 23 | Month 24
PRODUCT 1 -  UNIT SALES
- First Orders (Units) |  | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 101 | 102 | 103 | 104 | 105 | 106
- Repeat Orders
PRODUCT 2 -  UNIT SALES
- First Orders (Units) |  | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 101 | 102 | 103 | 104 | 105 | 106
- Repeat Orders
PRODUCT 3 -  UNIT SALES
- First Orders (Units) |  | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 101 | 102 | 103 | 104 | 105 | 106
- Repeat Orders
Spreadsheet: 109973d1306781177-dependant-custom-sort-tracking
Sheet: Sheet3

WellPhase |  | DrivePipe30in | SurfaceCasing20in | IntermediateCasing14in | StageList
DrivePipe30in |  | Delivery-DP | Delivery-SC | Delivery-IC | Delivery-DP
SurfaceCasing20in |  | Hammer-DP | [NAME] | [NAME] | Hammer-DP
IntermediateCasing14in |  | Other-DP | Drilling/Tripping-SC | Drilling/Tripping-IC | Other-DP
 |  |  | Casing-SC | Coring-IC | Delivery-SC
 |  |  | Cementing-SC | Casing-IC | [NAME]
 |  |  | [NAME] | Cementing-IC | Drilling/Tripping-SC
 |  |  | Other-SC | [NAME] | Casing-SC
 |  |  |  | Other-IC | Cementing-SC
 |  |  |  |  | [NAME]
 |  |  |  |  | Other-SC
 |  |  |  |  | Delivery-IC
 |  |  |  |  | [NAME]
 |  |  |  |  | Drilling/Tripping-IC
 |  |  |  |  | Coring-IC
 |  |  |  |  | Casing-IC
 |  |  |  |  | Cementing-IC
 |  |  |  |  | [NAME]
 |  |  |  |  | Other-IC
Spreadsheet: 843411d1695254138-converting-data-into-proper-dataset-example_sn-table
Sheet: Sheet1

What I have:
Part Number | Qty | Serial numbers
Part 1 | 2 | P1SN1 | P1SN2
Part 2 | 1 | P2SN1
Part 3 | 4 | P3SN1 | P3SN2 | P3SN3 | P3SN4
What Need:
Part Number | Serial numbers
Part 1 | P1SN1
Part 1 | P1SN2
Part 2 | P2SN1
Part 3 | P3SN1
Part 3 | P3SN2
Part 3 | P3SN3
Part 3 | P3SN4
Spreadsheet: mark_haedicke__24590__2002 Plan Budget Pack - Legal Group 021001(HCODE)
Sheet: Index

 |  | Page
 |  | 3 | Cost Summary
 |  |  | P&L Expense Analysis
 |  | 5 | Plan Legal Spend 2001
 |  | 6-7 | Plan Legal Spend 2002
 |  | 8 | Headcount Summary
 |  | 9 | Headcount Org Chart
 |  | 10 | Legal Department Core Activities
 |  | 11-12 | Allocations
 |  | 13 | Corporate Allocations
 |  | 14 | [NAME]
 |  |  | EXPENSE DETAIL
 |  | 15-18 | Expense Detail
Spreadsheet: darrell_schoolcraft__7319__imball0202
Sheet: EPFS

 | El Paso/TW Eddy Rec
 | 78093
Day | Measured | Scheduled
1 | 31118 | 31456
2 | 26432 | 31456
3 | 27387 | 31394
4 | 31954 | 31456
5 | 31066 | 34456
6 | 37507 | 36936
7 | 37808 | 38956
8 | 38181 | 39034
9 | 38435 | 39956
10 | 36511 | 39956
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
2002-01-31 00:00:00 |  |  | 100916
2002-02-10 00:00:00
CBS Volume
 |  |  | 62232
Spreadsheet: 89438d1289236150-excel-2007-copying-data-will-multiple-rows-to-another-worksheet-test
Sheet: Quote

QUOTE
Ref.No | RTZ/R335321/XYZ/523
DATE | 2010-11-08 00:00:00
Company name | Xyz Corp | using data validation
Address | 30, Raymond Street | using vlookup
City | [NAME] | using vlookup
SL.NO | [NAME] | WIDTH | LENGTH | QTY | PRICE
1 | Metal Sheet | 1700 MM | 1500 MM | 20 | 4500
2 | Metal Sheet | 2100 MM | 1250 MM | 45 | 3915
3 | Metal Sheet | 1450 MM | 937 MM | 23 | 4200
4 | Metal Sheet | 1325 MM | 1165 MM | 14 | 3150
5
TERMS & CONDITIONS:
PAYMENT | ADVANCE
VALIDITY | 1 WEEK
FREIGHT | [NAME]
 | this entered data, will be updated to database with the click of command button
PROBLEM: | SL.NO - 5 has no data entered but, the Ref.No, Date, Company Name, Address, City,Payment, Validity & Freight are same for all the items,
 | please show me better solution & simple
 | please tell me [NAME],  not macro
Spreadsheet: 886661d1736758114-multiple-coulmns-to-be-auto-generated-based-on-permutation-dataset
Sheet: Sheet1

 |  | Dataset
 |  | A | Ignore | 1001 | 1002 | Ignore | 1003
 |  | B | Ignore | 2001 | 2002 | Ignore | Ignore
 |  | ID | Subject 1 | Subject 2 | Subject 3 | Subject 5 | Subject 6
 |  | 1 | 100 | 200 | 300 | 800 | 900
 |  | 2
 |  | 3
 |  | 4
 |  | Desired output
 |  | A &B | ID | Amount | Amount
 |  | 1001 | 1
 |  | 1001 | 2
 |  | 1001 | 3
 |  | 1001 | 4
 |  | 1002 | 1
 |  | 1002 | 2
 |  | 1002 | 3
 |  | 1002 | 4
 |  | 1003 | 1
 |  | 1003 | 2
 |  | 1003 | 3
 |  | 1003 | 4
 |  | 2001 | 1 |  | 200
 |  | 2001 | 2 |  | 201
 |  | 2001 | 3 |  | 202
 |  | 2001 | 4 |  | 203
 |  | 2002 | 1 |  | 300
 |  | 2002 | 2
 |  | 2002 | 3
 |  | 2002 | 4
Spreadsheet: 700700d1603295179-sort-a-range-of-data-by-date-and-hour-two-columns-if-there-are-duplicate-entries-sample
Sheet: SEE HERE

DATE | HOUR | COURSES | R-1 | R-2 |  |  | DATE | HOUR | COURSES | R-1 | R-2
2020-10-26 00:00:00 | 13:30:00 | [NAME] | 9C | 10C
2020-11-02 00:00:00 | 13:30:00 | Fizik | 11C | 9C
2020-11-09 00:00:00 | 13:30:00 | [NAME] | 10C | 9C
2020-10-23 00:00:00 | 12:00:00 | Felsefe | 12A | 12A
2020-10-26 00:00:00 | 12:00:00 | [NAME] | 12A | 11A
2020-10-27 00:00:00 | 12:00:00 | İngilizce | 10B | 10B
2020-10-30 00:00:00 | 12:00:00 | Kimya |  | Yedek
2020-11-02 00:00:00 | 12:00:00 | Fizik |  | Yedek
2020-11-03 00:00:00 | 12:00:00 | Tarih | 10B | 10B
2020-11-05 00:00:00 | 12:00:00 | Almanca |  | Yedek
2020-11-06 00:00:00 | 12:00:00 | [NAME] |  | Yedek
2020-11-09 00:00:00 | 12:00:00 | [NAME] |  | Yedek
2020-10-22 00:00:00 | 10:30:00 | [NAME] | 11G | 12G
2020-10-28 00:00:00 | 09:00:00 | Seç. [NAME] | 11B | 12B
2020-11-03 00:00:00 | 12:00:00 | [NAME] | 12B | 11G
2020-11-05 00:00:00 | 10:30:00 | Almanca | 11G | 11G
2020-11-09 00:00:00 | 10:30:00 | [NAME] | 10A | 10A
Spreadsheet: 40332d1238622678-how-to-clear-the-lowest-10-values-from-a-list-of-30-values-student-top20scores
Sheet: FinalScores

TOP 20 SCORES - Tests, Quizzes
Name | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | Total | Average
Jack- | 10 | 10 | 10 | 10 | 9 | 9 | 8 | 8 | 8 | 8 | 7 | 7 | 7 | 7 | 7 | 7 | 6 | 6 | 6 | 5 | 155 | 7.75
Millie- | 10 | 10 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 8 | 8 | 7 | 7 | 7 | 7 | 3 | 3 | 2 | 2 | 2 | 139 | 6.95
Ryan- | 10 | 10 | 9 | 9 | 9 | 9 | 9 | 8 | 8 | 8 | 8 | 8 | 7 | 7 | 7 | 7 | 7 | 5 | 5 | 5 | 155 | 7.75
Spreadsheet: 07da590e-6cce-495d-947b-7c9f38a71061
Sheet: Sheet1

Table 6--Wholesale corn milling product and byproduct prices, 1/12/2013 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10
Mkt year and month 1/ | Corn meal, yellow,  Chicago, IL (dollars per cwt) |  | Corn meal, yellow,  New York, NY (dollars per cwt) |  | Corn starch,  Midwest 3/ (dollars per cwt) |  | Dextrose,  Midwest (cents per pound) |  | High-fructose corn syrup (42%),  Midwest (cents per pound)
 | 2011/12 | 2012/13 | 2011/12 | 2012/13 | 2011/12 | 2012/13 | 2011/12 | 2012/13 | 2011/12 | 2012/13
Sep | 27.9925 | 29.035 | 30.2975 | 30.985 | 23.25999999999998 | 24.21999999999998 | 30.85 | 34.85 | 21.375 | 23.375
Oct | 26.7825 | 28.555 | 29.0875 | 30.385 | 22.62999999999998 | 23.04999999999998 | 30.85 | 34.85 | 21.375 | 23.3765
Nov | 26.8975 | 28.34 | 29.2025 | 30.17 | 20.04999999999998 | 22.23999999999998 | 30.85 | 35.35 | 21.375 | 23.375
Dec | 25.74 | 28.01 | 28.045 | 29.84 | 20.88999999999998 |  | 30.85 | 35.1 | 21.375 | 23.375
Jan | 24.855 |  | 26.555 |  | 19.89999999999998 |  | 34.85 |  | 23.375
Feb | 26.39833333333333 |  | 30.37 |  | 21.39999999999998 |  | 33.85 |  | 23.375
Mar | 26.1675 |  | 27.92 |  | 21.78999999999998 |  | 35.85 |  | 23.375
Apr | 25.5175 |  | 27.545 |  | 22.08999999999998 |  | 34.85 |  | 23.375
May | 24.485 |  | 26.7675 |  | 21.33999999999998 |  | 34.85 |  | 23.375
Jun | 24.295 |  | 25.995 |  | 21.24999999999998 |  | 34.85 |  | 23.375
Jul | 28.345 |  | 30.045 |  | 20.64999999999998 |  | 35.35 |  | 23.375
Aug | 30.4625 |  | 32.1625 |  | 24.09999999999998 |  | 34.85 |  | 23.375
Mkt year 2/ | 26.49486111111111 |  | 28.66604166666667 |  | 21.61249999999998 |  | 33.55833333333334 |  | 22.70833333333333
1/ September-August. Latest month is preliminary. 2/ Simple average of monthly prices for the marketing year. 3/ Bulk-industrial, unmodified. Source: Milling and Baking News, except for corn starch which is from private industry.
Date run: 1/15/2013
Spreadsheet: 59060d1259478817-generate-a-master-spreadsheet-consolidated
Sheet: ERP

 |  |  |  |  |  |  |  |  |  |  | Energy Reduction Plan
Customer Information
 | Company Name: |  |  |  | Customer Name:
 | Company Sector: |  |  |  | Contact Details:
 | Account Number: |  |  |  | Region:
Annual Baseline Information
 | Baseline Consumption / MWh | 100018 |  |  | 2008 Consumption / MWh |  |  | 101611
 | Adjusted Baseline / MWh | 104920 |  |  | Target Consumption / MWh |  |  | 94428
 |  |  |  |  | Savings Required / MWh
Model Information
 | Electricity Price / (c/kWh) | 35 |  |  | Cut-off for payback / years |  |  | 3
Savings Initiatives | Initiatives | Implementation Months | Category | Elec. Saved kW | Utilisation | MWh saved per year | CAPEX | Elec. Savings R/yr | Opex R/yr | Pay back yrs | Relative CAPEX R million /MW |  | Invisible Graph 2
Comments | - De Hoek can seemingly achieve their target without large CAPEX.
Category Listing
1. Low Cost
2. [NAME]
3. [NAME]
Spreadsheet: 837227d1689949745-formula-to-pull-from-one-tab-to-another-efhelp
Sheet: Summary

PWO # | Status | SKU | Description | [NAME] | Fill Type | Qty Req | Bulk Code | Bulk Req | Label Code | Bottle Code | [NAME]
1 | Closed | HU16860 | HU Sea Kelp 4000mg 180 Vegan Tablets | 180 | Tablets | 1111 |  | 199980 | LAB-HU-16860 | BOT-100Clear | CAP-38mmGold
2 | Closed | CU16860 | DNR - CU Sea Kelp 2000mg 180 Tablets | 180 | Tablets | 1111 | BULK-16860 | 199980 | LAB-CU-16860 | BOT-100Clear | CAP-38mmSilver