tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: mary_fischer__25364__roi_version_2_a
Sheet: MRO Supply Chain Survey

 | MRO Supply Chain Survey | Response |  |  | Y
 |  |  |  |  | N
 | A) Please select the statement that best describes the customer's physical MRO inventory control practices | 2 |  |  | 1
 | 1) Decentralized with MRO items stored in unsecured cribs |  |  |  | 2
 | 2) Central storeroom with storekeeper but inventory is not assigned to jobs or people |  |  |  | 3
 | 3) Central storeroom with storekeeper with inventory assigned to specific jobs or people |  |  |  | 4
 | B) Please select the statement that best describes the customer's MRO inventory system | 2
 | 1) Paper based or manual system with little or no usage analysis
 | 2) Decentralized or standalone electronic system with minimal usage analysis
 | 3) Enterprise system integrated with an asset management or CMMS system with detailed EOQ and ABC analysis
 | C) Please select the statement that best describes the customer's MRO purchasing system | 1
 | 1) Paper based requisitions issued by hand, driven by manual re-order methods
 | 2) Requisitions generated electronically, driven by a standalone inventory system
 | 3) Requisitions generated and approved electronically, driven by an enterprise asset management system
 | D) Please select the statement that best describes the customer's integration with the MRO supply chain | 1
 | 1) Communications (e.g., orders, returns) are handled via phone and fax with little or no electronic integration between demand (e.g., work orders) and supply (e.g., distributor)
 | 2) Your purchasing system communicates directly with most of your suppliers' order management systems but with little or no linkage to an asset management system
 | 3) MRO supply chain is fully integrated.  Asset management system communicates demand directly to the purchasing system that places orders electronically with the suppliers' order management systems
 | E) What is total value of MRO inventory on-hand? | 17000000 |  | includes 750/550 parts
 | F) What % of the inventory on-hand is MRO generic vs. OEM? | 0.9
 | G) What is the current MRO inventory turns ratio (annual disbursements / average annual inv value)? | 0.5
 | H) What is the average lead time for generic MRO items? | 55 | days | 14-90
 | I) What is total MRO spend? | 8000000 | Days
 | J) What % of the total MRO Spend is addressable (exclude services, utilities, OEM) by DSTM? | 1
 | K) What % of the Addressable Spend is off-contract (non VPA)? | 0
 | L) Are MRO items expensed (Y/N)? | N
 | M) Total number of MRO purchase orders per year? | 2000
 | N) How many employees create, approve, or transmit MRO purchase orders? | 31
 | O) On average, what % of their time is devoted to processing (search, create, approve, transmit, etc) POs? | 0.16
 | P) What is average fully loaded salary for these employees? | 114400 | Days | $55/hr
 | * Sanity Check: Current cost to process 1 purchase order based on responses M-P (generally $50-$150)
Spreadsheet: 538298d1505501571-figure-gradation-figure-gradation
Sheet: Sheet1

32427.22 |  | Total Qty.
30349.6
25906.53 |  | Avg. Of Top [20%]
24613.42
22524.85 |  | Avg. Of Medium [30%]
22032.84
21978.23 |  | Avg. Of Bottom [50%]
14547.73
14338.12
13633.5
13238.04
12320.55
12248.12
11999.27
11188.6
10871.45
10585.2
10486.4
9816.09
9750.49
9717.23
9232.72
8998.79
8920.65
8687.53
8629.08
8576.1
8529.33
8410.44
8092.39
7306.12
6433.02
6395.58
5916.84
5892.87
5621.15
5606.63
5416.76
5177.2
5014.15
4874.6
4869.75
4812.87
4790.76
4658.45
4608.66
4527.6
4417.22
4388.68
4386.12
4320
4313.18
4152
4140.43
3862.1
3856.03
3712.94
3507.94
3496.65
3465.5
3373.88
3328.8
3317.79
3195.6
3191.9
3020.93
2765.49
2677.04
2665.55
2598.25
2590.21
2470.7
2436.2
2383.48
2308.76
2298.6
2239.02
2214.73
2175.79
2148.62
2146.5
2143.05
2109.07
2103.09
2090.78
2056.35
2027.92
2005.35
1987.4
1973.75
1910.65
1881.84
1792.2
1774.76
1750
1742.4
1725.1
1705.05
1698.75
1645.83
1598.47
1598
1556.44
1553.15
1540.49
1530.3
1482.35
1482.2
1450.25
1414.2
1412.37
1408.26
1378.05
1304.55
1288.8
1247.84
1237.67
1215.07
1208.06
1179.44
1166.7
1165.8
1152.53
1151.85
1127.95
1116.12
1104.2
1098.05
1095.01
1081.55
1080.03
1070.05
1069.43
1059.35
1049.9
1040.75
1037.21
1028.86
976.15
958.28
948.25
938.25
934.29
911.6
890.3
887.98
877.35
789.6
777.91
767.07
755.7
753.15
751.8
747.6
741.75
731.09
728.83
716.96
705.02
700.8
689.4
659.4
658.58
656
625.8
619.96
611.03
607.42
598.53
596.1
591.55
579.86
577.58
568.58
567.58
562.5
554.45
552.6
549.45
540.95
533.48
523.22
521.18
518.64
512.95
510.6
500.36
498.22
495.61
492.6
490.3
485.35
472.55
464.6
458.52
451.2
444.2
444.15
440.8
437.4
436.28
427.95
425
424.73
422.55
421.77
421.4
419.85
413.49
412.35
410.2
408.05
405.78
402.97
396
392.85
392.34
375
369.8
368.4
364.4
361.2
354.15
350
345.9
344.85
342.2
336.45
334.68
334.23
324.86
321.89
319.2
317.55
308.35
302.18
299.65
298.93
290.25
289.54
286.8
286.4
285.6
285.4
279.2
276.08
274.45
273.1
272.25
270.15
270.13
258.84
254.4
249.8
246.36
243.3
241.23
239.07
238.5
235.41
231.65
227
226.7
225
224.52
219.44
217.5
216.15
215.2
215.1
206.1
204.75
202.28
195.85
195.4
192
189.75
188.9
182.4
179.14
174
172.64
168.4
167.4
163.5
163.2
156.2
154.43
153.12
151.7
150.6
150
148.72
144.68
143.3
142.52
140.85
140
134.1
131.6
126.8
125
124.1
122.77
120.6
120
117.6
114.15
113.1
112.5
112.5
111.06
107.5
106.35
105
105
102.42
100.9
94.7
94.46
90.22
90.2
90
87.75
87.62
85.4
84
83.95
82.72
82.5
81.2
73.12
72.8
71.63
70.5
70
68.7
68.25
61.8
61.02
60.9
60.75
60.15
60
59.7
56.96
54.75
54.75
52.5
50.4
48
44.1
40
37.5
31.05
30
30
30
28.3
24.3
24.3
21.97
14.14
6.6
6.6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-375.45
Spreadsheet: 272364d1382366981-freight-calculator-for-ups-jetair-using-index-match-and-max-frieght-calculator_-icmpl
Sheet: Calculator

 |  | [NAME] |  |  |  |  |  | FUEL SURCHARGE
UPS EXPORT FREIGHT CALCULATOR |  |  |  |  |  |  |  | 1.19
COUNTRY | ZONE | PRODUCTS | LxBxH | ACTUAL WEIGHT ([NAME]) | CHARGEABLE WEIGHT ([NAME]) | FREIGHT | FRIEGHT AMOUNT
Bangladesh |  | NON-DOC | 5 | 3 | 450
 | IF($C$9="ENVELOPE",INDEX(UPS_Export!B4:J4,MATCH($F$9,UPS_Export!A7:A16,-1),MATCH(INDEX(Zone_List!C2:C224,MATCH($A$9,Zone_List!B2:B224,0)),UPS_Export!B6:J6,0)),IF($C$9="DOC",INDEX(UPS_Export!B7:J16,MATCH($F$9,UPS_Export!A7:A16,-1),MATCH(INDEX(Zone_List!C2:C224,MATCH($A$9,Zone_List!B2:B224,0)),UPS_Export!B6:J6,0)),IF($C$9="Non-Doc",INDEX(UPS_Export!B20:J112,MATCH($F$9,UPS_Export!A20:A112,-1),MATCH(INDEX(Zone_List!C2:C224,MATCH($A$9,Zone_List!B2:[NAME]:[NAME])),"")))
Spreadsheet: 853970d1703926448-found-max-value-but-its-finding-first-value-christmas-comp-23-24-pointscore-fix-error
Sheet: Bream

BREAM
Date | Angler Number | Length (mm) | Angler Name | Age Group
2023-12-23 00:00:00 | 84 | 260
2023-12-23 00:00:00 | 84 | 265 | a84 | High School
2023-12-26 00:00:00 | 75 | 380 | a75 | Junior
2023-12-27 00:00:00 | 7 | 330 | a7 | Junior
2023-12-27 00:00:00 | 84 | 332 | a84 | High School
2023-12-24 00:00:00 | 29 | 310 | a29 | Junior
2023-12-24 00:00:00 | 29 | 300 | a29 | Junior
2023-12-24 00:00:00 | 30 | 323 | a30 | Junior
2023-12-28 00:00:00 | 108 | 225 | a108 | Junior
2023-12-28 00:00:00 | 101 | 260 | [NAME] | Small Fry
XX | 57 | 250 | a57 | Junior
Spreadsheet: ea3d8d8e-46f6-440d-b01c-f40e63d065a6
Sheet: Flight 8

 | SINGLES | FLIGHT "8"
 |  |  | [NAME] (UCONN)
 |  |  |  | Palmer (UC)
 |  |  | BYE
 | [NAME] (Hart) |  | [NAME] (Hartford) |  | Palmer (UC)
 |  |  |  |  | 5-7, 6-7, 10-6
 |  | [NAME] (Hart) |  | Cepeda (BU)
 |  |  | [NAME] (Boston) | 6-0, 6-0
 |  |  |  |  |  | [NAME] (Bry)
 |  |  | [NAME] ([NAME]) |  |  | 6-4, 4-6, 10-8
 |  | Phan (BU)
 |  |  | [NAME] (Boston) | [NAME] (QU)
 |  |  |  | 6-4, 6-3
 |  |  | [NAME] (Bryant) |  | [NAME] (Bry)
 |  |  |  |  | 6-2, 6-1
 |  | Cusano (SH) |  | [NAME] (Bry)
 |  |  | [NAME] ([NAME]) | 6-0, 6-0
 | Sunday 9:00am | Saturday 1:00pm | Friday 2:30pm | Saturday 1:00pm | Sunday 9:00am
 | UCONN | EO Smith | EO Smith | EO Smith | UCONN
 |  |  | Quarter Finals | Semi Finals | Finals
Spreadsheet: 05fe99ce-2e3e-4653-8480-92c54b45c2f3
Sheet: 6. Office Trend by Agency

 | FY 2012 Federal Real Property Charts
 | Office Gross Square Feet by Agency†*
 | Agency | FY 2011 | FY 2012
 | Agriculture | 21058684 | 21054052
 | Air Force** | 57120429 | 57648749
 | Army** | 113212821.86 | 114038344.595
 | Commerce | 2749095 | 2075752
 | Corps of Engineers** | 3721624.91 | 3852344
 | Defense/WHS** | 7304649.5 | 7230138
 | Energy | 20214020 | 20241213
 | Environmental Protection Agency | 261334 | 261334
 | General Services Administration | 378629276.81 | 383073177.93
 | Health and Human Services | 5759917.48 | 5264404.4
 | Homeland Security | 7514738.27 | 9242928.76
 | Interior | 14523391.79 | 14919664.88
 | Justice | 1501261 | 1554096
 | Labor | 1261229 | 1212477
 | National Aeronautics And Space Administration | 10412218 | 11576162
 | National Science Foundation | 1153407 | 539703
 | Navy** | 56584037.52 | 55689714.35
 | Office of Personnel Management | 0 | 32717
 | State | 795789 | 875353
 | State (USAID) | 3553 | 3553
 | Transportation | 4798981.3 | 4975213.3
 | Treasury | 3539936 | 3607798
 | Veterans Affairs | 15633744 | 16041124
 | Total
 | † All real property data from the CFO Act agencies required to submit data to the FRPP
 | *includes only Office Space in US States and US Territories
 | ** Department of Defense
Spreadsheet: matt_motley__26405__July orig final
Sheet: Overview

Middle Market/Trading Origination Agreement
2001-05-01 00:00:00
Book | Starting (Benchmark) Value:  Actual Trading Earnings through April 30, 2001 | Middle Market % of Book |  | [NAME]
[NAME] (Motley) | 106290833 | 0.08
[NAME] Northwest (Swerzbin) | 146981038 | 0.12
[NAME] California (Badeer) | 53346914 | 0.08
Long Term West Management (Belden) | 15461811 | 0.12
Short Term Southwest (Fischer/Alonso) | 19642529 | 0.05
Short Term Northwest (Crandall/Scholtes) | 37823394 | 0.05
Short Term California (Richter) | 61104497 | 0.05
Total
Process
1.  Effective May 1, 2001 the methodology for setting Middle Market Origination will change and remain in effect through year end.
2.  Objective of new methodology is to approximate the Origination contribution of Middle Market Group and promote teamwork.
3.  Under the new approach, Middle Market Group will earn a % of each book's earnings rather than set Origination on a deal by deal basis.
At the conclusion of each Month, Middle Market earnings will be calculated as follows.
Each book's earnings will be defined as the difference between then current book earnings and the earnings indicated above.
The Middle Market % indicated in the table above will be multiplied by this difference to calculate Middle Market income that will be taken out of each book.
Middle Market Group will be given credit for the income (or loss if applicable).
4.  The methodology for setting Middle Market Origination for January - April will not change (I.e. Origination.
has been taken out of books on a deal by deal basis).
5.  This calculation will be done prior to any reserves taken out of, or returned to, any book.
6.  The Transaction Log of Middle Market Group will be retained and the process already in place to distribute a weekly report indicating
all Middle Market transactions and their estimated value, will continue.  This process will be used to allocate Middle Market Group Origination
to individual Middle Marketers and will not affect any Trading Book.
7.  The pro forma tracking statement indicating the new methodology is attached.
8.  Middle Market Group will allocate Origination to individuals based on their % contribution to the Transaction Log.
9.  "Gaming" of new methodology to spoil teamwork or for self-benefit will not be tolerated.
10.  Exceptions can be made for extraordinary large deals closed by Middle Marketer and large Trading Gains or losses.  [NAME]
Belden reserves right to make adjustments in Origination calculations but only if the actual results are dramatically different than
his perception of equitable results and only after discussions with all Traders and Middle Marketers.
Spreadsheet: michelle_lokay__26574__imbalsumm0012
Sheet: summary

Index is high - payback should be done on Dollar Valued payables
- payback should be done on Volumetric receivable
- payback should not be done on Dollar valued receivables
- payback should not be done on Volumetric payables
Positive = due [NAME]
Negative = due operator
Operator | Dollars | Volume | As of Date | Imbal Type | MS rep | Comments |  |  |  |  |  |  |  | index
El Paso |  |  |  | Volumetric | [NAME] |  |  |  |  |  |  |  |  | SJ
NGPL |  |  |  | Volumetric | [NAME] |  |  |  |  |  |  |  |  | AVG
PG&E |  |  |  | Volumetric | [NAME]
PNM |  |  |  | Dollar Valued | [NAME]
Mewborne |  |  |  | Dollar Valued | [NAME]
Mojave Pipeline |  |  |  | Volumetric | [NAME]
Oasis |  |  |  | Volumetric | [NAME]
TransColorado |  |  |  | Dollar Valued | [NAME]
GPM |  |  |  | Dollar Valued | [NAME]
Burlington |  |  |  | Dollar Valued | [NAME] | This balance is cashed out every month.
[NAME] |  |  |  | Dollar Valued | [NAME]
Amoco Abo |  |  |  | Dollar Valued | [NAME]
CIG |  |  |  | Dollar Valued | [NAME]
Duke |  |  |  | Dollar Valued | [NAME]
PG&E TX |  |  |  | Dollar Valued | [NAME] | This balance is cashed out every month
Red Cedar |  |  |  | Dollar Valued | [NAME]
Receivable imbalances
Operator | Dollars | Volume | As of Date | Imbal Type | MS rep | Comments
Northwest |  |  |  | Volumetric | [NAME]
EOG |  |  |  | Dollar Valued | [NAME]
[NAME] |  |  |  | Volumetric | Hernandez
NNG |  |  |  | Dollar Valued | [NAME]
Amoco |  |  |  | Volumetric | [NAME]
Continental |  |  |  | Dollar Valued | [NAME]
SoCal |  |  |  | Volumetric | [NAME]
Conoco |  |  |  | Dollar Valued | [NAME]
Agave |  |  |  | Dollar Valued | [NAME]
Lonestar |  |  |  | Volumetric | [NAME]
Pan-Alberta-shipper |  |  | 2000-12-27 00:00:00 | Dollar Valued | [NAME]
Payable imbalances
Net imbals
Note -  This report does not represent the total population of imbalances on Transwestern.
Spreadsheet: 820171d1677901333-if-time-range-is-between-a-set-range-enter-number-or-word-if-time-range-is-between-a-set-time-range
Sheet: Sheet1

 | Shifts |  |  |  |  | Time range event occurred
 | Start | End |  |  |  | Start | End |  | Shift
1st | 07:00:00 | 14:59:59 |  |  |  | 15:10:53 | 16:11:37
2nd | 15:00:00 | 22:59:59 |  |  |  | 07:21:46 | 07:26:57
3rd | 23:00:00 | 23:59:59 |  |  |  | 03:23:44 | 08:29:52
3rd | 00:00:00 | 06:59:59
Spreadsheet: 4c42d030-7526-46d5-aa68-04064e5ea220
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
RHUT | Test | RHUT | Rheumatoid Factor, Serum | Rheumatoid Factor, S | Turbidometry | Serum Gel Tube: SGT |  |  | 1 | mL | Container/Tube:  Preferred: Red top Acceptable: Serum gel [NAME]: 1 mL | 0.5 mL | Hemolysis	Mild OK; Gross OK Thawing	Warm OK; Cold OK Lipemia	Mild OK; Gross reject Icterus	Mild OK; [NAME] OK Other	NA | <15 IU/mL | Monday through Friday; Once a day | 2 days | 3 days | 1 | 86431 |  |  |  |  | Rochester
RHUT | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 14 days
RHUT | Result | RHUT | Rheumatoid Factor, S | Rheumatoid Factor, S | Numeric |  |  |  |  | IU/mL |  |  |  |  |  |  |  |  |  | 11572-5
Spreadsheet: 839431d1691980472-creation-of-a-parts-ordering-program-sunday-13082023-1150am
Sheet: POWER SW

BOARD NA-06375 | power sw |  |  |  |  |  |  |  |  |  | Mouser
PART # [NAME] | TEST RESULT | NEW PART # | COST EACH | VENDOR | VENDOR PART NUMBER |  |  |  |  | VENDOR PART NUMBER | COST EACH | QTY | TOTAL |  |  | VENDOR PART NUMBER | COST EACH | QTY | TOTAL
C751 |  | SPARK ARRESTOR | 13.72 | MOUSER | 539-504M02QA100 |  |  |  | MOUSER | 539-504M02QA100 | 13.72 | 2 | 27.44 |  | MOUSER | 539-504M02QA100 | 13.72 | 2 | 27.44
C752 |  | SPARK ARRESTOR | 13.72 | MOUSER | 539-504M02QA100
SOLDER |  | CARDAS QUAD CORE | 10.5
WIRE | 18ga OFC | BNTECHGO | 5.08
[NAME] |  |  |  |  | TBD
CLEANING SUPPLIES |  |  | 10
SHIPPING |  |  |  |  | TBD
Spreadsheet: b9273faa-f584-4747-a380-0c5e259fbe7c
Sheet: Sheet1

Battle ID | Date & Time | Side | Victory | Score | Opp. Score | Opp. ID | Opp. Name | Scenario ID | Front | Start Date | End Date | Name EN | Name FR
42256122 | 2014-07-11 17:09:05 | AXIS | 1 | 8 | 5 | 225841 | sacas | 14853 | western | 1944-08-07 |  | Mortain(online)
42257661 | 2014-07-11 19:43:14 | ALLIES | 1 | 8 | 7 | 225841 | sacas | 14853 | western | 1944-08-07 |  | Mortain(online)
42274468 | 2014-07-12 22:21:32 | AXIS | 0 | 6 | 8 | 90086 | palerider68 | 14853 | western | 1944-08-07 |  | Mortain(online)
42274756 | 2014-07-12 23:00:30 | ALLIES | 1 | 8 | 7 | 90086 | palerider68 | 14853 | western | 1944-08-07 |  | Mortain(online)
42407892 | 2014-07-22 14:27:28 | AXIS | 1 | 8 | 1 | 26778 | gheintze | 14853 | western | 1944-08-07 |  | Mortain(online)
Spreadsheet: 864728d1711828352-wondering-if-there-is-a-way-to-adjust-the-info-below-text-splitting-examples-tms
Sheet: Sheet1

 |  |  |  | Source |  | Text to Columns |  | Formula 1 | Formula 2
 |  |  |  | 5526352DTRBGJMK9Q VONS #1234 ****** CA |  | VONS #1234 ****** CA
 |  |  |  | 5531020DR2DA3Q36Z TARGET.COM * [PHONE] MN |  | TARGET.COM * [PHONE] MN
 |  |  |  | 5531020DTBM8E5KSF PETCO 1234 ******* CA |  | PETCO 1234 ******* CA
 |  |  |  | 0230537DTEHYNP4AJ TRADER JOE S #123 00000 CA |  | TRADER JOE S #123 00000 CA
 |  |  |  | 0230537DT00DTTW2P MARSHALLS #[PHONE] CA |  | MARSHALLS #[PHONE] CA
 |  |  |  | X |  | X
 |  |  |  |  |  | First, select the data.
 |  |  |  |  |  | Data
 |  |  |  |  |  | Text to Columns |  | 5531020DR2DA3Q36Z TARGET.COM * [PHONE] MN
 |  |  |  |  |  | Fixed Width |  | 5531020DTBM8E5KSF PETCO 1234 ******* CA
 |  |  |  |  |  | Add Field Break |  | 0230537DTEHYNP4AJ TRADER JOE S #123 00000 CA
 |  |  |  |  |  | Set "Do not import" |  | 0230537DT00DTTW2P MARSHALLS #[PHONE] CA
 |  |  |  |  |  | Output to cell(s) (starting at) F3 |  | X
 |  |  |  |  |  |  |  | 5531020DR2DA3Q36Z TARGET.COM * [PHONE] MN
 |  |  |  |  |  |  |  | 5531020DTBM8E5KSF PETCO 1234 ******* CA
 |  |  |  |  |  |  |  | 0230537DTEHYNP4AJ TRADER JOE S #123 00000 CA
 |  |  |  |  |  |  |  | 0230537DT00DTTW2P MARSHALLS #[PHONE] CA
 |  |  |  |  |  |  |  | X
Spreadsheet: 992b8105-3f8c-445e-b7ee-39ca2cb1ac7a
Sheet: Sheet1

ID | NAME | COUNTRY | CONTINENTAL GROUP | LATITUDE | LONGITUDE | NR. INDIVIDUALS
1 | Bantu_N.E. | Kenya | Subsaharian_Africa | -3 | 37 | 11
2 | Bantu_S.E. | South_Africa | Subsaharian_Africa | -26 | 26 | 8
3 | Biaka_Pygmies | Central_African_Republic | Subsaharian_Africa | 4 | 17 | 23
4 | Mandenka | Senegal | Subsaharian_Africa | 12 | -12 | 22
5 | Mbuti_Pygmies | Democratic_Republic_of_Congo | Subsaharian_Africa | 1 | 29 | 13
6 | San | Namibia | Subsaharian_Africa | -21 | 20 | 5
7 | Colombians | Colombia | America | 3 | -68 | 7
8 | [NAME] | Brazil | America | -10 | -63 | 14
9 | Maya | Mexico | America | 19 | -91 | 21
10 | Pima | Mexico | America | 29 | -108 | 14
11 | [NAME] | Brazil | America | -11 | -62 | 8
12 | Balochi | Pakistan | Central_South_Asia | 31 | 67 | 24
13 | Brahui | Pakistan | Central_South_Asia | 31 | 67 | 25
14 | Burusho | Pakistan | Central_South_Asia | 37 | 74 | 25
15 | Hazara | Pakistan | Central_South_Asia | 34 | 70 | 22
16 | Kalash | Pakistan | Central_South_Asia | 36 | 72 | 23
17 | Makrani | Pakistan | Central_South_Asia | 26 | 64 | 25
18 | Pathan | Pakistan | Central_South_Asia | 34 | 64 | 23
19 | Sindhi | Pakistan | Central_South_Asia | 26 | 69 | 24
20 | Uygur | China | Central_South_Asia | 44 | 81 | 10
21 | Cambodians | Cambodia | East_Asia | 12 | 105 | 10
22 | Dai | China | East_Asia | 21 | 100 | 10
23 | [NAME] | China | East_Asia | 49 | 124 | 9
24 | Hezhen | China | East_Asia | 48 | 134 | 9
25 | [NAME] | China | East_Asia | 22 | 100 | 8
26 | Miaozu | China | East_Asia | 28 | 109 | 10
27 | Mongola | China | East_Asia | 49 | 119 | 10
28 | Naxi | China | East_Asia | 26 | 100 | 8
29 | Oroqen | China | East_Asia | 51 | 127 | 9
30 | She | China | East_Asia | 27 | 119 | 10
31 | [NAME] | China | East_Asia | 36 | 101 | 10
32 | Tujia | China | East_Asia | 29 | 109 | 10
33 | [NAME] | China | East_Asia | 44 | 82 | 9
34 | Yakut | Russia | East_Asia | 63 | 130 | 25
35 | [NAME] | China | East_Asia | 28 | 103 | 10
36 | Adygei | Russia | Europe | 44 | 39 | 17
37 | French | France | Europe | 46 | 2 | 28
38 | French_Basque | France | Europe | 43 | 0 | 24
39 | North_Italian | Italy | Europe | 46 | 10 | 13
40 | Orcadian | Orkney_Islands | Europe | 59 | -3 | 15
41 | Russian | Russia | Europe | 61 | 40 | 25
42 | Sardinian | Italy | Europe | 40 | 9 | 28
43 | Bedouin | Israel | Middle_East | 31 | 35 | 46
44 | [NAME] | Israel | Middle_East | 32 | 35 | 42
45 | Mozabite | Algeria | North_Africa | 32 | 3 | 29
46 | Palestinian | Israel | Middle_East | 32 | 35 | 46
47 | NAN_Melanesian | Papua_New_Guinea | Oceania | -6 | 155 | 11
48 | Papuan | Papua_New_Guinea | Oceania | -4 | 143 | 17
49 | CHB | China | East_Asia | 33 | 114 | 84
50 | GIH | India | Central_South_Asia | 23 | 73 | 88
51 | [NAME] | Japan | East_Asia | 38 | 138 | 86
52 | LWK | Kenya | Subsaharian_Africa | 0 | 35 | 90
53 | MKK | Kenya | Subsaharian_Africa | -1 | 37 | 143
54 | TSI | Italy | Europe | 43 | 11 | 88
55 | YRI | Nigeria | Subsaharian_Africa | 8 | 6 | 113
 |  |  |  |  |  | 1537
Spreadsheet: 214748d1361105683-excel-formula-from-looking-the-base-date-and-convert-into-desire-result-date-calculation-pradeepb270-oeldere-
Sheet: Sheet1

 |  |  |  |  |  | 2013-01-31 00:00:00
 | Plnt | Vendor | Material | Material Description | Date | Qty | Amount | Category
 | HHHD | 100014 | 77200-KVH-9000 | SEAT COMP  DOUBLE | 2008-01-02 00:00:00 | 3 | 1091.03 | >4 Years |  |  |  |  | 0 | <1 Year
 | HHHD | 100014 | 77200-KWA-8300 | SEAT ASSY DOUBLE | 2012-11-05 00:00:00 | 6 | 2720.2 | <1 Year |  |  |  |  | 1 | >1 Year <2 Year
 | HHHD | 100014 | 42601-AAC-H430C | WHEEL REAR DRUM (JIELI) | 2012-01-21 00:00:00 | 13 | 14320.31 | >1 Year <2 Year |  |  |  |  | 2 | >2 Year <3 Year
 | HHHD | 100014 | 42601-AAE-H230C | WHEEL REAR DRUM (JIELI) | 2011-01-21 00:00:00 | 13 | 13381.87 | >2 Year <3 Year |  |  |  |  | 3 | >3 Year <4 Year
 | HHHD | 100014 | 7720A-KCC-9000 | SEAT ASSY.DOUBLE COMP. | 2010-01-15 00:00:00 | 30 | 11223.3 | >3 Year <4 Year |  |  |  |  | 4 | >4 Years
 |  |  |  | Excel formula from looking the base date and convert into desire result
I have an excel file.I want to solve the category condition from an excel formula.In this file,G3 will be my base date and I want the excel formula in colum no.I i.e.Category.For this,look the base date i.e.[NAME] and compare to column F i.e.Date Column of each material code.
For more clarification,please refer the attach file
Spreadsheet: 768364d1644937593-trying-to-look-up-and-filter-data-example
Sheet: KROK050

KROK050
Product | Component name | Result text
Spreadsheet: 61520d1262391351-water-tank-level-formula-last-3-days-water-tank-level-1-
Sheet: Version1

 | Top | Middle |  | Most recent 3 Days
Date | Water Level | Water Level |  |  | Top | Middle
2010-01-01 00:00:00 | 60 | 50 |  | Date | Water Level | Water Level
2010-01-02 00:00:00 | 55 | 45 |  | 2010-01-02 00:00:00 | 55 | 45
2010-01-03 00:00:00 | 50 | 40 |  | 2010-01-03 00:00:00 | 50 | 40
2010-01-04 00:00:00 | 45 | 50 |  | 2010-01-04 00:00:00 | 45 | 50
 |  |  |  | Average Change Per Day | -5 | 2.5
 |  |  |  | Days Remaining | 9 | Surplus