tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 689840d1596698783-index-and-match-on-multiple-similar-tables-book1
Sheet: Sheet1

Question 3: Use INDEX and MATCH for looking up a specific table and then within that specific table looking up a value that is at the intersection of a row and column. Need to find out Shipping/Unit on the basis of Region, Shipping Method & Customer Type
 | Customer Type 10
 |  | Shipping Method - Standard |  |  |  |  |  |  | Region
 | Region | Rail | Truck | Plane | Ship |  |  |  | West
 | NW | 0.125 | 0.135 | 1.525 | 0.225 |  |  |  | Shipping Method
 | West | 0.205 | 0.145 | 2.025 | 0.245 |  |  |  | Plane
 | SW | 0.265 | 0.165 | 2.125 | 0.225 |  |  |  | Customer Type
 | MidWest | 0.305 | 0.185 | 2.275 | 0.225 |  |  |  | Customer Type 20
 | East | 0.475 | 0.425 | 3.525 | 0.375 |  |  |  | Shipping per Unit
 | Customer Type 20
 |  | Shipping Method - Preferred
 | Region | Rail | Truck | Plane | Ship
 | NW | 0.115 | 0.125 | 1.375 | 0.205
 | West | 0.185 | 0.135 | 1.825 | 0.215
 | SW | 0.245 | 0.155 | 1.915 | 0.205
 | MidWest | 0.275 | 0.165 | 2.055 | 0.205
 | East | 0.435 | 0.385 | 3.175 | 0.345
 | Customer Type 30
 |  | Shipping Method - Most Preferred
 | Region | Rail | Truck | Plane | Ship
 | NW | 0.105 | 0.115 | 1.245 | 0.175
 | West | 0.175 | 0.125 | 1.645 | 0.165
 | SW | 0.215 | 0.135 | 1.725 | 0.185
 | MidWest | 0.255 | 0.155 | 1.845 | 0.185
 | East | 0.385 | 0.345 | 2.865 | 0.305
 |  |  |  |  |  |  |  |  |  |  | Customer Type 10
 |  |  |  |  |  |  |  |  |  |  | Customer Type 20
 |  |  |  |  |  |  |  |  |  |  | Customer Type 30
Spreadsheet: 267168d1379985471-list-box-with-prompt-function-listbox
Sheet: Sheet1

 |  |  | Apple
Fruits |  |  | [NAME]
 |  |  | Avocado
 |  |  | [NAME]
 |  |  | Breadfruit
 |  |  | [NAME]
 |  |  | Blackberry
 |  |  | Blackcurrant
 |  |  | Blueberry
 |  |  | [NAME]
 |  |  | Currant
 |  |  | [NAME]
 |  |  | Cherimoya
 |  |  | Chili
 |  |  | [NAME]
 |  |  | Coconut
 |  |  | [NAME]
 |  |  | Date
 |  |  | Dragonfruit
 |  |  | Durian
 |  |  | Elderberry
 |  |  | [NAME]
 |  |  | Fig
 |  |  | Gooseberry
 |  |  | Grape
 |  |  | Grapefruit
 |  |  | Guava
 |  |  | Huckleberry
 |  |  | Honeydew
 |  |  | Jackfruit
 |  |  | Jettamelon
 |  |  | Jambul
 |  |  | Jujube
 |  |  | Kiwi fruit
 |  |  | Kumquat
 |  |  | Legume
 |  |  | Lemon
 |  |  | Lime
 |  |  | Loquat
 |  |  | Lychee
 |  |  | Mango
 |  |  | Melon
Spreadsheet: 154819d1336573572-pulling-two-lists-into-one-and-showing-duplicates-refren
Sheet: NCMR

Internal NCMR
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | K17015045 Rev. A
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Part # |  |  |  | K11200811 Rev A
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | [NAME] #
 | Added By |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Company
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Company | [NAME] | Full. Date | Where It is
 | Date to be Filed |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Company NCMR ID
 | Part Number |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Internal RMA #
 | Part Revision |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Job #
 | Part Description |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Fabricators
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | NCMR Qty
 | Nonconformity
 | Disposition
 | Comments
 | Comments and/or Additional Details
 | PO: |  |  |  |  |  |  | PO Date: |  |  |  |  |  |  |  |  | Date Received:
Spreadsheet: 826446d1682012645-byrow-retrieve-value-in-a-dynamic-array-retrieve_value_byrow
Sheet: prices (2)

id | qty | expected_result | current_result
Al-100 | 50 | 1165 |  |  |  |  |  |  |  |  |  | Al-100 | 2023-04-17 00:00:00 | 30 | g | 1165 | USD
Al-100 | 100 | 1165 |  |  |  |  |  |  |  |  |  | Al-100 | 2023-04-17 00:00:00 | 1000 | g | 922 | USD
[NAME] | 250 | 1200 |  |  |  |  |  |  |  |  |  | [NAME] | 2023-04-17 00:00:00 | 30 | g | 1500 | USD
[NAME] | 500 | 1100 |  |  |  |  |  |  |  |  |  | [NAME] | 2023-04-17 00:00:00 | 500 | g | 1100 | USD
[NAME] | 1000 | 865 |  |  |  |  |  |  |  |  |  | [NAME] | 2023-04-17 00:00:00 | 1000 | g | 865 | USD
Al-102 | 50 | 1000 |  |  |  |  |  |  |  |  |  | Al-102 | 2023-04-17 00:00:00 | 30 | g | 1000 | USD
Al-102 | 100 | 1000 |  |  |  |  |  |  |  |  |  | Al-102 | 2023-04-17 00:00:00 | 1000 | g | 830 | USD
Al-103 | 250 | 940 |  |  |  |  |  |  |  |  |  | Al-103 | 2023-04-17 00:00:00 | 30 | g | 940 | USD
Al-103 | 500 | 940 |  |  |  |  |  |  |  |  |  | [NAME] | 2023-04-17 00:00:00 | 100 | g | 1200 | USD
Al-104 | 1000 | 46 |  |  |  |  |  |  |  |  |  | Al-104 | 2023-04-17 00:00:00 | 1000 | g | 46 | USD
Al-105 | 50 | 33 |  |  |  |  |  |  |  |  |  | Al-105 | 2023-04-17 00:00:00 | 25000 | g | 33 | USD
Al-130 | 100 | 29 |  |  |  |  |  |  |  |  |  | Al-130 | 2023-04-17 00:00:00 | 25000 | g | 29 | USD
Al-111 | 250 | 71 |  |  |  |  |  |  |  |  |  | Al-111 | 2023-04-17 00:00:00 | 1000 | g | 71 | USD
Al-112 | 500 | 39 |  |  |  |  |  |  |  |  |  | Al-112 | 2023-04-17 00:00:00 | 1000 | g | 39 | USD
Al-113 | 1000 | 7 |  |  |  |  |  |  |  |  |  | AA7075-100 | 2023-04-17 00:00:00 | 500 | g | 130 | USD
Al-113 | 50 | 8 |  |  |  |  |  |  |  |  |  | Al-113 | 2023-04-17 00:00:00 | 1000 | g | 7 | USD
AA7075-100 | 100 | 120 |  |  |  |  |  |  |  |  |  | AA7075-100 | 2023-04-17 00:00:00 | 1000 | g | 120 | USD
AA7075-101 | 250 | 106 |  |  |  |  |  |  |  |  |  | AA7075-101 | 2023-04-17 00:00:00 | 1000 | g | 106 | USD
AA7075-102 | 500 | ALERT |  |  |  |  |  |  |  |  |  | Al-113 | 2023-04-17 00:00:00 | 500 | g | 8 | USD
AA7075-103 | 1000 | ALERT
AA7075-104 | 50 | ALERT
Spreadsheet: 537845d1505298669-need-formula-assistance-need-formula-assistance
Sheet: Sheet1

Head | [NAME] | Loc2 | Loc3 | Loc4 | Loc5 | Loc6 | Loc7 | Loc8 | Loc9 | Loc10 | Loc11 | Loc12 | Loc13 | Loc14
AXA | KARACHI  [I] | KARACHI  [E] | MUNDRA  [E] | SOHAR  [E] | JEBEL ALI  [E] | BAHRAIN  [E] | SHUAIBA  [E] | UMM QASR  [E] | UMM QASR  [I] | BAHRAIN  [I] | ABU DHABI  [I] | [NAME]  [I] | JEBEL ALI  [I] | SOHAR  [I]
AXB | NHAVA SHEVA  [I] | NHAVA SHEVA  [E] | PIPAVA  [E] | COLOMBO  [E]
AXC | JEBEL ALI  [I] | JEBEL ALI  [E] | UMM QASR  [E]
AXD | COLOMBO  [I] | NHAVA SHEVA  [I] | NHAVA SHEVA  [E]
AXE | JEBEL ALI  [I] | JEBEL ALI  [E] | BANDAR ABBAS  [E]
AXC
 | Export | Import
Spreadsheet: 144717d1331112812-hyperlink-vlookup-copying-different-columns-by-order-from-hyperlink-doc-to-another-m_oioisju2
Sheet: Sheet1

 | 10 | 14 | 12 | 2 | 3 | 4 | 5 | 7 |  | 8
1 |  |  |  |  |  |  |  |  |  |  | Z
2 |  |  |  |  |  |  |  |  |  |  | Z
3 |  |  |  |  |  |  |  |  |  |  | P
 | Hi
 | See B1 to M1 number in =IFERROR(VLOOKUP($A2,[Book1.xlsx]Sheet1!$A$1:$O$4,E$1,FALSE),"")
 | See say E$1 is 2 It would have been =IFERROR(VLOOKUP($A2,[Book1.xlsx]Sheet1!$A$1:$O$4,2,FALSE),"")
 | I make this easy as you can change number to match from lookup.
 | All [NAME] are from A1 to A4 in Book 1 and 2 in order to work
 | Hope this what you looking for
Spreadsheet: 287404d1388778517-create-a-consolidated-list-sample-workbook2
Sheet: Customer by Rep

Select Sales Rep |  |  |  |  |  |  |  |  | Reps
AARO |  |  |  |  |  |  |  |  | AARO
 |  |  |  |  |  |  |  |  | BRAD
Customers |  |  |  |  |  |  |  |  | BREN
SalespersonNo | AARO |  |  |  |  |  |  |  | DENN
 |  |  |  |  |  |  |  |  | DON
Row Labels | CustomerName |  |  |  |  |  |  |  | DONN
03-0000136 | Customer 315 |  |  |  |  |  |  |  | FERN
03-0000356 | Customer 320 |  |  |  |  |  |  |  | HOUS
03-0000463 | Customer 323 |  |  |  |  |  |  |  | [NAME]
03-0000499 | Customer 326 |  |  |  |  |  |  |  | [NAME]
03-0000507 | Customer 327 |  |  |  |  |  |  |  | QUIN
03-0000537 | Customer 329 |  |  |  |  |  |  |  | MARK
03-0000568 | Customer 341
03-0000580 | Customer 344
03-0000595 | Customer 349
03-0000602 | Customer 352
03-0000604 | Customer 353
03-0000610 | Customer 354
03-0000636 | Customer 360
03-0000641 | Customer 362
03-0000671 | Customer 365
03-0000680 | Customer 367
03-0000686 | Customer 371
03-0000708 | Customer 374
03-0000718 | Customer 377
03-0000727 | Customer 380
03-0000742 | Customer 385
03-0000745 | Customer 386
03-0000746 | Customer 387
03-0000960 | Customer 390
03-0001293 | Customer 403
03-0001324 | Customer 405
03-0001332 | Customer 406
03-0001343 | Customer 407
03-0009179 | Customer 411
03-0009841 | Customer 413
03-0009883 | Customer 414
03-0010436 | Customer 423
Grand Total
Spreadsheet: 875999d1722628375-formula-macro-or-vba-to-solve-this-project-learning
Sheet: Vendor C

 | Date | Vendor | Category | [NAME] | Net | IVA | Total | Balance
 | 2024-06-04 00:00:00 | Vendor C | Plumbing | [NAME] | 159.99 | 20.8 | 180.79 | 180.79
 | 2024-06-08 00:00:00 | Vendor C | Electrical | Pendant Lights | 832.98 | 108.29 | 941.27
Spreadsheet: 736b7cc5-b045-4fd2-b15c-9dea8ed6bae8
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
INHP | Test | INHP | Isoniazid, Serum/Plasma | Isoniazid | High-Performance Liquid Chromatography (HPLC) | Plain, Red-Top Tube: Red |  |  | 2 | mL | Submit only 1 of the following specimens:   Serum Draw blood in a plain, red-top tube(s). (Serum gel tube is not acceptable.) Spin down and send 2 mL of serum frozen in plastic vial. Note:  	1. Indicate serum on request form. 		2. Label specimen appropriately (serum).   [NAME] blood in a lavender-top (EDTA) tube(s). ([NAME] tube is not acceptable.) Spin down and send 2 mL of EDTA plasma frozen in plastic vial. Note:  	1. Indicate plasma on request form.               2. Label specimen appropriately (plasma). | 0.7 mL | Specimens other than	Serum, plasma Anticoagulants other than	Plain red-top, EDTA Hemolysis	NA Thawing	Warm reject; Cold reject Lipemia	NA Icteric	NA | Reporting limit determined each analysis   Synonym(s): INH   Usual therapeutic range in the treatment of tuberculosis:  1-7 mcg/mL. Toxic symptoms present at approximately  20 mcg/mL and greater.      Test Performed by: NMS Labs                                       3701 Welsh Road                                       PO Box 433A                                       Willow Grove, PA 19090-0437 | Wednesday | 1 day | 3 - 9 days | 1 | 82491 |  |  |  |  | NMS Labs
INHP | [NAME] | VARIES | Varies |  |  |  | Frozen | 30 days
INHP | Result | [NAME] | Isoniazid | Isoniazid | Alphanumeric |  |  |  |  | mcg/mL |  |  |  |  |  |  |  |  |  | 3697-0 | Isoniazid:MCnc:Pt:Ser/Plas:Qn:
INHP | Result | Z1471 | Reporting Limit | Reporting Limit | Alphanumeric |  |  |  |  | mcg/mL |  |  |  |  |  |  |  |  |  | In Process
Spreadsheet: 271775d1382040796-using-indirect-within-a-vlookup-indirect-vlookup
Sheet: 111

111 Inverurie | All Periods
 | Actual | Budget | Actual V Budget |  | Correct Cost | Expense | Branch | FY13 | Budget | Required | Adjustment
Contract Revenue - Forecast | 500 | 670 | 170 |  | Should be £25 | Contract Revenue - Forecast | 111 | 41.66666666666666 | 55.83333333333334 | 25 | -30.83333333333334
Spreadsheet: 0ac3a506-aaba-4423-be2f-2fd5f8caadf0
Sheet: Sheet1

[NAME]" Lathe Parts List by Model # | Unnamed: 1 | Unnamed: 2
DJN - [EMAIL] |  | 2009-11-17 00:00:00
Notes:
1. Sorted in Excel numerical order by part number on second tab, by description on third tab
2. Each 12" lathe is in its own column
3. The number in the box is the bubble number from the corresponding parts .jpg picture.
4. Each lathe part number has an Excel spreadsheet listing the parts and a .jpg picture with bubble numbers.
5. Late production lathes had more than one picture and Excel parts list. They are coded as:
BD - Bed & Motor mtg
CA - Cabinet assy also
CB - Cabinet assy
CG - Change Gear parts
CR - Carriage and Apron assy
CS - Countershaft assy
DR - Drive assy - underdrive
GU - Guards
HD - Head & Tailstock assy
QC - Quick Change Gear Box
SP - Spindle
TH - Thread Dial & Apron
* You can see all the different lathes that a given part is used on by following the row along - second tab.
* The sheet is sorted by description on the third tab of the spreadsheet. This groups all similar parts together.
Spreadsheet: 723951d1615971063-check-occurrences-of-a-column-the-past-x-entries-and-highlight-cell-if-it-exceeds-y-example
Sheet: Tabelle1

Date (TT.MM.JJJJ) | Occurrence
2021-02-10 00:00:00 | A
2021-02-11 00:00:00 | B
2021-02-12 00:00:00 | C
2021-02-13 00:00:00 | D
2021-02-14 00:00:00 | E
2021-01-06 00:00:00 | F
2021-01-09 00:00:00 | G
2021-01-10 00:00:00 | B
2021-01-16 00:00:00 | A
2021-01-17 00:00:00 | C
2021-01-23 00:00:00 | D
2021-01-24 00:00:00 | E
2021-01-30 00:00:00 | F
2021-01-31 00:00:00 | A
2021-02-13 00:00:00 | B
2021-02-14 00:00:00 | C
2021-02-15 00:00:00 | D
2021-02-16 00:00:00 | E
2021-02-17 00:00:00 | F
2021-02-18 00:00:00 | G
2021-02-19 00:00:00 | B
2021-02-20 00:00:00 | A
2021-02-21 00:00:00 | C
2021-02-22 00:00:00 | D
2021-02-20 00:00:00 | E
2021-02-21 00:00:00 | F
2021-02-22 00:00:00 | D
Spreadsheet: 772838d1647489758-having-trouble-calculating-irr-irr-of-loans-2
Sheet: terms

Loan 1 | 945000
annl rate | 0.0925
1st int-only pmt date | 2016-04-15 00:00:00
#int-only pmts | 6
int-only pmt
1st reg pmt date
last pmt date | 2023-03-15 00:00:00
#[NAME] pmts
reg pmt
last pmt
PMI rate | 0.00125
monthly PMI
Loan 2 | 2221000
annl rate | 0.0945
1st int-only pmt date | 2016-04-15 00:00:00
#int-only pmts | 6
int-only pmt
1st reg pmt date
last pmt date | 2023-03-15 00:00:00
#[NAME] pmts
balloon pmt | 948291
balloon defn 1 (final bal)
reg pmt
final bal
last pmt
balloon defn 2 (last pmt)
reg pmt
last pmt
PMI rate | 0.00125
monthly PMI
Spreadsheet: 886285d1736326332-summing-sales-data-for-individual-component-parts-summing-sales-data-for-individual-component-parts
Sheet: Sales (2)

 |  |  |  |  |  |  |  |  |  |  |  |  |  | SUM | Use BYROW | Combined
SKU | Sales | Total Sales |  | Component |  |  |  | [NAME] |  |  |  | Convert to 1 col |  | each SKU | to fill SUM | [NAME]
SK-0001 | 5 |  |  |  | 0 | 0 | 0 |  | 0 | 0 | 0
SK-0002 | 10 | 20 |  | SK-0002 | 0 | 0 | 0 | 10 | 0 | 0 | 0 | 0 | 0 |  | 20 | 20
SK-0003 | 15 | 25 |  | SK-0003 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 0 |  | 25 | 25
SK-0004 | 20 | 30 |  | SK-0004 | 0 | 0 | 0 | 20 | 0 | 0 | 0 | 0 | 0 |  | 30 | 30
BOM-0001 | 5 | 0 |  | SK-0001 | SK-0002 | SK-0003 | SK-0004 | 5 | 5 | 5 | 5 | SK-0002 | 10 |  | 0 | 0
BOM-0002 | 5 | 0 |  | SK-0001 | SK-0003 | 0 | 0 | 5 | 5 | 0 | 0 | 0 | 0 |  | 0 | 0
BOM-0003 | 5 | 0 |  | SK-0002 | SK-0004 | 0 | 0 | 5 | 5 | 0 | 0 | 0 | 0 |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | SK-0003 | 15
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | SK-0004 | 20
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | SK-0001 | 5
 |  |  |  |  |  |  |  |  |  |  |  | SK-0002 | 5
 |  |  |  |  |  |  |  |  |  |  |  | SK-0003 | 5
 |  |  |  |  |  |  |  |  |  |  |  | SK-0004 | 5
 |  |  |  |  |  |  |  |  |  |  |  | SK-0001 | 5
 |  |  |  |  |  |  |  |  |  |  |  | SK-0003 | 5
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | SK-0002 | 5
 |  |  |  |  |  |  |  |  |  |  |  | SK-0004 | 5
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
 |  |  |  |  |  |  |  |  |  |  |  | 0 | 0
Spreadsheet: 97180d1296412827-formula-array-to-return-results-in-a-certain-range-missing-numbers
Sheet: Sheet1

 | 1-6-7-8-9-30 |  |  | 1
 | 2-3-4-5-8-24 |  |  | 2
 | 16-20-21-22-25 |  |  | 3
 | 12-16-17-21-29 |  |  | 4
 | 1-2-17-29-30 |  |  | 5
 | 3-4-6-7-12 |  |  | 6
 | 1-8-19-20-21 |  |  | 7
 | 16-20-21-24-37 |  |  | 8
 |  |  |  | 9
 |  |  |  | 10
 |  |  |  | 11
 |  |  |  | 12
 |  |  |  | 13
 |  |  |  | 14
 |  |  |  | 15
 |  |  |  | 16
 |  |  |  | 17
 |  |  |  | 18
 |  |  |  | 19
 |  |  |  | 20
 |  |  |  | 21
 |  |  |  | 22
 |  |  |  | 23
 |  |  |  | 24
 |  |  |  | 25
 |  |  |  | 26
 |  |  |  | 27
 |  |  |  | 28
 |  |  |  | 29
 |  |  |  | 30
Spreadsheet: 768351d1644934356-planned-vs-actual-weeks-behind-or-ahead-calculation-planned-vs-actual-week-status-rev
Sheet: Sheet2

Date | Planned Week | Actual Week | Planned Cumulative | Actual Cumulative | Status (Weeks behind or ahead) | Column F should read:
2022-01-03 00:00:00 | 0 | 0 |  |  |  | 0
2022-01-10 00:00:00 | 14 | 7 |  |  |  | -0.5
2022-01-17 00:00:00 | 14 | 14 |  |  |  | -0.5
2022-01-24 00:00:00 | 14 | 7 |  |  |  | -1
2022-01-31 00:00:00 | 21 | 7 |  |  |  | -1.5
2022-02-07 00:00:00 | 21 | 21 |  |  |  | -1.33
2022-02-14 00:00:00 | 14 | 21 |  |  |  | -1.33
2022-02-21 00:00:00 | 14 | 21 |  |  |  | -1
2022-02-28 00:00:00 | 7 | 21 |  |  |  | 0
2022-03-07 00:00:00 | 7 | 21 |  |  |  | 1
2022-03-14 00:00:00 | 14 | 21 |  |  |  | 1.5
2022-03-21 00:00:00 | 14 | 7 |  |  |  | 1
2022-03-28 00:00:00 | 14 | 7 |  |  |  | 0.5
2022-04-04 00:00:00 | 14 | 7 |  |  |  | 0
2022-04-11 00:00:00 | 14 | 7 |  |  |  | -0.5
2022-04-18 00:00:00 | 21 | 7 |  |  |  | -1
2022-04-25 00:00:00 | 21 | 7 |  |  |  | -1.67
2022-05-02 00:00:00 | 7 | 7 |  |  |  | -2.33
2022-05-09 00:00:00 | 7 | 7 |  |  |  | -3
2022-05-16 00:00:00 | 14 | 7 |  |  |  | -3.67
2022-05-23 00:00:00 | 14 | 7 |  |  |  | -4.33
Spreadsheet: 747324d1631385532-help-with-creating-a-price-comparison-database-price-comparison-by-year
Sheet: Sheet1

 |  |  |  | Product | Price Now | 2021 |  | 2021 |  | 2019
 |  |  |  | Coke | 1.21 | 2021-09-11 00:00:00 | 1.21 | 2020-11-07 00:00:00 | 1.14 | 2019-08-09 00:00:00 | 1.05
 |  |  |  |  |  | 2021-05-05 00:00:00 | 1.2 | 2020-07-06 00:00:00 | 1.1 | 2019-04-03 00:00:00 | 1.01
 |  |  |  |  |  | 2021-09-03 00:00:00 | 1.15
Spreadsheet: 66888d1267563722-formula-for-referencing-dates-that-change-dates-example
Sheet: Sheet1

Week | Date | How easy was it to access this? |  |  |  | 4 or 5 ratings | Total Count
35 | 2010-02-20 00:00:00 | 1 | 2010-02-19 00:00:00 | 0.35 |  | 7 | 20
35 | 2010-02-20 00:00:00 | 2 | 2010-02-20 00:00:00 | 0.3636363636363636 |  | 4 | 11
35 | 2010-02-20 00:00:00 | 4 | 2010-02-21 00:00:00 | 0.5 |  | 2 | 4
35 | 2010-02-20 00:00:00 | 5 | 2010-02-22 00:00:00 | 0.06666666666666667 |  | 1 | 15
35 | 2010-02-20 00:00:00 | 1
35 | 2010-02-20 00:00:00 | 1
35 | 2010-02-20 00:00:00 | 2
35 | 2010-02-20 00:00:00 | 3
35 | 2010-02-20 00:00:00 | 4
35 | 2010-02-20 00:00:00 | 5
35 | 2010-02-20 00:00:00 | 1
35 | 2010-02-19 00:00:00 | 2
35 | 2010-02-19 00:00:00 | 3
35 | 2010-02-19 00:00:00 | 2
35 | 2010-02-19 00:00:00 | 3
35 | 2010-02-19 00:00:00 | 2
35 | 2010-02-19 00:00:00 | 1
35 | 2010-02-19 00:00:00 | 4
35 | 2010-02-19 00:00:00 | 1
35 | 2010-02-19 00:00:00 | 2
35 | 2010-02-19 00:00:00 | 5
35 | 2010-02-19 00:00:00 | 1
35 | 2010-02-19 00:00:00 | 3
35 | 2010-02-19 00:00:00 | 4
35 | 2010-02-19 00:00:00 | 5
35 | 2010-02-19 00:00:00 | 5
35 | 2010-02-19 00:00:00 | 4
35 | 2010-02-19 00:00:00 | 1
35 | 2010-02-19 00:00:00 | 4
35 | 2010-02-19 00:00:00 | 1
35 | 2010-02-19 00:00:00 | 2
35 | 2010-02-21 00:00:00 | 3
35 | 2010-02-21 00:00:00 | 5
35 | 2010-02-21 00:00:00 | 4
35 | 2010-02-21 00:00:00 | 1
35 | 2010-02-22 00:00:00 | 2
35 | 2010-02-22 00:00:00 | 1
35 | 2010-02-22 00:00:00 | 1
35 | 2010-02-22 00:00:00 | 1
35 | 2010-02-22 00:00:00 | 2
35 | 2010-02-22 00:00:00 | 3
35 | 2010-02-22 00:00:00 | 2
35 | 2010-02-22 00:00:00 | 3
35 | 2010-02-22 00:00:00 | 2
35 | 2010-02-22 00:00:00 | 5
35 | 2010-02-22 00:00:00 | 3
35 | 2010-02-22 00:00:00 | 1
35 | 2010-02-22 00:00:00 | 3
35 | 2010-02-22 00:00:00 | 1
35 | 2010-02-22 00:00:00 | 1
Spreadsheet: 04ccdaaf-8b06-41c3-a52b-189040dff6f6
Sheet: 5. Summary graphs

 | Summary Graphs
 | Cost of PMTCT and paediatric treatment
 | Cost per HIV infection averted
 | Cost per HIV infection averted
 | Total savings on PMTCT*
 | Total savings on PMTCT*
 | *(average cost of paediatric treatment) x (# of infection averted) - (total cost of PMTCT)
 | Cost per congenital syphilis averted
Spreadsheet: dana_davis__4507__1 Central Records Form
Sheet: ZOO63220

ENA |  |  |  |  |  |  |  | Page | of
 |  |  | RECORDS TRANSFER LIST |  |  |  |  | 1 | 1
[NAME] Number |  |  | R.C. Number |  | Company Number | Destination Date |  | Transfer Number
 | 408 |  | 0771 |  | 413
Company |  |  |  |  | Department |  |  | Section
ENRON CORP |  |  |  |  | Merchant Finance
Retention |  | [NAME] by Filing Arrangement and |  |  |  | [NAME] |  |  | Record
Schedule |  | Record Series Range, eg. 1-5, A-H, etc. |  |  |  |  |  | Container | Center Only
Item Number |  | (Title Same as Used in [NAME]) |  |  |  | From | To | Number | Location #
20403 |  | Cactus Reports |  |  |  |  |  | Z0063220
 |  | 1997
 |  | Cactus Distribution Schedules
 |  | Cactus Report
Prepared By |  |  |  | Date | Building/Room/City
[NAME] |  |  |  |  | ENRON CORP./EB 2448a/HOUSTON
Department Head |  |  |  | Date | Computer Input By |  |  |  | Date
Hope Vargas
Checked and Received by |  |  |  | Date | Verified by |  |  |  | Date
Spreadsheet: 813003d1673494720-how-to-count-the-highest-possible-occurrence-in-multiple-tables-julians96-how-to-countif-highest-possible-occurrence-in-an-array-of-data
Sheet: Sheet2

 | Probable | Critical |  |  |  | Catastrophic |  | Critical |  | Marginal |  | Negligible
Highest | Probable | Catastrophic |  |  | Frequent | A |  | A |  | A |  | B
 | Probable | Critical |  |  | Probable | A |  | A |  | B |  | C
 | Probable | Negligible |  |  | Occasional | A |  | B |  | C |  | D
 | Probable | Negligible |  |  | Remote | B |  | C |  | D |  | D
 | Probable | Critical |  |  | Improbable | C |  | D |  | D |  | D
Highest | Probable | Catastrophic |  |  | Incredible | D |  | D |  | D |  | D
 | Incredible | Critical
Highest | Incredible | Catastrophic |  |  |  | Catastrophic |  | Critical |  | Marginal |  | Negligible
Highest | Incredible | Critical |  |  | Frequent | A |  | A |  | A |  | B
 | Incredible | Negligible |  |  | Probable | A |  | A |  | B |  | C
Highest | Improbable | Critical |  |  | Occasional | A |  | B |  | C |  | D
Highest | Improbable | Critical |  |  | Remote | B |  | C |  | D |  | D
 | Improbable | Negligible |  |  | Improbable | C |  | D |  | D |  | D
 | Improbable | Negligible |  |  | Incredible | D |  | D |  | D |  | D
Highest | Improbable | Marginal
Highest | Improbable | Marginal |  |  | In the coloured tables, find the highest possible occurrence [NAME] being highest, Then Critical, then [NAME] then negligble.
 |  |  |  |  | Then count how may of the highest possible occurrence matching column B were found and input it into Risk classification table.
 |  |  |  |  | The Table in Purple is the desired result
 | Catastrophic | Frequent
 | Critical | Probable
 | Marginal | Occasional
 | Negligible | Remote
 |  | Improbable
 |  | Incredible