tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: benjamin_rogers__1185__United American Energy 02-09-00
Sheet: IDC

IDC CALCULATIONS
Total Construction & Other Hard Costs (000$):
No. of Construction Months:
Interest During Construction:
 |  | Annual | Daily (360-Day)
 |  |  | Turbine Cost | Construction &
IDC Calculations |  |  | including [NAME] | Other Cost | Principal | Balance | Interest | Cum. Interest
Month | Date | % Drawn | (000$) | (000$) | (000$) | (000$) | (000$) | (000$)
0 | 2000-08-01 00:00:00 | 0 |  |  |  |  | 0
 | 2000-09-01 00:00:00 |  | 0
 | 2000-10-01 00:00:00 |  | 0
 | 2000-11-01 00:00:00 |  | 0
 | 2000-12-01 00:00:00 |  | 0
 | 2001-01-01 00:00:00 |  | 0
 | 2001-02-01 00:00:00 |  | 0
 | 2001-03-01 00:00:00 |  | 0
 | 2001-04-01 00:00:00 |  | 0
 | 2001-05-01 00:00:00 | 0 | 0
 | 2001-06-01 00:00:00 | 0 | 0
 | 2001-07-01 00:00:00 | 0 | 0
 | 2001-08-01 00:00:00 | 0 | 0
 | 2001-09-01 00:00:00 | 0 | 0
 | 2001-10-01 00:00:00 | 0 | 0
 | 2001-11-01 00:00:00 | 0 | 0
 | 2001-12-01 00:00:00 | 0 | 0
 | 2002-01-01 00:00:00 | 0 | 0
 | 2002-02-01 00:00:00 | 0 | 0
 | 2002-03-01 00:00:00 | 0 | 0
TURBINE DELIVERY SCHEDULE
 | UNIT | TURBINES | DELIVERY | LD'S
 | NUMBER | DELIVERED | SCHEDULE | ENFORCED ON
 | 1-3 | 3 | 2000-07-30 00:00:00 | 2000-10-30 00:00:00
 | 4-6 | 3 | 2000-08-30 00:00:00 | 2000-10-30 00:00:00
 | 7-8 | 2 | 2000-09-30 00:00:00 | 2000-10-30 00:00:00
 | 9-11 | 3 | 2000-10-30 00:00:00 | 2000-10-30 00:00:00
 | 12-13 | 2 | 2000-11-30 00:00:00 | 2000-11-30 00:00:00
 | 14-15 | 2 | 2000-12-30 00:00:00 | 2000-12-30 00:00:00
 | 16-18 | 3 | 2000-01-30 00:00:00 | 2000-01-30 00:00:00
 | 19-20 | 2 | 2001-02-28 00:00:00 | 2001-02-28 00:00:00
 | 21-22 | 2 | 2001-03-30 00:00:00 | 2001-03-30 00:00:00
 | 23-24 | 2 | 2001-04-30 00:00:00 | 2001-04-30 00:00:00
 | SUMMARY (000$):
 | Basis Per Turbine |  |  | 13950
 | Carry Cost Per Turbine |  |  | 289.6162739983738
 | WestLB Structuring, Restructuring & Legal Fees |  |  | 20.83333333333331
 | TOTAL PRICE
Spreadsheet: 96746d1296054830-count-base-on-the-day-of-the-week-counting
Sheet: Sheet2

WEEK START | 2011-01-03 00:00:00
WEEK NUM
DAY | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 1 | 2 | 3 | 4 | 5 | 6 | 7
START
FINISH
Spreadsheet: d074aa12-ae49-4887-8e61-863950966396
Sheet: Sheet1

Case/Controls | Population | Number of individuals | Genotype platform | Expression platform
Controls | Dutch | 414 | Hap370 | Human HT-12
Amyotophic Lateral Sclerosis patients | Dutch | 324 | Hap370 | Human HT-12
Ulcerative Colitis patients | Dutch | 49 | 610-Quad | Human HT-12
Chronic Obstructive Pulmonary Disease patients | Dutch | 453 | 610-Quad | Human HT-12
Celiac disease patients | UK | 111 | Hap300 | HumanRef-8 v2
Amyotrophic Lateral Sclerosis patients | Dutch | 59 | Hap300 | HumanRef-8 v2
Controls | Dutch | 59 | Hap300 | HumanRef-8 v2
 |  | 1469
 | Total
Spreadsheet: 817764d1676432840-calculating-payment-due-dates-automatically-subscription-tracker-1-
Sheet: Interface

 | Service details |  |  | Billing period |  |  |  |  |  | Context
 | Subscription | Date commenced | Payment Next Due | QTY | Unit |  |  |  |  | 1 | The date as of me creating this is 14 Feb 23.
 | Spotify | 2019-12-18 00:00:00 |  | 4 | w |  |  |  |  | 2 | The cells that are highlighted orange are user input. (Column B, C, E, F)
 | ExpressVPN | 2022-04-19 00:00:00 |  | 3 | m |  |  |  |  | 3 | The cells that are white with orange text are automatic calculations. (Column D)
 | Hulu | 2021-07-21 00:00:00 |  | 1 | m |  |  |  |  | 4 | Column D (Payment Next Due) needs to update every time the previous due date has passed.
 | [NAME] | 2023-01-29 00:00:00 |  | 1 | w |  |  |  |  | 5 | Cell [NAME] is left blank to provide space for solution.
 | Amazon Prime | 2023-02-11 00:00:00 |  | 1 | d |  |  |  |  | 6 | Problem: How do I create the auto-calculations for column D? Thank you for your time.
 | MasterClass | 2023-02-12 00:00:00 |  | 2 | d
 | Tidal | 2023-02-13 00:00:00 |  | 3 | d
 | Apple Music | 2021-11-09 00:00:00 |  | 12 | m
 | HubSpot | 2022-08-16 00:00:00 |  | 1 | m
 | Zenefits | 2020-07-22 00:00:00 |  | 1 | m
 | Disney+ | 2023-01-06 00:00:00 |  | 1 | w
 | Audible | 2022-04-26 00:00:00 |  | 1 | d
 | GrandBox | 2021-11-11 00:00:00 |  | 3 | m
 | Kindle Direct | 2021-02-11 00:00:00 |  | 3 | m
 | Netflix | 2022-01-09 00:00:00 |  | 12 | m
 | [NAME]
Spreadsheet: 775174d1648873100-match-function-between-dates-and-unique-id-example-1
Sheet: Toll Report

Posted Date/Time | Plate | Transaction Amount |  | EXPECTED RESULT
2022-03-23 18:06:55 | TX - 123456 | -1.13 |  | 13912669
2022-03-24 06:06:55 | TX - 234567 | -2.45 |  | Blank - No Match (Toll is before reservation)
2022-03-24 12:17:00 | TX - 234567 | -3.12 |  | 13958617
2022-03-24 16:18:00 | TX - 123456 | -1.65 |  | 13912669
2022-03-25 19:24:40 | TX - 123456 | -4.22 |  | 13912669
2022-03-28 21:38:12 | TX - 234567 | -1.89 |  | Blank - No Match (Toll is after reservation)
2022-03-28 18:31:55 | TX - 123456 | -1.25 |  | 13912669
2022-03-31 18:31:55 | TX - 123456 | -1.6 |  | 14057025
Spreadsheet: 287dd6ad-35bd-4211-ad43-953ece417d92
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1
Table S2. miRNA sequences
miR-205 s | TCCTTCATTCCACCGGAGTCTG
miR-205 as | GACTCCGGTGGAATGAAGCTTT
miR-206 s | TGGAATGTAAGGAAGTGTGTGG
miR-206 as | ACACACTTCCTTACATTCGTTT
miR-375 s | TTTGTTCGTTCGGCTCGCGTTA
miR-375 as | ACGCGAGCCGAACGAACATTTT
miR-30c s | TGTAAACATCCTACACTCTCAG
miR-30c as | GAGAGTGTAGGATGTTTAGTTT
pre-miR-205 | TCCTTCATTCCACCGGAGTCTGTGTAGTTGTTCAATCAGATTTCAGTGGTGTGAAGTGTA
Spreadsheet: 217053d1361976964-subtotal-max-min-with-if-urgent-help-required-apple-orange-banana-filter-example
Sheet: Sheet1

AutoFilter Field | Criteria Field | Value Field |  |  |  |  | Sum of Value Field | Column Labels
Orange | X | 2 |  |  |  |  | Row Labels | X | Y | Z | Grand Total
Apple | X | 10 |  |  |  |  | Apple | 10 |  | 31 | 41
[NAME] | Y | 12 |  |  |  |  | [NAME] | 16 | 12 | 14 | 42
Orange | X | 24 |  |  |  |  | Orange | 26 | 20 |  | 46
Apple | Z | 13 |  |  |  |  | Grand Total | 52 | 32 | 45 | 129
[NAME] | Z | 14
[NAME] | X | 16
Apple | Z | 18 |  |  |  |  | Max of Value Field | Column Labels
Orange | Y | 20 |  |  |  |  | Row Labels | X | Y | Z | Grand Total
 |  |  |  |  |  |  | Apple | 10 |  | 18 | 18
 |  |  |  |  |  |  | [NAME] | 16 | 12 | 14 | 16
 | Count | Total | Min | [NAME] |  |  | Orange | 24 | 20 |  | 24
X |  |  |  |  |  |  | Grand Total | 24 | 20 | 18 | 24
Y
 | Count of Value Field | Column Labels |  |  |  |  | Min of Value Field | Column Labels
 | Row Labels | X | Y | Z | Grand Total |  | Row Labels | X | Y | Z | Grand Total
 | Apple | 1 |  | 2 | 3 |  | Apple | 10 |  | 13 | 10
 | [NAME] | 1 | 1 | 1 | 3 |  | [NAME] | 16 | 12 | 14 | 12
 | Orange | 2 | 1 |  | 3 |  | Orange | 2 | 20 |  | 2
 | Grand Total | 4 | 2 | 3 | 9 |  | Grand Total | 2 | 12 | 13 | 2
Spreadsheet: 865958d1712903568-systematic-allocation-of-expense-sample
Sheet: Sheet1

 |  |  |  |  |  |  | Q1. How I Know this A1 which pay is cover the Project 1, project 2 & project3
 |  |  |  |  |  |  | Solution required by formula
 | Name | Project1 | Project2 | Project3 | Total Salary |  | Project1 | Project2 | Project3
 | A1 | 13000 | 9008.718232988998 | 9008.718232988998 |  |  | pay 1 &2 | Pay 3&4 | Pay 5&6
 | B1 | 0 | 0 | 0
 | A2 | 5000 | 7000 | 8000
 | A3 | 0 | 0 | 0
 | A4 | 3000 | 4000 | 5000
 | B2 | 2020.126928551948 | 12000 | 11003
 | B3 | 0 | 7865 | 6534
 | Name | Pay 1 | Pay 2 | Pay 3 | Pay 4 | Pay 5 | Pay 6 | Pay 7 | Total
 | A1 | 6000 | 7000 | 8000 | 4000 | 8000 | 8000 | 6000
 | B1 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | A2 | 5000 | 6000 | 6000 | 4000 | 6000 | 6000 | 3000
 | A3 | 0 | 0 | 0 | 0 | 0 | 0 | 0
 | A4 | 3000 | 4000 | 4074.44 | 4000 | 3000 | 3000 | 3000
 | B2 | 4000 | 4000 | 4000 | 4000 | 3000 | 3000 | 3000
 | B3 | 2000 | 2000 | 2000 | 4000 | 2000 | 2000 | 2000
Spreadsheet: hunter_shively__12525__Index Posting Example
Sheet: DayAhead Index

EOL Daily Index
Gas Day June 14, 2000 | 4.31
Physical | Daily Index | Daily Basis
Southeast
[NAME] | 4.31
Columbia Gulf Onshore | 4.29
FGT Zone 2 | 4.315
Tenn 500 | 4.24
[NAME] | 4.25
[NAME] | 4.16
TETCO ELA | 4.23
TETCO STX | 4.15
TETCO WLA | 4.19
TGT Zone SL | 4.3
TRANSCO St. 65 | 4.3275
Northeast
TETCO M3 | 4.645
CNG Transmission South Point Title Transfer Tracking | 4.49
Columbia, Appalach | 4.225
TRCO/Z6 Unr (NY) | 4.64
Midwest / Mid-continent
ANR Louisiana Gathered | 4.235
ANR Louisiana Transmission | 4.235
ANR SW Pool | 4.145
CHIC-PEOPLES | 4.39
Consumers Power Co | 4.38
Michcon | 4.385
NGPL- LA Pool | 4.245
NGPL Midcontinent | 4.145
NGPL NICOR | 4.3875
NGPL NIPSCO Citygate | 4.395
NGPL South Texas Pool | 4.22
NGPL TexOk GC Pool | 4.25
NNG-Demarc | 4.21
Trunkline ELA TAB 1 | 4.25
West
EPNG [NAME] | 4.24
EPNG SoCal Topock | 4.845
PG&E Ctygte Pool | 4.95
Texas
WAHA | 4.23
HPL Zone 15 - Katy | 4.265
HPL/HSC East Pool | 4.285
HPL/HSC Pool | 4.275
Canada
AECO
Dawn
Opal | 3.715
PEPL - Pool | 4.145
[NAME] | 4.18
Trunkline WLA TAB 1 | 4.29
HPL Zone 15 - Katy | 4.28
NBPL - Nicor (Minooka) | 4.2775
Oklahoma Natural Gas Transmission Co. | 4.13
Spreadsheet: acc39e1d-2806-4f65-bb20-c84d1af89679
Sheet: 11a

Product |  | Cleared** | Uncleared | TOTAL
Swap* | Basis | 544 |  | 544
 | FRA | 11940 |  | 11940
 | Exotic
 | Inflation
 | IRS- [NAME] | 31087 |  | 31087
 | OIS | 1572 |  | 1572
 | VNS | 112 |  | 112
 | Zero Coupon | 288 |  | 288
With Optionality | Callable Swap
 | Cap/Floor
 | Debt Option
 | Exotic Option
 | Swaption
Cross-Currency | Exotic
 | Swap
TOTAL |  | 45543 | N/A*** | 45543
Estimated swap transaction volumes, week ending July 26, by product type and tenor (number of trades), all participant types and currencies.
Total(s) may be less than total shown for this asset class in the All Swaps reports and/or other CFTC Swaps Report tables if products were excluded from this table that (a) presented disclosure risk or (b) did not belong in the categories shown.
*See Data Dictionary for product descriptions.
**See Explanatory Notes for cleared and uncleared descriptions.
***N/A indicates that data are not currently available.
Note: Transaction volumes currently include house and client trades by FCMs in the interest rate asset class.
The Commission requests feedback on the format and content of this CFTC Swaps Report table. Submit comments to [EMAIL].
Spreadsheet: 180094d1347474888-convert-2-column-spreadsheet-to-multi-columns-based-on-1-column-book8
Sheet: Sheet2

ADD | [NAME] |  |  | ADD |  | ADD | [NAME] | CAD
ADD | [NAME] |  |  | [NAME] | [NAME]
ADD | [NAME] |  |  | CAD | [NAME]
ADD | [NAME] |  |  |  | [NAME]
ADD | [NAME] |  |  |  | [NAME]
[NAME] | [NAME] |  |  |  | [NAME]
[NAME] | [NAME]
[NAME] | [NAME]
[NAME] | [NAME]
CAD | [NAME]
CAD | [NAME]
CAD | [NAME]
CAD | [NAME]
Step 3: In G2, dragged across and down, =IF(COUNTIFS($A$1:$A$13,G$1,$B$1:$B$13,$F2)>0,$F2,"")
Step 4: Copy, Paste Special Values over new table to remove formulas
Spreadsheet: 50803d1250278918-spreadsheet-w-logic-for-it-app-deployments-teamsfunc
Sheet: Sheet1

UserID's in scope for Deployment | Functional Team #1 | Functional Team #2 | Functional Team #3 | Functional Team #4 | Functional Team #5 | Functional Team #6 | Functional Team #7 | Functional Team #8 | Functional Team #9 | Functional Team #10 | Functional Team #11 | UserID that can be deployed | UserID that can't be deployed | If Cannot be deployed, then what Functional Team(s) are they a member of?
bobc |  |  |  |  |  |  |  |  |  |  |  | bobc
amya |  | amya |  |  |  |  |  |  |  |  | [NAME] |  | amya | 2,1
[NAME]
davidr
 |  |  |  |  | amya
[NAME]
 |  |  |  | davidr
 |  |  |  |  |  |  | bobc
 |  |  |  | bobc
 |  |  |  |  |  |  |  | amya
 |  |  |  |  |  |  |  |  |  |  | bobc
Spreadsheet: 85045d1285111484-increase-speed-for-match-formula-on-over-130k-rows-book1
Sheet: Roster

A | B | Match1 | Match2 |  |  |  |  | FFB
1 | FFY | 1 | 1 | #N/A |  | Start | 14
2 | FFY | 1 | 1 |  |  | Length | 11
3 | FFY | 1 | 1
4 | FFY | 1 | 1
5 | FFY | 1 | 1
6 | FFY | 1 | 1
7 | FFY | 1 | 1
8 | FFY | 1 | 1
9 | FFY | 1 | 0
10 | FFY | 1 | 1
11 | FFY | 1 | 1
12 | FFY | 1 | 1
13 | FFB | 1 | 1
14 | FFB | 1 | 1
15 | FFB | 1 | 1
16 | FFB | 1 | 1
17 | FFB | 1 | 1
18 | FFB | 1 | 1
19 | FFB | 1 | 1
20 | FFB | 1 | 1
21 | FFB | 1 | 1
22 | FFB | 1 | 1
23 | FFB | 1 | 1
24 | FFC | 1 | 1
25 | FFC | 1 | 1
26 | FFC | 1 | 1
27 | FFC | 1 | 1
28 | FFC | 1 | 1
29 | FFC | 1 | 1
Spreadsheet: 134356d1325247736-lookup-lookup-help
Sheet: Sheet1

Customer | 2009-01-01 00:00:00 | 2009-02-01 00:00:00 | 2009-03-01 00:00:00 | 2009-04-01 00:00:00 | 2009-05-01 00:00:00 | 2009-06-01 00:00:00 | 2009-07-01 00:00:00 | 2009-08-01 00:00:00 | 2009-09-01 00:00:00 | 2009-10-01 00:00:00 | 2009-11-01 00:00:00 | 2009-12-01 00:00:00 | 2010-01-01 00:00:00 | 2010-02-01 00:00:00 | 2010-03-01 00:00:00 | 2010-04-01 00:00:00
abc | 0.3129152450873604 | 0.2848153094622417 | 0.3322988283677505 | 0.2966350190999603 | 0.284576376152568 | 0.2180288862940509 | 0.2483312564837607 | 0.1494107037487408 | 0.1853569780337651 | 0.2935081013640936 | 0.3068192731607283 | 0.3889599531246479 | 0.3422624094188409 | 0.4104008893211978 | 0.4420447059754613 | 0.3589187703123313
def | 0.6870847549126397 | 0.7151846905377582 | 0.6677011716322494 | 0.7033649809000398 | 0.715423623847432 | 0.7819711137059492 | 0.7516687435162394 | 0.8505892962512591 | 0.814643021966235 | 0.7064918986359064 | 0.6931807268392716 | 0.6110400468753522 | 0.6577375905811591 | 0.5895991106788021 | 0.5579552940245387 | 0.6410812296876688
gfi | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1
jkl | 0.5070405326980054 | 0.584548334194505 | 0.7355940103711471 | 0.6349978807240075 | 0.8219299313030299 | 0.6944554549634538 | 0.5385061285525863 | 0.4591702865805662 | 0.5681100321086728 | 0.5957340767679284 | 0.4770343179912346 | 0.3853016189235636 | 0.2619413147372347 | 0.08160136496828674 | 0.1204892266476397 | 0.2450042110098767
mno | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15 | 0.15
pqr | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02
Month required | 2009-12-01 00:00:00 | formula should bring back % Share for month entered in B12
Customer | % Share
def | 0.6110400468753522 | [NAME] to bring back % share for Customer for month in cell B12
gfi | 1 | [NAME] to bring back % share for Customer for month in cell B12
Spreadsheet: 112150d1308295282-capture-data-on-another-sheet-dummyexcelsheet
Sheet: Sheet1

Data 1 | Fetched Data 1 | Fetched Data 2 | Data 2
111 | ? | ? | ABC
222 | ? | ? | DEF
333 | ? | ? | GHI
444 | ? | ? | JKL
555 | ? | ? | MNO
666 | ? | ? | PQR
777 | ? | ? | STU
888 | ? | ? | VWX
999 | ? | ? | YZA
Spreadsheet: 822424d1679338840-cone-are-book2_zimmy
Sheet: Sheet1

Area of the Cone: | volume = (1/3) × π × r² × h
 | pi() *r *(r+sqrt(h*h+r*r)
[NAME] of the Cone | Diameter
15 | 10
Height of the cone (h) = | r / TAN(a)
a = |  | degree
r = |  | inches
h = r / TAN(a) |  | inches
volume = (1/3) × π × r² × h   => |  | [NAME]
Area=pi() *r *(r+sqrt(h*h+r*r) |  | Square Inches
1) A cone when viewed from its side is similar to an isosceles triangle |  |  |  |  |  | Figure-1
2) The diameter of a cone's base is equivalent to the width of an isosceles triangle's base side. When an isosceles triangle is divided into two equal parts (vertically, as shown in the Figure 2), it forms two right triangles. The base side of each right triangle will be the counterpart of a radius (diameter/2) in a cone (being circle as its base). |  |  |  |  |  | Figure-2
3) In Trigonometry, the length of the opposite side of an angle in a right triangle (being represented now by the circle or cone base's radius), is calculated as the height multiplied by the tangent value of the angle.
Spreadsheet: mary_fischer__25403__wr594_data
Sheet: Fault Counts

Count of [NAME]
Site | ID | F051 | F052 | F071 | F072 | F077 | F083 | F084 | F089 | F098 | F123 | F195 | F206
Fenner | 840007001 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0
Fenner | 840007002 | 0 | 16 | 0 | 0 | 0 | 0 | 0 | 21 | 0 | 0 | 0 | 0
Fenner | 840007003 | 4 | 1 | 0 | 0 | 42 | 0 | 3 | 22 | 0 | 0 | 0 | 42
Fenner | 840007004 | 1 | 5 | 0 | 0 | 0 | 0 | 5 | 1 | 0 | 0 | 0 | 0
Fenner | 840007005 | 19 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0
Fenner | 840007006 | 33 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Fenner | 840007007 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 0
Fenner | 840007008 | 29 | 0 | 0 | 0 | 0 | 0 | 4 | 18 | 0 | 0 | 0 | 0
Fenner | 840007009 | 0 | 2 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 0 | 0
Fenner | 840007010 | 28 | 5 | 0 | 0 | 1 | 0 | 10 | 23 | 0 | 0 | 0 | 1
Fenner | 840007011 | 0 | 5 | 16 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0
Fenner | 840007012 | 0 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0
Fenner | 840007013 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0
Fenner | 840007014 | 0 | 2 | 1 | 1 | 0 | 0 | 2 | 15 | 0 | 1 | 1 | 0
Fenner | 840007015 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 0 | 0 | 0
Fenner | 840007016 | 0 | 5 | 3 | 3 | 0 | 0 | 1 | 6 | 0 | 3 | 3 | 0
Fenner | 840007017 | 3 | 5 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0
Fenner | 840007018 | 2 | 0 | 0 | 0 | 0 | 0 | 5 | 19 | 0 | 0 | 0 | 0
Fenner | 840007019 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1
Fenner | 840007020 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0
Spreadsheet: 172790d1344338374-dynamic-charting-excel-example
Sheet: Sheet1

 | 34232 | 234234 | 77767 | 9087 | 76443 | 8888 | 1111 | 6666 | 6666 | 5555 | 6666 | 45452
 |  |  |  |  |  |  |  |  | Untill what period:
 |  |  |  |  |  |  |  |  |  | P9/10
 |  |  |  |  |  |  |  | How many periods backwards:
 |  |  |  |  |  |  |  |  |  | 7
 | If Im interested in P2/10 - P9/10 meaning untill P9/10 and 7 periods backwards, I want the graph to look like this:
Spreadsheet: 174a123a-b730-4784-8753-600da4111155
Sheet: Rebecca Ellis

[NAME]
Fair Share Fee: Those Who Don't Pay Their Fair Share
Agree
Explain your fair share position, if you choose.
No response
Teachers' Retirement: Support in the State Budget
Agree
Explain your teachers' retirement position, if you choose.
No response
Health Care: Continuing System Reform
Agree
Explain your health care reform position, if you choose
The health plans in the exchange will provide a benchmark for health care coverage. Like all employees, teachers will be able
to bargain for additional benefits or compensation if they are not satisifed with the benchmarks.
Teaching Career: Retaining New Teachers
Agree
Explain your teaching career position, if you choose
No response
Teaching Profession: Simplifying Professional Relicensing
Agree
Explain your relicensing position, if you choose
No response
Name | email address | Address | Office sought | Are you an incumbent? |  | County
[NAME] | [EMAIL] | 1531 Ripley Road, Waterbury Ctr. VT 05677 | State Representative | Yes |  | Washington
Spreadsheet: b76de4c9-abfe-4f44-8b09-ed72e8576487
Sheet: Sheet1

Nombre
[NAME], [NAME], por la que se convocan las audiciones [NAME] producción del [NAME]
[NAME], temporada 2014-2015
[NAME] y [NAME]. Noviembre 2014
[NAME] para Espectáculos de Danza
Procedimiento de evaluación y [NAME] competencias profesionales: [NAME] en vivo
Hay un artista en mi cocina
Técnica, entrenamiento e interpretación vocal para profesionales del mundo de la Magia
Introducción a la [NAME]: Moodle
Promoción del tejido profesional [NAME], [NAME], la danza y los espectáculos dirigidos [NAME] infantil y juvenil en Andalucía, apoyo a la producción [NAME]
Enrédate 2015, [NAME] (teatros municipales)
Taller de programación de consolas de iluminación
Convocatoria del procedimiento de selección de ofertas de espacios [NAME]
Taller de sonorización y grabación de directos
Patronaje y confección a medida. [NAME], [NAME]
Taller de &quot;Microteatro&quot;
Curso &quot;Introducción al diseño [NAME];
Curso &quot;Técnica de Maquinaria Escénica y construcción de decorados&quot;
El Centro de Documentación de las Artes Escénicas de Andalucía galardonado en la II edición de los Premios del Teatro Andaluz
Teatros Romanos de Andalucía 2014
[NAME]: ciclos de formación en Danza Contemporánea, Española y Neoclásica 2014/2015
Espacios escénicos andaluces: estudio estadístico
Spreadsheet: 76778d1277270308-excel-2007-filtering-multiple-columns-for-unique-data-advfiltersample-excel2007-
Sheet: Sheet1

Name | Address | City | State
Same Company name | 40 S Main Street | Same City Name | SAME STATE
Same Company Name | 40 S Main Street | Same City Name | SAME STATE
Same Company name | 40 S. Main Street | Same City Name | SAME STATE
Same Company Name | 40 So Main St. | Same City Name | SAME STATE
Same Company Name | 40 South Main St | Same City Name | SAME STATE
Same Company name | Different Address | Different City | Different State
Same Company Name | P.O. Box 445 | Same City Name | SAME STATE
Same Company Name | P.O. Box 445 | Same City Name | SAME STATE
Different Company Name | 40 S Main St | Different City | SAME STATE
Spreadsheet: 32330d1228425429-accounting-for-multiple-possible-values-in-a-if-and-statement-book1
Sheet: Sheet1

 | 1 | 2008-12-02 00:00:00 | 2008-12-04 16:06:53 | 2 | WITHIN
 | 1 | 2008-12-03 00:00:00 | 2008-12-04 16:06:53 | 1 | WITHIN
 | 1 | 2008-12-04 00:00:00 | 2008-12-04 16:06:53 | 0 | WITHIN
 | 2 | 2008-12-05 00:00:00 | 2008-12-04 16:06:53 | -1 | NEEDS UPDATE
 | 2 | 2008-12-06 00:00:00 | 2008-12-04 16:06:53 | -2 | NEEDS UPDATE
 | 3 | 2008-12-07 00:00:00 | 2008-12-04 16:06:53 | -3 | NEEDS UPDATE
 | 3 | 2008-12-08 00:00:00 | 2008-12-04 16:06:53 | -4 | NEEDS UPDATE
 | 4 | 2008-12-09 00:00:00 | 2008-12-04 16:06:53 | -5 | NEEDS UPDATE
 | 5 | 2008-12-10 00:00:00 | 2008-12-04 16:06:53 | -6 | NEEDS UPDATE
 | 5 | 2008-12-11 00:00:00 | 2008-12-04 16:06:53 | -7 | NEEDS UPDATE
Spreadsheet: 547674d1510674075-using-excel-to-match-data-copy-of-sample-excel-sheet-watkinsam-
Sheet: Topics

[NAME] | Chemistry of Life | Water, Acids, and Bases | Macromolecules | Energy and Enzymes | Structure of a Cell | Membranes and Transport | Cellular Respiration | Photosynthesis | Cell Signaling | Cell Division | Classical and Molecular Genetics | DNA as the Genetic Material | Central Dogma (Dna to RNA to protein) | [NAME] | Biotechnology | Bacteria and Archea | Evolution and the Tree of Life | Ecology | Biodiversity and Conservation | Scientific Method
Student 1
Student 2
Student 3
Student 4
Student 5
Student 6
Student 7
Student 8
Student 9
Student 10
Student 11
Student 12
Student 13
Student 14
Student 15
Student 16
Student 17
Student 18
Student 19
Student 20
Student 21
Student 22
Student 23
Student 24
Spreadsheet: 776161d1649535096-count-days-in-a-month-from-given-range-count-days-in-a-month-for-specific-stock-beamer
Sheet: Entry Sheet

 | Daily Sales Date | Monthly Figures for:- |  |  |  | Week Starting:- | Week Ending:- |  |  | Months
 | 2022-02-07 00:00:00 | February |  |  |  | 2022-02-07 00:00:00 |  |  |  | January | 1
Company | Daily Sales % |  |  |  |  | Highest Weekly Sales | Lowest Weekly Sales |  |  | February | 2
DIVISLAB |  |  |  |  |  |  |  |  |  | March | 3
HINDALCO |  |  |  |  |  |  |  |  |  | April | 4
TATASTEEL |  |  |  |  |  |  |  |  |  | May | 5
DRREDDY |  |  |  |  |  |  |  |  |  | June | 6
 |  |  |  |  |  |  |  |  |  | July | 7
 |  |  |  |  |  |  |  |  |  | August | 8
 |  |  |  |  |  |  |  |  |  | September | 9
Data Source = | All companies day by day sale is in other sheet, "Source data Sheet"in this workbook only |  |  |  |  |  |  |  |  | October | 10
 |  |  |  |  |  |  |  |  |  | November | 11
I need help for these querries | B Coloumn = I want Sale of each company for Specific date mentioned in B2, So that I can just input the date and sale for that day will come instantly |  |  |  |  |  |  |  |  | December | 12
 | D Coloumn = I want highest sale of each company in specific month mentioned in D2
 | E Coloumn = I want lowest sale of each company in specific month mentioned in D2
 | G Coloumn = I want [NAME] sale for each company in specific Week and week range is mentioned in G2:H2
 | H Coloumn = I want lowest sale for each company in specific Week and week range is mentioned in G2:H2
 | All companies day by day sale is in other sheet names "Source data Sheet"in this workbook only
I Don’t want to convert this data in Table format, So It will be request for help with Specific Cell Numbers in formula.