tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 72748d1273487947-finding-a-column-name-iut-1vjezba-nova-web
Sheet: Sheet1

 |  | [NAME] | Istra | Kvarner | Sjeverna i  Srednja  Dalmacija | [NAME] | Unutra- šnjost | Zagreb
 |  | Croatia | Istria | Kvarner | Northern and Central Dalmatia | Southern  Dalmatia | Continent | Zagreb
 |  | 2007 | 2007 | 2007 | 2007 | 2007 | 2007 | 2007
Turoperator |  | 0.387 | 0.45 | 0.336 | 0.487 | 0.359 | 0.076 | 0.177 | Touroperator
[NAME] |  | 0.286 | 0.227 | 0.347 | 0.304 | 0.317 | 0.38 | 0.196 | Travel agent
[NAME] upit |  | 0.138 | 0.133 | 0.164 | 0.086 | 0.063 | 0.265 | 0.303 | Direct inquiry (by guest)
Vlastiti rezervacijski sustav |  | 0.075 | 0.096 | 0.086 | 0.061 | 0.076 | 0.048 | 0.038 | Own reservation system
Vlastita web stranica |  | 0.065 | 0.065 | 0.056 | 0.044 | 0.084 | 0.127 | 0.078 | Own web site
Globalni rezervacijski sustav |  | 0.014 | 0.001 | 0.001 | 0.001 | 0.053 | 0.004 | 0.088 | GDS
Ostale internet stranice |  | 0.014 | 0.013 | 0.003 | 0.003 | 0.028 | 0.03 | 0.045 | Other internet site
[NAME] |  | 0.011 | 0.001 | 0.006 | 0.002 | 0.002 | 0.054 | 0.075 | Hotel representative
Nezavisni rezervacijski sustav |  | 0.007 | 0.013 | 0.001 | 0 | 0.018 | 0.01 | 0 | Independent reseravation system
[NAME] poduzeće |  | 0.003 | 0 | 0 | 0.001 | 0 | 0.006 | 0 | Transportation company
Ukupno |  | 1 | 1 | 1 | 1 | 1 | 1 | 1 | Total
Spreadsheet: 856775d1705949987-multiple-criteria-data-validation-multiple-data-validation-etaf2
Sheet: Sheet1

 |  |  | Firm | Firm A | Firm B | Firm C | Firm D | Firm A | Firm B | Firm C | Firm A | Firm B | Firm A
 |  |  | Fund | Fund 1 | Fund 1 | Fund 1 | Fund 1 | Fund 2 | Fund 2 | Fund 2 | Fund 3 | Fund 3 | Fund 4
 |  |  | ID | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10
Choose Firm | Firm D
Choose Fund | Fund 1
ID | 8
 | I have 3 rows of information and I want to be able to select a firm in B4 and a fund in B5 that then outputs an ID in B6.
Spreadsheet: 61749d1262683306-work-out-a-sum-in-excel-book1
Sheet: Sheet1

 |  |  |  |  | PROD
 | Total Incidents Resolved | In Incidents in SLA | Total Requests Resolved | In requests in SLA | Total Resolved | Total In SLA | Total Out of SLA | Target | Daily SLA | Out of SLA Incidents | Out of SLA Requests | Open Tickets Out of SLA | MTD Resolved | MTD in SLA | MTD Incident SLA | MTD Request SLA | MTD Total SLA
2010-01-01 00:00:00 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0.95 | 0 | 22 | 64 | 86 | 1 | 0 | 0 | 0.01162790697674419 | 0
2010-01-02 00:00:00 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.95 | 1 | 22 | 64 | 86 | 1 | 0 | 0 | 0 | 0
2010-01-03 00:00:00 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0.95 | 0 | 22 | 64 | 86 | 2 | 0 | 0 | 0 | 0
2010-01-04 00:00:00 | 36 | 34 | 53 | 39 | 89 | 73 | 16 | 0.95 | 0.8202247191011236 | 22 | 50 | 72 | 91 | 73 | 34 | 0.7090909090909091 | 0.8021978021978022
2010-01-05 00:00:00 |  |  |  |  | 0 | 0 | 0 | 0.95 | #N/A |  |  | 0 | 91 | 73 | 34 |  | #N/A
2010-01-06 00:00:00 |  |  |  |  | 0 | 0 | 0 | 0.95 | #N/A |  |  | 0 | 91 | 73 | 0 |  | #N/A
2010-01-07 00:00:00 |  |  |  |  | 0 | 0 | 0 | 0.95 | #N/A |  |  | 0 | 91 | 73 | 0 |  | #N/A
Spreadsheet: 812050d1672929385-search-in-a-range-of-cells-to-see-if-date-is-in-the-same-week-number-annual-leave-log-april-2022-march-2023-1-
Sheet: employee1

Year total | 111.7 | hours | Based on 22.5 hours per week (15/08/2022 - 01/12/2022) and 30 hours (01/12/2022 - 31/03/2022)
Annual Leave |  |  | FT Annual Leave allowance = 33 days
Dates Booked | Hours Used | Running Hotel
2023-01-05 00:00:00 | 3
2023-03-03 00:00:00 | 4
2023-01-20 00:00:00 | 4
2023-03-05 00:00:00 | 6
2023-03-06 00:00:00 | 6
2023-03-07 00:00:00 | 6
2023-03-08 00:00:00 | 4
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
00:00:00
TOTAL LEFT
Spreadsheet: 739047d1625481060-calculate-monthly-revenue-target-calculate-monthly-revenue-target
Sheet: josephteh (2)

Revenue | Increase | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Jan | Feb | Mar | Apr | May | Total
2000000 |  |  |  |  |  |  |  |  |  |  |  |  |  | 4300000
 | Workings
 | P = Initial amount |  |  |  | 2000000
 | Increment required |  |  |  | 4300000
 | A = Final amount = Initial amount + Increment
 | t = Time in period |  |  |  | 12
 | r = Interest rate = (A/P)1/t-1
Spreadsheet: 3fdfe860-45f0-47e6-a0f8-0c641dcf4625
Sheet: HIST

Old course number | New course number
HIST-301 | [NAME]
HIST-310 | HIST-3100
HIST-311 | HIST-3110
HIST-312 | HIST-3120
HIST-470 | HIST-4700
HIST-500 | HIST-5100 and HIST-4100
HIST-500 | HIST-5100 and HIST-6100
HIST-501 | HIST-4110
HIST-505 | HIST-4115
HIST-515 | HIST-4150
HIST-516 | HIST-5160 and HIST-4160
HIST-520 | HIST-4200
HIST-525 | HIST-5250
HIST-530 | HIST-4300
HIST-533 | HIST-4330
HIST-534 | HIST-4340
HIST-540 | HIST-4400
HIST-540 | [NAME]
HIST-541 | HIST-4410
HIST-541 | [NAME]
HIST-542 | HIST-4420
HIST-544 | HIST-4440
HIST-544 | [NAME]
HIST-545 | HIST-4450
HIST-545 | HIST-6450
HIST-547 | HIST-4470
HIST-548 | HIST-4480
HIST-550 | HIST-4500
HIST-550 | HIST-6500
HIST-565 | HIST-4650
HIST-567 | [NAME]
HIST-570 | HIST-5701 and HIST-4675
HIST-720 | HIST-7200
HIST-780 | HIST-7800
HIST-830 | HIST-8300
HIST-840 | HIST-8400
HIST-870 | HIST-8700
HIST-312 | HIST-3120
Spreadsheet: 479954d1473688511-round-robin-team-generation-vb-tourney-fall-2016
Sheet: VB Tourney

 | Playoffs: Top 9 Seeds Get In |  |  |  |  |  |  | POINTS: [NAME] = 2 Pts | Game Wins=1 Pt          Tiebreaker Pts = Total Game Points Scored
 | #1 Seed = [NAME],  #2 & 3 Seed = 1st Round Bye |  |  |  |  |  |  | ROUND 1 |  |  |  | ROUND 2
 | [NAME]: (1,4,5  vs  7,8,9) |  |  |  |  |  |  | Match 1 |  |  |  | Match 1
 | Championship Game: (2,3,6  vs Winner) |  |  |  |  |  |  | Crispy Christ TP1 | vs | Woody Stew CW |  | [NAME] | vs | Christ [NAME]
 | Rank | Player | Points | GP | Tiebreaker | Bye Week |  | Scores: 21-18, 21-10, 6-21 |  | Winner: 2 games to 1
 | 1 | G. | 5 | 1 | 63 | 5 |  | Match 2 |  |  |  | Match 2
 | 1 | Hansie | 5 | 1 | 63 | 3 |  | [NAME] | vs | [NAME] Mr. [NAME] |  | [NAME] | vs | CW Mo RG
 | 1 | [NAME] | 5 | 1 | 63 | 6 |  | Winner: 3 games to 0 |  | Scores: 21-10, 21-13, 21-9
 | 4 | [NAME] | 4 | 1 | 48 | 4 |  | ROUND 3 |  |  |  | ROUND 4
 | 4 | Stew | 4 | 1 | 48 | 7/Oct 10th |  | Match 1 |  |  |  | Match 1
 | 4 | Woody | 4 | 1 | 48 | 4 |  | [NAME] | vs | Sweet RG Mr. [NAME] |  | Christ Mr. [NAME] | vs | [NAME]
 | 7 | Christ | 1 | 1 | 49 | 5
 | 7 | [NAME] | 1 | 1 | 49 | 3 |  | Match 2 |  |  |  | Match 2
 | 7 | [NAME] (TP1) | 1 | 1 | 49 | 7/Oct 10th |  | [NAME] | vs | G. Christ CW |  | TP1 [NAME] | vs | [NAME]
 | 10 | Mo | 0 | 1 | 32 | 6
 | 10 | Mr. [NAME] | 0 | 1 | 32 | 2 |  | ROUND 5 |  |  |  | ROUND 6
 | 10 | [NAME] (TP3) | 0 | 1 | 32 | 2 |  | Match 1 |  |  |  | Match 1
 | 13 | [NAME] | 0 | 0 | 0 | 1 |  | Woody RG TP1 | vs | [NAME] |  | CW Sweet TP1 | vs | G. Mr. [NAME]
 | 14 | Sweets | 0 | 0 | 0 | 1
 | *Clinched tournament spot. |  |  |  |  |  |  | Match 2 |  |  |  | Match 2
 |  |  |  |  |  |  |  | [NAME] Mr. [NAME] | vs | [NAME] |  | Woody [NAME] | vs | Christ [NAME]
 |  |  |  |  |  |  |  | ROUND 7
 |  |  |  |  |  |  |  | Match 1
 |  |  |  |  |  |  |  | Christ [NAME] | vs | Geo Crispwood
 |  |  |  |  |  |  |  | Match 2
 |  |  |  |  |  |  |  | TP3 CW RG | vs | [NAME] Mr. [NAME]
 |  |  |  |  |  |  |  | Hall of Champions:
 |  |  |  |  |  |  |  | 2016 Spring:     Geo Crispwood
 |  |  |  |  |  |  |  | 2016 Fall:
Spreadsheet: 700352d1603148493-if-blank-blank-else-cumulative-total
Sheet: Sheet1

 |  |  |  |  |  |  |  |  | 4
Spreadsheet: 167873d1342127224-aligning-values-besides-each-other-aligning-values-compared-to-another-column
Sheet: REPORT-Jayanna, Sunil -Case Loa

Section | Last Name | First Name |  | Color | Last Name | First Name |  | Color | Last Name | First Name
Section 6 | [NAME] | [NAME] |  | Green | [NAME] | [NAME] |  | Green | [NAME] | [NAME]
Section 6 | [NAME] | Nicole |  | Gray | [NAME] | Nicole |  | Yellow | Jones | [NAME]
Section 6 | Call | Holly |  | Black | Call | Holly |  | Black | Call | Holly
Section 6 | Call | Ricky |  |  |  |  |  | Pink | [NAME] | Kurt
Section 14 | [NAME] | Kurt |  | Pink | [NAME] | Kurt |  | Pink | [NAME] | Mark
Section 7 | [NAME] | Ricky |  | Orange | [NAME] | Ricky |  | Yellow | Gram | May
Section 16 | Gram | May |  | Yellow | Gram | May |  | Gray | [NAME] | Nicole
Section 3 | Gram | Winston |  |  |  |  |  | Orange | [NAME] | Ricky
Section 3 | Hall | [NAME] |  |  |  |  |  | Silver | [NAME] | Winn
Section 3 | Jones | [NAME] |  | Yellow | Jones | [NAME]
Section 4 | [NAME] | Winn |  | Silver | [NAME] | Winn
Section 4 | [NAME] | Mark |  | Pink | [NAME] | Mark
Spreadsheet: 822814d1679549095-random-time-between-starting-and-ending-time-generate-overtime
Sheet: Sheet1

 |  |  | Starting time | addition | Ending time
 |  |  | 21:30:00 | 12:00:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
 |  |  | 09:30:00
Spreadsheet: 839638d1692122706-index-match-formula-sample2
Sheet: Sheet1

 | Account |  | Check
 | 502
 | 601 |  |  | 1
 | 101 |  |  | 0
 | 501 |  |  | 1
 | 601 |  |  | 1
 | 501 |  |  | 1
 | 602 |  |  | 1
 | 603 |  |  | 1
 | 604 |  |  | 1
 | 502 |  |  | 1
 | 503 |  |  | 1
 | 504 |  |  | 1
Spreadsheet: 119049d1314173648-excel-2007-need-unique-vailue-using-multiple-criterias-book2
Sheet: Sheet1

Col1 | [NAME] | col3
1 | x | ab
2 | x | bc
2 | y | bc
3 | z | ab
4 | w | ab
5 | y | bc
1 | x | ab
5 | y | bc
Spreadsheet: 785498d1656446726-multi-skilled-productivity-tracker-to-be-able-to-discriminate-multi-tasker-numbers-sample
Sheet: Guide

SCORECARD GUIDE
 | Skill | Points (from) | Score |  | Sub-Weight | Overall Weight
Process | IB/OB | 0 | 1 |  | 0.4 | 0.8
 |  | 6 | 2
 |  | 16 | 3
 |  | 26 | 4
 |  | 36 | 5
 | Backoffice | 0 | 1 |  | 0.3
 |  | 6 | 2
 |  | 16 | 3
 |  | 26 | 4
 |  | 36 | 5
 | Call Outs - Internal | 3 | 1 |  | 0.15
 |  | 1 | 2
 |  | 0 | 3
 | Escalations - Onshore | 3 | 1 |  | 0.15
 |  | 1 | 2
 |  | 0 | 3
 | Attendance | Points (from) | Score |  | Sub-Weight | Overall Weight
Dependability | Lost Hours | 0 | 5 |  | 0.4 | 0.2
 |  | 2.6 | 4
 |  | 3.6 | 3
 |  | 5.1 | 2
 |  | 6.5 | 1
 | Absenteeism Rate | 0 | 5 |  | 0.6
 |  | 2.1 | 4
 |  | 3.6 | 3
 |  | 5.1 | 2
 |  | 6.5 | 1
Spreadsheet: 792476d1660917650-ifs-match-with-wildcard-to-return-dynamic-array-match-with-wildcard-to-return-spill-dynamic-array
Sheet: Sheet1

Type | Long ID | Some Calc Result |  |  | Desired Result
sometexthere |  | 99000000 |  |  | UNKNOWN
sometexthere |  | 123456
sometexthere | 101555 |  |  |  | 3rd party
sometexthere | 102000000 |  |  |  | VIP
sometexthere | 10245687 |  |  |  | Partner |  | Desired Result to be
sometexthere | [PHONE] |  |  |  | Partner |  | Spill Dynamic Array
AT102-TY |  |  |  |  | Material
TY-392-AT9 |  |  |  |  | Material
BY03KALSD
[NAME] |  |  |  |  | Material
Spreadsheet: 96493d1295891434-formula-to-count-editions-of-999-and-return-a-no-copy-of-publishing
Sheet: Invoice Publishing

 |  |  |  |  |  |  | INVOICE
Art & Escape Gallery Ltd
23-25 Barnet Road
EN6 2QX
Company No. 06972834
www.artandescape.com
[NAME] |  |  |  |  |  | INVOICE DATE | 2011-01-24 17:47:01
The Only Place for Pictures |  |  |  |  |  | INVOICE NUMBER
216 Upper Street |  |  |  |  |  | CLIENT REF | CL0020
Islington |  |  |  |  |  | DELIVERED VIA
London |  |  |  |  |  | PREPAID or COLLECT | PREPAID
N1 1RL
#N/A
REF | ARTIST | TITLE | SIZE (inches) | FRAME | UNIT COST | QTY | TOTAL
#N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A | #N/A
 |  |  |  |  |  | SUBTOTAL
 |  |  |  |  |  | VAT
 |  |  |  |  |  | DELIVERY
 |  |  |  |  |  | TOTAL
Please direct enquiries to: |  |  |  | Make all cheques payable to:
[NAME] |  |  |  | [NAME]
+44 (0) 7791 075 458 |  |  |  | Art & Escape Gallery Ltd
email: [EMAIL] |  |  |  | 23-25 Barnet Road
 |  |  |  | EN6 2QX
Thankyou for your business.  Please consider Art & Escape Gallery for all your Original and Published Contemporary Art.
Spreadsheet: 112589d1308675848-help-with-multiple-sheets-new-hub-workstream-log2
Sheet: B

Southern Hub Workstream Log |  | B | April - June
Work Priority |  |  | 1 - High | 2 - Medium | 3 - Low
Type | Project Description | Priority | Request Origin | Request Date | Estimated Deadline | Status
QRP-Related Task | TEST | 1 | Operations | 2011-06-10 00:00:00 | 2011-06-15 00:00:00 | Initiated
Presentation | a test | 1 | Operations | 2011-05-09 00:00:00 | 2011-05-06 00:00:00 | Not Started
Spreadsheet: 2909cd2c-2cb1-48f5-9ee1-ed01d15b9a38
Sheet: Sheet1

Table 8--U.S. cotton textile imports, by origin | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8
 |  | 2011 |  |  | 2010
Region/country | Oct. | Nov. | Dec. |  | Dec.
 | 1,000 pounds 1/
North America | 159239.718 | 141764.309 | 121203.393 |  | 157712.914
Canada | 3149.63 | 3104.546 | 3009.693 |  | 3168.836
Costa Rica | 847.781 | 746.783 | 885.449 |  | 918.371
Dominican Republic | 5568.037 | 6348.825 | 4833.101 |  | 6734.554
El Salvador | 21110.765 | 18502.673 | 18936.383 |  | 26105.236
Guatemala | 9157.4 | 6648.92 | 6409.125 |  | 8242.128
Haiti | 13030.663 | 11371.676 | 9094.41 |  | 12350.8
Honduras | 33444.515 | 32010.628 | 26375.645 |  | 37675.766
Mexico | 50297.509 | 46709.975 | 39852.847 |  | 46458.739
Nicaragua | 22608.854 | 16312.787 | 11804.823 |  | 16041.217
South America | 4440.901 | 3848.585 | 3507.243 |  | 5759.91
Brazil | 161.065 | 221.8 | 239.236 |  | 844.462
Colombia | 1662.387 | 1249.552 | 985.239 |  | 2095.628
Peru | 2485.36 | 2294.759 | 2211.177 |  | 2655.775
Europe | 14375.969 | 11734.077 | 9543.557 |  | 14574.575
Germany | 963.741 | 853.202 | 803.966 |  | 814.756
Italy | 1594.034 | 1549.487 | 1720.247 |  | 5319.526
Portugal | 1480.936 | 1567.901 | 939.781 |  | 1439.953
Turkey | 6379.305 | 4856.009 | 3574.108 |  | 4104.056
Asia | 538239.174 | 484589.029 | 416211.817 |  | 511609.709
Bahrain | 1999.292 | 1163.327 | 982.086 |  | 1615.344
Bangladesh | 37436.723 | 35570.597 | 30452.766 |  | 47196.525
Cambodia | 23978.43 | 20342.499 | 15515.65 |  | 20151.02
China | 249416.51 | 214369.607 | 189308.269 |  | 222219.264
Hong Kong | 931.176 | 1141.848 | 790.405 |  | 1100.648
India | 59305.389 | 54478.555 | 44271.902 |  | 53038.109
Indonesia | 26327.253 | 27042.342 | 22590.621 |  | 24590.871
Israel | 785.345 | 574.804 | 915.06 |  | 1198.703
Japan | 1066.969 | 1283.601 | 1116.963 |  | 1068.144
Jordan | 4341.5 | 3292.449 | 3478.358 |  | 4252.066
Malaysia | 2792.214 | 2594.716 | 2420.413 |  | 2967.969
Pakistan | 57661.503 | 59638.593 | 49442.861 |  | 62269.139
Philippines | 4727.335 | 4301.634 | 3965.455 |  | 4931.405
South Korea | 6890.26 | 5361.746 | 5749.101 |  | 5163.099
Sri Lanka | 7322.977 | 6328.95 | 4625.868 |  | 6592.312
Taiwan | 2860.004 | 2417.804 | 2422.93 |  | 3061.41
Thailand | 6930.364 | 6827.579 | 5408.504 |  | 10599.5
Vietnam | 42295.671 | 36488.853 | 31197.196 |  | 37639.458
Oceania | 29.018 | 43.046 | 54.919 |  | 46.691
Africa | 16600.662 | 13728.842 | 13946.638 |  | 15816.088
Egypt | 8157.807 | 6462.078 | 7643.285 |  | 9268.763
Kenya | 2083.372 | 1978.745 | 1431.192 |  | 2283.718
[NAME] | 4058.991 | 3349.525 | 3082.301 |  | 2643.237
[NAME] | 810.417 | 939.161 | 750.6 |  | 556.727
World 2/ | 732926.788 | 655709.079 | 564469.303 |  | 705524.119
 |  |  |  |  |  |  |  | 95
1/ Raw-fiber equivalent.  2/ Totals may not add due to rounding.
Last update:  03/12/12.
Sources: USDA, Economic Research Service; and USDC,
U.S. Census Bureau.
Spreadsheet: 24670d1215369115-help-splitting-data-1-column-to-multiple-sample2
Sheet: Sheet1

What I have
[NAME] |  |  |  | 3681A Sacramento St.
Calegari & Associates |  |  |  | San Francisco CA 94118
http://www.calegarisfrealestate.com |  |  |  | [PHONE]
 |  |  |  | [EMAIL]
[NAME] |  |  |  | 1699 Van Ness Ave.
TRI Coldwell Banker |  |  |  | San Francisco CA 94109
http://www.californiamoves.com |  |  |  | [PHONE]
 |  |  |  | [EMAIL]
[NAME] |  |  |  | 117 Greenwich St.
Sotheby's International Realty |  |  |  | San Francisco CA 94111
http://www.sothebyshomes.com |  |  |  | [PHONE]
 |  |  |  | [EMAIL]
What I want
Name | Company | Website | Address | City State Zip | Phone | [NAME]
[NAME] | Calegari & Associates | http://www.calegarisfrealestate.com | 3681A Sacramento St. | San Francisco CA 94118 | [PHONE] | [EMAIL]
[NAME] | TRI Coldwell Banker | http://www.californiamoves.com | 1699 Van Ness Ave. | San Francisco CA 94109 | [PHONE] | [EMAIL]
[NAME] | Sotheby's International Realty | http://www.sothebyshomes.com | 117 Greenwich St. | San Francisco CA 94111 | [PHONE] | [EMAIL]
Spreadsheet: 105507af-b7b6-4ab9-a12e-8492b32af570
Sheet: Form C

[NAME] |  |  |  |  |  |  |  | FORM C
[NAME]
نموذج الابلاغ عن النقل الجوي
الحركة حسب [NAME] (TFS)
الخدمات المنتظمة (الايرادية) - العمليات الدولية
[NAME]: |  |  |  |  |  | الدولة:
المنظمة: |  |  |  |  |  | شركة الطيران:
الهاتف:
[NAME]: |  |  |  |  |  | السنة:
البريد الالكتروني:
المحطات |  |  |  | [NAME] |  | الحركة الايرادية
 |  |  |  |  | إجمالي
 |  |  |  | مقاعد | سعة | الركاب | الشحن | البريد
 |  |  |  | الركاب | الحمولة | (العدد) | (أطنان) | (أطنان)
من | To | نوع الطائرة | عدد الرحلات | (العدد) | (أطنان)
(أ) | (ب) | (ج) | (د) | (ﻫ) | (و) | (ز) | (ح) | (ط)
الملاحظات (بما في [NAME] أي حيود عن تعليمات الابلاغ) لا يمكن تفاديه :
[NAME] صفحات إضافية حسب الاقتضاء.
Spreadsheet: 845995d1697292985-index-match-combo-possibly-food-and-drink
Sheet: Sheet1

Airport F&B | LGW | LHR | MAN | BHX | GLA | BRU | CDG | HEL
Starbucks |  | y
Pret |  |  |  |  |  |  |  | y
Burger King | y |  |  |  |  |  | y
Coffee Central
Eat and Fly |  |  | y |  |  | y
Take Off |  |  |  | y
[NAME] |  |  |  |  | y
Costa
Lookup MAN in B1:I1
Then in D2:D9 look for Y
Then return corresponding result from A2:A9
Answer Eat and Fly
Spreadsheet: 182208d1348348914-fetching-data-from-a-table-into-a-more-compact-form-1
Sheet: Arkusz1

Input table: |  |  | Wine  1 | Wine  2 | Wine  3 | Wine  4 | Wine  5 | Wine  6 | Wine  7 | Wine  8 | Wine  9 | Wine  10 | Wine  11 | Wine  12 | Wine  13 | Wine  14 | Wine  15 | Wine  16 | Wine  17 | Wine  18 | Wine  19 | Wine  20
 | Name 1 |  | 1 |  |  |  | 5 |  |  |  |  |  | 6 |  |  |  |  | 7
 | Name 2 |  |  |  | 2 |  |  | 3 |  |  |  | 3 |  |  |  |  |  |  |  | 1
 | Name 3 |  | 5 |  |  | 7 |  |  |  |  | 8 |  |  |  |  |  |  | 1
 | Name 4 |  | 2 |  |  |  |  | 3 |  | 3 |  |  |  |  | 4 |  |  |  |  | 6 |  | 1
 |  |  |  | Bottles
Desired output: |  | Name 1 | Wine 1 | 1
 |  |  | Wine 5 | 5
 |  |  | Wine 11 | 6
 |  |  | Wine 16 | 7
 |  | Name 2 | Wine 3 | 2
 |  |  | Wine 6 | 3
 |  |  | Wine 10 | 3
 |  |  | Wine 18 | 1
 |  |  | etc.
Spreadsheet: 683814d1592965099-formula-that-returns-a-value-under-specific-conditions-region-issuev4
Sheet: Sheet1 (2)

Entered Account # | Entered Date | Region (as returned from formula) |  |  |  | [NAME] that Returns a Value under Specific Conditions
ABC | 2018-02-01 00:00:00 |  | Returned Regsion from matched row in array because Span Duration - 365 or 366 |  |  | My problem is as below: I have some data that was dumped from a database and I need to return the "Region" from that data (for the "Entered Account #" and "Entered Date") under the following conditions: 1.  IF "Span Duration is = 365 or 366 and  2.  "Entered Date" is >= the "From Date" and  3.  "Entered Date" is <= the "To Date"THEN return "Region" from the "matched" row. BUT only perform steps 1-3 when the "Entered Account #" is = the "Account #" from the Database Data.  Need to check all the date spans within that "Account #". That's Part 1. Part 2 is:  IF < 365, THEN use the "Region" from the next row in the database data but ONLY if that next row is for the same "Account #" ELSE return "no match found" I tried using all kinds of combinations of INDIRECT, ADDRESS, CELL, COLUMN, ROW, iNDEX and am not having any luck.   I can't use a macro for this and was wondering if it is able to be done with a formula. I'm probably/definitely biting off more than I can chew :) but any help you can provide will be hugely appreciated.  Thanks!
ABC | 2020-03-01 00:00:00 |  | Returned Regsion from matched row in array because Span Duration - 365 or 366
ABC | 2020-02-01 00:00:00 |  | Returned Regsion from matched row in array because Span Duration - 365 or 366
DEF | 2018-06-15 00:00:00 |  | [NAME] from next tow after matched row in array because Span Duration <365
ABC | 2019-02-01 00:00:00 |  | Returned Regsion from matched row in array because Span Duration - 365 or 366
DEF | 2019-02-01 00:00:00 |  | Returned Regsion from matched row in array because Span Duration - 365 or 366
DEF | 2017-01-01 00:00:00 |  | Entered Date nor present in any Date Span for DEF
DEF | 2020-02-01 00:00:00 |  | Returned Regsion from matched row in array because Span Duration - 365 or 366
Database Data
Account # | Span Duration (Days) | From Date | To Date | Region
ABC |  | 2018-01-01 00:00:00 | 2018-12-31 00:00:00 | Boston
ABC |  | 2019-01-01 00:00:00 | 2019-12-31 00:00:00 | New York
ABC |  | 2020-01-01 00:00:00 | 2020-12-31 00:00:00 | Sacramento
DEF |  | 2018-01-01 00:00:00 | 2018-06-30 00:00:00 | Wichita
DEF |  | 2019-01-01 00:00:00 | 2019-12-31 00:00:00 | Sarasota
DEF |  | 2020-01-01 00:00:00 | 2020-12-31 00:00:00 | Denver
Spreadsheet: 40168d1238504270-change-sumproduct-to-if-with-exchange-rate-file
Sheet: JAN09SEA

Country | Currency | Value |  | Currency | Value | Type
USA | USD | 254 |  | HKD | 12 | FG
GBR | EUR | 105 |  | HKD | 15 | FG
CHN | HKD | 1523 |  | HKD | 18 | RM
GBR | EUR | 163 |  | HKD | 11 | RM
CHN | HKD | 1875 |  | HKD | 16 | RM
USA | USD | 256 |  | HKD | 13 | FG
Exchange Rate:
USD | 1
EUR | 1.3941061
HKD | 0.1290199
Spreadsheet: 736314d1623496313-need-help-calculating-of-new-customers-and-lost-customers-excel-forum-question
Sheet: Sheet1

Customer | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug
Name1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15000
[NAME] | 0 | 0 | 0 | 500 | 500 | 500 | 500 | 500
Name3 | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25
Name4 | 0 | 0 | 5000 | 5000 | 5000 | 0 | 0 | 0
Name5 | 0 | 0 | 0 | 0 | 0 | 0 | 8500 | 8500
Name6 | 0 | 0 | 0 | 1250 | 1250 | 1250 | 1250 | 1250
# of customers:
# of new customers:
# lost cutomers:
Spreadsheet: d54c50c7-b0dc-4bec-a4a2-0c5d65181530
Sheet: Sheet1

Bevölkerung des Freistaates Sachsen nach ausgewählten Altersgruppen | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
[NAME]
Alter von ... bis                     unter ... Jahren | 2011 | 2015 | 2020 | 2025
1 000
unter 3 | 3224 | 2677 | 2334 | 1960
3 -   6 | 3219 | 3024 | 2712 | 2359
6 - 11 | 5649 | 5462 | 5134 | 4629
11 - 17 | 6181 | 6599 | 6542 | 6237
17 - 19 | 1516 | 1954 | 2061 | 2093
19 - 25 | 7448 | 4721 | 5299 | 5371
Insgesamt | 27237 | 24437 | 24082 | 22649
%
unter 3 | 11.83683959320043 | 10.95469984040594 | 9.691886055975417 | 8.653803699942603
3 -   6 | 11.81848221169732 | 12.37467774276712 | 11.2615231293082 | 10.41547088171663
6 - 11 | 20.74016962220509 | 22.35135245733928 | 21.31882733992193 | 20.43798843216036
11 - 17 | 22.69339501413518 | 27.0041330768916 | 27.16551781413504 | 27.53763963088878
17 - 19 | 5.565958071740646 | 7.996071530875312 | 8.558259280790633 | 9.241026093867278
19 - 25 | 27.34515548702133 | 19.31906535172075 | 22.00398637986878 | 23.71407126142435
Insgesamt | 100 | 100 | 100 | 100
Gebietsstand: | 31. [NAME] 2008
Quelle: | 2011 Bevölkerungsfortschreibung auf Basis der [NAME] vom 03. Oktober 1990
 | 2012 - 2025 Bevölkerungsprognose
Bevölkerung jeweils am 31. Dezember
Prognoseergebnisse werden bei der Veröffentlichung immer auf volle [NAME] gerundet. [NAME] basieren [NAME] ungerundeten Werten. Beim [NAME] der [NAME] werden Ihnen die ungerundeten [NAME] zur Verfügung gestellt, damit [NAME] eigenen Berechnungen genauer durchführen können. Die Darstellung der Ergebnisse sollte dann aber wieder gerundet erfolgen.