tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 142621d1329932125-help-need-formula-that-generates-unique-identifier-generic-example-data
Sheet: Example Data

Key Identifier Combines Org and Email IDs | ChurchName | Unique Church ID (based on Office Phone) | OfficePhone | Email ID - how do I automate this column with a formula? | email_address | First Name
1 | Main St Foods | 1 | [PHONE] | 1 | [EMAIL] | [NAME]
 | Wayland Co |  | [PHONE] | 1 | [EMAIL] | [NAME]
 | Wayland Co |  | [PHONE] | 2 | [EMAIL] | [NAME]
 | Wayland Co |  | [PHONE] | 3 | [EMAIL] | [NAME]
 | Marks Town |  | [PHONE] | 1 | [EMAIL] | [NAME]
 | Marks Town |  | [PHONE] | 2 | [EMAIL] | [NAME]
 | Binville |  | [PHONE] | 1 | [EMAIL] | [NAME]
Spreadsheet: 61959d1262868094-return-column-name-example3
Sheet: Sheet1

Expense | Category | alpha | beta | gamma | delta | epsilon | zeta | eta | theta | iota | [NAME]
1 | alpha | 500 |  |  |  |  |  |  |  |  |  | alpha
2 | beta |  | 1000 |  |  |  |  |  |  |  |  | beta
3 | gamma |  |  | 2000 |  |  |  |  |  |  |  | gamma
4 | delta |  |  |  | 3000 |  |  |  |  |  |  | delta
5 | epsilon |  |  |  |  | 4000 |  |  |  |  |  | epsilon
6 |  |  |  |  |  |  | 5000 |  |  |  |  | zeta
7 |  |  |  |  |  |  |  | 6000 |  |  |  | eta
8 |  |  |  |  |  |  |  |  | 7000 |  |  | theta
9 |  |  |  |  |  |  |  |  |  | 8000 |  | iota
10 |  |  |  |  |  |  |  |  |  |  | 9000 | [NAME]
 | For the column labeled category:
 | I need it to return the name of the column which has the number in it.
Spreadsheet: 271490d1381951919-sum-up-categories-then-sort-it-t-calc-ex1
Sheet: Sheet1

ID | Type | Date IN | Date OUT | Days In Between | Category | # of items
th40 | cash | 2013-08-30 00:00:00 | 2013-08-31 00:00:00
[NAME] | cash | 2013-08-27 00:00:00 | 2013-08-27 00:00:00 |  | cash+0 | 2
th42 | bond | 2013-08-27 00:00:00 | 2013-08-28 00:00:00
th42 | bond | 2013-08-28 00:00:00 | 2013-08-29 00:00:00 |  | bond+1 | 2
th41 | cash | 2013-08-31 00:00:00 | 2013-09-02 00:00:00 |  | cash+1 | 1
th41 | stock | 2013-08-27 00:00:00 | 2013-08-28 00:00:00 |  | stock+1 | 1 |  | 2013-08-15 00:00:00
th40 | cash | 2013-08-14 00:00:00 | 2013-08-16 00:00:00
th42 | cash | 2013-08-12 00:00:00 | 2013-08-16 00:00:00
th42 | cash | 2013-08-28 00:00:00 | 2013-08-30 00:00:00
th49 | cash | 2013-08-29 00:00:00 | 2013-09-02 00:00:00 |  | cash+2 | 4
th40 | stock | 2013-08-26 00:00:00 | 2013-08-28 00:00:00
th45 | stock | 2013-08-28 00:00:00 | 2013-08-31 00:00:00 |  | stock+2 | 2
th50 | bond | 2013-08-27 00:00:00 | 2013-09-01 00:00:00 |  | bond+3 | 1
th42 | cash | 2013-08-27 00:00:00 | 2013-09-01 00:00:00
th44 | cash | 2013-08-30 00:00:00 | 2013-09-04 00:00:00 |  | cash+3 | 2
th42 | stock | 2013-08-28 00:00:00 | 2013-09-02 00:00:00 |  | stock+3 | 1
th44 | bond | 2013-08-29 00:00:00 | 2013-09-04 00:00:00 |  | bond+4 | 1
th41 | bond | 2013-09-01 00:00:00 | 2013-09-06 00:00:00 |  | bond+5 | 1
th44 | bond | 2013-08-27 00:00:00 | 2013-09-04 00:00:00 |  | bond+6 | 1
Spreadsheet: kate_symes__18214__EESSales_dailymarch
Sheet: 3-7

POSITIVE [NAME] = LONG POSITION
NEGATIVE VARIANCE = SHORT POSITION
NP15 | 2001-03-07 00:00:00 |  |  |  |  |  | SP15 |  |  |  |  |  |  | ZP26
Fixed Peak | 334 | Fixed Off Peak | 224.36 |  |  |  | Fixed Peak | 319.21 |  | Fixed Off Peak | 208 |  |  | Fixed Peak | 319.21 |  | Fixed Off Peak | 208
Index Peak |  | Index [NAME] |  |  |  |  | Index Peak |  |  | Index [NAME] |  |  |  | Index Peak |  |  | Index [NAME]
HE | Fixed | Other | DJ Index | Load | var |  | HE | Fixed | Other | DJ Index | Load | var |  | HE | Fixed | Other | DJ Index | Load | var
1 | 5.28 | 0 | 0 | -5.28 |  |  | 1 | 25.65 | 0 | 0 | 1.349999999999994 |  |  | 1 | 1.99 | 0 | 0 | -1.99
2 | 4.49 | 0 | 0 | -4.49 |  |  | 2 | 26.27 | 0 | 0 | 4.72999999999999 |  |  | 2 | 1.96 | 0 | 0 | -1.96
3 | 4.03 | 0 | 0 | -4.03 |  |  | 3 | 26.89 | 0 | 0 | 6.110000000000014 |  |  | 3 | 1.94 | 0 | 0 | -1.94
4 | 3.97 | 0 | 0 | -3.97 |  |  | 4 | 26.74 | 0 | 0 | 6.259999999999991 |  |  | 4 | 1.94 | 0 | 0 | -1.94
5 | 4.33 | 0 | 0 | -4.33 |  |  | 5 | 25.99 | 0 | 0 | 3.009999999999991 |  |  | 5 | 1.96 | 0 | 0 | -1.96
6 | 6.25 | 0 | 0 | -6.25 |  |  | 6 | 24.14 | 0 | 0 | 8.860000000000014 |  |  | 6 | 2.03 | 0 | 0 | -2.03
7 | 9.91 | 0 | 0 | -9.91 |  |  | 7 | 33.3 | 0 | 20 | -0.3000000000000114 |  |  | 7 | 2.19 | 0 | 0 | -2.19
8 | 12.41 | 0 | 0 | -12.41 |  |  | 8 | 31.17 | 0 | 20 | -11.17 |  |  | 8 | 2.29 | 0 | 0 | -2.29
9 | 12.88 | 0 | 0 | -12.88 |  |  | 9 | 30.23 | 0 | 20 | -20.23 |  |  | 9 | 2.31 | 0 | 0 | -2.31
10 | 13.36 | 0 | 0 | -13.36 |  |  | 10 | 30.2 | 0 | 20 | -26.2 |  |  | 10 | 2.33 | 0 | 0 | -2.33
11 | 13.37 | 0 | 0 | -13.37 |  |  | 11 | 29.66 | 0 | 20 | -29.66 |  |  | 11 | 2.34 | 0 | 0 | -2.34
12 | 12.95 | 0 | 0 | -12.95 |  |  | 12 | 30.61 | 0 | 20 | -31.61 |  |  | 12 | 2.32 | 0 | 0 | -2.32
13 | 13.46 | 0 | 0 | -13.46 |  |  | 13 | 29.5 | 0 | 20 | -32.5 |  |  | 13 | 2.33 | 0 | 0 | -2.33
14 | 13.48 | 0 | 0 | -13.48 |  |  | 14 | 29.44 | 0 | 20 | -32.44 |  |  | 14 | 2.33 | 0 | 0 | -2.33
15 | 13.24 | 0 | 0 | -13.24 |  |  | 15 | 30.38 | 0 | 20 | -31.38 |  |  | 15 | 2.33 | 0 | 0 | -2.33
16 | 13.28 | 0 | 0 | -13.28 |  |  | 16 | 30.25 | 0 | 20 | -28.25 |  |  | 16 | 2.33 | 0 | 0 | -2.33
17 | 13.32 | 0 | 0 | -13.32 |  |  | 17 | 29.85 | 0 | 20 | -22.85 |  |  | 17 | 2.33 | 0 | 0 | -2.33
18 | 14.65 | 0 | 0 | -14.65 |  |  | 18 | 28.92 | 0 | 20 | -22.92 |  |  | 18 | 2.38 | 0 | 0 | -2.38
19 | 16.49 | 0 | 0 | -16.49 |  |  | 19 | 27.05 | 0 | 20 | -23.05 |  |  | 19 | 2.46 | 0 | 0 | -2.46
20 | 15.33 | 0 | 0 | -15.33 |  |  | 20 | 27.37 | 0 | 20 | -20.37 |  |  | 20 | 2.42 | 0 | 0 | -2.42
21 | 13.88 | 0 | 0 | -13.88 |  |  | 21 | 29.35 | 0 | 20 | -16.35 |  |  | 21 | 2.35 | 0 | 0 | -2.35
22 | 12.29 | 0 | 0 | -12.29 |  |  | 22 | 30.58 | 0 | 20 | -8.580000000000013 |  |  | 22 | 2.29 | 0 | 0 | -2.29
23 | 9.79 | 0 | 0 | -9.79 |  |  | 23 | 20.35 | 0 | 0 | -0.3499999999999943 |  |  | 23 | 2.19 | 0 | 0 | -2.19
24 | 7.05 | 0 | 0 | -7.05 |  |  | 24 | 23.29 | 0 | 0 | 9.710000000000008 |  |  | 24 | 2.07 | 0 | 0 | -2.07
Spreadsheet: 480673d1474020328-complex-nested-condition-book3
Sheet: Sheet1

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Spreadsheet: 268526d1380665419-desired-multiple-data-into-single-cell-09-13
Sheet: DEPL

DUTY DEPLOYMENT OF HOME GUARDS NIRMAL - UNIT  FOR THE MONTH OF SEPTEMBER- 2013
Sl. No. | Name of the P.S. | Total HGs | Home Guard Nos.
1 | SDPO Office NRL | 7 | 326, 330, 338, 436, 524, 501, WHG 1008
2 | CI Office, Nirmal Rural | 4 | 306, 697, WHG 1066, 1122
3 | P.S. Nirmal (Rural) | 8 | 342, 353, 552, 678, 909, 829, 1054
4 | P.S. Nirmal (Town), [NAME] | 16 | 334, 341, 358, 365, 397, 477, 483, 489, 523, 537, 557, 750, 827, 994, 997,
5 | P.S. Nirmal (Town), Traffic | 8 | 172, 311, 455, 488, 534, 990, 993, 996,
6 | P.S. Nirmal (Town), PS Duties and General Duties | 9 | 13, 288, 302, WHG 308, 369, 490, WHG 572, 573, 691,
7 | P.S. Sarangapur | 6 | 153, 319, 404, 902, WHG 941, 1000
8 | P.S. Soan | 4 | 366, 480, 982, WHG 1052
9 | P.S. Narsapur (G) | 3 | 368, WHG 529, 824, 854
10 | P.S. Khanapur | 14 | WHG 90, 295, 309, 317, 322, 346,  352, 479, 541, 569, 696, 753, 898, 938
11 | [NAME] | 7 | 304, 312, 471, 695, 703, WHG 705, 896,
12 | P.S. Pembi | 3 | 347, 751, 991
13 | P.S. Mamada | 5 | 310, 332, 700, 771, 1073
14 | P.S. Laxmanchanda | 3 | 340, 486, WHG 588
15 | Court Duty | 2 | 315, 327
16 | HGs Office Attach | 1 | 321
17 | RM Office Duty | 1 | 1034
 | Total on Duty | 101
18 | Deputation | 12 | 31, 817, 344, 354, 823, 826, 833, 992, 1007, 1015, 1018 , 336
19 | Absentees | 2 | 665, 699
20 | Permission | 0
21 | BSNL Waiting | 2 | 1029, 821
22 | Doing duty at RI HG ADD | 0
23 | Present Strength | 117
Spreadsheet: 145253d1331439464-supply-a-column-of-table-as-a-data-validation-list-chandrajit_sample_10mar12_01
Sheet: Sheet1

 | I want data validation in this cell such that I can have the values of Table1>Name as the dropdown. I want this because this serve as a dynamic list | <<< Click in this cell and check out the List Of Values; add values to the following table and then check this List Of Values again.
 |  |  |  |  |  | table
 |  |  |  |  |  | SR | Name
 |  |  |  |  |  | 1 | Name1
 |  |  |  |  |  | 2 | [NAME]
 |  |  |  |  |  | 3 | Name3
 |  |  |  |  |  | 4 | Name4
 |  |  |  |  |  | 5 | Name5
 |  |  |  |  |  | 6 | Name6
 |  |  |  |  |  | 7 | Name7
 |  |  |  |  |  | 8 | Name8
 |  |  |  |  |  | 9 | Name9
 |  |  |  |  |  | 10 | Name10
Spreadsheet: 057dd55e-04d7-416b-b091-8c53e29c30b0
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Travel and Training January 16, 2012  through March 15, 2012 | Unnamed: 4 | Unnamed: 5
 | Name | Month | Vendor | Amount | Description
City Manager | City Manager [NAME] | Jan 16 to Mar 15 |  | 55 | NM Municipal League Municipal Day Registration
 |  |  |  | 50 | NM Regional Chamber Municipal Day
 |  |  |  | 275 | ICMA Internet Mountain Plains Conference
Municipal Judge | Municipal Judge [NAME] | Jan 16 to Mar 15 |  | 717.72 | Southwest Airlines - National Conference
 |  |  |  | 1230 | Registration - National Conference
 |  |  |  | Note: Other conference reimbursements were paid and will be reported for the period March 16, 2012 to June 30, 2012
Governing Body | City Councilors | Jan 16 to Mar 15 |  | 100 | District 6 Councilor [NAME] Regional Chamber Municipal Day
Spreadsheet: af2a60b4-a376-4a59-92a0-ad4b45d92aff
Sheet: Sheet1

Bevölkerung des Freistaates Sachsen nach ausgewählten Altersgruppen | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4
Oberlungwitz, Stadt - Variante 1
Alter von ... bis                     unter ... Jahren | 2011 | 2015 | 2020 | 2025
1 000
unter 20 | 845 | 863 | 829 | 777
20 - 65 | 3820 | 3522 | 3089 | 2661
65 und mehr | 1627 | 1712 | 1875 | 2036
Insgesamt | 6292 | 6097 | 5793 | 5474
%
unter 20 | 13.4297520661157 | 14.15450221420371 | 14.31037459002244 | 14.19437340153453
20 - 65 | 60.7120152574698 | 57.76611448253239 | 53.32297600552391 | 48.61161856046767
65 und mehr | 25.8582326764145 | 28.0793833032639 | 32.36664940445365 | 37.1940080379978
Insgesamt | 100 | 100 | 100 | 100
Abhängigkeitsquotient
Jugendquotient | 22.12041884816754 | 24.50312322544009 | 26.83716413078666 | 29.19954904171364
Altenquotient | 42.59162303664921 | 48.60874503123225 | 60.69925542246681 | 76.51258925216085
Gesamtquotient | 64.71204188481676 | 73.11186825667234 | 87.53641955325348 | 105.7121382938745
Gebietsstand: | 1. Januar 2012
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.
Spreadsheet: kim_ward__20947__hedge 070301
Sheet: Sheet1

City of Palo Alto Hedge
2001-07-03 00:00:00
At Citygate
 |  | MMBTu/day | days/month | MMBtu per Month
 | 2001-08-01 00:00:00 | 180 | 31
 | 2001-09-01 00:00:00 | 190 | 30
 | 2001-10-01 00:00:00 | 185 | 31
 | 2001-11-01 00:00:00 | 185 | 30
 | 2001-12-01 00:00:00 | 180 | 32
 | 2002-01-01 00:00:00 | 195 | 31
 | 2002-02-01 00:00:00 | 215 | 28
 | 2002-03-01 00:00:00 | 205 | 31
 | 2002-04-01 00:00:00 | 190 | 30
 | 2002-05-01 00:00:00 | 185 | 31
 | 2002-06-01 00:00:00 | 175 | 30
 | 2002-07-01 00:00:00 | 180 | 31
Spreadsheet: 330554d1404799172-re-cell-text-contents-act-to-trigger-multiple-cells-magoo_new
Sheet: Sheet1

Client list | Sales Stage |  | Probability of success | actions |  |  | Suspect target | 1 |  | 0%-30% |  | 0 | 0.3
Customer one | Suspect target |  |  | complete task x and cascade to client.. |  |  | Engaged client | 2 |  | 31%-60% |  | 0.31 | 0.6
customer two | Engaged client |  |  | respond to client questions |  |  | Negotiation | 3 |  | 61%-100% |  | 0.61 | 1
customer three | Short-list |  |  | propose suitable commercial contract… |  |  | Short-list | 4
 |  |  |  |  |  |  | Win | 5
 |  |  |  |  |  |  | Lose | 6
Spreadsheet: 29575d1224661922-locking-formulas-master
Sheet: Site Visits

 | Job No: | 0
 | Main Contractor | 0
 | Site | 0
 | Descripion | #N/A
Site Visits
Date | Name | Reason For Visit | Hours | Cost per/hr | Total Cost
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  |  | 35 | 0
 |  |  | Total Cost To Date |  | 0
Spreadsheet: 173846d1344810441-how-to-place-the-active-cell-after-an-hiperlink-action-test
Sheet: MEDALS

COUNTRY | GOLD | TOTAL
Brazil | 3 | 15
China | 38 | 87
France | 10 | 33
Great Britain | 28 | 62
USA | 44 | 102
Venezuela | 1 | 1
Spreadsheet: 731569d1620413700-help-formula-to-find-a-match-for-cell-and-return-value-of-the-title-of-that-column-league-2
Sheet: GNT

S.N. | Particulars | Bought  Units | Unit or GNT Price | Bought/ Sold Price  ($US) | Bought/ Sold Price (BTC) | Token Unit Price During Txn | Activity  Date | Received Date | Fee  ($US) | Fee (%) | Total Price ($US) | Estimated  Price ($US) | Status | Notes
1 | [NAME] Bittrex - Purchase | 308.39409388 | 3.018e-05 |  | -0.00933367 | 18981.9 | 2017-12-18 00:00:00 | 2017-12-18 00:00:00 |  |  |  |  | SOLD
2 | [NAME] Bittrex - Purchase | 2937.62135922 | 3.079e-05 |  | -0.0906999 | 18981.9 | 2017-12-18 00:00:00 | 2017-12-18 00:00:00 |  |  |  |  | SOLD
3 | [NAME] Bittrex - Sale | -3246.0154531 | 3.673e-05 |  | 0.11895713 | 16596.1 | 2017-12-20 00:00:00
4 | [NAME] Bittrex - Purchase | 130 | 5.51e-05 |  | -0.00718219 | 14575 | 2017-12-29 00:00:00 | 2017-12-29 00:00:00 |  |  |  |  | SOLD
5 | Fees for transferring 130 GNT from Bittrex to Ledger (MEW) | -9 |  |  |  |  | 2018-01-28 00:00:00
6 | [NAME] Bittrex - Sale | -121 | 3.726e-05 |  | 0.00449719 | 10180 | 2018-02-26 00:00:00
7
8
9
10
 | Next Buy
 | Golem in [NAME] (via MEW) | 0
 | Golem in Bittrex | 0
 | Golem in BitStamp | 0
 | Total Investment Loss/Profit ($US)
 | Website: https://
 | Contract address:
 | Symbol:
 | Decimals:
 | About/Idea
 | Team Members (reputation, prior projects, LinkedIn, social presence)
 | Website Design
 | White Paper
 | ICO Rating
 | www.icoranker.com
 | www.icobench.com
 | www.tokenmarket.net
 | Marketing
 | Twitter
 | Instagram
 | Facebook
 | CEO Presence in the market
 | Roadmap & timeline
 | When are they hitting the exchanges?
Spreadsheet: 99865d1298407796-graphing-design-question-day92-physician-productivity
Sheet: Sheet1

 | 2008-01-01 00:00:00 | 2008-02-01 00:00:00 | 2008-03-01 00:00:00 | 2008-04-01 00:00:00 | 2008-05-01 00:00:00 | 2008-06-01 00:00:00 | 2008-07-01 00:00:00 | 2008-08-01 00:00:00 | 2008-09-01 00:00:00 | 2008-10-01 00:00:00 | 2008-11-01 00:00:00 | 2008-12-01 00:00:00 | 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 | 2010-05-01 00:00:00 | 2010-06-01 00:00:00 | 2010-07-01 00:00:00 | 2010-08-01 00:00:00 | 2010-09-01 00:00:00 | 2010-10-01 00:00:00 | 2010-11-01 00:00:00 | 2010-12-01 00:00:00
Physician 1 | 250 | 222 | 232 | 541 | 214 | 220 | 221 | 201 | 199 | 187 | 78 | 89 | 115 | 220 | 236 | 235 | 254 | 201 | 199 | 121 | 122 | 111 | 99 | 40 | 199 | 252 | 248 | 259 | 330 | 235 | 225 | 352 | 359 | 360 | 111 | 89
Physician 2 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 58 | 40
Physician 3 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 160 | 188 | 204
Average of All Physicians
Fair Market Value | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255 | 255
Quarter | 1
Year | 2008
Quarter
Physician 1
Physician 2
Physician 3
Average of All Physicians
Fair Market Value
Spreadsheet: 207059d1358354818-compile-non-empty-cells-into-one-column-excel-question-non-linear-example
Sheet: Sheet1

 |  |  |  | 2 | 3 | 3 | 1
 |  |  | Section A | Section B | Section C | Section D | Section E |  | All Sections
 |  | length | 10 | 22 | 3 | 16 | 35 |  | 86
 |  | Increment | 1 | 2 | 1 | 4 | 7
 |  |  | 0 | 6 | 11 | 13 | 56 |  | 0
 |  |  | 1 | 8 | 12 | 17 | 63 |  | 1
 |  |  | 2 | 10 | 13 | 21 | 70 |  | 2
 |  |  | 3 | 12 | 14 | 25 | 77 |  | 3
 |  |  | 4 | 14 | 15 | 29 | 84 |  | 4
 |  |  | 5 | 16 | 16 | 33 |  |  | 5
 |  |  | 6 | 18 | 17 | 37 |  |  | 6
 |  |  | 7 | 20 | 18 | 41 |  |  | 7
 |  |  | 8 | 22 | 19 | 45 |  |  | 8
 |  |  | 9 | 24 | 20 | 49 |  |  | 9
 |  |  | 10 | 26 | 21 |  |  |  | 10
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Spreadsheet: 831265d1685530403-check-if-date-persist-within-2-ranges-work
Sheet: Work

User Id | Username | 2023-04-26 00:00:00 | 2023-04-27 00:00:00 | 2023-04-28 00:00:00 | 2023-04-29 00:00:00 | 2023-04-30 00:00:00 | 2023-05-01 00:00:00 | 2023-05-02 00:00:00 | 2023-05-03 00:00:00 | 2023-05-04 00:00:00 | 2023-05-05 00:00:00
ID1 | User1
ID2 | User2
ID3 | User3
ID4 | User4
ID5 | [NAME]
ID6 | [NAME]
ID7 | User7
ID8 | User8
ID9 | [NAME]
ID10 | User10
ID11 | User11
User ID | Reason | From | Until
ID1 | Holiday | 2023-04-29 00:00:00 | 2023-04-30 00:00:00
ID1 | Sick | 2023-05-03 00:00:00 | 2023-05-06 00:00:00 | -> missing at the table above
ID3 | Holiday | 2023-05-03 00:00:00 | 2023-05-06 00:00:00
ID5 | Sick | 2023-04-27 00:00:00 | 2023-04-30 00:00:00
ID5 | Day-Off | 2023-05-03 00:00:00 | 2023-05-04 00:00:00 | -> missing at the table above
ID8 | Holiday | 2023-04-27 00:00:00 | 2023-04-30 00:00:00
ID9 | Sick | 2023-05-01 00:00:00 | 2023-05-04 00:00:00
ID11 | Holiday | 2023-04-26 00:00:00 | 2023-04-27 00:00:00
ID11 | Sick | 2023-05-01 00:00:00 | 2023-05-01 00:00:00 | -> missing at the table above
ID11 | Holiday | 2023-05-04 00:00:00 | 2023-05-05 00:00:00 | -> missing at the table above
Spreadsheet: 3e2d68c1-b7d7-41b1-89c7-4b0eadc9ede5
Sheet: Sheet1

MOSQUITO MARINA AND FUEL CONCESSION - OVERVIEW | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10
Category
of Revenue | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012
FOOD AND BEVERAGE | 11335.37 | 14067.7 | 23614.72 | 31045.03 | 32720.7 | 35456.30999999999 | 35056.23 | 43817.47 | 37503.88 | 36102.77
GASOLINE AND OIL | 17787.61 | 20139.78 | 28354.05 | 26340.27 | 23327.48 | 22321.81 | 21571.86 | 22097.79 | 24304.93 | 18054.56
BAIT AND TACKLE | 16095.02 | 23874.35 | 29623.49 | 34434.63999999999 | 30265.1 | 30405.55 | 33955.31 | 32974.66 | 28444.08 | 30818.15
MARINE EQUIPMENT/SUPPLIES | 428.15 | 1343.88 | 1243.03 | 2287.420000000001 | 1494.5 | 662.03 | 330.37 | 1754.33 | 1630.78 | 992.26
ALL OTHER RECEIPTS | 3125.95 | 3404.75 | 3325.81 | 5360.13 | 5688.95 | 4792.04 | 4901.580000000001 | 4227.000000000001 | 3808.31 | 2789.64
Total | 48772.10000000001 | 62830.46 | 86161.09999999999 | 99467.49 | 93496.73 | 93637.73999999999 | 95815.34999999999 | 104871.25 | 95691.98 | 88757.38
Commissions Paid | 3831.55 | 5105.849999999999 | 7032.150000000001 | 8361.74 | 7898.879999999999 | 8008.09 | 8257.880000000001 | 9170.89 | 8163.54 | 7833.52
Concession began in 2003
Spreadsheet: 16707c03-e681-447b-8415-5a1a9fd44627
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2
 |  | U.S. Census Bureau
 |  | Source: New Residential Construction
 |  | Housing Units Completed: United States
 |  | Not Seasonally Adjusted Single-family Units [Thousands of Units]
 |  | Period: 2008 to 2012
 |  | Data Extracted on: October 30, 2014 (8:10 pm)
Period | Value
Jan-2008 | 69
Feb-2008 | 63.2
Mar-2008 | 69
Apr-2008 | 62
May-2008 | 73.6
Jun-2008 | 73.6
Jul-2008 | 69.2
Aug-2008 | 62.3
Sep-2008 | 75.3
Oct-2008 | 68.5
Nov-2008 | 66.8
Dec-2008 | 66.3
Jan-2009 | 39
Feb-2009 | 36.4
Mar-2009 | 41.3
Apr-2009 | 41.3
May-2009 | 41.1
Jun-2009 | 44.4
Jul-2009 | 41.1
Aug-2009 | 44.5
Sep-2009 | 43.9
Oct-2009 | 49
Nov-2009 | 50.1
Dec-2009 | 48
[NAME] | 30
[NAME] | 30.7
Mar-2010 | 37.6
Apr-2010 | 42.9
[NAME] | 43
[NAME] | 60.1
[NAME] | 39.2
Aug-2010 | 41.4
Sep-2010 | 43.9
Oct-2010 | 44.7
Nov-2010 | 38.7
Dec-2010 | 44
Jan-2011 | 28.4
Feb-2011 | 32.9
Mar-2011 | 28.2
Apr-2011 | 33.3
May-2011 | 36.6
Jun-2011 | 39.7
Jul-2011 | 40.2
Aug-2011 | 42.1
Sep-2011 | 38.4
Oct-2011 | 41.3
Nov-2011 | 40.7
Dec-2011 | 44.8
Jan-2012 | 26
Feb-2012 | 29.4
Mar-2012 | 33.6
Apr-2012 | 37.6
May-2012 | 39.3
Jun-2012 | 42.4
Jul-2012 | 38.3
Aug-2012 | 43.3
Sep-2012 | 46.6
Oct-2012 | 50.1
Nov-2012 | 45.6
Dec-2012 | 50.7