tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 24114d1214235591-repeating-a-copy-paste-cycle-kayrat
Sheet: Tabelle1

WD/St.sz | Dis/Gen | Def/gen |  |  |  |  |  |  |  |  | PV/St.sz | Dis/Gen | Def/gen
0 | 0.259 | 0.244 |  |  |  |  |  |  |  |  | 0 | 0.307 | 0.303
50 | 0.238 | 0.223 |  |  |  |  |  |  |  |  | 50 | 0.287 | 0.282
100 | 0.228 | 0.213 |  |  |  |  |  |  |  |  | 100 | 0.27 | 0.266
150 | 0.221 | 0.206 |  |  |  |  |  |  |  |  | 150 | 0.255 | 0.251
200 | 0.215 | 0.2 |  |  |  |  |  |  |  |  | 200 | 0.241 | 0.237
300 | 0.204 | 0.189 |  |  |  |  |  |  |  |  | 300 | 0.215 | 0.211
400 | 0.196 | 0.18 |  |  |  |  |  |  |  |  | 400 | 0.195 | 0.191
500 | 0.188 | 0.173 |  |  |  |  |  |  |  |  | 500 | 0.186 | 0.181
600 | 0.182 | 0.167 |  |  |  |  |  |  |  |  | 600 | 0.181 | 0.176
700 | 0.176 | 0.161 |  |  |  |  |  |  |  |  | 700 | 0.176 | 0.171
800 | 0.171 | 0.156 |  |  |  |  |  |  |  |  | 800 | 0.173 | 0.169
900 | 0.167 | 0.151 |  |  |  |  |  |  |  |  | 900 | 0.172 | 0.167
1000 | 0.162 | 0.147 |  |  |  |  |  |  |  |  | 1000 | 0.17 | 0.166
1500 | 0.146 | 0.131 |  |  |  |  |  |  |  |  | 1500 | 0.168 | 0.163
2000 | 0.133 | 0.118 |  |  |  |  |  |  |  |  | 2000 | 0.166 | 0.161
2500 | 0.124 | 0.109 |  |  |  |  |  |  |  |  | 2500 | 0.165 | 0.161
3500 | 0.11 | 0.095 |  |  |  |  |  |  |  |  | 3500 | 0.164 | 0.159
4000 | 0.103 | 0.088 |  |  |  |  |  |  |  |  | 4000 | 0.163 | 0.159
5000 | 0.093 | 0.078 |  |  |  |  |  |  |  |  | 5000 | 0.162 | 0.157
7500 | 0.075 | 0.06 |  |  |  |  |  |  |  |  | 7500 | 0.159 | 0.155
10000 | 0.062 | 0.046 |  |  |  |  |  |  |  |  | 10000 | 0.156 | 0.152
12500 | 0.056 | 0.041 |  |  |  |  |  |  |  |  | 12500 | 0.153 | 0.149
15000 | 0.052 | 0.037 |  |  |  |  |  |  |  |  | 15000 | 0.151 | 0.146
17500 | 0.047 | 0.032 |  |  |  |  |  |  |  |  | 17500 | 0.148 | 0.143
20000 | 0.042 | 0.028 |  |  |  |  |  |  |  |  | 20000 | 0.145 | 0.14
22500 | 0.038 | 0.025 |  |  |  |  |  |  |  |  | 22500 | 0.142 | 0.137
25000 | 0.033 | 0.023 |  |  |  |  |  |  |  |  | 25000 | 0.139 | 0.134
27500 | 0.028 | 0.021 |  |  |  |  |  |  |  |  | 27500 | 0.136 | 0.132
30000 | 0.025 | 0.018 |  |  |  |  |  |  |  |  | 30000 | 0.133 | 0.1289
32500 | 0.022 | 0.016 |  |  |  |  |  |  |  |  | 35000 | 0.128 | 0.123
35000 | 0.02 | 0.014 |  |  |  |  |  |  |  |  | 40000 | 0.122 | 0.117
37500 | 0.018 | 0.011 |  |  |  |  |  |  |  |  | 45000 | 0.116 | 0.112
40000 | 0.015 | 0.009 |  |  |  |  |  |  |  |  | 50000 | 0.11 | 0.106
42500 | 0.013 | 0.009 |  |  |  |  |  |  |  |  | 55000 | 0.105 | 0.1
45000 | 0.011 | 0.009 |  |  |  |  |  |  |  |  | 60000 | 0.099 | 0.094
47500 | 0.008 | 0.009 |  |  |  |  |  |  |  |  | 65000 | 0.093 | 0.089
50000 | 0.006 | 0.009 |  |  |  |  |  |  |  |  | 70000 | 0.087 | 0.083
52500 | 0.004 | 0.009 |  |  |  |  |  |  |  |  | 80000 | 0.076 | 0.073
55000 | 0.001 | 0.009 |  |  |  |  |  |  |  |  | 90000 | 0.064 | 0.073
 |  |  |  |  |  |  |  |  |  |  | 100000 | 0.053 | 0.073
 |  |  |  |  |  |  |  |  |  |  | 110000 | 0.041 | 0.073
 |  |  |  |  |  |  |  |  |  |  | 120000 | 0.03 | 0.073
 |  |  |  |  |  |  |  |  |  |  | 130000 | 0.018 | 0.073
 |  |  |  |  |  |  |  |  |  |  | 140000 | 0.007 | 0.073
 |  |  |  |  |  |  |  |  |  |  | 145000 | 0.001 | 0.073
Spreadsheet: 93854d1293632763-want-a-running-function-to-avoid-using-countif-multilookup-sort
Sheet: S

Sr.No | Policy Holders Name | POLICY NO | Date of  Comm | T-T | MODE | NAME OF THE PLAN | Plan Type | SUM ASSURED
1 | Sachin Pradhan | 762383788 | 2004-06-28 00:00:00 | 14-32 | [NAME] | ENDOWMENT  WITH BONUS | Insurance | 55000
2 | Sachin Pradhan | 762667563 | 2005-02-15 00:00:00 | 169-22 | SGL | JEEVAN NIDHI WITH GUAR ADDTNS | Pension | 220000
3 | Sachin Pradhan | 762667568 | 2005-02-15 00:00:00 | 14-32 | HLY | ENDOWMENT  WITH BONUS | Insurance | 55000
4 | Sachin Pradhan | 762667566 | 2005-02-15 00:00:00 | 14-33 | [NAME] | ENDOWMENT  WITH BONUS | Insurance | 55000
5 | Sachin Pradhan | 762667567 | 2005-02-15 00:00:00 | 14-34 | [NAME] | ENDOWMENT  WITH BONUS | Insurance | 55000
6 | Sachin Pradhan | 762686286 | 2005-07-20 00:00:00 | 150-30 | ECS | NEW BIMA KIRAN | Insurance | 300000
7 | Sachin Pradhan | 762986286 | 2005-07-20 00:00:00 | 14-35 | [NAME] | ENDOWMENT  WITH BONUS | Insurance | 55000
8 | Sachin Pradhan | 762666858 | 2006-06-21 00:00:00 | 173-70 | [NAME] | JEEVAN PLUS | ULIP+Risk | 50000
9 | Sachin Pradhan | 762666856 | 2006-06-21 00:00:00 | 172-21 | [NAME] | FUTURE PLUS | ULIP | 50000
Spreadsheet: 735600d1623088902-trouble-with-countifs-hlookup-formula-teaching-evaluation-sample
Sheet: Ideal finished sheet

 | The Teacher outlined learning objectives |  |  |  | The teacher provided support completing assignments |  |  |  | The instructor makes every effort to answer questions adequately
Teacher | Strongly Disagree | Moderately Disagree | Moderately Agree | Strongly Agree | Strongly Disagree | Moderately Disagree | Moderately Agree | Strongly Agree | Strongly Disagree | Moderately Disagree | Moderately Agree | Strongly Agree
[NAME] | 1 |  | 1 | 1 | 2 |  |  | 1 | 2 |  | 1
[NAME] | 1 |  | 2 | 1 | 4 |  |  |  | 4
[NAME] | 3 |  |  | 1 | 2 | 1 | 1 |  | 4
Spreadsheet: f7d9dd17-9e16-4ca8-b2a1-c9997569aace
Sheet: Sheet1

Release: Regional and State Employment and Unemployment (Seasonally Adjusted) | Unnamed: 1 | Unnamed: 2
Link: http://alfred.stlouisfed.org/release?rid=250
ALFRED (ArchivaL Federal Reserve Economic Data)
Economic Research Division
Federal Reserve Bank of St. Louis
File Created: 2013-05-26 3:32 AM CDT
 | Real-Time | Period
Name: | Start | End
Regional and State Employment and Unemployment (Seasonally Adjusted) | 2012-01-24 00:00:00 | Current
Link:
[NAME] | 2012-01-24 00:00:00 | Current
Source:
Federal Reserve Bank of St. Louis | 2012-01-24 00:00:00 | Current
Notes:
Bureau of Labor Statistics data that is seasonally adjusted by the | 2012-01-24 00:00:00 | Current
Federal Reserve Bank of St. Louis.
Release Dates Notes:
Release dates are determined by the following process:
When available, the actual release date as provided by the source is
entered into the ALFRED database.  If a release date is not available
from the source, the release date given by our data providers is used.
If a release date cannot be determined either from the source or from
our data providers, the date that the series was first available in
the St. Louis Fed's FRED database is used.
The release date list contains the dates when any series from this
release was revised.  Note that all series from a release do not
necessarily revise on every release date.
Release Dates:
2012-01-24 00:00:00
2012-03-13 00:00:00
2012-03-30 00:00:00
2012-04-20 00:00:00
2012-05-18 00:00:00
2012-06-15 00:00:00
2012-07-20 00:00:00
2012-07-23 00:00:00
2012-08-17 00:00:00
2012-09-21 00:00:00
2012-10-19 00:00:00
2012-11-20 00:00:00
2012-12-21 00:00:00
2013-01-18 00:00:00
2013-03-18 00:00:00
2013-03-29 00:00:00
2013-04-19 00:00:00
2013-05-17 00:00:00
Spreadsheet: 726049d1617028515-pulling-data-at-the-end-of-a-business-day-sample2
Sheet: FormulasReferences

 |  |  |  |  |  |  | DataCleaning |  |  |  | hide entire tab
APP: Total Applications |  |  |  |  |  |  | Dash Started
APP: Unique Applicants |  |  |  |  |  |  | Gender | Y
APP: Total Positions |  |  |  |  |  |  | [NAME] | Y
APP: Time To Fill |  |  |  |  |  |  | Race/Ethnicity
EE: Retention
APP: [NAME]
EE: Avg EE Age
APP: [NAME]
EE: [NAME]
APP: Avg Experience
EE: Avg Experience |  |  |  |  | Alternative Race/Ethnicity Labels
American Indian or [NAME] |  |  |  |  | Ind | Alask
Asian |  |  |  |  | Asi | Asain
Black or African American |  |  |  |  | Afr | Bl
Hispanic or Latino |  |  |  |  | Hisp | Lat
Native Hawaiian or Other Pacific Islander |  |  |  |  | Pac | Isl | Haw
Not Specified |  |  |  |  | N/A | Not A | No A | None | NA | N A
Two or More Races |  |  |  |  | 2 | Two | more | mult
White |  |  |  |  | Wh | Cauc | Ang
[NAME] | male
gender2 | female
gender3 | split
Spreadsheet: 723799d1615902653-help-consolidate-data-1615886507823_example-1-
Sheet: data

item code | DATE 1 | QTY 1 | DATE 2 | QTY 2 | DATE 3 | QTY 3 | DATE 4 | QTY 4
4810 | 2021-03-01 00:00:00 | 1 | 2021-05-01 00:00:00 | 3 | 2022-03-01 00:00:00 | 2 | 2021-03-01 00:00:00 | 3
4811 | 2021-03-02 00:00:00 | 5 | 2022-05-02 00:00:00 | 4 | 2022-01-01 00:00:00 | 3 | 2021-03-01 00:00:00 | 5
4812 | 2021-03-03 00:00:00 | 6 | 2021-07-03 00:00:00 | 3 | 2022-06-01 00:00:00 | 2 | 2024-03-01 00:00:00 | 2
9320 | 2021-03-04 00:00:00 | 1 | 2022-05-04 00:00:00 | 5 | 2020-03-04 00:00:00 | 1 | 2023-03-01 00:00:00 | 1
4256 | 2021-04-05 00:00:00 | 3 | 2020-05-05 00:00:00 | 1 | 2021-03-05 00:00:00 | 6 | 2022-03-01 00:00:00 | 3
1350 | 2021-03-06 00:00:00 | 4 | 2023-05-06 00:00:00 | 7 | 2022-05-06 00:00:00 | 2 | 2020-03-01 00:00:00 | 2
2020 | 2021-03-07 00:00:00 | 3 | 2025-06-07 00:00:00 | 2 | 2022-04-07 00:00:00 | 1 | 2021-03-01 00:00:00 | 6
9821 | 2021-03-08 00:00:00 | 4 | 2021-02-08 00:00:00 | 1 | 2021-06-08 00:00:00 | 4 | 2023-03-01 00:00:00 | 4
2543 | 2021-03-09 00:00:00 | 2 | 2021-06-09 00:00:00 | 2 | 2021-09-09 00:00:00 | 6 | 2022-04-01 00:00:00 | 9
1876 | 2023-03-10 00:00:00 | 1 | 2021-01-10 00:00:00 | 3 | 2022-02-10 00:00:00 | 5 | 2022-10-01 00:00:00 | 1
1930 | 2022-03-11 00:00:00 | 7 | 2021-08-11 00:00:00 | 5 | 2022-03-11 00:00:00 | 4 | 2022-12-01 00:00:00 | 0
Spreadsheet: 685121d1593747031-difficulties-using-solver-for-staff-schedule-complicated-criteria-set-schedule2
Sheet: Constraints(Night)

Count of night shifts |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Count of number of night shifts in the next 4 days (forward and inclusive); [NAME] 3
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Constraint |  | <=3 | what if on 2 days of day 3 and on day 4?
 |  | Employee
Date | Week | [NAME] | [NAME] | Ayisha | [NAME] | Kaitlin | Jayme | [NAME] | [NAME] | Felix | [NAME] | Casual1 | Casual2 | Casual3 | Casual4 | Casual5 |  | Employuee
Spreadsheet: 551789d1513155137-formula-good-until-row-5000-then-no-data-after-5000th-row-workbook1
Sheet: Sheet1

 |  | This sheet 1 is where I pull data from for sheet 2
 |  | C8 + C9 goes in sheet 2, Then below it is C8 + C12, Then C8 + C13
 |  | Then it is C8 + L8 , Then C8 + L9. In column A on sheet 2 is where the numbers will show you how they change
 |  | Don’t worry about column "M" on sheet 1 it is referenced to something else
 |  | If I keep copying this down, I start losing formula transfer at row 5000
 |  | Also note: these numbers keep going down also, the pattern stays the same, but numbers change
 |  | 1 |  |  |  |  |  |  |  |  | 11
 |  | 2 |  |  |  |  |  |  |  |  | 12 | -81
 |  | 3 |  |  |  |  |  |  |  |  | 13
 |  | 4 |  |  |  |  |  |  |  |  | 14 | -84
 |  | 5 |  |  |  |  |  |  |  |  | 15
 |  | 6 |  |  |  |  |  |  |  |  | 16 | -92
 |  | 7 |  |  |  |  |  |  |  |  | 17
 |  | 8 |  |  |  |  |  |  |  |  | 18 | -95
 |  | -87 |  |  |  |  |  |  |  |  | 41
 |  | -41 |  |  |  |  |  |  |  |  | -46 | -88
 |  | -93 |  |  |  |  |  |  |  |  | 47
 |  | -41 |  |  |  |  |  |  |  |  | -46 | -100
 |  | -91 |  |  |  |  |  |  |  |  | 52
 |  | -34 |  |  |  |  |  |  |  |  | -39 | -103
Spreadsheet: 716846d1612378293-multiple-if-statements-including-deleting-data-in-cell-above-if-formula-conditions-are-met-actual-vs-projection
Sheet: Sheet1

Month | Code | Date | Actual | Projection
JAN | AA | 2020-01-01 00:00:00 | 50
JAN | AA | 2020-01-15 00:00:00 | 51
JAN | AA | 2020-01-29 00:00:00 | 55
FEB | AA | 2020-02-12 00:00:00 | 56
FEB | AA | 2020-02-26 00:00:00 | 55 | 55
MAR | AA | 2020-03-11 00:00:00 |  | 53
MAR | AA | 2020-03-25 00:00:00 |  | 61
APR | AA | 2020-04-08 00:00:00 |  | 66
APR | AA | 2020-04-22 00:00:00 |  | 70
JAN | AB | 2020-01-01 00:00:00 | 49
JAN | AB | 2020-01-15 00:00:00 | 48
JAN | AB | 2020-01-29 00:00:00 | 46
FEB | AB | 2020-02-12 00:00:00 | 52
FEB | AB | 2020-02-26 00:00:00 | 53 | 53
MAR | AB | 2020-03-11 00:00:00 |  | 55
MAR | AB | 2020-03-25 00:00:00 |  | 60
APR | AB | 2020-04-08 00:00:00 |  | 62
APR | AB | 2020-04-22 00:00:00 |  | 63
Spreadsheet: 0d71727f-fed2-4b90-9bf0-dfa305c1c3b4
Sheet: MENENGAH 3

MENENGAH 3
SENIN & RABU, 10.00-12.00 |  |  | SELASA & KAMIS, 18.00-20.00 |  |  | SABTU, 09.00-13.00
NO | NAMA |  | NO | NAMA |  | NO | NAMA
1 | [NAME] |  | 1 | [NAME] |  | 1 | [NAME]
2 | [NAME] |  | 2 | Ana Puspaningdiah |  | 2 | [NAME]
3 | [NAME] |  | 3 | Citra Handayani |  | 3 | [NAME]
4 | Dewi Rosida |  | 4 | Devinoraya R. |  | 4 | [NAME]
5 | [NAME] |  | 5 | [NAME] |  | 5 | Fadilatunnisa
6 | Presilia Agustin S |  | 6 | Fanny |  | 6 | Finary
7 | Sazkia Gabriellia Zakaria |  | 7 | [NAME] [NAME] |  | 7 | Galih Priya Sejati
8 | [NAME] |  | 8 | [NAME] |  | 8 | I Gusti Ayu [NAME]
9 | [NAME] |  | 9 | [NAME] |  | 9 | [NAME]
10 |  |  | 10 | Lely Kurnianingsih |  | 10 | Reinette Berliana
 |  |  | 11 | [NAME] |  | 11 | [NAME]
 |  |  | 12 | [NAME] |  | 12 | [NAME]
 |  |  | 13 | Octavia Pratama |  | 13 | [NAME]
 |  |  | 14 | [NAME] |  | 14 | Stefani Lobionda
 |  |  | 15 | [NAME] |  | 15 | Wiastuti Nurdina
Spreadsheet: 127882d1320671677-conditional-formatting-to-indicate-start-date-and-end-date-sample1
Sheet: May

Name | T | W | T | F | S | S | M | T | W | T | F | S | S | M | T | W | T | F | S | S | M | T | W | T | F | S | S | M | T | W | T
 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31
 | 2012-05-01 00:00:00 | 2012-05-02 00:00:00 | 2012-05-03 00:00:00 | 2012-05-04 00:00:00 | 2012-05-05 00:00:00 | 2012-05-06 00:00:00 | 2012-05-07 00:00:00 | 2012-05-08 00:00:00 | 2012-05-09 00:00:00 | 2012-05-10 00:00:00 | 2012-05-11 00:00:00 | 2012-05-12 00:00:00 | 2012-05-13 00:00:00 | 2012-05-14 00:00:00 | 2012-05-15 00:00:00 | 2012-05-16 00:00:00 | 2012-05-17 00:00:00 | 2012-05-18 00:00:00 | 2012-05-19 00:00:00 | 2012-05-20 00:00:00 | 2012-05-21 00:00:00 | 2012-05-22 00:00:00 | 2012-05-23 00:00:00 | 2012-05-24 00:00:00 | 2012-05-25 00:00:00 | 2012-05-26 00:00:00 | 2012-05-27 00:00:00 | 2012-05-28 00:00:00 | 2012-05-29 00:00:00 | 2012-05-30 00:00:00 | 2012-05-31 00:00:00
Spreadsheet: 698083d1601729959-accumulated-numbers-are-generated-by-four-conditions-help-1003-1-
Sheet: Sheet2

Start | 1 | End | 10 | increase a nos. | 4 | increase each time | 2
 | Accumulated numbers are generated by four conditions
 | Formular Starting from J2, the four conditions are B1, D1, F1, H1
 | J2 cell how to write the formula down
 | B1 is starting first number
 | D1 is Ending number
 | F1 increase a nnumbers
 | H1 increase each time
Spreadsheet: 0b368d3f-4872-4720-b30b-6bd70639057b
Sheet: Sheet1

Table 3--Soybean oil:  U.S. supply and disappearance | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11
 | Supply |  |  |  |  | Disappearance
Year beginning | Beginning | Production | Imports | Total |  | Domestic |  |  | Exports | Total | Ending
October 1 | stocks |  |  |  |  | Total | Biodiesel | Food |  |  | stocks
 | Million pounds
2011/12 | 2425.347 | 19740 | 149.325 | 22314.672 |  | 18310.522 | 4870 | 13440.522 | 1464.15 | 19774.672 | 2540
2012/131 | 2540 | 19840 | 250 | 22630 |  | 18550 | 4600 | 13950 | 2150 | 20700 | 1930
2013/142 | 1930 | 19035 | 250 | 21215 |  | 18550 | 5700 | 12850 | 1050 | 19600 | 1615
1 Estimated.  2 Forecast.
Source: USDA, World Agricultural Outlook Board, World Agricultural Supply and Demand Estimates.
Last update: | 2013-09-16 10:09:59.390000
Spreadsheet: 874248d1720804654-ifna-xlookup-excel-forum-example
Sheet: Sheet1

IF($C$5="","",IF(IFNA(XLOOKUP($C$5,'Weed Info'!A:A,'Weed Info'!B:B),FALSE),(XLOOKUP($C$5,'Weed Info'!A:A,'Weed Info'!B:B)),""))
 | Weed: | Absinth wormwood
 |  | Result: | Artemisia absinthium
 | Weed: | Dandelion
 |  | Intended result:
 |  | Actual result: | 0
[NAME]
[NAME] | Scientific Name
Absinth wormwood | Artemisia absinthium
American black nightshade | Solanum americanum
Austrian fieldcress | Rorippa austriaca
Black henbane | Hyoscyamus niger
Black nightshade | Solanum nigrum
Blueweed | Echium vulgare
Broomrape | Orobanche spp.
Buckhorn plantain | Plantago lanceolata
Cut-leaf teasel | Dipsacus laciniatus
Dalmatian toadflax | Linaria dalmatica
Dame’s rocket | [NAME] matronalis
Deadly nightshade | Solanum interius
Diffuse knapweed | Centaurea diffusa
Spreadsheet: 128194d1320849190-find-first-duplicate-value-and-display-difference-between-rows-check-and-display
Sheet: Sheet1

 |  | £--£-£
 |  | £$$£$£ |  |  | 5
 |  | -£$£$£ |  |  | 6
 |  | £$$£$£ |  |  | 2
 |  | -£$£$£ |  |  | 2 |  |  | The previous occurrence of C13 is in C7.
 |  | £$-+++ |  |  | 9
 |  | +--++£ |  |  | 10
 |  | £--£-£ |  |  | 11
 |  | +-+++£ |  |  | 12
 |  | £$$£$£ |  |  | 6
 |  | £--£-£ |  |  | 3 |  |  | In the list, the first duplicate of the value in C15 is in C8. So I would like to receive 7. There might be many duplicates
 |  | -£$£$£ |  |  | 7 |  |  | but I am interested in the first duplicate value checking the list backwards
 |  | £££$$£ |  |  | 16
 |  |  |  |  |  |  |  | If there are no duplicates. I'd like to get the number of the row the value. For example, there is no duplicate of
 |  |  |  |  |  |  |  | the value in C18 so I would like to get 18 as this is the first time this value appears on the list
Spreadsheet: 834339d1687695405-modify-formula-to-handle-positive-and-negative-values-different-book1
Sheet: Sheet1

 | F9 | H9 | J
=IF cell F9<0, and if cell H9<0=(H9-F9)-J) | -4 | -11 | 2
=IF cell F9>0, and if cell H9>0=(H9-F9)-J) | 4 | 11 | 2
=IF cell F9<0, and if cell H9>0=(H9+F9)-J) | -4 | 11 | 2
=IF cell F9>0, and if cell [NAME]) | 4 | -11 | 2
 |  |  |  |  | -4 |  | 11 |  | 2
Spreadsheet: 99895d1298425102-tracking-income-and-invoices-for-projects-multiple-search-results-test-project-trackingvera
Sheet: July 2010

 | Income and Expense Report |  |  |  |  |  |  | NO
 |  | 2010-07-01 00:00:00 |  |  |  |  |  | YES
 |  |  |  |  |  |  |  | N/A
 |  | -190.58 | LOSS
 | Date | Payment Type | Reference / Debtor No. | Supplier Invoice Number | Income  ($) | Purchasing Property | Total Invoice Costs ($) | MAC | GN | HF | BM | Comments
 |  |  |  |  | 0 | -190.58 | 190.58 | 0 | 0 | 190.58 | 0
 | 2010-07-13 00:00:00 | Invoice Only | fA235292 | 40484 |  | [NAME] | 12.96 |  |  | 12.96
 | 2010-07-06 00:00:00 | Invoice Only | fA235292 | 40441 |  | [NAME] | 33.17 |  |  | 33.17
 | 2010-07-12 00:00:00 | Invoice Only | fA235292 | 40476 |  | [NAME] | 92.75 |  |  | 92.75
 | 2010-07-01 00:00:00 | Invoice Only | fA147959 | 40425 |  | Hickford | 23.32 |  |  | 23.32
 | 2010-07-01 00:00:00 | Invoice Only | fA72494 | 40425 |  | [NAME] | 23.32 |  |  | 23.32
 | 2010-07-01 00:00:00 | Invoice Only | fA145521 | 40425 |  | Symons | 5.06 |  |  | 5.06
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  |  |  |  |  |  | 0
 |  | PIF-ROW
 |  | Initial Instal'
 |  | Instalment
 |  | Final Instal'
 |  | Invoice Only
 |  | Other
Spreadsheet: 852340d1702401407-formula-to-generate-a-to-z-if-the-qty-is-entered-sample
Sheet: Sheet1

No | Item | Qty
 |  | 1
 |  | 2
 |  | 3
 |  | 4
 |  | 5
 |  | 6
 |  | 7
 |  | 8
 |  | 9
 |  | 1
 |  | 1
Spreadsheet: 173139d1344446526-find-lowest-score-and-match-to-person-from-list-book1
Sheet: Sheet1

GOLFER | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | total
[NAME] | 4 | 5 | 6 | 5 | 2 | 6 | 1 | 8 | 1 | 8 | 2 | 9 | 1 | 8 | 8 | 2 | 1 | 8 | 85
[NAME] | 5 | 5 | 9 | 4 | 3 | 7 | 2 | 7 | 2 | 7 | 3 | 8 | 2 | 7 | 7 | 5 | 2 | 7 | 92
[NAME] | 3 | 6 | 3 | 6 | 4 | 4 | 3 | 6 | 3 | 6 | 4 | 7 | 3 | 6 | 9 | 6 | 3 | 6 | 88
fred | 2 | 4 | 5 | 7 | 5 | 9 | 4 | 5 | 4 | 5 | 5 | 6 | 4 | 5 | 3 | 8 | 4 | 5 | 90
 |  |  | PLACE | 1 | 2 | 3 | 4
 |  |  | SCORE | 85 | 88 | 90 | 92
 |  |  | GOLFER | ? | ? | ? | ?
Spreadsheet: 017a395b-425c-4fce-8526-867f69a8dc1d
Sheet: masked_enroll

DIST_OF_RES_IRN | Enrolled1 | Enrolled2 | Enrolled3 | ORG_NM
043489 | 255 | 158 | 321 | Akron City
043497 | <10 | <10 | 13 | Alliance City
043513 | <10 | <10 | 43 | Ashtabula Area City
043711 | 51 | 43 | 126 | Canton City
043752 | 1032 | 623 | 1671 | Cincinnati City
043794 | 32 | <10 | <10 | Cleveland Heights-University Heights City
043802 | 667 | 525 | 1660 | Columbus City School District
043844 | 404 | 309 | 1100 | Dayton City
043901 | 61 | 33 | 45 | East Cleveland City School District
043919 | 16 | <10 | 40 | East Liverpool City
043943 | <10 | <10 | 13 | Elyria City Schools
043950 | 172 | 39 | 367 | Euclid City
044222 | 39 | 52 | 159 | Lima City
044263 | 167 | 94 | 166 | Lorain City
044297 | 13 | 43 | 335 | Mansfield City
044305 | 74 | 59 | 16 | Maple Heights City
044339 | 27 | 22 | 36 | Marion City
044404 | 95 | 51 | 45 | Middletown City
044412 | <10 | 12 | 95 | Mt Healthy City
044669 | <10 | 28 | 52 | Portsmouth City
044677 | <10 | <10 | <10 | Princeton City
044743 | <10 | <10 | 44 | Sandusky City
044800 | 19 | 15 | 29 | South-Western City
044818 | 146 | 104 | 325 | Springfield City
044909 | 550 | 374 | 992 | Toledo City
044990 | 53 | 60 | 17 | Warren City
045005 | 85 | 31 | 88 | Warrensville Heights City
045070 | 26 | <10 | <10 | Whitehall City
045161 | 211 | 225 | 368 | Youngstown City Schools
045179 | 31 | <10 | <10 | Zanesville City
046979 | <10 | <10 | 46 | [NAME]
048686 | 13 | 14 | 52 | Jefferson Township Local
048694 | 11 | <10 | 19 | Trotwood-Madison City
049288 | <10 | <10 | <10 | Preble Shawnee Local
050013 | <10 | <10 | <10 | [NAME]
050195 | <10 | <10 | 111 | Liberty Local
Spreadsheet: 37439d1235466562-match-and-delete-matchdelete
Sheet: Sheet1

A | AA | AAA |  | AAAAAA | A | AA | AAA
B | AA | AAA |  | BAAAAA | B | AA | AAA
A | BB | AAA |  | ABBAAA | A | BB | AAA
A | AA | BBBB |  | AAABBBB | A | AA | BBBB
A | AA | AAA |  | AAAAAA
B | AA | AAA |  | BAAAAA
A | BB | AAA |  | ABBAAA
A | AA | BBBB |  | AAABBBB
A | AA | AAA |  | AAAAAA
B | AA | AAA |  | BAAAAA
A | BB | AAA |  | ABBAAA
A | AA | BBBB |  | AAABBBB
Spreadsheet: 135411d1326035850-refreshing-pivot-table-data-example
Sheet: data

Client | Country | Amount
v0008 | greece | 13478
v0012 | germany | 6
v0009 | brazil | 1
v0017 | germany | 9927
v0013 | denmark | 123
v0009 | greece | 6639
v0019 | brazil | 5
v0019 | greece | 2
v0019 | brazil | 2
v0004 | netherlands | 1386
v0009 | brazil | 19887
v0009 | greece | 6845
v0009 | sweden | 9552
v0012 | canada | 22013
v0017 | germany | 9858
v0019 | greece | 7
v0009 | brazil | 18606
v0013 | germany | 249
v0013 | sweden | 202
v0008 | canada | 3462
v0013 | netherlands | 332
v0010 | sweden | 1227
v0008 | netherlands | 33208
v0012 | canada | 22877
v0017 |  | 31
v0012 | canada | 22026
v0019 | greece | 1
v0009 | brazil | 19044
v0004 |  | 1
v0004 | netherlands | 1338
v0008 | canada | 3605
v0014 | denmark | 1
v0018 | germany | 0
v0004 | sweden | 1286
v0017 | germany | 9743
v0008 | canada | 3410
v0004 | netherlands | 1386
v0008 | sweden | 27792
v0012 | germany | 3
v0013 | denmark | 125
v0001 | australia | 1
v0010 | sweden | 1162
v0008 | netherlands | 33033
v0009 | germany | 27697
v0008 | norway | 8919
v0008 | sweden | 27739
v0008 | netherlands | 33303
v0004 | sweden | 1323
v0019 | brazil | 2
v0013 | sweden | 231
v0008 | norway | 8848
v0009 | greece | 6683
v0012 | sweden | 1
v0009 | sweden | 9063
v0012 | bulgaria | 11483
v0012 | germany | 10
v0004 | sweden | 1357
v0012 | bulgaria | 11276
v0013 | germany | 209
v0017 | germany | 10284
v0009 | sweden | 9173
v0010 | sweden | 1211
v0014 | netherlands | 3
v0004 | netherlands | 1358
v0013 | denmark | 122
v0012 |  | 1
v0008 | sweden | 27901
v0009 | germany | 26143
v0008 | greece | 13046
v0013 | germany | 210
v0009 | sweden | 9187
v0010 |  | 5
v0012 | canada | 22318
v0013 | netherlands | 266
v0009 | brazil | 18849
v0010 | sweden | 1205
v0008 | netherlands | 34593
v0008 | greece | 13036
v0008 | canada | 3477
v0008 | norway | 8804
v0013 | denmark | 139
v0019 | none | 1
v0009 | germany | 26263
v0012 | bulgaria | 11550
v0012 | germany | 6
v0009 | greece | 7054
v0004 | sweden | 1384
v0008 | norway | 9426
v0013 | sweden | 194
v0013 | netherlands | 284
v0019 | greece | 0
v0012 | bulgaria | 11874
v0008 | sweden | 4
v0013 | germany | 215
v0019 | portgueese | 1
v0013 | sweden | 208
v0009 | germany | 26604
v0013 | netherlands | 238
v0008 | sweden | 28749
v0008 | greece | 13278