tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 94884d1294656730-help-needed-agent-stats-tracker-teamstats
Sheet: AM

 |  | [NAME] | Packs Out | Collections | Packs Back | Col % 2 PB | FMP Out | FMP In | Calls Taken | Calls Out | Attendence
 | 2011-01-17 00:00:00 |  |  |  |  | 1
 | 2011-01-18 00:00:00 | 7.5 | 7 | 5 | 4 | 0.8 | 282
 | 2011-01-19 00:00:00 | 7.5 | 7 | 5 | 4 | 0.8 | 1000
 | 2011-01-20 00:00:00 | 7.5 | 7 | 4 | 4 | 1 | 664
 | 2011-01-21 00:00:00 | 7.5 | 5 | 3 | 3 | 1 | 995
 | Weekly Total | 37.5 | 33 | 21 | 19 | 0.9047619047619048 | 3391 | 0 | 0 | 0 | 0
 | 2011-01-24 00:00:00 |  | 7 | 4 | 4 | 1 | 450
 | 2011-01-25 00:00:00 |  | 7 | 5 | 4 | 0.8 | 282
 | 2011-01-26 00:00:00 |  | 7 | 5 | 4 | 0.8 | 1000
 | 2011-01-27 00:00:00 |  | 7 | 4 | 4 | 1 | 664
 | 2011-01-28 00:00:00 |  | 5 | 3 | 3 | 1 | 995
 | Weekly Total |  | 33 | 21 | 19 | 0.9047619047619048 | 3391 | 0 | 0 |  | 0
 | 2011-01-31 00:00:00 |  | 7 | 4 | 4 | 1 | 450
 | 2011-02-01 00:00:00 |  | 7 | 5 | 4 | 0.8 | 282
 | 2011-02-02 00:00:00 |  | 7 | 5 | 4 | 0.8 | 1000
 | 2011-02-03 00:00:00 |  | 7 | 4 | 4 | 1 | 664
 | 2011-02-04 00:00:00 |  | 5 | 3 | 3 | 1 | 995
 | Weekly Total |  | 33 | 21 | 19 | 0.9047619047619048 | 3391 | 0 | 0 |  | 0
 | 2011-02-07 00:00:00 |  | 7 | 4 | 4 | 1 | 450
 | 2011-02-08 00:00:00 |  | 7 | 5 | 4 | 0.8 | 282
 | 2011-02-09 00:00:00 |  | 7 | 5 | 4 | 0.8 | 1000
 | 2011-02-10 00:00:00 |  | 7 | 4 | 4 | 1 | 664
 | 2011-02-11 00:00:00 |  | 5 | 3 | 3 | 1 | 995
 | Weekly Total |  | 33 | 21 | 19 | 0.9047619047619048 | 3391 | 0 | 0 |  | 0
 | 2011-02-14 00:00:00 |  | 5 | 4 | 4 | 1
 | 2011-02-15 00:00:00 |  | 7 | 5 | 4 | 0.8
 | Weekly Total |  | 12 | 9 | 8 | 0.8888888888888888 | 0 | 0 | 0 |  | 0
 | Monthly Total |  | 144 | 93 | 84 | 0.9032258064516129 | 13564 | 0 | 0 |  | 0
Spreadsheet: 744968d1629618355-vlookup-n-a-error-naerrorhelp_updated
Sheet: Working

Tree | Dbhob | pole | mProduct | Type | Y20 Value | Y20 DBH | Harvestable? | Product length | Harvestable Pole FV | UH Pole FV | Desired results
10001 | 16.72 | r | 9.5 | pole | 0 | 16.72 | 0 | 9.5 | 0 |  | 43
10005 | 15.72 | r | 12.5 | pole | 0 | 15.72 | 0 | 12.5 | 0 |  | 91
10018 | 12.78 | r | 12.5 | pole | 0 | 12.78 | 0 | 12.5 | 0 |  | 91
10062 | 6.42 | r | 9.5 | pole | 0 | 6.42 | 0 | 9.5 | 0 |  | 43
10066 | 5.57 | r | 12.5 | pole | 0 | 5.57 | 0 | 12.5 | 0 |  | 91
10069 | 5.57 | r | 9.5 | pole | 0 | 5.57 | 0 | 9.5 | 0 |  | 43
10081 | 3.91 | r | 9.5 | pole | 0 | 3.91 | 0 | 9.5 | 0 |  | 43
10092 | 3.1 | r | 14 | pole | 0 | 3.1 | 0 | 14 | 0 |  | 122
10101 | 2.3 | r | 9.5 | pole | 0 | 2.3 | 0 | 9.5 | 0 |  | 43
10104 | 2.3 | r | 9.5 | pole | 0 | 2.3 | 0 | 9.5 | 0 |  | 43
Spreadsheet: 177231d1346239221-set-cell-value-to-another-cell-sensors
Sheet: Std Lists

Sensors | ME Numbers | Color Sensors
Std Part Presence | ME2101 | SPECTRO3-50-FCL |  |  | Color | Sensor Used
18mm Laser (for small parts) | ME2102 | CZ-V21P RGB Digital Amplifier
Diffused, Background Suppressed Mass | ME2103 | CZ-H32 Fiber Head
30mm Unshielded Proximity | ME2107 | CA-H35S Fiber Head
12mm Unshielded Prox (>4mm Range) | ME2106 | X-Rite
12mm Shielded Prox (Metal Screw) | ME2105
30mm BGL | ME2108
Mechanical Flag | ME9102
Spreadsheet: 599443d1543079317-formula-to-update-second-workbook-based-on-todays-date-from-row-in-1st-workbook-workbook-2
Sheet: Sheet1

2018-01-01 00:00:00 | 555
2018-01-02 00:00:00 | 256 |  |  | Data taken from workbook 1
2018-01-03 00:00:00 | 539 |  |  | Cells highlighted in red are expected results which should mirror workbook 1 and updated after every entry
2018-01-04 00:00:00 | 956
2018-01-05 00:00:00 | 458
2018-01-06 00:00:00 | 255
2018-01-07 00:00:00 | 333
2018-01-08 00:00:00 | 964
2018-01-09 00:00:00 | 152
2018-01-10 00:00:00 | 2258
2018-01-11 00:00:00 | 2699
2018-01-12 00:00:00 | 5564
2018-01-13 00:00:00 | 258
2018-01-14 00:00:00 | 555
2018-01-15 00:00:00 | 6632
2018-01-16 00:00:00 | 254
2018-01-17 00:00:00 | 459
2018-01-18 00:00:00 | 523
2018-01-19 00:00:00 | 552
2018-01-20 00:00:00 | 158
2018-01-21 00:00:00 | 2654
2018-01-22 00:00:00 | 222
2018-01-23 00:00:00 | 339
2018-01-24 00:00:00 | 884
2018-01-25 00:00:00 | 158
2018-01-26 00:00:00 | 1522
2018-01-27 00:00:00 | 2222
2018-01-28 00:00:00 | 2325
2018-01-29 00:00:00 | 2365
2018-01-30 00:00:00
2018-01-31 00:00:00
2018-02-01 00:00:00
2018-02-02 00:00:00
2018-02-03 00:00:00
2018-02-04 00:00:00
2018-02-05 00:00:00
2018-02-06 00:00:00
2018-02-07 00:00:00
2018-02-08 00:00:00
2018-02-09 00:00:00
2018-02-10 00:00:00
2018-02-11 00:00:00
2018-02-12 00:00:00
2018-02-13 00:00:00
2018-02-14 00:00:00
2018-02-15 00:00:00
2018-02-16 00:00:00
2018-02-17 00:00:00
2018-02-18 00:00:00
2018-02-19 00:00:00
Spreadsheet: 825526d1681378871-how-to-get-sum-of-rows-where-several-rows-are-empty-in-between-gettotalsumofeachfieldname
Sheet: Sheet1

Field name |  | Total Time par fields |  |  | Fields name | Total Time par fields
Test1 |  |  |  |  | Test1 | 00:00:04
Test2 |  |  |  |  | Test2 | 00:00:02
Test3 |  |  |  |  | Test3 | 00:00:04
Test4 |  |  |  |  | Test4 | 00:00:02
Test5 |  |  |  |  | Test5 | 00:00:00
Test6 |  |  |  |  | Test6 | 00:00:01
[NAME] |  |  |  |  | [NAME] | 00:00:01
Test8 |  |  |  |  | Test8 | 00:00:02
Test9 |  |  |  |  | Test9 | 00:00:01
Spreadsheet: 127229d1320245197-3-month-moving-average-dashboard-forum_sample
Sheet: Sample Report

Drop-down | Month-YYYY
 | Current Month | Previous Month | 3 month MA | Trendline
Global | % completed | % completed | % completed | Sparkline
R1 | % | % | % | Sparkline
R2 | % | % | % | Sparkline
R3 | % | % | % | Sparkline
R4 | % | % | % | Sparkline
 | Current Month | Previous Month | 3 month MA | Trendline
Country 1 | % | % | % | Sparkline
Country 2 | % | % | % | Sparkline
Country 3 | % | % | % | Sparkline
Country 4 | % | % | % | Sparkline
Country 5 | % | % | % | Sparkline
Country 6 | % | % | % | Sparkline
Country 7 | % | % | % | Sparkline
Country 8 | % | % | % | Sparkline
Country 9 | % | % | % | Sparkline
Country 10 | % | % | % | Sparkline
Country 11 | % | % | % | Sparkline
Country 12 | % | % | % | Sparkline
Country 13 | % | % | % | Sparkline
Country 14 | % | % | % | Sparkline
Country 15 | % | % | % | Sparkline
Country 16 | % | % | % | Sparkline
Country 17 | % | % | % | Sparkline
Country 18 | % | % | % | Sparkline
Country 19 | % | % | % | Sparkline
Country 20 | % | % | % | Sparkline
Country 21 | % | % | % | Sparkline
Country 22 | % | % | % | Sparkline
Country 23 | % | % | % | Sparkline
Country 24 | % | % | % | Sparkline
Country 25 | % | % | % | Sparkline
Country 26 | % | % | % | Sparkline
Country 27 | % | % | % | Sparkline
Country 28 | % | % | % | Sparkline
Country 29 | % | % | % | Sparkline
Country 30 | % | % | % | Sparkline
Country 31 | % | % | % | Sparkline
Country 32 | % | % | % | Sparkline
Country 33 | % | % | % | Sparkline
Spreadsheet: 112271d1308385836-excel-2007-fill-numbers-between-two-colums-dummu-file
Sheet: DATA EXTRACTED

VPL |  | BANGLORE |  | RP
CS-1234 | CS-1252 | CS-1270 | CS-1288
CS-1235 | CS-1253 | CS-1271 | CS-1289
CS-1236 | CS-1254 | CS-1272 | CS-1290
CS-1237 | CS-1255 | CS-1273 | CS-1291
CS-1238 | CS-1256 | CS-1274 | CS-1292
[NAME] | CS-1257 | CS-1275 | CS-1293
CS-1240 | CS-1258 | CS-1276 | CS-1294
CS-1241 | CS-1259 | CS-1277 | CS-1295
CS-1242 | CS-1260 | CS-1278 | CS-1296
CS-1243 | CS-1261 | CS-1279 | CS-1297
CS-1244 | CS-1262 | CS-1280 | CS-1298
CS-1245 | CS-1263 | CS-1281 | CS-1299
CS-1246 | CS-1264 | CS-1282
CS-1247 | CS-1265 | CS-1283
CS-1248 | CS-1266 | CS-1284
CS-1249 | CS-1267 | CS-1285
CS-1250 | [NAME] | CS-1286
[NAME] | CS-1269 | CS-1287
 | TOTAL: 66
 | (SIXTY SIX)
Spreadsheet: 887135d1737301735-assistance-with-comparing-and-identifying-differences-in-excel-match-lay-out
Sheet: new

 | Test Name | Sex | Low Range | High Range | Alert low | Alert High
 | ALB |  | 3.5 | 4.9
 | AST |  | 1 | 35
 | BUN | F | 6 | 23
 | CL |  | 96 | 108
 | CREA | M | 0.7 | 1.3
 | GLUC |  | 60 | 100 | 50 | 500
 | K |  | 3.5 | 5.2 | 2.6 | 6.4
 | NA |  | 135 | 145 | 120 | 155
 | PO4 |  | 2.4 | 4.7 | 1.7 | 10
 | TBIL |  | 0.1 | 1.2 | 0 | 16
 | TCO2 |  | 22 | 30 | 40 | 5
 | CA |  | 8.5 | 10.5 | 6.6 | 12.9
Spreadsheet: 854013d1703967571-pls-provide-me-a-if-function-from-the-group-of-4-numbers-on-last-two-values-2007-book1
Sheet: Sheet1

 |  | UNIT |  |  |  | UNIT |  |  |  | UNIT |  |  |  | UNIT
 |  | -6955 |  |  |  | -6955 |  |  |  | 2410 |  |  |  | -6955
 |  | -4857.5 |  |  |  | -4857.5 |  |  |  | 436.2500000000001 |  |  |  | -4857.5
 |  | -1427.5 |  |  |  | -1427.5 |  |  |  | -6955 |  |  |  | -1427.5
 |  | 2410 |  |  |  | 2410 |  |  |  | -3650 |  |  |  | 2410
 |  | -1520 |  |  |  | 436.25 |  |  |  | -2415 |  |  |  | -3510
 |  | PROBLEM SOLVED |  |  |  | PROBLEM SOLVED
 | (HERE I WANT - POSITIVE INDICATION) BECAUSE ABOVE GROUP OF NUMBERS -1520 NOT COVER 2410 VALUE INDICATE POSITIVE |  |  |  | (HERE I WANT - POSITIVE INDICATION) BECAUSE ABOVE GROUP OF NUMBERS 436.25 VALUE INDICATE POSITIVE ALSO 2410 INDICATE POSITIVE |  |  |  | Negative if formula works well |  |  |  | Negative if formula works well
 |  |  |  |  | I WANT INTO ONE FORMULA
Spreadsheet: 0f8fd283-bd55-4049-b6d3-4b71dfe28aee
Sheet: Table IV.4

Table IV.4 الجدول
Selected Indicators for Air Quality in Egypt
مؤشرات مختارة لقياس نوعية الهواء في مصر
 | 2001 | 2006 | 2007 | 2008
Cost of Environmental Degradation of Air (‘000 US Dollars)a/ | 8856000 | 11881000 | 12721000 | … | كلفة التدهور البيئي للهواء
City Nameb | [NAME] |  |  |  | [NAME]
Annual Mean Concentrations of Sulfur Dioxide (SO2) in Ambient Air in Urban City (µg/m3) | 17.31 | 20.94 | 16.75 | 17.3 | معدل التركز السنوي لثاني أكسيد الكبريت (SO2) في الهواء المحيط في مدينة حضرية
Annual Mean Concentrations of Lead (Pb) in Ambient Air in Urban City (µg/m3) | 0.199 | 0.085 | 0.087 | 0.13 | معدل التركز السنوي للرصاص في الهواء المحيط في مدينة حضرية
Annual Mean Concentrations of Suspended Particulate Matter (<10 µm) (SPM10) in Ambient Air in Urban City (µg/m3)* | 257.61 | 284.99 | 346.35 | 295.95 | معدل التركز السنوي للجسيمات العالقة في الهواء المحيط في مدينة حضرية
City Nameb/ | Greater Cairo |  |  |  | [NAME]
Annual Mean Concentrations of Sulfur Dioxide (SO2) in Ambient Air in Urban City (µg/m3) | 18.9 | 29.3 | 21.06 | 11.05 | معدل التركز السنوي لثاني أكسيد الكبريت(SO2) في الهواء المحيط في مدينة حضرية
Annual Mean Concentrations of Lead (Pb) in Ambient Air in Urban City (µg/m3) | 0.541 | 0.128 | 0.118 | 0.13 | معدل التركز السنوي للرصاص في الهواء المحيط في مدينة حضرية
Annual Mean Concentrations of Suspended Particulate Matter (<10 µm) (SPM10) in Ambient Air in Urban City (µg/m3)* | 348.7 | 466.45 | 582.38 | 545.27 | معدل التركز السنوي للجسيمات العالقة في الهواء المحيط في مدينة حضرية
Sources: | a/ | Egypt in Figures 2010
 | [NAME] | Egypt Annual Statistical Abstract 2010, CAPMAS.
 | * | CAPMAS reply to ESCWA on the preliminary tables for the Compendium of Environment Statistics 2010-2011.
Spreadsheet: 0b9961ed-cef3-47c2-a09b-38f31e6b8601
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3
Cable Diameter Caculator
Type of wire | Diameter of wire(mm) | Number of wires | Cable/Bundle Diameter(mm)
1 |  |  | 0
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Enter the diameter of wire &Number of wire to get the Cable/Bundle diameter.Use only required cells in these two columns & Leave other cells as blank
Above table gives approximate cable diameter.
Spreadsheet: 265223d1379111631-writing-formulas-to-move-data-from-one-worksheet-to-another-userdata
Sheet: MasterSheet

ROW | RANDOM | RANDOM2 | INITIALS | CRITERIA
 | 35 | 64 | MES | sdf
 | 53 | 81 | AJR | g
 | 51 | 77 | AJR | df
 | 57 | 87
 | 34 | 73
 | 31 | 88 | MES | C
 | 60 | 61 | AJR
 | 46 | 85 | AJR | df
 | 56 | 69 |  | dfg
 | 41 | 69 | MES | df
 | 33 | 75 | MES
 | 59 | 73 |  | sdf
 | 49 | 68 |  | sdf
 | 36 | 82 | AJR
 | 58 | 80 |  | f
 | 53 | 75 | MES | gh
 | 48 | 76 |  | sdf
 | 34 | 73 |  | d
 | 59 | 80 | AJR | C
 | 36 | 85 |  | sdf
 | 31 | 73
 | 55 | 78 | MES | sdf
 | 49 | 61 |  | f
 | 38 | 83 |  | sdf
 | 32 | 71
 | 52 | 79 | MES
 | 58 | 61 |  | sdf
 | 53 | 83 | MES | C
 | 45 | 83 | MES | sf
 | 43 | 84 | AJR | df
Spreadsheet: 450660d1457832409-reference-table-from-another-sheet-table-from-other-sheet
Sheet: New Sheet

Name | Company | Sold | Price | Total |  |  |  | Name | Sold
 |  |  |  |  |  |  |  | Name 41 | 1
 |  |  |  |  |  |  |  | Name 89 | 2
 |  |  |  |  |  |  |  | Name 48 | 3
 |  |  |  |  |  |  |  | Name 65 | 4
 |  |  |  |  |  |  |  | Name 50 | 5
 |  |  |  |  |  |  |  | Name 29 | 6
 |  |  |  |  |  |  |  | Name 66 | 7
 |  |  |  |  |  |  |  | Name 88 | 8
 |  |  |  |  |  |  |  | Name 47 | 9
 |  |  |  |  |  |  |  | Name 45 | 10
 |  |  |  |  |  |  |  | Name 57 | 11
 |  |  |  |  |  |  |  | Name 12 | 12
 |  |  |  |  |  |  |  | Name 45 | 13
 |  |  |  |  |  |  |  | Name 83 | 14
 |  |  |  |  |  |  |  | Name 72 | 15
 |  | Col C finds the match in Col I against each cell in Col A, and puts that into Col C
 |  |  |  |  |  |  |  | Col I lists the entries in Col A
 |  |  |  |  |  |  |  |  | Col J is your "new" information
 |  | To "test" the format, sort the orignal sheet into Company order.
Spreadsheet: 216390d1361751736-code-to-generate-a-unique-reference-codenames
Sheet: Sheet1

Emeline | Earlywine | EE1
Chung | [NAME] | CC1
Annetta | Armistead | AA1
[NAME] | Daigle | DD1
Yoko | Yule | YY1
Sasha | [NAME] | SS1
Deana | Dycus | DD2
Elda | Epley | EE2
Sabine | Severns | SS2
Nenita | [NAME] | NN1
[NAME] | Damiano | DD3
[NAME] | Jessee | JJ1
[NAME] | [NAME] | JJ2
Apolonia | Alm | AA2
[NAME] | Ofarrell | OO1
Carolyne | Cerutti | CC2
Leonora | Layfield | LL1
Jalisa | Jorge | JJ3
Jasper | [NAME] | JJ4
Makeda | Michener | MM1
Jetta | [NAME] | [NAME]
Edelmira | Evangelista | EE3
[NAME] | [NAME] | GG1
Eli | Edmond | EE4
Corrin | Cheesman | CC3
Carlota | Czajkowski | CC4
[NAME] | Engels | EE5
[NAME] | Wasielewski | WW1
[NAME] | Ragon | RR1
Tenesha | Toye | TT1
Alissa | Aylor | AA3
[NAME] | Lehto | LL2
Eusebia | Edmunds | EE6
Aja | Alberts | AA4
[NAME] | Manos | MM2
Helaine | Hollinger | HH1
Neva | Neve | NN2
Alisia | Ammann | AA5
Lachelle | Lannon | LL3
Alpha | Abeita | AA6
Cecily | Croghan | CC5
[NAME] | Daigre | DD4
Fatimah | Falgoust | FF1
Caryn | [NAME] | CC6
Sunshine | Scheele | SS3
Paulene | Polizzi | PP1
Meagan | Micco | MM3
[NAME] | Atwell | AA7
Brigette | Boso | BB1
[NAME] | Meisner | MM4
Spreadsheet: 586882d1534707015-formula-add-the-largest-sequence-of-only-consecutive-positive-numbers-from-a4-a20-largest-run-of-pos-numbers-using-helper
Sheet: Sheet1

Numbers | Helper |  | Answer
134
544
-41
-97
434
789
344
871
-45
97
59
91
Spreadsheet: 810606d1671885454-combine-data-in-2-rows-into-1-single-row-afl_data_
Sheet: Output

 | Team Name |  | Result |  | PREPLAY_LAST_TRADED_PRICE |  | PREPLAY_MIN_PRICE |  | PREPLAY_MAX_PRICE |  | INPLAY_MIN_PRICE |  | INPLAY_MAX_PRICE
Date | T1 | T2 | T1 result | T2 result | P_LTP T1 | P_LTP T2 | P_MIN T1 | P_MIN T2 | P_MAX T1 | P_MAX T2 | I_MIN T1 | I_MIN T2 | I_MAX T1 | I_MAX T2
2018-03-03 00:00:00 | Hawthorn | Western Bulldogs | L | W | 2.12 | 1.89 | 2 | 1.67 | 2.46 | 1.89 | 1.64 | 1.05 | 4 | 1.34
 | Collingwood | Hawthorn | W | L | 2.92 | 1.52 | 2.12 | 1.3 | 4.3 | 1.59 | 1.01 | 1.3 | 4.4 | 110
2015-02-27 00:00:00 | Carlton | West Coast Eagles | L | W | 6.8 | 1.16 | 3 | 1.13 | 8.6 | 1.42 | 7.8 | 1.01 | 20 | 1.15
2015-02-28 00:00:00 | [NAME] | Brisbane Lions | L | W | 5.1 | 1.24 | 4 | 1.13 | 8.8 | 1.33 | 1.07 | 3.15 | 1.46 | 4.4
2015-02-28 00:00:00 | Richmond | Western Bulldogs | L | W | 4.8 | 1.24 | 1.99 | 1.22 | 4.8 | 2.06 | 1.08 | 1.34 | 3.5 | 13.5
2015-03-01 00:00:00 | North Melbourne | Adelaide Crows | L | W | 2.14 | 1.78 | 2.1 | 1.35 | 2.42 | 1.87 | 1.2 | 2.42 | 1.7 | 3.15
2015-03-01 00:00:00 | Geelong Cats | Gold Coast Suns | L | W | 1.82 | 2.22 | 1.24 | 2.22 | 1.82 | 3 | 1.01 | 1.45 | 3.15 | 5.2
Spreadsheet: 792959d1661245897-creating-a-results-list-of-multiple-races-results-1-
Sheet: Sheet1

 |  | Plaats | place | Race 2 | Race 3 | Race 4 |  |  | Flag | Race SUM | Rank
 |  | 1 | 147 | 85 | 147 | 85
 |  | 2 | 200 | 7 | 114 | 63 |  |  | 3
 |  | 3 | 7 | 63 | 14 | 133 |  |  | 6
 |  | 4 | 220 | 250 | 19 | 222 |  |  | 7
 |  | 5 | 48 | 133 | 222 | 19 |  |  | 14
 |  | 6 | 14 | 222 | 7 | 1015 |  |  | 19
 |  | 7 | 87 | 113 | 250 | 200 |  |  | 47
 |  | 8 | 1015 | 19 | 85 | 220 |  |  | 48
 |  | 9 | 199 | 87 | 48 | 113 |  |  | 57
 |  | 10 | 63 | 220 | 113 | 87 |  |  | 63
 |  | 11 | 85 | 200 | 63 | 6 |  |  | 85
 |  | 12 | 145 | 2 | 2 | 145 |  |  | 87
 |  | 13 | 19 | 48 | 87 | 1013 |  |  | 113
 |  | 14 | 57 | 960 | 1015 | 960 |  |  | 114
 |  | 15 | 3 | 14 | 960 | 2 |  |  | 133
 |  | 16 | 2 | 147 | 1013 | 47 |  |  | 145
 |  | 17 | 960 | 199 | 145 | 599 |  |  | 147
 |  |  |  |  |  |  |  |  | 199
 |  |  |  |  |  |  |  |  | 200
 |  |  |  |  |  |  |  |  | 220
 |  |  |  |  |  |  |  |  | 222
 |  |  |  |  |  |  |  |  | 250
 |  |  |  |  |  |  |  |  | 599
 |  |  |  |  |  |  |  |  | 960
 |  |  |  |  |  |  |  |  | 1013
 |  |  |  |  |  |  |  |  | 1015
Spreadsheet: 842685d1694695203-extract-data-from-rows-to-column-order-file_1
Sheet: Output

Acct No | Qty | Price
M1 | 2 | 2 |  |  | 2 | 2
M4 | 3 | 1 |  | M4 | 3 | 1
M5 | 2 | 3 |  | M5 | 2 | 3
M2 | 5 | 1 |  | M2 | 5 | 1
M3 | 2 | 6 |  | M3 | 2 | 6
M1 | 3 | 3 |  | M1 | 3 | 3
M2 | 2 | 1 |  | M2 | 2 | 1
M3 | 3 | 1 |  | M3 | 3 | 1
M4 | 1 | 1 |  | M4 | 5 | 1
 |  |  |  | M1 | 1 | 5
 |  |  |  | M4 | 3 | 2
 |  |  |  | x1 | 10 | 10/ea
 |  |  |  | x2 | 11 | 3.73/kg
Spreadsheet: 114847d1310553278-excel-2007-total-numbers-of-specific-text-in-a-row-example
Sheet: Sheet1

REMARKS
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 | TOTAL NUMBERS
Spreadsheet: 106490d1303763576-text-to-columns-rowstocolumns-parsemacros
Sheet: Part 1b

Person | Date | Child1 | Date | Child2 | Date | Child3
[NAME] | 2000-07-01 00:00:00 | billy | 2000-07-10 00:00:00 | [NAME] | 2000-07-14 00:00:00 | [NAME]
[NAME] | 2000-07-02 00:00:00 | jen
[NAME] | 2000-07-03 00:00:00 | [NAME] | 2000-07-11 00:00:00 | doug | 2000-07-15 00:00:00 | britanny
Fred | 2000-07-04 00:00:00 | tom |  |  | 2000-07-12 00:00:00 | zack
Greta | 2000-07-05 00:00:00 | gina |  |  | 2000-07-13 00:00:00 | tina
 |  |  |  |  |  |  | This version allows you to merge down more than one column in a group
 |  |  |  |  |  |  | Press Alt-F8 and run the ReOrganize2 macro
 |  |  |  |  |  |  | If your data has no titles, an even easier
 |  |  |  |  |  |  | macro ParseByColumns2 can be used
Spreadsheet: darrell_schoolcraft__7735__imball0203
Sheet: SoCal

 | 10487 |  | 56697
Day | Measured | Scheduled | Measured | Scheduled
1 | -582808 | -589587
2 | -491131 | -493683
3 | -483505 | -493167
4 | -445803 | -487144
5 | -518969 | -516271
6 | -574375 | -598988
7 | -558264 | -565744
8 | -579105 | -609898
9 | -573367 | -599107
10 | -609561 | -607106
11 | -611554 | -604165
12 | -604577 | -604385
13 | -615104 | -618594
14 | -658471 | -683443
15 | -629597 | -639441
16 | -630498 | -627876
17 | -626075 | -638228
18 | -627066 | -621950
19 | -621466 | -615405
20
21
22
23
24
25
26
27
28
29
30
31
2002-02-28 00:00:00 |  |  |  |  | 78487
2002-03-19 00:00:00
CBS Dollars
 |  |  | 277487
Spreadsheet: 68223d1268759056-sumproduct-with-multiple-criteria-and-dynamic-range-eg-sumproduct2-1
Sheet: Sheet1

Day | Order Date | Products | Type | Price | Change | Change % | Price | Total | Note
2010-03-15 00:00:00 | 2010-03-15 00:00:00 | Steel | Small | 1500 | 11.25 | 0.0075 | 1511.25 | 1511.25
2010-03-15 00:00:00 | 2010-03-15 00:00:00 | Bricks | Medium | 150 | 1.125 | 0.0075 | 151.125 | 151.125
2010-03-15 00:00:00 | 2010-03-15 00:00:00 | Concrete | Large | 900 | 4.5 | 0.005 | 904.5 | 904.5
2010-03-15 00:00:00 | 2010-03-15 00:00:00 | Timber | Medium | 50 | 0.75 | 0.015 | 50.75 | 50.75
2010-03-15 00:00:00 | 2010-03-15 00:00:00 | ►DayTotal |  | 2600 |  |  |  | 2600
2010-03-16 00:00:00 | 2010-03-16 00:00:00 | Plaster | Small | 100 | 0.75 | 0.0075 | 100.75 | 100.75
2010-03-16 00:00:00 | 2010-03-16 00:00:00 | [NAME] | Small | 1050 | 7.875 | 0.0075 | 1057.875 | 1057.875
 |  | Total |  |  |  |  |  | 6376.25
Spreadsheet: 856427d1705670146-cash-flow-help-quote-example-document
Sheet: Sheet1

Quote No | Leads | Client | Estimator | Company (GRBC / SES / Higgins/SHH) | Budget / Estimate quote | Contact Name | Contact Info | Margin | Start Date | Duration | Trade | % likely | Update | Date of Update | Next Action | January | February | March | April | May | June | July | August | September | October | November | December
34428 | Mains Water Pipe Installation - Mechanical | AVD | RC | Projects | 21714.44 |  | 01782 383124 | 0.2165 | January | 4 | M |  | Manager who Response is resigned.  Following up by another Engineer | 2024-01-15 00:00:00
34429 | Mains upgrade |  | RC | Building Services | 50000 |  |  | 0.19 | March | 10 | M | 0.75 |  |  |  |  |  | 20000 | 20000 | 10000
34430 | EICR |  | RC | Sustainable Solutions | 10000 |  |  | 0.18 | May | 3 | M | 0.9 |  |  |  |  |  |  |  | 10000
 | Overall Total:
 | Total: | Projects
 | Total: | Building Services
 | Total: | Sustainable Solutions
 | Total: | SHH
 | Overall Total:
 | Averages
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Overall:
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Electrical
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Mechancial
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Specialist Gas
Spreadsheet: 876536d1723237283-help-with-pulling-in-a-currency-amount-into-a-sentence-in-excel-from-another-cell-excel-help
Sheet: Sheet1

 | Payment Milestones
 | All payments to be made upon confirmed installation percentage of milestone achieved via photos, onsite walks, and turnover of progressive close-out documentation to align with completed scope. Construction (“CX”) Start to be invoiced once NTP is signed. |  |  |  | 1877397.72 | Total FOO
 | Description | Amount |  |  |  | Total Labor
 | Invoice #1  - CX Start - 10% of total cost |  |  |  | 692333.92 | Materials, tax and shipping
 |  |  |  |  |  | CX Start | 0.1
 | Invoice #3 - 10% CX Complete |  |  |  |  | Balance
 | Invoice #4 - 20% CX Complete
 | Invoice #5 - 30% CX Complete |  |  | Carrier Allocation
 | Invoice #6 - 40% CX Complete |  |  | Carrier | Share | %
 | Invoice #7 - 50% CX Complete |  |  | AT&T |  | 0.4936131506932325
 | Invoice #8 - 60% CX Complete |  |  | TMO |  | 0
 | Invoice #9 - 70% CX Complete |  |  | VERIZON |  | 0.5063868493067673
 | Invoice #10 - 80% CX Complete |  |  | Total
 | Invoice #11 - 90% CX Complete
 | Invoice #12 - 100% CX Complete
 | Invoice #13 - 10% Retention on 100% CX Complete
 | Total
Spreadsheet: 104598d1302133555-summarizing-countif-data-for-help-forum
Sheet: Sheet1

028594 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028688
028595 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028694
028596 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028695
028600 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028697
028601 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028698
028602 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028720
028603 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028721
028604 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028732
028605 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028733
028607 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028736
028612 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028737
028613 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028744
028617 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028601
028618 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028746
028619 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028747
028625 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028748
028627 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028753
028629 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028605
028632 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028760
028633 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028765
028635 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 028635