tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 33496d1229951025-modelling-sample-document
Sheet: Sheet1

Client ID | Name | Latitude | longitude | Daily Probability | Notes
1 |  | 53.875 | -1.915 |  | The base in Keighley
2 | Dal Pescatore Restaurant | 53.870022108399 | -1.895254247292 | 0.025
3 | Lamb & Flag | 53.870812797935 | -1.900298365258 | 0.02
4 | The Cricketers | 53.875864376805 | -1.885532660256 | 0.05
5 | The Bell | 53.87294610127 | -1.86568701944 | 0.025
6 | Three Castles | 53.872648530802 | -1.896493313269 | 0.02
7 | The Brewers and the Vinters | 53.86822879155 | -1.887992703166 | 0.03
8 | The Crofters | 53.870711433975 | -1.908542960977 | 0.005
9 | The [NAME] and Crown | 53.86564752009 | -1.888048244488 | 0.025
10 | Per Se Restaurant | 53.864669229234 | -1.900975912421 | 0.015
11 | The Barney Hotel | 53.861345357966 | -1.885528038093 | 0.03
12 | The Drapers | 53.861308195841 | -1.897181071201 | 0.02
 |  |  |  |  |  |  | This is a sample from one of the workbooks. It shows us the location of the client and the probability that the service will need to be provided to the client. The question asks to design and construct a model to simulate deail patterns of  the service activity. We have to use a random process for generating the demand. High marks go to models which are well designed and structured, have clarity, are intuitive to use, are flexible and are not overly complex. We have been told that the average is estimated at around four call outs per day.
 |  |  |  |  |  |  | Techniques we have been taught; use of functions, recording of macros and basic VBA alterations
 |  |  |  |  |  |  | I have produced a very simple model, shown below, which I feel is  too simple and doesn't give the correct answer as the next question is to produce a histogram showing of the data for a 100, or so, days. With my model there will be lots of 0's and a few very high numbers thereby not producing a histogram! A running of the simulation 100 times produces the results shown in cells A28:128
Demand Simulation
Demand |  |  | This is the random demand
Number of Locations to Visit |  |  | This shows the number of locations which are greater than the random demand
 |  |  |  |  |  |  | What am I looking for?
 |  |  |  |  |  |  | How would you produce a model to answer such a question? I'm stuck and have produced a pretty crap answer I feel.
Day | Callouts |  | Average
1 | 0
2 | 0
3 | 0
4 | 0
5 | 0
6 | 0
7 | 0
8 | 0
9 | 0
10 | 0
11 | 0
12 | 0
13 | 0
14 | 0
15 | 0
16 | 0
17 | 0
18 | 0
19 | 0
20 | 0
21 | 0
22 | 0
23 | 0
24 | 0
25 | 0
26 | 0
27 | 0
28 | 0
29 | 0
30 | 0
31 | 0
32 | 14
33 | 0
34 | 0
35 | 0
36 | 0
37 | 0
38 | 0
39 | 0
40 | 0
41 | 0
42 | 0
43 | 45
44 | 0
45 | 0
46 | 0
47 | 0
48 | 0
49 | 204
50 | 106
51 | 0
52 | 0
53 | 0
54 | 0
55 | 0
56 | 0
57 | 0
58 | 0
59 | 0
60 | 0
61 | 0
62 | 0
63 | 0
64 | 0
65 | 0
66 | 0
67 | 0
68 | 0
69 | 0
70 | 0
71 | 0
72 | 0
73 | 0
74 | 0
75 | 0
76 | 0
77 | 0
78 | 0
79 | 0
80 | 0
81 | 0
82 | 175
83 | 0
84 | 0
85 | 0
86 | 0
87 | 0
88 | 0
89 | 0
90 | 0
91 | 0
92 | 0
93 | 0
94 | 0
95 | 0
96 | 3
97 | 0
98 | 0
99 | 0
100 | 0
Spreadsheet: dan_hyvl__4717__Clark County Master Physical worksheet 01112001
Sheet: AMASTPSA 

MASTER FIRM PURCHASE/SALE AGREEMENT INFORMATION SHEET
ENA Entity: | ENA | ATTORNEY: | [NAME]
DATE: | 2001-01-11 00:00:00 | ENA CONTACT: | [NAME]
COUNTERPARTY: | Public Utility District No. 1 of Clark County | CONTACT:
ADDRESS: | P.O. Box 8900 | TITLE:
 | Vancouver, WA 98668 | PHONE:
 |  | FAX:
INCORPORATION STATE: |  | S&P RATING: | A+ (Underlying Rating)
STRUCTURE | COUNTERPARTY | ENA ENTITY
COLLATERAL
THRESHOLD  in $ | Not Applicable | Not Applicable
COMMITTED VOLUMES
THRESHOLD in $[NAME] | N/A | N/A
COLLATERAL REQUIRED FOR:
ALL TRADES
OTHER | N/A | N/A
COLLATERAL TYPE
Letter of Credit | OK | OK
Cash | OK | OK
COLLATERAL  MULTIPLE | 250000 | 250000
GUARANTOR (RATING) | N/A | Enron Corp. (BBB+)
LIMIT in $[NAME] |  | 10000000
Incorporation State: |  | OR
MATERIAL ADVERSE CHANGE TRIGGERS  APPLY TO:
-Counterparty | X
-Guarantor |  | X
Debt Ratings Change | X | X
-Below = | A- (S&P) or A3 (Moody's) | BBB- (S&P) | The MACs for the CP measures
Financial Covenants | X |  | the CPs "Underlying Rating"
-Funded Debt/Net Worth | > 2:1 |  | whereas Enron Corp. is measured
-Minimum Net worth | < $100,000,000 |  | against its "Senior, Unsecured
-EBITDA/Interest |  |  | Debt Rating."
-Current Ratio
Non-Specific
-Unilateral
Ownership Change
-Less than 51% owned by:
Non-Standard Definitions
-Funded Debt
-Net Worth
-Cash Flow
EVENTS OF DEFAULT
3rd party debt | X | X
-Counterparty | 10000000
-Guarantor ($[NAME]) |  | 100000000
FIN'L STATEMENTS
-Standard | X | X | Upon request
CREDIT DECISION: | APPROVED:  X | DECLINED:
OUTSTANDING PHYSICAL TRADES: |  | YES: | NO:  X
ALL TRADES TO ROLL UP UNDER NEW MASTER: |  | YES:    X | NO:
OTHER COMMENTS
CREDIT REVIEW  PREPARED BY: |  | [NAME] | Ext. 53923
Spreadsheet: 229008d1366280871-autocomplete-form-purchase-order-form
Sheet: Order Form

ETAVONI LIMITED
Unit A Wellsway Works  Wells Road
Radstock  BA3 3RZ
TEL: 01761 420774  FAX:  01761 434459
[NAME]:  [EMAIL]  Website: www.etavoni.com
PURCHASE ORDER
NAME: | Habasit |  |  |  | ORDER NO.
ADDRESS: |  |  |  |  | DATE:
 |  |  |  |  | RAISED BY:
 |  |  |  |  | B LIST N°:
 |  |  |  |  | [NAME]: | YES/NO/DK
TEL:
FAX: |  |  |  |  | PAYMENT METHOD:
EMAIL: |  |  |  |  | On Account | YES
CONTACT: |  |  |  |  | Credit Card
DELIVERY ADDRESS (if different from above): |  |  |  |  | Cheque N°
[NAME]. | Qty Del. | [NAME]. |  | Job N°. | Unit Price £ | Total Price £
* DELIVERY CHARGE WHERE APPLICABLE
Registered in England & Wales - Reg No. 5228818 |  |  |  |  | Total Excl VAT
Reg Address: [NAME], Broadway, Chilcompton, Somerset BA3 4JW |  |  |  |  | VAT @ 20%
VAT Number: 850 4574 26 |  |  |  |  | Total Incl VAT
Spreadsheet: andy_zipper__206__DYNEGY-ICE VOL May24
Sheet: DD-Lookup

Dynegy DIrect
User Lookup
ENA |  |  | EPM |  |  | EGL |  |  | Count of Transaction ID
User Name | Real Name |  | User Name | Real Name |  | User Name | Real Name |  | Units | Total | DELIVERY | CONV
AFAIRLEY | [NAME] |  | CDEANEPM | [NAME] |  | AGROSSPHY | [NAME] |  | Barrel | 14 | Monthly
AGOSALIA | [NAME] |  | DBAUGHMANPHY | [NAME] |  | EGLSTHOM | [NAME] |  | Barrel per day | 1
AGROSS | [NAME] |  | EMETOYEREPM | [NAME] |  | LJACKSONPHY | [NAME] |  | Barrel per month | 304 | Monthly
AZIPPER | [NAME] |  | ENAPDADAM | [NAME] |  | WWHICKSPHY | Wade Hicks |  | [NAME] | 7
BGUILMINO | [NAME] |  | ENAPJLAVO | [NAME] |  | 0 | No Activity |  | [NAME] | 36 | Monthly | 42
BHENDRY | Brent Hendry |  | ENAPRHERN | [NAME] |  |  |  |  | GJ | 193
CDEANENA | [NAME] |  | ENAPSHAN | [NAME] |  |  |  |  | IPE mt | 18
CPENNIX | [NAME] |  | ENPSTHOM | [NAME] |  |  |  |  | LME Registered 20 mt LOT | 7
[NAME] | [NAME] |  | ESAIBIEPM | [NAME] |  |  |  |  | LME Registered 25 mt Lot | 502
DBAUGHMAN_PHY | [NAME] |  | GGUPTA_PHY | [NAME] |  |  |  |  | LME Registered 5 mt LOT | 12
DHYVL1 | [NAME] |  | JKINGEPM | [NAME] |  |  |  |  | LME Registered 6 mt Lot | 45
DSAMUELS | [NAME] |  | JSTEPENO_PHY | [NAME] |  |  |  |  | MMBtu | 3061
EMETOYER | [NAME] |  | KTHOMPSONEPM | [NAME] |  |  |  |  | MMBtu/Lots (Options) | 49 |  | 10000
ENECGERMANY | [NAME] |  | MCARSONEPM | [NAME] |  |  |  |  | mt | 2
ENECUILLA | [NAME] |  | NMISRA_PHY | Narsimha Misra |  |  |  |  | MWh | 835
ENEDADAM | [NAME] |  | PMAKKAIEPM | [NAME] |  |  |  |  | MWh (Canada) | 12
[NAME] | [NAME] |  | RSTALFORD_PHY | [NAME] |  |  |  |  | therm | 144
ENEHENDR | [NAME] |  | SPIWETZEPM | [NAME] |  |  |  |  | Thousand Board Feet | 1
ENEJARNO | [NAME] |  | TMAY_PHY | [NAME] |  |  |  |  | (blank)
ENEJMCKA | [NAME] |  | 0 | No Activity |  |  |  |  | IPE Barrels | 6 | Monthly
ENEJOLAV | [NAME] |  |  |  |  |  |  |  | Crack bl/m | 4 | Monthly
ENEJSHAN | [NAME] |  |  |  |  |  |  |  | Grand Total | 5253
ENEJTOWNSEND | [NAME]
ENEJUNEK | [NAME]
ENEMCKAY | [NAME]
ENEPEREI | [NAME]
ENERHERN | [NAME]
ENERING | [NAME]
ENESANDRA | [NAME]
ENESTHOM | [NAME]
ENETHUR | Patrice Mims-Thurston
ENEVVERS | [NAME]
ENEkelli | [NAME]
ESAIBIENA | [NAME]
GGUPTA_FIN | [NAME]
GWHALLEY | [NAME]
JARNOLD | [NAME]
[NAME] | [NAME]
JBELL1 | [NAME]
JKING1 | [NAME]
JLAVORATO | [NAME]
JMASSEY | [NAME]
JMASSEY1 | [NAME]
JSHANKMAN | [NAME]
JSTEPENO_FIN | [NAME]
JTHOME | [NAME]
KMCGOWAN | [NAME]
KTHOMPSON | [NAME]
LHANSEN | [NAME]
LJACKSON | [NAME]
LKITCHEN | [NAME]
MBRIDGES | [NAME]
MCARSONENA | [NAME]
MNETTEL | [NAME]
NMISRA_FIN | Narsimha Misra
PMAKKAIENA | [NAME]
PTHOMASENA | [NAME]
RHERNDON | [NAME]
RJAFRY | [NAME]
RSTALFORD_FIN | [NAME]
RTOMASKI | [NAME]
SPIWETZ | [NAME]
SSEVER | [NAME]
SSHACKLE | [NAME]
TJONES | [NAME]
TKUYKENDALL | Tori Kuykendall
TMAY_FIN | [NAME]
WGRESHAM | [NAME]
WWHICKSFIN | Wade Hicks
ENESTOREY | [NAME]
0 | No Activity
Spreadsheet: 170213d1343210203-if-to-work-when-cell-blank-also-testing
Sheet: Revenue By Client

 |  | Data
Client Name | Partner | Sum of Jan-12 | Sum of Feb-12 | Sum of Mar-12 | Sum of Apr-12 | Sum of May-12 | Sum of Jun-12 | Sum of Jul-12 | Sum of Aug-12 | Sum of Sep-12 | Sum of Oct-12 | Sum of Nov-12 | Sum of Dec-12
#N/A | (blank) | 15000 | 15000 | 15000 | 15000 | 15000 | 15000 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667
Grand Total |  | 15000 | 15000 | 15000 | 15000 | 15000 | 15000 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667 | 31666.66666666667
Spreadsheet: 795928d1663010283-combining-sheets-into-a-master-file-s666-pq-test
Sheet: MJ

Concat | Customer Number | Account Manager | Company Chain | Mode | Product Code | Site | Incoterm
1006TruckSADNLVCIP | 1006 | MJ | AB US | Truck | 123 | NLV | CIP
1021RailSADWYPCIP | 1021 | MJ | A G | Rail | 123 | WYP | CIP
1023RailSADWYPCIP | 1023 | MJ | A G | Rail | 123 | WYP | CIP
1023TruckSADTOLCIP | 1023 | MJ | A G | Truck | 123 | TOL | CIP
1024RailSADWYPCIP | 1024 | MJ | A G | Rail | 123 | WYP | CIP
1070RailSADWYPCIP | 1070 | MJ | Ar G | Rail | 123 | WYP | CIP
Spreadsheet: 46223d1245118840-excel-grid-to-list-headstamps
Sheet: What I Want

*\L\*
HDWM/?(B)/479▲/B
(*-*)
(*-*)
(*-*)
(*/*/*/*)
(297/230)
(Pic of Acorn)
*|*
/3/070/7
/6/027/7
▲\93\45 AUTO
04|59
05|72
12|GA
1943\WΠ\K4
23|73
3/45/OXO/-St
61|90
661|87
71|87
AFF|89
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
BLANK
bxn\52\I
C
C
C
C\J\91
C\J\93
CAC\1943\VII
CAC\40\VII
CAC\42\VII
CAC\44\LV
CAC\44\VII
CAC\57\7
CAC|303
CAC|303
CAC|304
CAC|CHAMPIONSHIP
CLEVER|MIRAGE
D
D.C Co
DAG
DAG
dnh/St+/3/43
[NAME]
[NAME]
[NAME]
[NAME]
DWM/K/431F/K
E
ELEY
ELEY-KYNOCH
ELEY-KYNOCH
Eley-Kynoch|ICI
FC
FC
FC
FC
FEDERAL
FEDERAL
FIOCCHI
FNB
FNB
FRONTIER
G.F.L
G.F.L
GORDON|SYSTEM
GRAF
H
H
H
HORNADY
HORNADY
HORNADY
HORNADY
HORNADY
HORNADY
IMI
IVI\04
[NAME]
[NAME]
K-K
KYNOCH
KYNOCH
KYNOCH
L/C/8/3
L\HORNADY\R
LAPUA
LAPUA
LAPUA
[NAME]
[NAME]
[NAME]
NORMA
NORMA
[NAME]
NORMA
NORMA Re
ODL
[NAME]
[NAME]
PMC
PMC
PMC
PPU
R (in shield)
R\A\42
R\A\42
R·P
R·P
R·P
R·P
REM-UMC
REM-UMC
RG\75\L13A1
R-P
R-P
R-P
R-P
R-P
R-P
R-P
R-P
R-P
R-P
RWS
RWS
S & B
S & B
S & B
S & B
S & B
S&W
SAKO
SAVAGE
SELLIER & BELLIOT
SPEER
SPEER
SUPER
SUPER X
SUPER X
SUPER X
Super-X
T
U
U
Unreadable
Unreadable
Unreadable
V.F.M & OLE LIEGE
W
W I N
W.R.A CO
W.R.A.
W.R.A. Co
W.R.A. CO.
W.R.A. CO.
W.R.A.Co
WCC|71
WEATHERBY
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
WINCHESTER
Winchester
WINCHESTER
WINCHESTER
WINCHESTER
W-W
W-W
W-W SUPER
W-W SUPER
W-W SUPER
W-W SUPER
W-W SUPER
W-W SUPER
W-W SUPER
ZV\69\7.62
ППУ
ППУ
Spreadsheet: 300851d1393588330-in-column-their-are-multiple-cells-with-same-data-but-i-want-last-row-testeidprocess
Sheet: Sheet1

Enrolment_ID | Registrar | EA_Code | Packet_Status
1372100080020420130731162311 | 618 | 1372 | Segmentation
1372100080020420130731162311 | 618 | 1372 | In_Progress
1372100080020420130731162311 | 618 | 1372 | Hold
1372100080020820130801102637 | 618 | 1372 | Segmentation
1372100080020820130801102637 | 618 | 1372 | In_Progress
1372100080021920130801164849 | 618 | 1372 | Segmentation
1372100080021920130801164849 | 618 | 1372 | In_Progress
1372100080021920130801164849 | 618 | 1372 | Completed_with_Print_Letter_Pending
1372100080032320130901143410 | 618 | 1372 | In_Progress
1372100080032320130901143410 | 618 | 1372 | Rejected
Spreadsheet: 151477d1334935129-excel-2007-macro-help-pulling-whole-row-based-on-highest-value-of-a-specific-supplier-number-raw
Sheet: Sheet1

Supplier Number | [NAME] | Ship-to Location Name | PO Billed Amount (US Currency)
54099 | Company 1 | Sweetwater - 861 | 68730.52
10010 | Company 2 | Research - 474 | 64227.48
20178 | Company 3 | North Kansas City - 218 | 9964
44107 | Company 4 | Sweetwater - 861 | 175565.5
16062 | Company 5 | [NAME] - 417 | 18321.6
16062 | Company 5 | Baltimore - 833 | 4587.68
16062 | Company 5 | Bridgeport - 850 | 1590.99
16062 | Company 5 | Detroit - 891 | 1239
16062 | Company 5 | East Chicago - 714 | 13209
16062 | Company 5 | Galena Park - 454 | 4220.79
16062 | Company 5 | Hagersville - 066 | 71076
16062 | Company 5 | Jacksonville - 225 | 8242.98
16062 | Company 5 | Norfolk - 389 | 4889.63
16062 | Company 5 | Plaster City - 301 | 9754
16062 | Company 5 | Rainier - 240 | 5458
16062 | Company 5 | Shoals - 360 | 74854
16062 | Company 5 | Sigurd - 223 | 62750.18
16062 | Company 5 | Sweetwater - 861 | 48692.57
16062 | Company 5 | Walworth - 281 | 129.42
24437 | Company 6 | Chamblee - 215 | 430525.38
10033 | Company 7 | [NAME] - 417 | 1842.77
10033 | Company 7 | Cartersville - 605 | 1059.18
10033 | Company 7 | Clark - 372 | 5262.9
10033 | Company 7 | Fremont - 452 | 314.21
10033 | Company 7 | [NAME] | 5461.06
10033 | Company 7 | South Gate - 847 | 13596.63
10033 | Company 7 | Weirton - 785 | 335.96
Spreadsheet: 148972d1333636232-if-x-contains-y-from-another-sheet-then-lookup-extract
Sheet: Lookup

BROKER | SCHEME NAME (A) | SCHEME NAME (B) | SCHEME NAME (C) | SCHEME NAME (D) | FROM | TO | YEAR OF ACCOUNT
[NAME] | Crystal |  |  |  | 2010-04-01 00:00:00 | 2011-03-31 00:00:00 | 2010
[NAME] | Crystal |  |  |  | 2011-04-01 00:00:00 | 2012-03-31 00:00:00 | 2011
Kelly | Police |  |  |  | 2010-04-01 00:00:00 | 2011-03-31 00:00:00 | 2010
Kelly | Police |  |  |  | 2011-04-01 00:00:00 | 2012-03-31 00:00:00 | 2011
[NAME] | Secondary |  |  |  | 2010-04-01 00:00:00 | 2011-03-31 00:00:00 | 2010
[NAME] | Secondary |  |  |  | 2011-04-01 00:00:00 | 2012-03-31 00:00:00 | 2011
Spreadsheet: 43431d1242112652-formula-to-copy-cell-data-from-another-worksheet-for-a-particular-condition-example
Sheet: 1_1 to 1_20

 | Class | Item # | Color | Area | Sale Date | Date Range
 | A | UPQ456 | Red | East | 2009-01-01 00:00:00 | 1/1-1/20
 | A | UPQ879 | Yellow | Northeast | 2009-01-02 00:00:00 | 1/1-1/20
 | B | MLP789 | Yellow | East Coast | 2009-01-07 00:00:00 | 1/1-1/20
 | B | MLP654 | Orange | East Coast | 2009-01-08 00:00:00 | 1/1-1/20
 | C | QRP879 | Daylight | Central | 2009-01-12 00:00:00 | 1/1-1/20
 | C | QRP546 | Blue | East | 2009-01-13 00:00:00 | 1/1-1/20
 | Total | 6 |  |  |  | 1/1-1/20
 | Extra |  |  |  |  | 1/1-1/20
 | A | UPQ529 | Green | West | 2009-01-03 00:00:00 | 1/1-1/20
 | A | UPQ123 | Blue | West | 2009-01-04 00:00:00 | 1/1-1/20
 | B | MLP754 | Orange | Northeast | 2009-01-09 00:00:00 | 1/1-1/20
 | B | MLP789 | Purple | South | 2009-01-10 00:00:00 | 1/1-1/20
 | C | QRP741 | Silver | Northeast | 2009-01-14 00:00:00 | 1/1-1/20
 | C | #N/A | #N/A | #N/A | #N/A | 1/1-1/20
Spreadsheet: 863373d1710875239-count-number-of-in-a-filtered-column-test
Sheet: TEST

 | Item | Decision | Project  Reference  Number
 | AA1 | Throw | 1 / 58
 | AA2 | Throw | 2 / 58
 | AA3 | Throw | 33
 | AA4 | Throw | 4 / 58
 | AA5 | Throw | 5 / 58
 | AA6 | Throw | 9
 | AA7 | Throw | 10
 | AA8 | Throw | 11
 | AA9 | Throw | 29
 | AA10 | Sell | 30
 | AA11 | Throw | 35
 | AA12 | Throw | 38
 | AA13 | Throw | 41
 | AA14 | Throw | 43
 | AA15 | Throw | 44
 | AA16 | Throw | 46
 | AA17 | Throw | 47
 | AA18 | Keep | 48
 | AA19 | Throw | 49
 | AA20 | Throw | 50
 | AA21 | Throw | 55
 | AA22 | Sell | 57
 | AA23 | Throw | 32 / 75
 | AA24 | Throw | 32 / 76
 | AA25 | Throw | 32 / 77
 | AA26 | Throw | 32 / 78
 | AA27 | Throw | 32 / 79
 | AA28 | Throw | 32 / 80
 | AA29 | Throw | 32 / 81
 | AA30 | Throw | 32 / 98
 | AA31 | Throw | 32 / 99
 | AA32 | Throw | 32 / 100
 | AA33 | Throw | 32 / 101
 | AA34 | Throw | 32 / 102
 | AA35 | Undecided | 110
Spreadsheet: 266469d1379620825-use-selections-from-two-data-validation-lists-to-lookup-and-return-a-combined-result-state-county-fips-codes
Sheet: MISSOURI-24

 | COUNTY | CODE
 | Adair | 1
 | [NAME]
 | Atchison
 | Audrain
 | [NAME]
 | Barton
 | Bates
 | [NAME]
 | Bollinger
 | Boone
 | [NAME]
 | Butler
 | Caldwell
 | Callaway
 | Camden
 | Cape Girardeau
 | Carroll
 | [NAME]
 | [NAME]
 | Cedar
 | Chariton
 | Christian
 | [NAME]
 | Clay
 | [NAME]
 | Cole
 | Cooper
 | Crawford
 | Dade
 | Dallas
 | Daviess
 | DeKalb
 | Dent
 | [NAME]
 | Dunklin
 | Franklin
 | Gasconade
 | Gentry
 | Greene
 | [NAME]
 | [NAME]
 | [NAME]
 | Hickory
 | Holt
 | [NAME]
 | Howell
 | Iron
 | [NAME]
 | Jasper
 | [NAME]
 | [NAME]
 | Knox
 | Laclede
 | Lafayette
 | [NAME]
 | Lewis
 | Lincoln
 | [NAME]
 | [NAME]
 | McDonald
 | Macon
 | [NAME]
 | Maries
 | Marion
 | Mercer
 | [NAME]
 | Mississippi
 | Moniteau
 | Monroe
 | Montgomery
 | Morgan
 | New Madrid
 | Newton
 | Nodaway
 | Oregon
 | Osage
 | Ozark
 | Pemiscot
 | [NAME]
 | Pettis
 | Phelps
 | Pike
 | Platte
 | Polk
 | Pulaski
 | Putnam
 | Ralls
 | Randolph
 | Ray
 | Reynolds
 | Ripley
 | St. Charles
 | St. Clair
 | Ste. Genevieve | 186
 | St. Francois | 187
 | St. Louis
 | St. Louis City | 510
 | Saline | 195
 | Schuyler
 | Scotland
 | Scott
 | Shannon
 | Shelby
 | Stoddard
 | Stone
 | [NAME]
 | Taney
 | Texas
 | Vernon
 | [NAME]
 | Washington
 | Wayne
 | [NAME]
 | Worth
 | [NAME]
Spreadsheet: 803236d1667323418-concatenate-errors-example
Sheet: Sheet1

CONCATENATE | MONTH+YEAR | X | Y | Year | Month | Date 1 | Date 2 |  | Doc number
 |  | [NAME] | 7887000001 | 2022 | 9 | 2022-09-09 00:00:00 | 2022-09-09 00:00:00 | SA | 6100007692
 |  | [NAME] | 7887000001 | 2022 | 9 | 2022-09-28 00:00:00 | 2022-09-28 00:00:00 | SA | 6100008052
 |  | [NAME] | 7887000001 | 2022 | 9 | 2022-09-26 00:00:00 | 2022-09-26 00:00:00 | SA | 6100007966
 |  | [NAME] | 7210070100 | 2022 | 10 | 2022-10-01 00:00:00 | 2022-10-01 00:00:00 | DI | 1900003736
 |  | [NAME] | 7210074000 | 2022 | 10 | 2022-10-01 00:00:00 | 2022-10-01 00:00:00 | DI | 1900003736
 |  | [NAME] | 7210074000 | 2022 | 10 | 2022-10-01 00:00:00 | 2022-10-01 00:00:00 | DI | 1900003736
The RED lines are wrong. For example A7 should be 1900003736102022
Spreadsheet: 182529d1348516273-adding-up-values-per-team-alltime
Sheet: All-Time

 |  |  | Wins | Losses
Spreadsheet: 43364d1242043404-analysing-survel-data-mode-or-count-survey-demo
Sheet: Sheet1

 | 1) | Which is the best spreadsheet
 |  |  | Total | Rank |  | %
 | 1 | Kspread | 5 | 3 |  | 0.2083333333333333
 | 2 | Excel | 8 | 1 | < Most Chosen | 0.3333333333333333
 | 3 | Open Office | 6 | 2 |  | 0.25
 | 4 | [NAME] | 4 | 4 |  | 0.1666666666666667
 | 5 | Ashampoo Office | 1 | 5 | < least Chosen | 0.04166666666666666
Spreadsheet: 770242d1645930730-if-function-why-return-o-input-if
Sheet: CONFIGQ1

 |  | FYP
 |  | Min | [NAME] | Row | BE43 | BT24 | BT25 | BT26 | BT23 | BE04 | BE78 | BN06 | BN07 | BN08 | BE40 | BE82 | BE70 | BE71 | BE72 | BU02 | BU03 | BU04 | BU05
Spreadsheet: 124515d1318449399-conditional-formula-freight-calculation-sheet
Sheet: Sheet2

1.  Enter Quantity needed: |  | 20000
Supplier | Product Type | Size | EH PO# P2006…. | Pc/box | Weight/box | CBM | [NAME] | dw/pcs | Approx Weight/pc (kg) | Quantity | Weight | Dimensional Weight (CBM x1000)
BS | Tubes | 0.1oz | 1744 | 5816 | 11.08 | 0.095
BS | Tubes | 0.5oz | 1914 | 798 | 5.41 | 0.058
Master Tube | Tubes | 0.5oz |  | 3000 |  | 0.2
[NAME] | Tubes | 1oz | 2162 | 4920 | 45 | 0.5
Master Tube | Tubes | 1oz |  | 2880 |  | 0.2
BS | Tubes | 1.7oz | 1991 | 384 | 5.14 | 0.058
Guangzhou | Tubes | 1.7oz | 1855 | 397850 | 1909.6 | 14.679
BS | Tubes | 2oz | 1956 | 270 | 4.6 | 0.058
master [NAME] | Tubes | 2oz |  | 1156 |  | 0.2
BS | Tubes | 2.5oz | 2118 | 324 | 4.4 | 0.076
BS | Tubes | 2.5oz | 2156 | 5120 | 74 | 1.06
BS | Tubes | 3oz | 1741 | 226 | 4.3 | 0.058
BS | Tubes | 4oz | 1781 | 216 | 4.95 | 0.062
[NAME] | Tubes | 4oz | 2162 | 5184 | 127.2 | 1.94
Master Tube | Tubes | 4oz |  | 700 |  | 0.2
BS | Tubes | 5oz | 1913 | 160 | 6.7 | 0.095
CP2 | Tubes | 6oz | 1925 | 285 | 5.1 | 0.09
BS | Tubes | 6oz | 1913 | 160 | 6.7 | 0.095
[NAME] | Tubes | 6oz | 2162 | 5184 | 144 | 2.44
Master Tube | Tubes | 6oz |  | 420 |  | 0.2
BS | Tubes | 8oz | 1782 | 160 | 6.01 | 0.107
2. Enter Dimensional Weight below, calculated above for the size of item you need
From | To | Price |  |  |  |  |  |  |  | Dimensional Weight (CBMx1000) |  | Piece Count | Total Price | Price per Piece
Shenzen | LA / LGB | 100 |  |  |  |  |  |  |  | 327
 | SFO | 140
 | DFW | 140
 | MIA | 175
 | TPA | 180
 | JAX | 180
 | ORL | 178
 | ORD | 150
From | To | Price |  |  |  |  |  |  |  | Dimensional Weight (CBMx1000) |  | Piece Count | Total Price | Price per Piece
Ningbo | LA / LGB | 100
 | SFO | 125
 | DFW | 120
 | MIA | 100
 | TPA | 120
 | JAX | 115
 | ORL | 145
 | ORD | 100
Spreadsheet: eb1f2bbe-0fc5-4f9d-a460-5b450220f6c6
Sheet: pathway

threshold | TP | FP | TN | FN | Pre | Rec | F1 | FPR
0.5 | 0 | 0.16 | 753.38 | 23 | 0 | 0 | 0 | 1
1 | 0 | 0 | 753.54 | 23 | 0 | 0 | 0 | 1
0.4 | 0 | 0.3 | 753.24 | 23 | 0 | 0 | 0 | 1
0.8 | 0 | 0 | 753.54 | 23 | 0 | 0 | 0 | 1
0.1 | 3.28 | 55.1 | 698.44 | 19.72 | 0.0623845778678 | 0.142608695652 | 0.0738070643861 | 0.12981779481
0.3 | 0 | 0.64 | 752.9 | 23 | 0 | 0 | 0 | 1
0.6 | 0 | 0 | 753.54 | 23 | 0 | 0 | 0 | 1
0.2 | 0.54 | 6.9 | 746.64 | 22.46 | 0.0611646886494 | 0.0234782608696 | 0.030031570813 | 0.605942361933
0.9 | 0 | 0 | 753.54 | 23 | 0 | 0 | 0 | 1
0.05 | 11.54 | 241.92 | 511.62 | 11.46 | 0.0485967255777 | 0.501739130435 | 0.0879376397221 | 0.319426077224
0.7 | 0 | 0 | 753.54 | 23 | 0 | 0 | 0 | 1
Spreadsheet: 680426d1591015349-simplest-way-to-filter-dates-date-filters
Sheet: Sheet1

Customer ID | Total Invoiced | date |  |  |  |  | Row Labels | Sum of Total Invoiced
71061 | 5248 | 2020-02-01 00:00:00 |  |  |  |  | Qtr1 | 113761
71183 | 5240 | 2020-02-01 00:00:00 |  |  |  |  | Jan | 45045
72064 | 5323 | 2020-02-03 00:00:00 |  |  |  |  | Feb | 58094
71631 | 5263 | 2020-03-02 00:00:00 |  |  | Quantity |  | Mar | 10622
71840 | 5264 | 2020-05-02 00:00:00 |  | Q1 |  |  | Qtr2 | 62966
71842 | 5280 | 2020-05-02 00:00:00 |  | Q2 |  |  | May | 57663
71844 | 5287 | 2020-05-02 00:00:00 |  |  |  |  | Jun | 5303
71356 | 5303 | 2020-06-02 00:00:00 |  |  |  |  | Qtr3 | 10460
70571 | 5241 | 2020-07-01 00:00:00 |  |  |  |  | Jul | 10460
70775 | 5219 | 2020-07-01 00:00:00 |  |  |  |  | Qtr4 | 26424
70726 | 5266 | 2020-10-01 00:00:00 |  |  |  |  | Oct | 10542
71841 | 5276 | 2020-10-02 00:00:00 |  |  |  |  | Nov | 10544
71432 | 5284 | 2020-11-02 00:00:00 |  |  |  |  | Dec | 5338
71737 | 5260 | 2020-11-02 00:00:00 |  |  |  |  | Grand Total | 213611
72220 | 5338 | 2020-12-03 00:00:00
71693 | 5270 | 2020-02-13 00:00:00
70699 | 6749 | 2020-01-14 00:00:00
72087 | 5307 | 2020-02-14 00:00:00
71843 | 5282 | 2020-02-14 00:00:00
71606 | 6748 | 2020-01-15 00:00:00
70700 | 5256 | 2020-01-15 00:00:00
71062 | 5259 | 2020-01-15 00:00:00
72685 | 5347 | 2020-05-15 00:00:00
72643 | 5320 | 2020-05-15 00:00:00
72650 | 5321 | 2020-05-15 00:00:00
72632 | 5311 | 2020-05-15 00:00:00
72635 | 5312 | 2020-05-15 00:00:00
71839 | 5216 | 2020-02-18 00:00:00
72255 | 5296 | 2020-02-18 00:00:00
71845 | 5295 | 2020-02-18 00:00:00
72273 | 5359 | 2020-03-19 00:00:00
70776 | 5251 | 2020-01-20 00:00:00
71846 | 5302 | 2020-02-20 00:00:00
72738 | 7610 | 2020-05-22 00:00:00
71463 | 5254 | 2020-01-23 00:00:00
71775 | 5315 | 2020-02-25 00:00:00
72737 | 7611 | 2020-05-25 00:00:00
71063 | 5267 | 2020-01-29 00:00:00
71542 | 5261 | 2020-01-31 00:00:00