Spreadsheet to access

P

pastorkc

Board Regular
Joined
Jan 29, 2020
Messages
125
Office Version
  1. 2010
Platform
  1. Windows
Anyone know I can get a spreadsheet that is organized one way into an Access database that is setup different. I have attached the spreadsheet and what the data table looks like.

Week Ending:
MONDAYTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM E9423
Total Blue 19400023$ -$ 3.00
MONDAYTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
4:30 PM W1566111
Total Blue 215606111$ -$ 7.50
MONDAYTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM W10721
Total Blue 310702010$ -$ 6.00
MONDAYTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:30 PM W10721
Total Blue 410702010$ -$ 6.00
MONDAYTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:39 PM N/S3223171
Total Red 1322301071$ -$ 19.00
MONDAYTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:40 PM S/N2891621
Total Red 1289016021$ -$ 12.50
Monday Totals
Blue Route4424010154$ -$ 22.50
Red Route6032017092$ -$ 31.50
Special Service
MONDAY TOTAL104560271146$ -$ 54.00
TuesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM E1575111
Total Blue 115705111$ -$ 4.50
TuesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
4:30 PM W1711222
Total Blue 2171102022$ -$ 9.50
TuesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM W981
Total Blue 39801000$ -$ 7.00
TuesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:30 PM W7511
Total Blue 47500011$ -$ 4.00
TuesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:39 PM N/S2915725
Total Red 1291507025$ 16.00
TuesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:40 PM S/N28910153
Total Red 1289010153$ -
Tuesday Totals
Blue Route483108144$ -$ 25.00
Red Route5724017178$ -$ 16.00
Special Service
Tuesday TOTAL1055502521112$ -$ 41.00
WednesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM E195833
Total Blue 119508330$ -$ 5.00
WednesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
4:30 PM W11101
Total Blue 2111001000$ -$ 4.00
WednesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM W122622
Total Blue 312206022$ -$ 1.00
WednesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:30 PM W158232
Total Blue 415802032$ -$ 7.00
WednesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:39 PM N/S322363
Total Red 1322300063$ -$ 20.00
WednesdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:40 PM S/N31247
Total Red 1312400070$ -$ 17.00
Wednesday Totals
Blue Route5725017384$ -$ 17.00
Red Route6347000133$ -$ 37.00
Special Service
Wednesday TOTAL120720173217$ -$ 54.00
ThursdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM E1410121
Total Blue 1141001021$ -$ 9.00
ThursdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
4:30 PM W144415
Total Blue 214404150$ -$ 2.50
ThursdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM W174814
Total Blue 317408140$ -$ 3.50
ThursdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:30 PM W7511
Total Blue 47501010$ -$ 3.50
ThursdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:39 PM N/S4023476
Total Red 1402304076$ -$ 17.00
ThursdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:40 PM S/N40274144
Total Red 1402704144$ -$ 20.50
Thursday Totals3
Blue Route52230142121$ -$ 18.50
Red Route80500811110$ -$ 37.50
Special Service
Thursday TOTAL1327302232311$ -$ 56.00
FridayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM E9612
Total Blue 19601020$ -$ 4.50
FridayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
4:30 PM W11551
Total Blue 211505100$ -$ 3.50
FridayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM W72122
Total Blue 37201022$ -$ 1.50
FridayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:30 PM W178522
Total Blue 417805220$ -$ 5.00
FridayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:39 PM N/S77141611
Total Red 17714010611$ -$ 11.00
FridayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:40 PM S/N2814122
Total Red 12814012020$ -$ 16.00
Friday Totals
Blue Route4421012362$ -$ 14.50
Red Route54280130631$ -$ 27.00
Special Service15
Friday TOTAL113490253693$ -$ 41.50
SaturdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5 PM E322633
Total Blue 1322600033$ -$ 20.00
SaturdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
7:30 AM E0
8:30 AM W0
9:30 AM E0
10:30 AM W0
11:30 AM E0
12:30 PM W0
1:30 PM E0
2:30 PM W0
3:30 PM E0
4:30 PM W0
Total Blue 20000000$ -$ -
SaturdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
8 AM E0
9 AM W0
10 AM E0
11 AM W0
12 PM E0
1 PM W0
2 PM E0
3 PM W0
4 PM E0
5 PM W0
Total Blue 30000000$ -$ -
SaturdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
8:30 AM E0
9:30 AM W0
10:30 AM E0
11:30 AM W0
12:30 PM E0
1:30 PM W0
2:30 PM E0
3:30 PM W0
4:30 PM E0
5:30 PM W0
Total Blue 40000000$ -$ -
SaturdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:39 PM N/S2518124
Total Red 1251800124$ -$ 11.50
SaturdayTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
5:40 PM S/N11542
Total Red 111504020$ -$ 5.00
Saturday Totals
Blue Route322600033$ -$ 20.00
Red Route362304144$ -$ 16.50
Special Service
Saturday TOTAL684904177$ -$ 36.50
WEEKLY TOTALSTotal TripsPax (5-65)Pax <5Senior/DAADA-FlexTransfersPromo/FreeTICKET BOOKSFARE REVENUE
Blue Route277150061103818$ -$ 117.50
Red Route350204059310728$ -$ 165.50
Special Service15000000$ -$ -
Total for Week64235401201314546$ -$ 283.00
 

Attachments

  • Screenshot 2023-07-12 113934.png
    Screenshot 2023-07-12 113934.png
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Use =VLOOKUP(A2,CHOOSE({1,2},$Z$1:$Z$99,$Y$1:$Y$99),2,False) to lookup Y values to left of Z values.
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Typically, what I would do is to create an Excel macro to reformat all the data in the structure needed to import it into Access.
Based on the current structure of your data, that could take a bit of effort.
 
Upvote 0
Joe4 said:
Typically, what I would do is to create an Excel macro to reformat all the data in the structure needed to import it into Access.
Based on the current structure of your data, that could take a bit of effort.
Click to expand...
Yes, that is what I was seeing too. I inherited the spreadsheet. I was just looking to see in anyone with more experience than me had any ideas.
 
Upvote 0
pastorkc said:
Yes, that is what I was seeing too. I inherited the spreadsheet. I was just looking to see in anyone with more experience than me had any ideas.
Click to expand...
I really do not see any other way.
That has always been one of the biggest challenges in working with external data and access - trying to take messy, de-normalized data and import it into Access.
In a perfect world, you would get them to change the format of the data they send you to something more useable, but that is not always possible.
So in those cases, you have to come up with a way to convert it to a useable format.

It can be a cumbersome, painful process to create a data conversion Macro (we used to charge our clients programming time to create one for them if they could not meet our file format), but the good news is it should be a one-time thing and once you complete creating the conversion Macros, you should be able ro re-use them going forward (as long as the data format they send you is consistent).
 
Upvote 0
Joe4 said:
I really do not see any other way.
That has always been one of the biggest challenges in working with external data and access - trying to take messy, de-normalized data and import it into Access.
In a perfect world, you would get them to change the format of the data they send you to something more useable, but that is not always possible.
So in those cases, you have to come up with a way to convert it to a useable format.

It can be a cumbersome, painful process to create a data conversion Macro, but the good news is once you complete creating the conversion Macros, you should be able ro re-use them going forward (as long as the data format they send you is consistent).
Click to expand...
Thank you
 
Upvote 0
With Power Query, I can get you close.
Power Query: 
let
    Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
    #"Added Custom" = Table.AddColumn(Source, "DATE", each if [Total Trips] = "Total Trips" then [MONDAY] else null),
    #"Filled Up" = Table.FillUp(#"Added Custom",{"DATE"}),
    #"Reordered Columns" = Table.ReorderColumns(#"Filled Up",{"DATE", "MONDAY", "Total Trips", "Pax (5-65)", "Pax <5", "Senior/DA", "ADA-Flex", "Transfers", "Promo/Free", "TICKET BOOKS", "FARE REVENUE"}),
    #"Filtered Rows" = Table.SelectRows(#"Reordered Columns", each Text.StartsWith([MONDAY], "Total")),
    #"Split Column by Delimiter" = Table.SplitColumn(#"Filtered Rows", "MONDAY", Splitter.SplitTextByDelimiter(" ", QuoteStyle.Csv), {"MONDAY.1", "MONDAY.2", "MONDAY.3"}),
    #"Removed Columns" = Table.RemoveColumns(#"Split Column by Delimiter",{"MONDAY.1", "MONDAY.3"}),
    #"Grouped Rows" = Table.Group(#"Removed Columns", {"DATE", "MONDAY.2"}, {{"TOTAL TRIPS", each List.Sum([Total Trips]), type number}, {"TOTAL PAX(5-65)", each List.Sum([#"Pax (5-65)"]), type number}, {"TOTAL PAX <5", each List.Sum([#"Pax <5"]), type number}, {"TOTAL SENION/DA", each List.Sum([#"Senior/DA"]), type number}, {"TOTAL ADA FLEX", each List.Sum([#"ADA-Flex"]), type number}, {"TOTAL TRANSFERS", each List.Sum([Transfers]), type number}, {"TOTAL PROMO FEE", each List.Sum([#"Promo/Free"]), type number}, {"TOTAL FARE REVENUE", each List.Sum([FARE REVENUE]), type any}}),
    #"Filtered Rows1" = Table.SelectRows(#"Grouped Rows", each ([DATE] <> null)),
    #"Unpivoted Other Columns" = Table.UnpivotOtherColumns(#"Filtered Rows1", {"DATE", "MONDAY.2"}, "Attribute", "Value"),
    #"Added Custom1" = Table.AddColumn(#"Unpivoted Other Columns", "FARE REVENUE", each if [Attribute] = "TOTAL FARE REVENUE" then [Value] else null)
in
    #"Added Custom1"
DATEMONDAY.2AttributeValueFARE REVENUE
MONDAYBlueTOTAL TRIPS44
MONDAYBlueTOTAL PAX(5-65)24
MONDAYBlueTOTAL PAX <50
MONDAYBlueTOTAL SENION/DA10
MONDAYBlueTOTAL ADA FLEX1
MONDAYBlueTOTAL TRANSFERS5
MONDAYBlueTOTAL PROMO FEE4
MONDAYBlueTOTAL FARE REVENUE22.522.5
MONDAYRedTOTAL TRIPS32
MONDAYRedTOTAL PAX(5-65)23
MONDAYRedTOTAL PAX <50
MONDAYRedTOTAL SENION/DA1
MONDAYRedTOTAL ADA FLEX0
MONDAYRedTOTAL TRANSFERS7
MONDAYRedTOTAL PROMO FEE1
MONDAYRedTOTAL FARE REVENUE1919
TuesdayRedTOTAL TRIPS57
TuesdayRedTOTAL PAX(5-65)24
TuesdayRedTOTAL PAX <50
TuesdayRedTOTAL SENION/DA23
TuesdayRedTOTAL ADA FLEX0
TuesdayRedTOTAL TRANSFERS4
TuesdayRedTOTAL PROMO FEE6
TuesdayRedTOTAL FARE REVENUE28.528.5
TuesdayBlueTOTAL TRIPS48
TuesdayBlueTOTAL PAX(5-65)31
TuesdayBlueTOTAL PAX <50
TuesdayBlueTOTAL SENION/DA8
TuesdayBlueTOTAL ADA FLEX1
TuesdayBlueTOTAL TRANSFERS4
TuesdayBlueTOTAL PROMO FEE4
TuesdayBlueTOTAL FARE REVENUE2525
WednesdayRedTOTAL TRIPS60
WednesdayRedTOTAL PAX(5-65)32
WednesdayRedTOTAL PAX <50
WednesdayRedTOTAL SENION/DA10
WednesdayRedTOTAL ADA FLEX1
WednesdayRedTOTAL TRANSFERS11
WednesdayRedTOTAL PROMO FEE6
WednesdayRedTOTAL FARE REVENUE2020
WednesdayBlueTOTAL TRIPS57
WednesdayBlueTOTAL PAX(5-65)25
WednesdayBlueTOTAL PAX <50
WednesdayBlueTOTAL SENION/DA17
WednesdayBlueTOTAL ADA FLEX3
WednesdayBlueTOTAL TRANSFERS8
WednesdayBlueTOTAL PROMO FEE4
WednesdayBlueTOTAL FARE REVENUE1717
ThursdayRedTOTAL TRIPS71
ThursdayRedTOTAL PAX(5-65)47
ThursdayRedTOTAL PAX <50
ThursdayRedTOTAL SENION/DA4
ThursdayRedTOTAL ADA FLEX0
ThursdayRedTOTAL TRANSFERS14
ThursdayRedTOTAL PROMO FEE6
ThursdayRedTOTAL FARE REVENUE3434
ThursdayBlueTOTAL TRIPS52
ThursdayBlueTOTAL PAX(5-65)23
ThursdayBlueTOTAL PAX <50
ThursdayBlueTOTAL SENION/DA14
ThursdayBlueTOTAL ADA FLEX2
ThursdayBlueTOTAL TRANSFERS12
ThursdayBlueTOTAL PROMO FEE1
ThursdayBlueTOTAL FARE REVENUE18.518.5
FridayRedTOTAL TRIPS117
FridayRedTOTAL PAX(5-65)41
FridayRedTOTAL PAX <50
FridayRedTOTAL SENION/DA5
FridayRedTOTAL ADA FLEX1
FridayRedTOTAL TRANSFERS65
FridayRedTOTAL PROMO FEE5
FridayRedTOTAL FARE REVENUE31.531.5
FridayBlueTOTAL TRIPS44
FridayBlueTOTAL PAX(5-65)21
FridayBlueTOTAL PAX <50
FridayBlueTOTAL SENION/DA12
FridayBlueTOTAL ADA FLEX3
FridayBlueTOTAL TRANSFERS6
FridayBlueTOTAL PROMO FEE2
FridayBlueTOTAL FARE REVENUE14.514.5
SaturdayRedTOTAL TRIPS28
SaturdayRedTOTAL PAX(5-65)14
SaturdayRedTOTAL PAX <50
SaturdayRedTOTAL SENION/DA12
SaturdayRedTOTAL ADA FLEX0
SaturdayRedTOTAL TRANSFERS2
SaturdayRedTOTAL PROMO FEE0
SaturdayRedTOTAL FARE REVENUE1616
SaturdayBlueTOTAL TRIPS32
SaturdayBlueTOTAL PAX(5-65)26
SaturdayBlueTOTAL PAX <50
SaturdayBlueTOTAL SENION/DA0
SaturdayBlueTOTAL ADA FLEX0
SaturdayBlueTOTAL TRANSFERS3
SaturdayBlueTOTAL PROMO FEE3
SaturdayBlueTOTAL FARE REVENUE2020
 
Upvote 0
alansidman said:
With Power Query, I can get you close.
Power Query: 
let
    Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
    #"Added Custom" = Table.AddColumn(Source, "DATE", each if [Total Trips] = "Total Trips" then [MONDAY] else null),
    #"Filled Up" = Table.FillUp(#"Added Custom",{"DATE"}),
    #"Reordered Columns" = Table.ReorderColumns(#"Filled Up",{"DATE", "MONDAY", "Total Trips", "Pax (5-65)", "Pax <5", "Senior/DA", "ADA-Flex", "Transfers", "Promo/Free", "TICKET BOOKS", "FARE REVENUE"}),
    #"Filtered Rows" = Table.SelectRows(#"Reordered Columns", each Text.StartsWith([MONDAY], "Total")),
    #"Split Column by Delimiter" = Table.SplitColumn(#"Filtered Rows", "MONDAY", Splitter.SplitTextByDelimiter(" ", QuoteStyle.Csv), {"MONDAY.1", "MONDAY.2", "MONDAY.3"}),
    #"Removed Columns" = Table.RemoveColumns(#"Split Column by Delimiter",{"MONDAY.1", "MONDAY.3"}),
    #"Grouped Rows" = Table.Group(#"Removed Columns", {"DATE", "MONDAY.2"}, {{"TOTAL TRIPS", each List.Sum([Total Trips]), type number}, {"TOTAL PAX(5-65)", each List.Sum([#"Pax (5-65)"]), type number}, {"TOTAL PAX <5", each List.Sum([#"Pax <5"]), type number}, {"TOTAL SENION/DA", each List.Sum([#"Senior/DA"]), type number}, {"TOTAL ADA FLEX", each List.Sum([#"ADA-Flex"]), type number}, {"TOTAL TRANSFERS", each List.Sum([Transfers]), type number}, {"TOTAL PROMO FEE", each List.Sum([#"Promo/Free"]), type number}, {"TOTAL FARE REVENUE", each List.Sum([FARE REVENUE]), type any}}),
    #"Filtered Rows1" = Table.SelectRows(#"Grouped Rows", each ([DATE] <> null)),
    #"Unpivoted Other Columns" = Table.UnpivotOtherColumns(#"Filtered Rows1", {"DATE", "MONDAY.2"}, "Attribute", "Value"),
    #"Added Custom1" = Table.AddColumn(#"Unpivoted Other Columns", "FARE REVENUE", each if [Attribute] = "TOTAL FARE REVENUE" then [Value] else null)
in
    #"Added Custom1"
DATEMONDAY.2AttributeValueFARE REVENUE
MONDAYBlueTOTAL TRIPS44
MONDAYBlueTOTAL PAX(5-65)24
MONDAYBlueTOTAL PAX <50
MONDAYBlueTOTAL SENION/DA10
MONDAYBlueTOTAL ADA FLEX1
MONDAYBlueTOTAL TRANSFERS5
MONDAYBlueTOTAL PROMO FEE4
MONDAYBlueTOTAL FARE REVENUE22.522.5
MONDAYRedTOTAL TRIPS32
MONDAYRedTOTAL PAX(5-65)23
MONDAYRedTOTAL PAX <50
MONDAYRedTOTAL SENION/DA1
MONDAYRedTOTAL ADA FLEX0
MONDAYRedTOTAL TRANSFERS7
MONDAYRedTOTAL PROMO FEE1
MONDAYRedTOTAL FARE REVENUE1919
TuesdayRedTOTAL TRIPS57
TuesdayRedTOTAL PAX(5-65)24
TuesdayRedTOTAL PAX <50
TuesdayRedTOTAL SENION/DA23
TuesdayRedTOTAL ADA FLEX0
TuesdayRedTOTAL TRANSFERS4
TuesdayRedTOTAL PROMO FEE6
TuesdayRedTOTAL FARE REVENUE28.528.5
TuesdayBlueTOTAL TRIPS48
TuesdayBlueTOTAL PAX(5-65)31
TuesdayBlueTOTAL PAX <50
TuesdayBlueTOTAL SENION/DA8
TuesdayBlueTOTAL ADA FLEX1
TuesdayBlueTOTAL TRANSFERS4
TuesdayBlueTOTAL PROMO FEE4
TuesdayBlueTOTAL FARE REVENUE2525
WednesdayRedTOTAL TRIPS60
WednesdayRedTOTAL PAX(5-65)32
WednesdayRedTOTAL PAX <50
WednesdayRedTOTAL SENION/DA10
WednesdayRedTOTAL ADA FLEX1
WednesdayRedTOTAL TRANSFERS11
WednesdayRedTOTAL PROMO FEE6
WednesdayRedTOTAL FARE REVENUE2020
WednesdayBlueTOTAL TRIPS57
WednesdayBlueTOTAL PAX(5-65)25
WednesdayBlueTOTAL PAX <50
WednesdayBlueTOTAL SENION/DA17
WednesdayBlueTOTAL ADA FLEX3
WednesdayBlueTOTAL TRANSFERS8
WednesdayBlueTOTAL PROMO FEE4
WednesdayBlueTOTAL FARE REVENUE1717
ThursdayRedTOTAL TRIPS71
ThursdayRedTOTAL PAX(5-65)47
ThursdayRedTOTAL PAX <50
ThursdayRedTOTAL SENION/DA4
ThursdayRedTOTAL ADA FLEX0
ThursdayRedTOTAL TRANSFERS14
ThursdayRedTOTAL PROMO FEE6
ThursdayRedTOTAL FARE REVENUE3434
ThursdayBlueTOTAL TRIPS52
ThursdayBlueTOTAL PAX(5-65)23
ThursdayBlueTOTAL PAX <50
ThursdayBlueTOTAL SENION/DA14
ThursdayBlueTOTAL ADA FLEX2
ThursdayBlueTOTAL TRANSFERS12
ThursdayBlueTOTAL PROMO FEE1
ThursdayBlueTOTAL FARE REVENUE18.518.5
FridayRedTOTAL TRIPS117
FridayRedTOTAL PAX(5-65)41
FridayRedTOTAL PAX <50
FridayRedTOTAL SENION/DA5
FridayRedTOTAL ADA FLEX1
FridayRedTOTAL TRANSFERS65
FridayRedTOTAL PROMO FEE5
FridayRedTOTAL FARE REVENUE31.531.5
FridayBlueTOTAL TRIPS44
FridayBlueTOTAL PAX(5-65)21
FridayBlueTOTAL PAX <50
FridayBlueTOTAL SENION/DA12
FridayBlueTOTAL ADA FLEX3
FridayBlueTOTAL TRANSFERS6
FridayBlueTOTAL PROMO FEE2
FridayBlueTOTAL FARE REVENUE14.514.5
SaturdayRedTOTAL TRIPS28
SaturdayRedTOTAL PAX(5-65)14
SaturdayRedTOTAL PAX <50
SaturdayRedTOTAL SENION/DA12
SaturdayRedTOTAL ADA FLEX0
SaturdayRedTOTAL TRANSFERS2
SaturdayRedTOTAL PROMO FEE0
SaturdayRedTOTAL FARE REVENUE1616
SaturdayBlueTOTAL TRIPS32
SaturdayBlueTOTAL PAX(5-65)26
SaturdayBlueTOTAL PAX <50
SaturdayBlueTOTAL SENION/DA0
SaturdayBlueTOTAL ADA FLEX0
SaturdayBlueTOTAL TRANSFERS3
SaturdayBlueTOTAL PROMO FEE3
SaturdayBlueTOTAL FARE REVENUE2020
Click to expand...
Thank you
 
Upvote 0
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