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anonymous123141
Frequent Visitor

Show All Dates one item was sold

Hello,

 

I am having issues listing all dates a particular item sold.

 

The following table represents the data loaded to Power BI via SQL.

 

anonymous123141_0-1652979849839.png

I want to represent quickly all the dates a particular Item was sold.  I am missing something because I can only pull the first date.  I need something like the following.

anonymous123141_1-1652980046851.png

Is there a way to accomplish this in Power BI?  

 

Thanks!

 

 

 

1 ACCEPTED SOLUTION

Hi @anonymous123141 ,

I cannot access your datasource so unfortunately I cannot load any data. However, there couple of mistakes at the end of the script that I can see right away which I have highlighted in red below :

 

let
Source = Sql.Database("ricetec-prod.database.windows.net", "agX-dev"), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"FieldID" = _t, Grower = _t, EventDate = _t, #"ChemUsed" = _t, AppliedRate = _t, Applied Rate Units = _t, #"Acres" = _t, #"App/Rec" = _t, LayerName = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"FieldID", Int64.Type}, {"Grower", type text}, {"EventDate", type text}, {"ChemUsed", type text}, {"Applied Rate", type number}, {"Applied Rate Units", type text}, {"Acres", Int64.Type}, {"App/Rec", type text}, {"LayerName", type text}}),
#"Removed Other Columns" = Table.SelectColumns(#"Changed Type",{"FieldID", "EventDate", "Grower"}),
#"Grouped Rows" = Table.Group(#"Removed Other Columns", {"FieldID #", "Grower"}, {{"Count", each _, type table [#"FieldID #"=nullable number, EventDate=nullable text, ChemUed=nullable text]}}),

in
#"ReplaceValue" #"Grouped Rows"

 

 

Lose the comma at the end of the grouped rows step and the end should be #"Grouped Rows" and not 

#"ReplaceValue"

 

 

Kind regards,

Rohit


Please mark this answer as the solution if it resolves your issue.
Appreciate your kudos! 😊

View solution in original post

5 REPLIES 5
rohit_singh
Solution Sage
Solution Sage

Hi @anonymous123141 ,

 

Thanks for sending across the data. I have a potential solution for you using Power Query.

 

Here is the M-code :

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Customer #" = _t, Warehouse = _t, EventDate = _t, #"Item Name" = _t, Size = _t, UoM = _t, #"Total Amount" = _t, #"App/Rec" = _t, LayerName = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Customer #", Int64.Type}, {"Warehouse", type text}, {"EventDate", type text}, {"Item Name", type text}, {"Size", type number}, {"UoM", type text}, {"Total Amount", Int64.Type}, {"App/Rec", type text}, {"LayerName", type text}}),
    #"Removed Other Columns" = Table.SelectColumns(#"Changed Type",{"Customer #", "EventDate", "Item Name"}),
    #"Grouped Rows" = Table.Group(#"Removed Other Columns", {"Customer #", "Item Name"}, {{"Count", each _, type table [#"Customer #"=nullable number, EventDate=nullable text, Item Name=nullable text]}}),
    #"Added Custom" = Table.AddColumn(#"Grouped Rows", "Custom", each [Count][EventDate]),
    #"Removed Columns" = Table.RemoveColumns(#"Added Custom",{"Count"}),
    #"Added Custom1" = Table.AddColumn(#"Removed Columns", "Custom.1", each List.Distinct([Custom])),
    #"Removed Columns1" = Table.RemoveColumns(#"Added Custom1",{"Custom"}),
    #"Extracted Values" = Table.TransformColumns(#"Removed Columns1", {"Custom.1", each Text.Combine(List.Transform(_, Text.From), " , "), type text}),
    #"Pivoted Column" = Table.Pivot(#"Extracted Values", List.Distinct(#"Extracted Values"[#"Item Name"]), "Item Name", "Custom.1"),
    #"Replaced Value" = Table.ReplaceValue(#"Pivoted Column",null,"",Replacer.ReplaceValue,{"Lava3626", "Flip344", "Jamz22", "Bath344"})
in
    #"Replaced Value"


and here is the result

 

rohit_singh_0-1652985102453.png

 

Kind regards,

Rohit


Please mark this answer as the solution if it resolves your issue.
Appreciate your kudos! 😊

@rohit_singh 

Thank you so very much!  I am coming from a SQL database, it is not working for me.  I have adjusted the code as such.  do you see where I made a mistake?

 

let
Source = Sql.Database("ricetec-prod.database.windows.net", "agX-dev"), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"FieldID" = _t, Grower = _t, EventDate = _t, #"ChemUsed" = _t, AppliedRate = _t, Applied Rate Units = _t, #"Acres" = _t, #"App/Rec" = _t, LayerName = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"FieldID", Int64.Type}, {"Grower", type text}, {"EventDate", type text}, {"ChemUsed", type text}, {"Applied Rate", type number}, {"Applied Rate Units", type text}, {"Acres", Int64.Type}, {"App/Rec", type text}, {"LayerName", type text}}),
#"Removed Other Columns" = Table.SelectColumns(#"Changed Type",{"FieldID", "EventDate", "Grower"}),
#"Grouped Rows" = Table.Group(#"Removed Other Columns", {"FieldID #", "Grower"}, {{"Count", each _, type table [#"FieldID #"=nullable number, EventDate=nullable text, ChemUed=nullable text]}}),

in
#"ReplaceValue"

Hi @anonymous123141 ,

I cannot access your datasource so unfortunately I cannot load any data. However, there couple of mistakes at the end of the script that I can see right away which I have highlighted in red below :

 

let
Source = Sql.Database("ricetec-prod.database.windows.net", "agX-dev"), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"FieldID" = _t, Grower = _t, EventDate = _t, #"ChemUsed" = _t, AppliedRate = _t, Applied Rate Units = _t, #"Acres" = _t, #"App/Rec" = _t, LayerName = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"FieldID", Int64.Type}, {"Grower", type text}, {"EventDate", type text}, {"ChemUsed", type text}, {"Applied Rate", type number}, {"Applied Rate Units", type text}, {"Acres", Int64.Type}, {"App/Rec", type text}, {"LayerName", type text}}),
#"Removed Other Columns" = Table.SelectColumns(#"Changed Type",{"FieldID", "EventDate", "Grower"}),
#"Grouped Rows" = Table.Group(#"Removed Other Columns", {"FieldID #", "Grower"}, {{"Count", each _, type table [#"FieldID #"=nullable number, EventDate=nullable text, ChemUed=nullable text]}}),

in
#"ReplaceValue" #"Grouped Rows"

 

 

Lose the comma at the end of the grouped rows step and the end should be #"Grouped Rows" and not 

#"ReplaceValue"

 

 

Kind regards,

Rohit


Please mark this answer as the solution if it resolves your issue.
Appreciate your kudos! 😊

rohit_singh
Solution Sage
Solution Sage

Hi @anonymous123141 ,

Could you please provide sample data in text format (and not screenshot) so that I might be able to help you with a solution?

Kind regards,

 

Rohit

@rohit_singh 

Thank you.  Here is the data

Spoiler
 
Customer #WarehouseEventDateItem NameSizeUoMTotal AmountApp/RecLayerName
3699Bradshaw5/10/2022Lava362610liters542Recommendation68AAF301-77ED-4688-9A13-106EC575B85E
6594Bradshaw4/8/2022Lava3626500grams27720RecommendationABA16DEC-E9A5-4A6F-9809-4221405D3FB6
558899Bradshaw4/8/2022Lava3626500grams39700RecommendationBBBCB2F5-D98A-4610-9240-54780447423F
4857Bradshaw4/8/2022Lava3626500grams43520RecommendationC5E1C569-5193-4C07-9EEE-7E86B920EF97
3699Bradshaw5/10/2022Flip34415liters812Recommendation68AAF301-77ED-4688-9A13-106EC575B85E
2487RK5/17/2022Jamz22140liters18950RecommendationC68ADF56-15B6-4305-83EA-4228E341AC1C
584574HCC5/17/2022Jamz2210.2liters1258Recommendation1B3BB5A6-D611-4EDD-9485-D80B38A852FC
584574HCC5/17/2022Jamz22320liters39408Recommendation74A96DF4-C80A-4EAA-B3CF-7BD4E8E85328
584574HCC5/17/2022Jamz22320liters39408Recommendation9513779A-CF8E-46A5-80BB-A219C04C5841
6594Bradshaw4/8/2022Jamz22320liters17740RecommendationABA16DEC-E9A5-4A6F-9809-4221405D3FB6
558899Bradshaw4/8/2022Jamz22320liters25408RecommendationBBBCB2F5-D98A-4610-9240-54780447423F
4857Bradshaw4/8/2022Jamz22320liters27854RecommendationC5E1C569-5193-4C07-9EEE-7E86B920EF97
6594Bradshaw4/8/2022Bath3444liters222RecommendationABA16DEC-E9A5-4A6F-9809-4221405D3FB6
558899Bradshaw4/8/2022Bath3444liters318RecommendationBBBCB2F5-D98A-4610-9240-54780447423F
4857Bradshaw4/8/2022Bath3444liters350RecommendationC5E1C569-5193-4C07-9EEE-7E86B920EF97
3699Bradshaw5/10/2022Bath3442liters110Recommendation68AAF301-77ED-4688-9A13-106EC575B85E
3699Bradshaw5/16/2022Lava362610liters542Recommendation68AAF301-77ED-4688-9A13-106EC575B85E
6594Bradshaw5/13/2022Lava3626500grams27720RecommendationABA16DEC-E9A5-4A6F-9809-4221405D3FB6
558899Bradshaw5/13/2022Lava3626500grams39700RecommendationBBBCB2F5-D98A-4610-9240-54780447423F
4857Bradshaw5/13/2022Lava3626500grams43520RecommendationC5E1C569-5193-4C07-9EEE-7E86B920EF97
3699Bradshaw5/16/2022Flip34415liters812Recommendation68AAF301-77ED-4688-9A13-106EC575B85E
2487RK5/19/2022Jamz22140liters18950RecommendationC68ADF56-15B6-4305-83EA-4228E341AC1C
584574HCC5/19/2022Jamz2244liters5420Recommendation1B3BB5A6-D611-4EDD-9485-D80B38A852FC
584574HCC5/19/2022Jamz22320liters39408Recommendation74A96DF4-C80A-4EAA-B3CF-7BD4E8E85328
584574HCC5/19/2022Jamz22320liters39408Recommendation9513779A-CF8E-46A5-80BB-A219C04C5841
6594Bradshaw5/13/2022Jamz22320liters17740RecommendationABA16DEC-E9A5-4A6F-9809-4221405D3FB6
558899Bradshaw5/13/2022Jamz22320liters25408RecommendationBBBCB2F5-D98A-4610-9240-54780447423F
4857Bradshaw5/13/2022Jamz22320liters27854RecommendationC5E1C569-5193-4C07-9EEE-7E86B920EF97
6594Bradshaw5/13/2022Bath3444liters222RecommendationABA16DEC-E9A5-4A6F-9809-4221405D3FB6
558899Bradshaw5/13/2022Bath3444liters318RecommendationBBBCB2F5-D98A-4610-9240-54780447423F
4857Bradshaw5/13/2022Bath3444liters350RecommendationC5E1C569-5193-4C07-9EEE-7E86B920EF97
3699Bradshaw5/16/2022Bath3442liters110Recommendation68AAF301-77ED-4688-9A13-106EC575B85E

 

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