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Hello, I have Dataset that keeps track of Client purchases. This DAX code will return 1 for the first time the client occurs in the data. So if the client purchased multiple items in different days. It will return 1 for the first date and 0 for the rest.
Column = IF (
CALCULATE (
COUNTROWS ( Sales ),
FILTER (
ALLEXCEPT ( Sales, Sales[client_id] ),
Sales[date_purchase] <= EARLIER ( Sales[date_purchase] )
)
)
> 1,
0,
1
)
I want to find the same result using Power Query M code. Or find the equivalent M code of this DAX.
Thank you
Regards
Solved! Go to Solution.
Hello @TAZ95 ,
to get a decent performance here in Power Query, I'd recommend to group the table on client_id first and perform a sort/add index on those partitions:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUTLUNdQ1MjA2VorVgQkYAQWMjJAEjBECRtgFjNAFDKECsQA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [client_id = _t, date_purchase = _t]),
#"Changed Type" = Table.TransformColumnTypes(
Source,
{{"client_id", Int64.Type}, {"date_purchase", type date}}
),
#"Grouped Rows" = Table.Group(
#"Changed Type",
{"client_id"},
{{"All", each _, type table [client_id = nullable number, date_purchase = nullable date]}}
),
#"Added Custom" = Table.AddColumn(
#"Grouped Rows",
"Custom",
each Table.AddIndexColumn(
Table.Sort([All], {{"date_purchase", Order.Ascending}}),
"Index",
1,
1
)
),
#"Removed Columns" = Table.RemoveColumns(#"Added Custom", {"All"}),
#"Expanded Custom" = Table.ExpandTableColumn(
#"Removed Columns",
"Custom",
{"date_purchase", "Index"},
{"date_purchase", "Index"}
),
#"Replaced Value" = Table.ReplaceValue(
#"Expanded Custom",
each [Index],
each if [Index] > 1 then 0 else 1,
Replacer.ReplaceValue,
{"Index"}
)
in
#"Replaced Value"
Please paste this code into the advanced editor of a new blank query, replacing all the existing default values in there. Then follow the steps.
Imke Feldmann (The BIccountant)
If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!
How to integrate M-code into your solution -- How to get your questions answered quickly -- How to provide sample data -- Check out more PBI- learning resources here -- Performance Tipps for M-queries
Thanks, It did the work
Hello @TAZ95 ,
to get a decent performance here in Power Query, I'd recommend to group the table on client_id first and perform a sort/add index on those partitions:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUTLUNdQ1MjA2VorVgQkYAQWMjJAEjBECRtgFjNAFDKECsQA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [client_id = _t, date_purchase = _t]),
#"Changed Type" = Table.TransformColumnTypes(
Source,
{{"client_id", Int64.Type}, {"date_purchase", type date}}
),
#"Grouped Rows" = Table.Group(
#"Changed Type",
{"client_id"},
{{"All", each _, type table [client_id = nullable number, date_purchase = nullable date]}}
),
#"Added Custom" = Table.AddColumn(
#"Grouped Rows",
"Custom",
each Table.AddIndexColumn(
Table.Sort([All], {{"date_purchase", Order.Ascending}}),
"Index",
1,
1
)
),
#"Removed Columns" = Table.RemoveColumns(#"Added Custom", {"All"}),
#"Expanded Custom" = Table.ExpandTableColumn(
#"Removed Columns",
"Custom",
{"date_purchase", "Index"},
{"date_purchase", "Index"}
),
#"Replaced Value" = Table.ReplaceValue(
#"Expanded Custom",
each [Index],
each if [Index] > 1 then 0 else 1,
Replacer.ReplaceValue,
{"Index"}
)
in
#"Replaced Value"
Please paste this code into the advanced editor of a new blank query, replacing all the existing default values in there. Then follow the steps.
Imke Feldmann (The BIccountant)
If you liked my solution, please give it a thumbs up. And if I did answer your question, please mark this post as a solution. Thanks!
How to integrate M-code into your solution -- How to get your questions answered quickly -- How to provide sample data -- Check out more PBI- learning resources here -- Performance Tipps for M-queries
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