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C 21/03/19 C 72.000 |
into 4 new column where my assetype(another column containing values equity,option)=equity
Solved! Go to Solution.
Please try to add 2 new columns:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WclYwMtQ3MNY3tFRwVjA30jMwUNJRctXxV4rViVZy93WFShuYAqWNzE1R5b1dQRwwMyTYxxFhVICCqYGBAapiR9+gYIjyWAA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Column1 = _t, Column2 = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Column1", type text}, {"Column2", type text}}),
#"Added Custom" = Table.AddColumn(#"Changed Type", "Custom", each Text.BeforeDelimiter([Column1], " ")),
#"Added Custom1" = Table.AddColumn(#"Added Custom", "Custom.1", each Text.BetweenDelimiters([Column1], " ", ".", 2, 1))
in
#"Added Custom1"
Please try to add 2 new columns:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WclYwMtQ3MNY3tFRwVjA30jMwUNJRctXxV4rViVZy93WFShuYAqWNzE1R5b1dQRwwMyTYxxFhVICCqYGBAapiR9+gYIjyWAA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Column1 = _t, Column2 = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Column1", type text}, {"Column2", type text}}),
#"Added Custom" = Table.AddColumn(#"Changed Type", "Custom", each Text.BeforeDelimiter([Column1], " ")),
#"Added Custom1" = Table.AddColumn(#"Added Custom", "Custom.1", each Text.BetweenDelimiters([Column1], " ", ".", 2, 1))
in
#"Added Custom1"
@PoojaTekriwal , In power query, ISe split option right click of column Based on Space in new 4 columns
refer my Video: https://www.youtube.com/watch?v=FyO9Vmhcfag
or
https://www.tutorialgateway.org/how-to-split-columns-in-power-bi/
My requirement is that i want to split my first column when my fifth column value is option,equity otherwise no split
Hello @PoojaTekriwal ,
I am not sure its possible to split column with condition. But you can filter the value on the column and then split the column. But that will skipped the other data. I am not sure whether you will get the desired result you want.
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