Forum Discussion
Anonymous
2 years agoNot applicable
Converting python code to PowerBI
I have a table in PowerBI which I want to transform using PowerQuery. I am trying to do the PowerQuery equivalent of applying the python function value_counts() to every column in the dataframe. Howe...
- 2 years ago
Hi Anonymous
You can use this code in Power Query, just update the Source:
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WKkvMKU2NN1TSgbKM4CwTOMsUiRWrg08PdnOw6UGwjLGy8NtjjNWV+O3BZiPQbbEA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Day 1" = _t, #"Day 2" = _t, #"Day 3" = _t, #"Day 4" = _t, #"Day 5" = _t]), UnpivotedColumns = Table.UnpivotOtherColumns(Source, {}, "Attribute", "Value"), GroupedRows = Table.Group(UnpivotedColumns, {"Attribute", "Value"}, {{"Count", each Table.RowCount(_), type number}}), #"Pivoted Column" = Table.Pivot(GroupedRows, List.Distinct(GroupedRows[Attribute]), "Attribute", "Count", List.Sum) in #"Pivoted Column"The sample file is attached.
If this post helps, please consider accepting it as the solution to help the other members find it more quickly.
Appreciate your Kudos!!
VahidDM
2 years agoSuper User
Hi Anonymous
You can use this code in Power Query, just update the Source:
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WKkvMKU2NN1TSgbKM4CwTOMsUiRWrg08PdnOw6UGwjLGy8NtjjNWV+O3BZiPQbbEA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Day 1" = _t, #"Day 2" = _t, #"Day 3" = _t, #"Day 4" = _t, #"Day 5" = _t]),
UnpivotedColumns = Table.UnpivotOtherColumns(Source, {}, "Attribute", "Value"),
GroupedRows = Table.Group(UnpivotedColumns, {"Attribute", "Value"}, {{"Count", each Table.RowCount(_), type number}}),
#"Pivoted Column" = Table.Pivot(GroupedRows, List.Distinct(GroupedRows[Attribute]), "Attribute", "Count", List.Sum)
in
#"Pivoted Column"
The sample file is attached.
If this post helps, please consider accepting it as the solution to help the other members find it more quickly.
Appreciate your Kudos!!
Anonymous
2 years agoNot applicable
Perfect this worked, thank you!