Converting python code to PowerBI

[Anonymous]

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. However, I cannot find a way to do it.

df.apply(pd.Series.value_counts)

 As an example, I have this dataframe:

When I apply the python code to it, it results in this dataframe:

I would be grateful for any ideas, thank you

[some_bih]

Hi @Anonymous one options to get results like in jupyter cells view outuput for single column

Powerquery, Tab Transform and picture below

[VahidDM · Accepted solution]

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.

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[Anonymous]

Perfect this worked, thank you!