[FIXED] Calculate percentage Pandas groupby

Issue

I have a Dataframe with 4 columns: 'ID' (clients), 'item', 'tier' (high/low), 'units' (number). Now for each item and each tier I would like to find the total units and how many clients bough at least one item for each tier. I do this with

df.groupby(['item','tier']).agg(
    ID_amount=('ID', 'size'),
    total_units=('units', 'sum'))


item        tier    ID_amount      total_units
100010001   high    83             178,871.00
            low     153            1,450,986.00
100010002   high    722            10,452,778.00
            low     911            5,505,136.00
100020001   high    400              876,490.00
            low     402              962,983.00
100020002   high    4933          61,300,403.00
            low     13759        1,330,932,723.00
100020003   high    15063          176,846,161.00
            low     24905          288,232,057.00

What I would like is to have another column that represents the percentage of the 'total_units' column. When I try

df.groupby(['item','tier']).agg(
        ID_amount=('ID', 'size'),
        total_units=('units', 'sum'),
        percen_units=('units', lambda x: 100*x/x.sum())

it gives the error Must produce aggregated value. How can I modify my code to give me those percentages? Thanks

Solution

I think you want this:

dfs = df.groupby(['item','tier']).agg(
        ID_amount=('ID', 'size'),
        total_units=('units', 'sum'))

dfs['percent_units'] = dfs.groupby('item')['total_units']\
                          .transform(lambda x: x/x.sum()*100)

dfs

Answered By - Scott Boston