Btukfyl

import pandas as pd



df = pd.DataFrame({'customer': [1,2,1,3,1,2,3],

           "group_code": ['111', '111', '222', 

           '111', '111', '111', '333'],

          "ind_code": ['A', 'B', 'AA', 'A', 

          'AAA', 'C', 'BBB'],

          "amount": [100, 200, 140, 400, 225, 

          125, 600],

          "card": ['XXX', 'YYY', 'YYY', 'XXX', 

         'XXX', 'YYY', 'XXX']})

  agg = df.groupby(['card', 'group_code']).agg({'amount':'sum'}).reset_index()

  mask = agg.groupby('card') ['amount'].transform(max) == agg['amount']

 result = agg[mask]

 print(result)

With the above data frame , i wanted to group by card no and get the group code which has the max sum of amount for each card.

Expected dataframe should have the below 3 columns :

Card , Highest Total sum of amount by groupwise, name of the group which has the highest total sum

I am getting the answer as expected.
Suppose,Instead of getting the Maximum sum and corresponding group code . In larger picture, i have a huge huge data set with 14 GB. In that case can you help me in getting the Top 3 Group codes for a particular Card based on the sum of Amount.

Kindly help