Pandas Dataframe: Groupby on first two columns and count the occurence for first column

Question

I had a dataset as a result of groupby as :

CUSTID TRANSACTION_ID COUNT

CU_1    TR_1                1  
CU_1    TR_2                1
CU_1    TR_3                1
CU_2    TR_4                1  
CU_2    TR_5                1

I needed to have result as CUSTID TOTAL_COUNT

CU_1       3          
CU_2       2

What have you tried? Did you groupby the first columns and simply take the count of the second column? — David Erickson, Sep 20 '20 at 07:46

Valdi_Bo · Accepted Answer · 2020-09-20T12:15:14.940

0

Run just:

df.groupby('CUSTID').COUNT.sum()

You need to group by a single column (CUSTID) only, then, from each group, take COUNT column and compute its sum().

Additional step may be to provide the required name to the resulting Series. If it is important, append .rename('TOTAL_COUNT') to the above code.

Yet another step may be to convert this Series into a DataFrame. To do it, append .to_frame() to the above code.

edited Sep 20 '20 at 12:15

answered Sep 20 '20 at 12:09

Valdi_Bo

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Thanks for the help @Valdi_Bo , I was able to get through with the step David mentioned above . – Aakash Yadav Sep 21 '20 at 18:40

Pandas Dataframe: Groupby on first two columns and count the occurence for first column

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