How to groupby based on two columns in pandas?

Question

A similar question might have been asked before, but I couldn't find the exact one fitting to my problem. I want to group by a dataframe based on two columns. For exmaple to make this

id product quantity
1  A       2
1  A       3
1  B       2
2  A       1
2  B       1
3  B       2
3  B       1

Into this:

id product quantity
1  A       5
1  B       2
2  A       1
2  B       1
3  B       3

Meaning that summation on "quantity" column for same "id" and same "product".

Answer 1

You need groupby with parameter as_index=False for return DataFrame and aggregating mean:

df = df.groupby(['id','product'], as_index=False)['quantity'].sum()
print (df)
   id product  quantity
0   1       A         5
1   1       B         2
2   2       A         1
3   2       B         1
4   3       B         3

Or add reset_index:

df = df.groupby(['id','product'])['quantity'].sum().reset_index()
print (df)
   id product  quantity
0   1       A         5
1   1       B         2
2   2       A         1
3   2       B         1
4   3       B         3

Answer 2

You can use pivot_table with aggfunc='sum'

df.pivot_table('quantity', ['id', 'product'], aggfunc='sum').reset_index()

   id product  quantity
0   1       A         5
1   1       B         2
2   2       A         1
3   2       B         1
4   3       B         3