sum several column values per group in pandas

Question

I have a dataframe with the following format:

typeA typeB  valueA valueB valueC
A      16      1      1      1
A      16      2      1      0
B      16      1      0      0
B      16      0      0      0
B      22      2      2      2
...

How can I sum all columns for every group? that I have the following output:

typeA typeB valueA valueB valueC
A     16     3      2       1
B     16     1      0       0
B     22     2      2       2
...

`groupby(['typeA', 'typeB']).sum()`? – Ch3steR May 18 '21 at 08:19 — Ch3steR, May 18 '21 at 08:19

score 2 · Accepted Answer · answered May 18 '21 at 08:17

You can use pivot_table:

df.pivot_table(index=['typeA', 'typeB'],
               values=['valueA', 'valueB', 'valueC'],
               aggfunc=sum)\
  .reset_index()

Output:

   typeA  typeB  valueA  valueB  valueC
0      A     16       3       2       1
1      B     16       1       0       0
2      B     22       2       2       2

sum several column values per group in pandas

1 Answers1