How to sum all rows for each column in a dataframe

Question

I have a df as such:

         column A    column B    column C  .... ColumnZ 
 index
   X        1           4           7              10
   Y        2           5           8              11
   Z        3           6           9              12

For the life on me I can't figure out how to sum rows for each column, to arrive at a summation df:

         column A    column B    column C  .... ColumnZ 
 index
 total       6           16          25             33

Any thoughts?

`df.sum().to_frame().T.rename_axis('Total')` ... ? – anky Jul 24 '20 at 18:26 — anky, Jul 24 '20 at 18:26

score 10 · Answer 1 · answered Jul 24 '20 at 18:27

10

You can use:

df.loc['total'] = df.sum(numeric_only=True, axis=0)

answered Jul 24 '20 at 18:27

Jonas

1,749
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1

I would just like to add: df.sum(numeric_only=True, axis=1) to sum the columns instead of rows. Thanks! – M_Idk392845 Jun 19 '23 at 16:20

score 5 · Answer 2 · answered Jul 24 '20 at 18:29

Try this:

import pandas as pd

df = pd.DataFrame({'column A': [1, 2, 3], 'column B': [4, 5, 6], 'column C': [7, 8, 9]})

df.loc['total'] = df.sum()

print(df)

Output:

       column A  column B  column C
0             1         4         7
1             2         5         8
2             3         6         9
total         6        15        24

How to sum all rows for each column in a dataframe

2 Answers2