Adding certain columns from dataframe

Question

I have the following dataframe df:

    A  B  C  D  E

J   4  2  3  2  3
K   5  2  6  2  1
L   2  6  5  4  7

I would like to create an additional column that adds by index the df except column A (which also are numbers), therefore what I have tried is :

df['summation'] = df.iloc[:, 1:4].sum(axis=0)

However, the column summation is added but gives NaN values.

Desired output is:

    A  B  C  D  E  summation

J   4  2  3  2  3    10
K   5  2  6  2  1    11
L   2  6  5  4  7    22

The sum along the row starting at B to the end.

@Wen thnks for your input! but i would like to sum from loc.['B'] 1 along the row — JamesHudson81
– JamesHudson81, Commented Dec 13, 2017 at 20:31
Ok, Your column one is str, so it will not count in sum, you can just do df.sum(1) — BENY
– BENY, Commented Dec 13, 2017 at 20:32
The only thing wrong in your approach is the axis. If you pass axis=0 it will take the sum for each column. Since this cannot be aligned with row labels, it will give NaNs. Just change the axis parameter. A label friendly way is df.loc[:, 'B':].sum(axis=1) — user2285236
– user2285236, Commented Dec 13, 2017 at 20:39

Cleb · Accepted Answer · 2017-12-13 22:52:39Z

1

As pointed out in the comments, you apply sum on the wrong axis. If you want to exclude columns from the sum, you can use drop (which also accepts a list of column names which might be handy if you want to exclude columns at e.g. index 0 and 3; then iloc might not be ideal)

df.drop('A', axis=1).sum(axis=1)

which yields

J    10
K    11
L    22

Also @ayhan's solution in the comments works fine.

edited Dec 13, 2017 at 22:52

answered Dec 13, 2017 at 22:36

Cleb

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