Pandas: sum DataFrame rows for given columns

I have the following DataFrame:

    In [1]:

    import pandas as pd
    df = pd.DataFrame({'a': [1,2,3], 'b': [2,3,4], 'c':['dd','ee','ff'], 'd':[5,9,1]})
    df
    Out [1]:
       a  b   c  d
    0  1  2  dd  5
    1  2  3  ee  9
    2  3  4  ff  1

I would like to add a column 'e' which is the sum of column 'a', 'b' and 'd'.

Going across forums, I thought something like this would work:

    df['e'] = df[['a','b','d']].map(sum)

But no!

I would like to realize the operation having the list of columns ['a','b','d'] and df as inputs.

You can just sum and set param axis=1 to sum the rows, this will ignore none numeric columns:

    In [91]:

    df = pd.DataFrame({'a': [1,2,3], 'b': [2,3,4], 'c':['dd','ee','ff'], 'd':[5,9,1]})
    df['e'] = df.sum(axis=1)
    df
    Out[91]:
       a  b   c  d   e
    0  1  2  dd  5   8
    1  2  3  ee  9  14
    2  3  4  ff  1   8

If you want to just sum specific columns then you can create a list of the columns and remove the ones you are not interested in:

    In [98]:

    col_list= list(df)
    col_list.remove('d')
    col_list
    Out[98]:
    ['a', 'b', 'c']
    In [99]:

    df['e'] = df[col_list].sum(axis=1)
    df
    Out[99]:
       a  b   c  d  e
    0  1  2  dd  5  3
    1  2  3  ee  9  5
    2  3  4  ff  1  7

From: stackoverflow.com/q/25748683

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