I have the following DataFrame:
import pandas as pd df = pd.DataFrame({'a': [1,2,3], 'b': [2,3,4], 'c':['dd','ee','ff'], 'd':[5,9,1]}) 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 If you have just a few columns to sum, you can write:
df['e'] = df['a'] + df['b'] + df['d'] This creates new column e with the values:
a b c d e 0 1 2 dd 5 8 1 2 3 ee 9 14 2 3 4 ff 1 8 For longer lists of columns, EdChum's answer is preferred.
This is a simpler way using iloc to select which columns to sum:
df['f']=df.iloc[:,0:2].sum(axis=1) df['g']=df.iloc[:,[0,1]].sum(axis=1) df['h']=df.iloc[:,[0,3]].sum(axis=1) Produces:
a b c d e f g h 0 1 2 dd 5 8 3 3 6 1 2 3 ee 9 14 5 5 11 2 3 4 ff 1 8 7 7 4 I can't find a way to combine a range and specific columns that works e.g. something like:
df['i']=df.iloc[:,[[0:2],3]].sum(axis=1) df['i']=df.iloc[:,[0:2,3]].sum(axis=1)