Make new column in Panda dataframe by adding values from other columns

Question

I have a dataframe with values like   A B 1 4 2 6 3 9   I need to add a new column by adding values from column A and B  like  A B C 1 4 5 2 6 8 3 9 12   I believe this can be done using lambda function  but I can t figure out how to do it

User · Answer

I wanted to add a comment responding to the error message n00b was getting but I don't have enough reputation. So my comment is an answer in case it helps anyone...

n00b said:

I get the following warning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead

He got this error because whatever manipulations he did to his dataframe prior to creating df['C'] created a view into the dataframe rather than a copy of it. The error didn't arise form the simple calculation df['C'] = df['A'] + df['B'] suggested by DeepSpace.

Have a look at the Returning a view versus a copy docs.

User · Answer

The simplest way would be to use DeepSpace answer  However  if you really want to use an anonymous function you can use apply   df  C     df apply lambda row  row  A     row  B    axis 1

User · Answer

You could do   df  C     df sum axis 1    If you only want to do numerical values   df  C     df sum axis 1  numeric only True

User · Answer

You could use sum function to achieve that as  EdChum mentioned in the comment   df  C      df   A    B    sum axis 1   In  245   df Out 245       A  B   C 0  1  4   5 1  2  6   8 2  3  9  12

User · Answer

You can solve it by adding simply  df  C     df  A     df  B

User · Answer

Concerning n00b s comment   I get the following warning  A value is trying to be set on a copy of a slice from a DataFrame  Try using  loc row indexer col indexer    value instead    I was getting the same error  In my case it was because I was trying to perform the column addition on a dataframe that was created like this   df b   df   colA    colB    colC      instead of    df c   pd DataFrame df  columns   colA    colB    colC      df b is a copy of a slice from df df c is an new dataframe  So  df c  colD     df  colA     df  colB    df  colC     will add the columns and won t raise any warning  Same if  sum axis 1  is used

User · Answer

Can do using loc  In  37    df   pd DataFrame   A   1 2 3   B   4 6 9     In  38   df Out 38      A  B 0  1  4 1  2  6 2  3  9  In  39   df  C   df loc     A   B    sum axis 1   In  40   df Out 40      A  B   C 0  1  4   5 1  2  6   8 2  3  9  12

User · Answer

As of Pandas version 0 16 0 you can use assign as follows   df   pd DataFrame   A    1 2 3    B    4 6 9    df assign C   df A   df B     Out 383         A  B   C   0  1  4   5   1  2  6   8   2  3  9  12   You can add multiple columns this way as follows   df assign C   df A   df B            Diff   df B - df A            Mult   df A   df B    Out 379         A  B   C  Diff  Mult   0  1  4   5     3     4   1  2  6   8     4    12   2  3  9  12     6    27

User · Answer

Very simple   df  C     df  A     df  B

User · Answer

Building a little more on Anton s answer   you can add all the columns like this   df  sum     df list df columns   sum axis 1

[python] Make new column in Panda dataframe by adding values from other columns

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