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

Answer 1

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

Answer 2

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.

Answer 3

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.

Answer 4

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)