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

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)

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

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

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)

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)

The parameter axis takes as arguments either 0 or 1, with 0 meaning to sum across columns and 1 across rows.

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.

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.

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

You can solve it by adding simply:
df[‘C’] = df[‘A’] + df[‘B’]

eval lets you sum and create columns right away:

In [8]: df.eval('C = A + B', inplace=True)

In [9]: df
Out[9]: 
   A  B   C
0  1  4   5
1  2  6   8
2  3  9  12

Since inplace=True you don’t need to assign it back to df.