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

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

Answer 2

Very simple:

df['C'] = df['A'] + df['B']

Answer 3

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

Answer 4

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

Answer 5

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)

Answer 6

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)