I have the following DataFrame with named columns and index:

  'a'     'a*'    'b'    'b*'
1  5      NaN     9      NaN
2  NaN    3       3      NaN
3  4      NaN     1      NaN
4  NaN    9       NaN    7

The data source has caused some column headings to be copied slightly differently. For example, as above, some column headings are a string and some are the same string with an additional '*' character.

I want to copy any values (which are not null) from a* and b* columns to a and b, respectively.

Is there an efficient way to do such an operation?

Use np.where

df['a']= np.where(df['a'].isnull(), df['a*'], df['a'])
df['b']= np.where(df['b'].isnull(), df['b*'], df['b'])

Output:

     a  a*  b   b*
0   5.0 NaN 9.0 NaN
1   3.0 3.0 3.0 NaN
2   4.0 NaN 1.0 NaN
3   9.0 9.0 7.0 7.0