Good evening,

I have a dataframe like this:

What is the best way to replace emptiness in the columns with the same value from another row if the Corp value is equal? The result should be like this:

Thanks for all help!

CodePudding user response：

We could use GroupBy.apply with ffill and bfill:

df.groupby('Corp').apply(lambda x: x.ffill().bfill())

    Corp     TDS     VVT  SOAR
0  Steam  3429.0   450.0   NaN
1  Steam  3429.0  1365.0   NaN
2   Bliz  3425.1    34.0  11.0
3   Bliz   353.3    34.0  11.0
4  Tesla  2243.3     NaN  18.0
5  Tesla  2243.3     NaN  32.0
6    OYV     NaN    15.0  16.0
7    OYV     NaN    15.0  16.0

If you have blanks:

df.replace(r'^\s*$', np.nan, regex=True)\
  .groupby('Corp').apply(lambda x: x.ffill().bfill())