Replace NaN with column value on a row by row basis

In my Pandas DataFrame I’d like to replace all instances of NaN (np.nan) on a row by row basis with the corresponding value from column "E".

This DataFrame here..

should result in..

I cannot find any code to solve this issue.

Data:

{'A': [1, nan],
 'B': [nan, 5],
 'C': [3, nan],
 'D': [nan, 4],
 'E': [88, 55]}

>Solution :

You could transpose + fillna + transpose back:

df = df.T.fillna(df['E']).T.astype(int)

Output:

    A   B   C   D   E
0   1  88   3  88  88
1  55   5  55   4  55