What is the most efficient way to fillna multiple columns with values from other columns in a way that they can be paired with a suffix?

This is my DataFrame:

import pandas as pdimport numpy as npdf = pd.DataFrame(    {'x': [1, np.nan, 3, np.nan, 5],'y': [np.nan, 7, 8, 9, np.nan],'x_a': [1, 2, 3, 4, 5],'y_a': [6, 7, 8, 9, 10]    })

Expected output is fill_na columns x and y:

     x     y  x_a  y_a0  1.0   6.0    1    61  2.0   7.0    2    72  3.0   8.0    3    83  4.0   9.0    4    94  5.0  10.0    5   10

Basically I want to fillna x with x_a and y with y_a. In other words each column should be paired with another column that has the suffix _a and the column name.

I can get this output by using this code:

for col in ['x', 'y']:    df[col] = df[col].fillna(df[f'{col}_a'])

But I wonder if it is the best/most efficient way? Suppose I got hundreds of columns like these