Assuming that the columns of missing values are numeric, then we can replace the missing values with corresponding mean values of the column as follows:
import pandas as pd import numpy as np df = pd.DataFrame({'id':list(range(10)), 'A':[10,9,8,7,np.nan,np.nan,20,15,12,np.nan], 'D':[np.nan,20,18,22,18,17,19,np.nan,17,23]}) df
df = df.fillna(df.mean()) df