Pandas dynamically replace nan values-CodePudding

I have a DataFrame that looks like this:

df = pd.DataFrame({'a':[1,2,np.nan,1,np.nan,np.nan,4,2,3,np.nan], 
    'b':[4,2,3,np.nan,np.nan,1,5,np.nan,5,8]
})

   a    b
0  1.0  4.0
1  2.0  2.0
2  NaN  3.0
3  1.0  NaN
4  NaN  NaN
5  NaN  1.0
6  4.0  5.0
7  2.0  NaN
8  3.0  5.0
9  NaN  8.0

I want to dynamically replace the nan values. I have tried doing (df.ffill() df.bfill())/2 but that does not yield the desired output, as it casts the fill value to the whole column at once, rather then dynamically. I have tried with interpolate, but it doesn't work well for non linear data.

I have seen