How to fillna in pandas dataframe based on pattern like in excel dragging?

I have dataframe which should be filled by understanding rows understanding like we do in excel. If its continious integer it fill by next number itself.

Is there any function in python like this?

import pandas as pd
d = { 'year': [2019,2020,2019,2020,np.nan,np.nan], 'cat1': [1,2,3,4,np.nan,np.nan], 'cat2': ['c1','c1','c1','c2',np.nan,np.nan]}
df = pd.DataFrame(data=d)
df
    year    cat1    cat2
0   2019.0  1.0     c1
1   2020.0  2.0     c1
2   2019.0  3.0     c1
3   2020.0  4.0     c2
4   NaN     NaN     NaN
5   NaN     NaN     NaN

output required:

    year    cat1    cat2
0   2019.0  1.0     c1
1   2020.0  2.0     c1
2   2019.0  3.0     c1
3   2020.0  4.0     c2
4   2019.0  5.0     c2 #here can be ignored if it can't understand the earlier pattern
5   2020.0  6.0     c2 #here can be ignored if it can't understand the earlier pattern

I tried df.interpolate(method='krogh') #it fill 1,2,3,4,5,6 but incorrect others.

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