Pandas find last positive value in each column and Replace NaN with that value

I have a dataframe.

import pandas as pd
df = pd.DataFrame({'menu1': [5, 5, 5, 5, 5, None, None], 
                  'menu2': [4, 4, None, 4, None, None, None], 
                  'menu3': [None, None, 9, 9, None, None, None]
                            })
df

For each column, I would like to find the last positive value and replace NAN with that value.

df = pd.DataFrame({'menu1': [5, 5, 5, 5, 5, 5, 5], 
                  'menu2': [4, 4, None, 4, 4, 4, 4], 
                  'menu3': [None, None, 9, 9, 9, 9, 9]
                            })
df

>Solution :

Using interpolation method pandas.DataFrame.interpolate with specific options:

df.interpolate(limit_direction='forward', limit_area='outside')

• limit_direction='forward' – tells in what direction NaNs will be filled in
• limit_area='outside' – tells to only fill NaNs outside valid values (means that NaN should not be surrounded by valid values)

  menu1  menu2  menu3
0    5.0    4.0    NaN
1    5.0    4.0    NaN
2    5.0    NaN    9.0
3    5.0    4.0    9.0
4    5.0    4.0    9.0
5    5.0    4.0    9.0
6    5.0    4.0    9.0