fill column based on value in rows-CodePudding

I have a dataframe named emails_visits:

    Rep  Doctor       Date   type date_after
0     1       1 2021-01-25  email        NaT
1     1       1 2021-05-29  email        NaT
2     1       2 2021-03-15  email        NaT
3     1       2 2021-04-02  email        NaT
4     1       2 2021-04-29  email        NaT
30    1       2 2021-06-01  visit 2021-06-01
5     1       3 2021-01-01  email        NaT
6     1       3 2021-01-10  email        NaT
7     1       3 2021-01-25  email        NaT
8     1       3 2021-02-19  email        NaT
9     1       4 2021-03-03  email        NaT

I need to fill in column date_afterfrom bottom to top based on values in column Rep and Doctor. if values row(x-1) Rep and Doctor ==values row(x) Rep and Doctor == then date_afterin row(x-1) should be == todate_afterin row(x)

example of desired result below

    Rep  Doctor       Date   type date_after
0     1       1 2021-01-25  email        NaT
1     1       1 2021-05-29  email        NaT
2     1       2 2021-03-15  email 2021-06-01
3     1       2 2021-04-02  email 2021-06-01
4     1       2 2021-04-29  email 2021-06-01
30    1       2 2021-06-01  visit 2021-06-01
5     1       3 2021-01-01  email        NaT
6     1       3 2021-01-10  email        NaT
7     1       3 2021-01-25  email        NaT
8     1       3 2021-02-19  email        NaT
9     1       4 2021-03-03  email        NaT

CodePudding user response：

Use groupby_bfill:

df['date_after'] = df.groupby(['Rep', 'Doctor'])['date_after'].bfill()
print(df)

# Output
    Rep  Doctor        Date   type date_after
0     1       1  2021-01-25  email        NaT
1     1       1  2021-05-29  email        NaT
2     1       2  2021-03-15  email 2021-06-01
3     1       2  2021-04-02  email 2021-06-01
4     1       2  2021-04-29  email 2021-06-01
30    1       2  2021-06-01  visit 2021-06-01
5     1       3  2021-01-01  email        NaT
6     1       3  2021-01-10  email        NaT
7     1       3  2021-01-25  email        NaT
8     1       3  2021-02-19  email        NaT
9     1       4  2021-03-03  email        NaT