Delete previous rows in Pandas Dataframe based on condition

Question

I have a dataframe with user_id and some informations about them

User_id   type     info
31       R*1005    no
31       R*10335   no
25       R*1005    no
25       R*243     no
25       R*4918    yes
25       R*9017    no
25       R*9015    no
46       R*9470    no

I want to drop previous rows from user_id when the column info is "yes". In the case above will be like:

User_id   type     info
31       R*1005    no
31       R*10335   no
25       R*9017    no
25       R*9015    no
46       R*9470    no

How to do this in a smart way?

Answer 1

Idea is test if at least one yes in group and then for this group remove previous yes rows:

m = df['info'].eq('yes')
g = m.groupby(df['User_id'])

m1 = g.transform('any')
m2 = g.cumsum().ne(0)

df = df[(~m1 | m2) & ~m]
print (df)
   User_id     type info
0       31   R*1005   no
1       31  R*10335   no
5       25   R*9017   no
6       25   R*9015   no
7       46   R*9470   no