Delete rows with dates after conversion value in another column for making attribution chains

Question

I have a pd.dataframe that looks like this:

cookie     date           channel       goal_reached
cookie_1   2020-01-12     paid          0
cookie_1   2020-02-17     organic       0
cookie_1   2020-04-02     referral      1
cookie_1   2020-05-13     direct        0
cookie_1   2020-05-16     direct        0
cookie_2   2020-01-18     referral      0
cookie_2   2020-03-13     paid          1
cookie_2   2020-04-01     organic       0
cookie_2   2020-05-16     organic       0
cookie_2   2020-05-22     paid          0
cookie_3   2020-01-13     direct        0
cookie_3   2020-04-14     organic       0
cookie_3   2020-06-10     organic       0

I want to to group by for each cookie value and drop all the rows after the date with goal_reached value 1. If for cookie there is no goal_reached value 1, i need take all rows.

I want to have an end output like this:

cookie     channel                         goal_reached
cookie_1   paid > organic > referral       1
cookie_2   referral > paid                 1
cookie_3   direct > organic > organic      0

I have the following code, but it can group by with all the rows:

df = df.sort_values(['cookie', 'date'],
                    ascending=[False, True])
df = df.groupby('cookie', as_index=False).agg({'channel': lambda x: "%s" % ' > '.join(x), 'reg_goal': 'max'})

Answer 1

You can try this:

df = df[df.groupby('cookie')['goal_reached'].transform(lambda x: x.cumsum().cumsum()).lt(2)]
df = df.groupby('cookie').agg({'channel': lambda x: ' > '.join(x), 'goal_reached': 'max'})
print(df)

                             channel  goal_reached
cookie                                            
cookie_1   paid > organic > referral             1
cookie_2             referral > paid             1
cookie_3  direct > organic > organic             0