I have the following data frame in Pandas:
df = pd.DataFrame({
'ID': [1,2,1,1,2,3,1,3,3,3,2],
'date': ['2021-04-28','2022-05-21','2011-03-01','2021-11-28','1992-12-01','1999-10-28','2022-01-12','2019-02-28','2001-03-28','2022-01-01','2009-05-28']
})
I want to produce a column time since first occur
that is the time passed in days since their first occurrence.
Here is what I did:
df['date'] = pd.to_datetime(df['date'], dayfirst=True)
df.sort_values(by=['ID', 'date'], ascending = [True, False], inplace=True)
and I got the sorted data frame
ID date
6 1 2022-01-12
3 1 2021-11-28
0 1 2021-04-28
2 1 2011-03-01
1 2 2022-05-21
10 2 2009-05-28
4 2 1992-12-01
9 3 2022-01-01
7 3 2019-02-28
8 3 2001-03-28
5 3 1999-10-28
so the output should look like
ID date time since first occur
6 1 2022-01-12 3970
3 1 2021-11-28 3925
0 1 2021-04-28 3711
2 1 2011-03-01 0
1 2 2022-05-21 10763
10 2 2009-05-28 6022
4 2 1992-12-01 0
9 3 2022-01-01 8101
7 3 2019-02-28 7063
8 3 2001-03-28 517
5 3 1999-10-28 0
Thanks in advance for helping.
CodePudding user response:
After sorting the dataframe, you can get the difference between date
and minimal date in group
df['time since first occur'] = (df['date'] - df.groupby('ID')['date'].transform('min')).dt.days
print(df)
ID date time since first occur
6 1 2022-01-12 3970
3 1 2021-11-28 3925
0 1 2021-04-28 3711
2 1 2011-03-01 0
1 2 2022-05-21 10763
10 2 2009-05-28 6022
4 2 1992-12-01 0
9 3 2022-01-01 8101
7 3 2019-02-28 7063
8 3 2001-03-28 517
5 3 1999-10-28 0