In a pandas DataFrame I have weird datetime format like so:
0 201913907050435
1 201913908520126
2 201914004163647
3 201914019315651
4 201914019320917
Name: DATETIME, dtype: object
What I know is, that it's Year followed by day of the year. I guess the number after that is the time in milliseconds or nanoseconds.
I want to transform the type to a pandas datetime object. So far I have:
pd.to_datetime(df.DATETIME, format='%Y%j%f')
which gives me:
0 2019-05-19 00:00:00.070504350
1 2019-05-19 00:00:00.085201260
2 2019-05-20 00:00:00.041636470
3 2019-05-20 00:00:00.193156510
4 2019-05-20 00:00:00.193209170
Name: DATETIME, dtype: datetime64[ns]
The problem is that HH:MM:SS is always 0 and not filled in correctly. What datetime code do I need instead of %f that can represent milliseconds (or whatever this number is)?
I could not find it in this table.
Thank you!
### try this
print(pd.to_datetime('201913907050435', format="%Y%j%H%M%S%f"))
##output:
2019-05-19 07:05:04.350000