How to split date and time from string?

Question

I have a dataset from excel imported in pandas. There is a one column date and time in string format.

16-MAR-16 11.35.27.000000000 AM
05-APR-16 05.21.14.000000000 PM
16-FEB-16 09.56.36.000000000 AM
16-MAR-16 11.35.27.000000000 AM
16-MAR-16 09.28.11.000000000 AM
19-MAY-16 03.50.38.000000000 PM

I want to split this data into date and time into different columns. I have gone through a couple of the same questions but could not find an answer.

This codes that I tried

(1)df["timestamp"] = pd.to_datetime(df['Invoice Date'],dayfirst = True)

(Error)File "C:\Users\admin\Anaconda3\lib\site-packages\dateutil\parser.py", line 559, in parse
raise ValueError("Unknown string format")
ValueError: Unknown string format


(2)from datetime import datetime

df["timestamp"] = df["Invoice Date"].apply(lambda x: datetime.strptime(x,"dd-mmm-yy hh.mm.ss.%f aa"))

(Error)  ValueError: time data '16-MAR-16 11.35.27.000000000 AM' does not match format 'dd-mmm-yy hh.mm.ss.%f aa'

Please help me out here.

Check the python strftime reference http://strftime.org/ – David Leon Feb 06 '18 at 07:37 — David Leon, Feb 06 '18 at 07:37

jezrael · Accepted Answer · 2018-02-06T07:32:30.230

4

Use parameter format, reference:

df["timestamp"] = pd.to_datetime(df['Invoice Date'], format='%d-%b-%y %H.%M.%S.%f %p')
print (df)

                      Invoice Date           timestamp
0  16-MAR-16 11.35.27.000000000 AM 2016-03-16 11:35:27
1  05-APR-16 05.21.14.000000000 PM 2016-04-05 05:21:14
2  16-FEB-16 09.56.36.000000000 AM 2016-02-16 09:56:36
3  16-MAR-16 11.35.27.000000000 AM 2016-03-16 11:35:27
4  16-MAR-16 09.28.11.000000000 AM 2016-03-16 09:28:11
5  19-MAY-16 03.50.38.000000000 PM 2016-05-19 03:50:38

If want 2 separate columns for dates and times:

d = pd.to_datetime(df['Invoice Date'], format='%d-%b-%y %H.%M.%S.%f %p')
df['date'] = d.dt.date
df['time'] = d.dt.time
print (df)

                      Invoice Date        date      time
0  16-MAR-16 11.35.27.000000000 AM  2016-03-16  11:35:27
1  05-APR-16 05.21.14.000000000 PM  2016-04-05  05:21:14
2  16-FEB-16 09.56.36.000000000 AM  2016-02-16  09:56:36
3  16-MAR-16 11.35.27.000000000 AM  2016-03-16  11:35:27
4  16-MAR-16 09.28.11.000000000 AM  2016-03-16  09:28:11
5  19-MAY-16 03.50.38.000000000 PM  2016-05-19  03:50:38

edited Feb 06 '18 at 07:32

answered Feb 06 '18 at 07:26

jezrael

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how come you know so much pandas...i see almost all questions being answered by you....do you have a good resource to master pandas – vks Feb 06 '18 at 07:29
@jezrael OP clearly asked "I want to split this data into date and time in different columns.", – Vikas Periyadath Feb 06 '18 at 07:30
@vks - Yes, If I have time I try answer. – jezrael Feb 06 '18 at 07:32
looks better :) – Vikas Periyadath Feb 06 '18 at 07:33

How to split date and time from string?

1 Answers1