Python pandas: extract date and time from timestamp

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I have a timestamp column (Time) where the timestamp is in the following format

0       02.28.2020 10:21:26.0734 vorm.
1       02.28.2020 10:21:27.0720 vorm.
2       02.28.2020 10:21:30.0705 vorm.
3       02.28.2020 10:21:31.0742 vorm.
4       02.28.2020 10:21:32.0606 vorm.

3978    02.28.2020 11:30:11.1122 vorm.
3979    02.28.2020 11:30:12.1078 vorm.
3980    02.28.2020 11:30:13.1100 vorm.
3981    02.28.2020 11:30:14.1190 vorm.
3982    02.28.2020 11:30:15.1086 vorm.
Name: Time, Length: 3983, dtype: object

I tried to convert the string object in Timestamp object in the following manner:

df['Time'] = [datetime.datetime.strptime(d, "%d.%m.%Y %H:%M:%S.%f %p.") for d in df["Time"]]

But I get the following error:

ValueError: time data '02.28.2020 10:21:26.0734 vorm.' does not match format '%d.%m.%Y %H:%M:%S.%f %p.'

I assume that the error comes from "vorm.", which is the indication for "AM".

pandas timestamp date python
1 Answers

Use to_datetime with change format to %H to %I for match hours in 12H format, also swapped %d and %m months with days and for correct parse AM and PM is necessary replace value in dict:

df['Time'] = pd.to_datetime(df["Time"].replace({'vorm.' :'AM'}, regex=True), 
                            format="%m.%d.%Y %I:%M:%S.%f %p")
print (df)
                           Time
0    2020-02-28 10:21:26.073400
1    2020-02-28 10:21:27.072000
2    2020-02-28 10:21:30.070500
3    2020-02-28 10:21:31.074200
4    2020-02-28 10:21:32.060600
3978 2020-02-28 11:30:11.112200
3979 2020-02-28 11:30:12.107800
3980 2020-02-28 11:30:13.110000
3981 2020-02-28 11:30:14.119000
3982 2020-02-28 11:30:15.108600
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