[Python] Extract date and time from pandas timestamp

I have a timestamp column where the timestamp is in the following format

2016-06-16T21:35:17.098+01:00


I want to extract date and time from it. I have done the following:

import datetime as dt

df['timestamp'] = df['timestamp'].apply(lambda x : pd.to_datetime(str(x)))

df['dates'] = df['timestamp'].dt.date


This worked for a while. But suddenly it does not.

If I again do df['dates'] = df['timestamp'].dt.date I get the following error

Can only use .dt accessor with datetimelike values


Luckily, I have saved the data frame with dates in the csv but I now want to create another column time in the format 23:00:00.051

EDIT

From the raw data file (15 million samples), the timestamp column looks like following (first 5 samples):

timestamp

0 2016-06-13T00:00:00.051+01:00
1 2016-06-13T00:00:00.718+01:00
2 2016-06-13T00:00:00.985+01:00
3 2016-06-13T00:00:02.431+01:00
4 2016-06-13T00:00:02.737+01:00


After the following command

df['timestamp'] = df['timestamp'].apply(lambda x : pd.to_datetime(str(x)))


the timestamp column looks like with dtype as dtype: datetime64[ns]

0 2016-06-12 23:00:00.051
1 2016-06-12 23:00:00.718
2 2016-06-12 23:00:00.985
3 2016-06-12 23:00:02.431
4 2016-06-12 23:00:02.737


Then finally

df['dates'] = df['timestamp'].dt.date

0 2016-06-12
1 2016-06-12
2 2016-06-12
3 2016-06-12
4 2016-06-12


EDIT 2

Found the mistake. I had cleaned the data and saved the data frame in a csv file, so I don't have to do the cleaning again. When I read the csv, the timestamp dtype changes to object. Now how do I fix this?

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