Combine Date and Time columns using python pandas -

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i have pandas dataframe following columns;

date              time 01-06-2013      23:00:00 02-06-2013      01:00:00 02-06-2013      21:00:00 02-06-2013      22:00:00 02-06-2013      23:00:00 03-06-2013      01:00:00 03-06-2013      21:00:00 03-06-2013      22:00:00 03-06-2013      23:00:00 04-06-2013      01:00:00

how combine data['date'] & data['time'] following? there way of doing using pd.to_datetime?

date 01-06-2013 23:00:00 02-06-2013 01:00:00 02-06-2013 21:00:00 02-06-2013 22:00:00 02-06-2013 23:00:00 03-06-2013 01:00:00 03-06-2013 21:00:00 03-06-2013 22:00:00 03-06-2013 23:00:00 04-06-2013 01:00:00

it's worth mentioning may have been able read in directly e.g. if using read_csv using parse_dates=[['date', 'time']].

assuming these strings add them (with space), allowing apply to_datetime:

in [11]: df['date'] + ' ' + df['time'] out[11]: 0    01-06-2013 23:00:00 1    02-06-2013 01:00:00 2    02-06-2013 21:00:00 3    02-06-2013 22:00:00 4    02-06-2013 23:00:00 5    03-06-2013 01:00:00 6    03-06-2013 21:00:00 7    03-06-2013 22:00:00 8    03-06-2013 23:00:00 9    04-06-2013 01:00:00 dtype: object  in [12]: pd.to_datetime(df['date'] + ' ' + df['time']) out[12]: 0   2013-01-06 23:00:00 1   2013-02-06 01:00:00 2   2013-02-06 21:00:00 3   2013-02-06 22:00:00 4   2013-02-06 23:00:00 5   2013-03-06 01:00:00 6   2013-03-06 21:00:00 7   2013-03-06 22:00:00 8   2013-03-06 23:00:00 9   2013-04-06 01:00:00 dtype: datetime64[ns]

note: surprisingly (for me), works fine nans being converted nat, worth worrying conversion (perhaps using raise argument).


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