pandas.Series.dt.tz_convert#
- Series.dt.tz_convert(*args, **kwargs)[source]#
Convert tz-aware Datetime Array/Index from one time zone to another.
- Parameters
- tzstr, pytz.timezone, dateutil.tz.tzfile or None
Time zone for time. Corresponding timestamps would be converted to this time zone of the Datetime Array/Index. A tz of None will convert to UTC and remove the timezone information.
- Returns
- Array or Index
- Raises
- TypeError
If Datetime Array/Index is tz-naive.
See also
DatetimeIndex.tz
A timezone that has a variable offset from UTC.
DatetimeIndex.tz_localize
Localize tz-naive DatetimeIndex to a given time zone, or remove timezone from a tz-aware DatetimeIndex.
Examples
With the tz parameter, we can change the DatetimeIndex to other time zones:
>>> dti = pd.date_range(start='2014-08-01 09:00', ... freq='H', periods=3, tz='Europe/Berlin')
>>> dti DatetimeIndex(['2014-08-01 09:00:00+02:00', '2014-08-01 10:00:00+02:00', '2014-08-01 11:00:00+02:00'], dtype='datetime64[ns, Europe/Berlin]', freq='H')
>>> dti.tz_convert('US/Central') DatetimeIndex(['2014-08-01 02:00:00-05:00', '2014-08-01 03:00:00-05:00', '2014-08-01 04:00:00-05:00'], dtype='datetime64[ns, US/Central]', freq='H')
With the
tz=None
, we can remove the timezone (after converting to UTC if necessary):>>> dti = pd.date_range(start='2014-08-01 09:00', freq='H', ... periods=3, tz='Europe/Berlin')
>>> dti DatetimeIndex(['2014-08-01 09:00:00+02:00', '2014-08-01 10:00:00+02:00', '2014-08-01 11:00:00+02:00'], dtype='datetime64[ns, Europe/Berlin]', freq='H')
>>> dti.tz_convert(None) DatetimeIndex(['2014-08-01 07:00:00', '2014-08-01 08:00:00', '2014-08-01 09:00:00'], dtype='datetime64[ns]', freq='H')