pandas.Series.dt.tz_convert

Series.dt.tz_convert(*args, **kwargs)

Convert tz-aware DatetimeIndex from one time zone to another.

Parameters:

tz : string, pytz.timezone, dateutil.tz.tzfile or None

Time zone for time. Corresponding timestamps would be converted to this time zone of the DatetimeIndex. A tz of None will convert to UTC and remove the timezone information.

Returns:

normalized : DatetimeIndex

Raises:

TypeError

If DatetimeIndex 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.DatetimeIndex(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.DatetimeIndex(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')