modin.pandas.DatetimeIndex.tz_localize

DatetimeIndex.tz_localize(tz, ambiguous: TimeAmbiguous = 'raise', nonexistent: TimeNonexistent = 'raise') → DatetimeIndex[source]

Localize tz-naive Datetime Array/Index to tz-aware Datetime Array/Index.

This method takes a time zone (tz) naive Datetime Array/Index object and makes this time zone aware. It does not move the time to another time zone.

This method can also be used to do the inverse – to create a time zone unaware object from an aware object. To that end, pass tz=None.

Parameters:

  • tz (str, pytz.timezone, dateutil.tz.tzfile, datetime.tzinfo or None) – Time zone to convert timestamps to. Passing None will remove the time zone information preserving local time.

  • ambiguous ('infer', 'NaT', bool array, default 'raise') –

    When clocks moved backward due to DST, ambiguous times may arise. For example in Central European Time (UTC+01), when going from 03:00 DST to 02:00 non-DST, 02:30:00 local time occurs both at 00:30:00 UTC and at 01:30:00 UTC. In such a situation, the ambiguous parameter dictates how ambiguous times should be handled.

    • ’infer’ will attempt to infer fall dst-transition hours based on order

    • bool-ndarray where True signifies a DST time, False signifies a non-DST time (note that this flag is only applicable for ambiguous times)

    • ’NaT’ will return NaT where there are ambiguous times

    • ’raise’ will raise an AmbiguousTimeError if there are ambiguous times.

  • nonexistent ('shift_forward', 'shift_backward, 'NaT', timedelta, default 'raise') –

    A nonexistent time does not exist in a particular timezone where clocks moved forward due to DST.

    • ’shift_forward’ will shift the nonexistent time forward to the closest existing time

    • ’shift_backward’ will shift the nonexistent time backward to the closest existing time

    • ’NaT’ will return NaT where there are nonexistent times

    • timedelta objects will shift nonexistent times by the timedelta

    • ’raise’ will raise an NonExistentTimeError if there are nonexistent times.

Returns:

Array/Index converted to the specified time zone.

Return type:

Same type as self

Raises:

TypeError – If the Datetime Array/Index is tz-aware and tz is not None.

See also

DatetimeIndex.tz_convert

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

Examples

>>> tz_naive = pd.date_range('2018-03-01 09:00', periods=3)
>>> tz_naive
DatetimeIndex(['2018-03-01 09:00:00', '2018-03-02 09:00:00',
               '2018-03-03 09:00:00'],
              dtype='datetime64[ns]', freq=None)
Copy

Localize DatetimeIndex in US/Eastern time zone:

>>> tz_aware = tz_naive.tz_localize(tz='US/Eastern')
>>> tz_aware
DatetimeIndex(['2018-03-01 09:00:00-05:00', '2018-03-02 09:00:00-05:00',
               '2018-03-03 09:00:00-05:00'],
              dtype='datetime64[ns, UTC-05:00]', freq=None)
Copy

With the tz=None, we can remove the time zone information while keeping the local time (not converted to UTC):

>>> tz_aware.tz_localize(None)
DatetimeIndex(['2018-03-01 09:00:00', '2018-03-02 09:00:00',
               '2018-03-03 09:00:00'],
              dtype='datetime64[ns]', freq=None)
Copy
Language: English