pandas.Timestamp.tz_localize#

Timestamp.tz_localize(tz, ambiguous='raise', nonexistent='raise')#

Localize the Timestamp to a timezone.

Convert naive Timestamp to local time zone or remove timezone from timezone-aware Timestamp.

Parameters
tzstr, pytz.timezone, dateutil.tz.tzfile or None

Time zone for time which Timestamp will be converted to. None will remove timezone holding local time.

ambiguousbool, ‘NaT’, 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.

The behavior is as follows:

  • bool contains flags to determine if time is dst or not (note that this flag is only applicable for ambiguous fall dst dates).

  • ‘NaT’ will return NaT for an ambiguous time.

  • ‘raise’ will raise an AmbiguousTimeError for an ambiguous time.

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.

The behavior is as follows:

  • ‘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
localizedTimestamp
Raises
TypeError

If the Timestamp is tz-aware and tz is not None.

Examples

Create a naive timestamp object:

>>> ts = pd.Timestamp('2020-03-14T15:32:52.192548651')
>>> ts
Timestamp('2020-03-14 15:32:52.192548651')

Add ‘Europe/Stockholm’ as timezone:

>>> ts.tz_localize(tz='Europe/Stockholm')
Timestamp('2020-03-14 15:32:52.192548651+0100', tz='Europe/Stockholm')

Analogous for pd.NaT:

>>> pd.NaT.tz_localize()
NaT