# pandas.DataFrame.tz_localize¶

Localize tz-naive index of a Series or DataFrame to target time zone.

This operation localizes the Index. To localize the values in a
timezone-naive Series, use `Series.dt.tz_localize()`

.

- param tz
string or pytz.timezone object

- param axis
the axis to localize

- param level
- int, str, default None
If axis ia a MultiIndex, localize a specific level. Otherwise must be None

- param copy
- boolean, default True
Also make a copy of the underlying data

- param ambiguous
- ‘infer’, bool-ndarray, ‘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.

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

- bool-ndarray where True signifies a DST time, False designates
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

- param nonexistent
- str, default ‘raise’
A nonexistent time does not exist in a particular timezone where clocks moved forward due to DST. Valid values are:

- ‘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

New in version 0.24.0.

- return
Series or DataFrame Same type as the input.

- raises
- TypeError
If the TimeSeries is tz-aware and tz is not None.

Warning

This feature is currently unsupported by Intel Scalable Dataframe Compiler