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DOC: mention tz_convert(None) and tz_localize(None) for dataframe or series #49691

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Merged
merged 4 commits into from
Nov 21, 2022
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DOC: mention tz_convert(None) and tz_localize(None) for dataframe or series #49691

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16694d4
DOC: mention tz_convert(None) and tz_localize(None) for dataframe or …
georeth Nov 14, 2022
70094e3
DOC: remove function-level doc of tz_convert(None) and tz_localize(None)
georeth Nov 18, 2022
ca4fcdc
DOC: add example for tz_convert and tz_localize
georeth Nov 18, 2022
f978e67
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georeth Nov 18, 2022
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34 changes: 32 additions & 2 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10139,7 +10139,9 @@ def tz_convert(

Parameters
----------
tz : str or tzinfo object
tz : str or tzinfo object or None
Target time zone. Passing ``None`` will convert to
UTC and remove the timezone information.
axis : the axis to convert
level : int, str, default None
If axis is a MultiIndex, convert a specific level. Otherwise
Expand All @@ -10156,6 +10158,24 @@ def tz_convert(
------
TypeError
If the axis is tz-naive.

Examples
--------
Change to another time zone:

>>> s = pd.Series([1],
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
>>> s.tz_convert('Asia/Shanghai')
2018-09-15 07:30:00+08:00 1
dtype: int64

Pass None to convert to UTC and get a tz-naive index:

>>> s = pd.Series([1],
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
>>> s.tz_convert(None)
2018-09-14 23:30:00 1
dtype: int64
"""
axis = self._get_axis_number(axis)
ax = self._get_axis(axis)
Expand Down Expand Up @@ -10206,7 +10226,9 @@ def tz_localize(

Parameters
----------
tz : str or tzinfo
tz : str or tzinfo or None
Time zone to localize. Passing ``None`` will remove the
time zone information and preserve local time.
axis : the axis to localize
level : int, str, default None
If axis ia a MultiIndex, localize a specific level. Otherwise
Expand Down Expand Up @@ -10262,6 +10284,14 @@ def tz_localize(
2018-09-15 01:30:00+02:00 1
dtype: int64

Pass None to convert to tz-naive index and preserve local time:

>>> s = pd.Series([1],
... index=pd.DatetimeIndex(['2018-09-15 01:30:00+02:00']))
>>> s.tz_localize(None)
2018-09-15 01:30:00 1
dtype: int64

Be careful with DST changes. When there is sequential data, pandas
can infer the DST time:

Expand Down