Skip to content

Commit 8e56e11

Browse files
jbrockmendeljbrockmendel
committed
Merge branch 'main' into depr-make_block
2 parents e3a3378 + 2aa155a commit 8e56e11

37 files changed

+804
-316
lines changed

‎ci/code_checks.sh

Lines changed: 4 additions & 34 deletions
Original file line numberDiff line numberDiff line change
@@ -164,12 +164,8 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
164164
-i "pandas.Series.dt.tz_convert PR01,PR02" \
165165
-i "pandas.Series.dt.tz_localize PR01,PR02" \
166166
-i "pandas.Series.dt.unit GL08" \
167-
-i "pandas.Series.eq SA01" \
168167
-i "pandas.Series.ge SA01" \
169168
-i "pandas.Series.gt SA01" \
170-
-i "pandas.Series.kurt RT03,SA01" \
171-
-i "pandas.Series.kurtosis RT03,SA01" \
172-
-i "pandas.Series.le SA01" \
173169
-i "pandas.Series.list.__getitem__ SA01" \
174170
-i "pandas.Series.list.flatten SA01" \
175171
-i "pandas.Series.list.len SA01" \
@@ -220,22 +216,19 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
220216
-i "pandas.Series.str.wrap RT03,SA01" \
221217
-i "pandas.Series.str.zfill RT03" \
222218
-i "pandas.Series.struct.dtypes SA01" \
223-
-i "pandas.Series.sum RT03" \
224219
-i "pandas.Series.to_dict SA01" \
225220
-i "pandas.Series.to_frame SA01" \
226221
-i "pandas.Series.to_markdown SA01" \
227-
-i "pandas.Series.to_string SA01" \
228222
-i "pandas.Series.update PR07,SA01" \
229-
-i "pandas.Timedelta PR07,SA01" \
230223
-i "pandas.Timedelta.as_unit SA01" \
231224
-i "pandas.Timedelta.asm8 SA01" \
232225
-i "pandas.Timedelta.ceil SA01" \
233226
-i "pandas.Timedelta.components SA01" \
234227
-i "pandas.Timedelta.days SA01" \
235228
-i "pandas.Timedelta.floor SA01" \
236-
-i "pandas.Timedelta.max PR02,PR07,SA01" \
237-
-i "pandas.Timedelta.min PR02,PR07,SA01" \
238-
-i "pandas.Timedelta.resolution PR02,PR07,SA01" \
229+
-i "pandas.Timedelta.max PR02" \
230+
-i "pandas.Timedelta.min PR02" \
231+
-i "pandas.Timedelta.resolution PR02" \
239232
-i "pandas.Timedelta.round SA01" \
240233
-i "pandas.Timedelta.to_numpy PR01" \
241234
-i "pandas.Timedelta.to_timedelta64 SA01" \
@@ -247,20 +240,15 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
247240
-i "pandas.TimedeltaIndex.nanoseconds SA01" \
248241
-i "pandas.TimedeltaIndex.seconds SA01" \
249242
-i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
250-
-i "pandas.Timestamp.astimezone SA01" \
251-
-i "pandas.Timestamp.ceil SA01" \
252243
-i "pandas.Timestamp.combine PR01,SA01" \
253244
-i "pandas.Timestamp.ctime SA01" \
254245
-i "pandas.Timestamp.date SA01" \
255246
-i "pandas.Timestamp.day GL08" \
256-
-i "pandas.Timestamp.dst SA01" \
257247
-i "pandas.Timestamp.floor SA01" \
258248
-i "pandas.Timestamp.fold GL08" \
259249
-i "pandas.Timestamp.fromordinal SA01" \
260250
-i "pandas.Timestamp.fromtimestamp PR01,SA01" \
261251
-i "pandas.Timestamp.hour GL08" \
262-
-i "pandas.Timestamp.is_leap_year SA01" \
263-
-i "pandas.Timestamp.isocalendar SA01" \
264252
-i "pandas.Timestamp.isoweekday SA01" \
265253
-i "pandas.Timestamp.max PR02" \
266254
-i "pandas.Timestamp.microsecond GL08" \
@@ -273,7 +261,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
273261
-i "pandas.Timestamp.now SA01" \
274262
-i "pandas.Timestamp.quarter SA01" \
275263
-i "pandas.Timestamp.replace PR07,SA01" \
276-
-i "pandas.Timestamp.resolution PR02,PR07,SA01" \
264+
-i "pandas.Timestamp.resolution PR02" \
277265
-i "pandas.Timestamp.second GL08" \
278266
-i "pandas.Timestamp.strptime PR01,SA01" \
279267
-i "pandas.Timestamp.time SA01" \
@@ -287,7 +275,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
287275
-i "pandas.Timestamp.today SA01" \
288276
-i "pandas.Timestamp.toordinal SA01" \
289277
-i "pandas.Timestamp.tz SA01" \
290-
-i "pandas.Timestamp.tz_convert SA01" \
291278
-i "pandas.Timestamp.tz_localize SA01" \
292279
-i "pandas.Timestamp.tzinfo GL08" \
293280
-i "pandas.Timestamp.tzname SA01" \
@@ -296,18 +283,14 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
296283
-i "pandas.Timestamp.utcoffset SA01" \
297284
-i "pandas.Timestamp.utctimetuple SA01" \
298285
-i "pandas.Timestamp.value GL08" \
299-
-i "pandas.Timestamp.weekday SA01" \
300286
-i "pandas.Timestamp.year GL08" \
301-
-i "pandas.api.extensions.ExtensionArray._from_sequence_of_strings SA01" \
302-
-i "pandas.api.extensions.ExtensionArray._hash_pandas_object RT03,SA01" \
303287
-i "pandas.api.extensions.ExtensionArray._pad_or_backfill PR01,RT03,SA01" \
304288
-i "pandas.api.extensions.ExtensionArray._reduce RT03,SA01" \
305289
-i "pandas.api.extensions.ExtensionArray._values_for_factorize SA01" \
306290
-i "pandas.api.extensions.ExtensionArray.astype SA01" \
307291
-i "pandas.api.extensions.ExtensionArray.dropna RT03,SA01" \
308292
-i "pandas.api.extensions.ExtensionArray.dtype SA01" \
309293
-i "pandas.api.extensions.ExtensionArray.duplicated RT03,SA01" \
310-
-i "pandas.api.extensions.ExtensionArray.equals SA01" \
311294
-i "pandas.api.extensions.ExtensionArray.fillna SA01" \
312295
-i "pandas.api.extensions.ExtensionArray.insert PR07,RT03,SA01" \
313296
-i "pandas.api.extensions.ExtensionArray.interpolate PR01,SA01" \
@@ -316,21 +299,18 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
316299
-i "pandas.api.extensions.ExtensionArray.nbytes SA01" \
317300
-i "pandas.api.extensions.ExtensionArray.ndim SA01" \
318301
-i "pandas.api.extensions.ExtensionArray.ravel RT03,SA01" \
319-
-i "pandas.api.extensions.ExtensionArray.shift SA01" \
320302
-i "pandas.api.extensions.ExtensionArray.take RT03" \
321303
-i "pandas.api.extensions.ExtensionArray.tolist RT03,SA01" \
322304
-i "pandas.api.extensions.ExtensionArray.unique RT03,SA01" \
323305
-i "pandas.api.extensions.ExtensionArray.view SA01" \
324306
-i "pandas.api.indexers.VariableOffsetWindowIndexer PR01,SA01" \
325307
-i "pandas.api.interchange.from_dataframe RT03,SA01" \
326-
-i "pandas.api.types.infer_dtype PR07,SA01" \
327308
-i "pandas.api.types.is_any_real_numeric_dtype SA01" \
328309
-i "pandas.api.types.is_bool PR01,SA01" \
329310
-i "pandas.api.types.is_bool_dtype SA01" \
330311
-i "pandas.api.types.is_categorical_dtype SA01" \
331312
-i "pandas.api.types.is_complex PR01,SA01" \
332313
-i "pandas.api.types.is_complex_dtype SA01" \
333-
-i "pandas.api.types.is_datetime64_any_dtype SA01" \
334314
-i "pandas.api.types.is_datetime64_dtype SA01" \
335315
-i "pandas.api.types.is_datetime64_ns_dtype SA01" \
336316
-i "pandas.api.types.is_datetime64tz_dtype SA01" \
@@ -352,11 +332,9 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
352332
-i "pandas.api.types.is_period_dtype SA01" \
353333
-i "pandas.api.types.is_re PR07,SA01" \
354334
-i "pandas.api.types.is_re_compilable PR07,SA01" \
355-
-i "pandas.api.types.is_scalar SA01" \
356335
-i "pandas.api.types.is_signed_integer_dtype SA01" \
357336
-i "pandas.api.types.is_sparse SA01" \
358337
-i "pandas.api.types.is_string_dtype SA01" \
359-
-i "pandas.api.types.is_timedelta64_dtype SA01" \
360338
-i "pandas.api.types.is_timedelta64_ns_dtype SA01" \
361339
-i "pandas.api.types.is_unsigned_integer_dtype SA01" \
362340
-i "pandas.api.types.pandas_dtype PR07,RT03,SA01" \
@@ -462,9 +440,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
462440
-i "pandas.errors.UnsortedIndexError SA01" \
463441
-i "pandas.errors.UnsupportedFunctionCall SA01" \
464442
-i "pandas.errors.ValueLabelTypeMismatch SA01" \
465-
-i "pandas.get_option SA01" \
466443
-i "pandas.infer_freq SA01" \
467-
-i "pandas.interval_range RT03" \
468444
-i "pandas.io.formats.style.Styler.apply RT03" \
469445
-i "pandas.io.formats.style.Styler.apply_index RT03" \
470446
-i "pandas.io.formats.style.Styler.background_gradient RT03" \
@@ -527,9 +503,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
527503
-i "pandas.testing.assert_index_equal PR07,SA01" \
528504
-i "pandas.testing.assert_series_equal PR07,SA01" \
529505
-i "pandas.timedelta_range SA01" \
530-
-i "pandas.tseries.api.guess_datetime_format SA01" \
531506
-i "pandas.tseries.offsets.BDay PR02,SA01" \
532-
-i "pandas.tseries.offsets.BMonthBegin PR02" \
533507
-i "pandas.tseries.offsets.BQuarterBegin PR02" \
534508
-i "pandas.tseries.offsets.BQuarterBegin.freqstr SA01" \
535509
-i "pandas.tseries.offsets.BQuarterBegin.is_on_offset GL08" \
@@ -538,7 +512,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
538512
-i "pandas.tseries.offsets.BQuarterBegin.normalize GL08" \
539513
-i "pandas.tseries.offsets.BQuarterBegin.rule_code GL08" \
540514
-i "pandas.tseries.offsets.BQuarterBegin.startingMonth GL08" \
541-
-i "pandas.tseries.offsets.BQuarterEnd PR02" \
542515
-i "pandas.tseries.offsets.BQuarterEnd.freqstr SA01" \
543516
-i "pandas.tseries.offsets.BQuarterEnd.is_on_offset GL08" \
544517
-i "pandas.tseries.offsets.BQuarterEnd.n GL08" \
@@ -583,7 +556,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
583556
-i "pandas.tseries.offsets.BusinessHour.rule_code GL08" \
584557
-i "pandas.tseries.offsets.BusinessHour.start GL08" \
585558
-i "pandas.tseries.offsets.BusinessHour.weekmask GL08" \
586-
-i "pandas.tseries.offsets.BusinessMonthBegin PR02" \
587559
-i "pandas.tseries.offsets.BusinessMonthBegin.freqstr SA01" \
588560
-i "pandas.tseries.offsets.BusinessMonthBegin.is_on_offset GL08" \
589561
-i "pandas.tseries.offsets.BusinessMonthBegin.n GL08" \
@@ -650,7 +622,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
650622
-i "pandas.tseries.offsets.DateOffset.nanos GL08" \
651623
-i "pandas.tseries.offsets.DateOffset.normalize GL08" \
652624
-i "pandas.tseries.offsets.DateOffset.rule_code GL08" \
653-
-i "pandas.tseries.offsets.Day PR02" \
654625
-i "pandas.tseries.offsets.Day.freqstr SA01" \
655626
-i "pandas.tseries.offsets.Day.is_on_offset GL08" \
656627
-i "pandas.tseries.offsets.Day.n GL08" \
@@ -755,7 +726,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
755726
-i "pandas.tseries.offsets.QuarterBegin.normalize GL08" \
756727
-i "pandas.tseries.offsets.QuarterBegin.rule_code GL08" \
757728
-i "pandas.tseries.offsets.QuarterBegin.startingMonth GL08" \
758-
-i "pandas.tseries.offsets.QuarterEnd PR02" \
759729
-i "pandas.tseries.offsets.QuarterEnd.freqstr SA01" \
760730
-i "pandas.tseries.offsets.QuarterEnd.is_on_offset GL08" \
761731
-i "pandas.tseries.offsets.QuarterEnd.n GL08" \

‎doc/source/user_guide/merging.rst

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -763,7 +763,7 @@ Joining a single Index to a MultiIndex
763763
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
764764

765765
You can join a :class:`DataFrame` with a :class:`Index` to a :class:`DataFrame` with a :class:`MultiIndex` on a level.
766-
The ``name`` of the :class:`Index` with match the level name of the :class:`MultiIndex`.
766+
The ``name`` of the :class:`Index` will match the level name of the :class:`MultiIndex`.
767767

768768
.. ipython:: python
769769

‎doc/source/user_guide/style.ipynb

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -211,7 +211,7 @@
211211
"source": [
212212
"## Styler Object and HTML \n",
213213
"\n",
214-
"The [Styler][styler] was originally constructed to support the wide array of HTML formatting options. Its HTML output creates an HTML `<table>` and leverages CSS styling language to manipulate many parameters including colors, fonts, borders, background, etc. See [here][w3schools] for more information on styling HTML tables. This allows a lot of flexibility out of the box, and even enables web developers to integrate DataFrames into their exiting user interface designs.\n",
214+
"The [Styler][styler] was originally constructed to support the wide array of HTML formatting options. Its HTML output creates an HTML `<table>` and leverages CSS styling language to manipulate many parameters including colors, fonts, borders, background, etc. See [here][w3schools] for more information on styling HTML tables. This allows a lot of flexibility out of the box, and even enables web developers to integrate DataFrames into their existing user interface designs.\n",
215215
"\n",
216216
"Below we demonstrate the default output, which looks very similar to the standard DataFrame HTML representation. But the HTML here has already attached some CSS classes to each cell, even if we haven't yet created any styles. We can view these by calling the [.to_html()][tohtml] method, which returns the raw HTML as string, which is useful for further processing or adding to a file - read on in [More about CSS and HTML](#More-About-CSS-and-HTML). This section will also provide a walkthrough for how to convert this default output to represent a DataFrame output that is more communicative. For example how we can build `s`:\n",
217217
"\n",

‎doc/source/user_guide/timeseries.rst

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -326,7 +326,7 @@ which can be specified. These are computed from the starting point specified by
326326
.. note::
327327

328328
The ``unit`` parameter does not use the same strings as the ``format`` parameter
329-
that was discussed :ref:`above<timeseries.converting.format>`). The
329+
that was discussed :ref:`above<timeseries.converting.format>`. The
330330
available units are listed on the documentation for :func:`pandas.to_datetime`.
331331

332332
Constructing a :class:`Timestamp` or :class:`DatetimeIndex` with an epoch timestamp

‎doc/source/whatsnew/v3.0.0.rst

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -247,6 +247,7 @@ Removal of prior version deprecations/changes
247247
- Removed the "closed" and "normalize" keywords in :meth:`DatetimeIndex.__new__` (:issue:`52628`)
248248
- Removed the deprecated ``delim_whitespace`` keyword in :func:`read_csv` and :func:`read_table`, use ``sep=r"\s+"`` instead (:issue:`55569`)
249249
- Require :meth:`SparseDtype.fill_value` to be a valid value for the :meth:`SparseDtype.subtype` (:issue:`53043`)
250+
- Stopped automatically casting non-datetimelike values (mainly strings) in :meth:`Series.isin` and :meth:`Index.isin` with ``datetime64``, ``timedelta64``, and :class:`PeriodDtype` dtypes (:issue:`53111`)
250251
- Stopped performing dtype inference when setting a :class:`Index` into a :class:`DataFrame` (:issue:`56102`)
251252
- Stopped performing dtype inference with in :meth:`Index.insert` with object-dtype index; this often affects the index/columns that result when setting new entries into an empty :class:`Series` or :class:`DataFrame` (:issue:`51363`)
252253
- Removed the "closed" and "unit" keywords in :meth:`TimedeltaIndex.__new__` (:issue:`52628`, :issue:`55499`)
@@ -476,7 +477,7 @@ Groupby/resample/rolling
476477
Reshaping
477478
^^^^^^^^^
478479
- Bug in :meth:`DataFrame.join` inconsistently setting result index name (:issue:`55815`)
479-
-
480+
- Bug in :meth:`DataFrame.unstack` producing incorrect results when ``sort=False`` (:issue:`54987`, :issue:`55516`)
480481

481482
Sparse
482483
^^^^^^

‎pandas/_config/config.py

Lines changed: 6 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -157,6 +157,12 @@ def get_option(pat: str) -> Any:
157157
------
158158
OptionError : if no such option exists
159159
160+
See Also
161+
--------
162+
set_option : Set the value of the specified option or options.
163+
reset_option : Reset one or more options to their default value.
164+
describe_option : Print the description for one or more registered options.
165+
160166
Notes
161167
-----
162168
For all available options, please view the :ref:`User Guide <options.available>`

‎pandas/_libs/lib.pyx

Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -184,6 +184,13 @@ def is_scalar(val: object) -> bool:
184184
bool
185185
Return True if given object is scalar.
186186

187+
See Also
188+
--------
189+
api.types.is_list_like : Check if the input is list-like.
190+
api.types.is_integer : Check if the input is an integer.
191+
api.types.is_float : Check if the input is a float.
192+
api.types.is_bool : Check if the input is a boolean.
193+
187194
Examples
188195
--------
189196
>>> import datetime
@@ -1442,6 +1449,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
14421449
Parameters
14431450
----------
14441451
value : scalar, list, ndarray, or pandas type
1452+
The input data to infer the dtype.
14451453
skipna : bool, default True
14461454
Ignore NaN values when inferring the type.
14471455

@@ -1476,6 +1484,14 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
14761484
TypeError
14771485
If ndarray-like but cannot infer the dtype
14781486

1487+
See Also
1488+
--------
1489+
api.types.is_scalar : Check if the input is a scalar.
1490+
api.types.is_list_like : Check if the input is list-like.
1491+
api.types.is_integer : Check if the input is an integer.
1492+
api.types.is_float : Check if the input is a float.
1493+
api.types.is_bool : Check if the input is a boolean.
1494+
14791495
Notes
14801496
-----
14811497
- 'mixed' is the catchall for anything that is not otherwise

‎pandas/_libs/tslibs/nattype.pyx

Lines changed: 50 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -419,6 +419,12 @@ class NaTType(_NaT):
419419
420420
Monday == 0 ... Sunday == 6.
421421
422+
See Also
423+
--------
424+
Timestamp.dayofweek : Return the day of the week with Monday=0, Sunday=6.
425+
Timestamp.isoweekday : Return the day of the week with Monday=1, Sunday=7.
426+
datetime.date.weekday : Equivalent method in datetime module.
427+
422428
Examples
423429
--------
424430
>>> ts = pd.Timestamp('2023-01-01')
@@ -528,6 +534,12 @@ class NaTType(_NaT):
528534
"""
529535
Return a named tuple containing ISO year, week number, and weekday.
530536
537+
See Also
538+
--------
539+
DatetimeIndex.isocalendar : Return a 3-tuple containing ISO year,
540+
week number, and weekday for the given DatetimeIndex object.
541+
datetime.date.isocalendar : The equivalent method for `datetime.date` objects.
542+
531543
Examples
532544
--------
533545
>>> ts = pd.Timestamp('2023-01-01 10:00:00')
@@ -542,6 +554,14 @@ class NaTType(_NaT):
542554
"""
543555
Return the daylight saving time (DST) adjustment.
544556
557+
This method returns the DST adjustment as a `datetime.timedelta` object
558+
if the Timestamp is timezone-aware and DST is applicable.
559+
560+
See Also
561+
--------
562+
Timestamp.tz_localize : Localize the Timestamp to a timezone.
563+
Timestamp.tz_convert : Convert timezone-aware Timestamp to another time zone.
564+
545565
Examples
546566
--------
547567
>>> ts = pd.Timestamp('2000-06-01 00:00:00', tz='Europe/Brussels')
@@ -814,6 +834,11 @@ class NaTType(_NaT):
814834
"""
815835
Convert timezone-aware Timestamp to another time zone.
816836
837+
This method is used to convert a timezone-aware Timestamp object to a
838+
different time zone. The original UTC time remains the same; only the
839+
time zone information is changed. If the Timestamp is timezone-naive, a
840+
TypeError is raised.
841+
817842
Parameters
818843
----------
819844
tz : str, pytz.timezone, dateutil.tz.tzfile or None
@@ -829,6 +854,13 @@ class NaTType(_NaT):
829854
TypeError
830855
If Timestamp is tz-naive.
831856
857+
See Also
858+
--------
859+
Timestamp.tz_localize : Localize the Timestamp to a timezone.
860+
DatetimeIndex.tz_convert : Convert a DatetimeIndex to another time zone.
861+
DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
862+
datetime.datetime.astimezone : Convert a datetime object to another time zone.
863+
832864
Examples
833865
--------
834866
Create a timestamp object with UTC timezone:
@@ -1196,6 +1228,12 @@ timedelta}, default 'raise'
11961228
------
11971229
ValueError if the freq cannot be converted.
11981230
1231+
See Also
1232+
--------
1233+
Timestamp.floor : Round down a Timestamp to the specified resolution.
1234+
Timestamp.round : Round a Timestamp to the specified resolution.
1235+
Series.dt.ceil : Ceil the datetime values in a Series.
1236+
11991237
Notes
12001238
-----
12011239
If the Timestamp has a timezone, ceiling will take place relative to the
@@ -1256,6 +1294,11 @@ timedelta}, default 'raise'
12561294
"""
12571295
Convert timezone-aware Timestamp to another time zone.
12581296
1297+
This method is used to convert a timezone-aware Timestamp object to a
1298+
different time zone. The original UTC time remains the same; only the
1299+
time zone information is changed. If the Timestamp is timezone-naive, a
1300+
TypeError is raised.
1301+
12591302
Parameters
12601303
----------
12611304
tz : str, pytz.timezone, dateutil.tz.tzfile or None
@@ -1271,6 +1314,13 @@ timedelta}, default 'raise'
12711314
TypeError
12721315
If Timestamp is tz-naive.
12731316
1317+
See Also
1318+
--------
1319+
Timestamp.tz_localize : Localize the Timestamp to a timezone.
1320+
DatetimeIndex.tz_convert : Convert a DatetimeIndex to another time zone.
1321+
DatetimeIndex.tz_localize : Localize a DatetimeIndex to a specific time zone.
1322+
datetime.datetime.astimezone : Convert a datetime object to another time zone.
1323+
12741324
Examples
12751325
--------
12761326
Create a timestamp object with UTC timezone:

0 commit comments

Comments
 (0)