From 3ce2133016daa11c662c2fe55550bfdd243d1f04 Mon Sep 17 00:00:00 2001 From: cloudboat <15851404+cloudboat111@user.noreply.gitee.com> Date: Tue, 11 Nov 2025 22:25:18 +0800 Subject: [PATCH 1/4] REF: Replace @Substitution with hardcoded docstring in strftime --- pandas/core/arrays/datetimelike.py | 288 +++++++++++++++++++++++++++++ 1 file changed, 288 insertions(+) diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py index 1fbcd0665c467..7ff1130b6c95a 100644 --- a/pandas/core/arrays/datetimelike.py +++ b/pandas/core/arrays/datetimelike.py @@ -2265,6 +2265,102 @@ def round( ambiguous: TimeAmbiguous = "raise", nonexistent: TimeNonexistent = "raise", ) -> Self: + """ + Perform round operation on the data to the specified `freq`. + + Parameters + ---------- + freq : str or Offset + The frequency level to round the index to. Must be a fixed + frequency like 's' (second) not 'ME' (month end). See + :ref:`frequency aliases ` for + a list of possible `freq` values. + ambiguous : 'infer', bool-ndarray, 'NaT', default 'raise' + Only relevant for DatetimeIndex: + + - '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 a ValueError 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 a ValueError if there are + nonexistent times. + + Returns + ------- + DatetimeIndex, TimedeltaIndex, or Series + Index of the same type for a DatetimeIndex or TimedeltaIndex, + or a Series with the same index for a Series. + + Raises + ------ + ValueError if the `freq` cannot be converted. + + See Also + -------- + DatetimeIndex.floor : + Perform floor operation on the data to the specified `freq`. + DatetimeIndex.snap : + Snap time stamps to nearest occurring frequency. + + Notes + ----- + If the timestamps have a timezone, rounding will take place relative to the + local ("wall") time and re-localized to the same timezone. When rounding + near daylight savings time, use ``nonexistent`` and ``ambiguous`` to + control the re-localization behavior. + + Examples + -------- + **DatetimeIndex** + + >>> rng = pd.date_range("1/1/2018 11:59:00", periods=3, freq="min") + >>> rng + DatetimeIndex(['2018-01-01 11:59:00', '2018-01-01 12:00:00', + '2018-01-01 12:01:00'], + dtype='datetime64[ns]', freq='min') + + >>> rng.round("h") + DatetimeIndex(['2018-01-01 12:00:00', '2018-01-01 12:00:00', + '2018-01-01 12:00:00'], + dtype='datetime64[ns]', freq=None) + + **Series** + + >>> pd.Series(rng).dt.round("h") + 0 2018-01-01 12:00:00 + 1 2018-01-01 12:00:00 + 2 2018-01-01 12:00:00 + dtype: datetime64[ns] + + When rounding near a daylight savings time transition, use ``ambiguous`` or + ``nonexistent`` to control how the timestamp should be re-localized. + + >>> rng_tz = pd.DatetimeIndex(["2021-10-31 03:30:00"], tz="Europe/Amsterdam") + + >>> rng_tz.floor("2h", ambiguous=False) + DatetimeIndex(['2021-10-31 02:00:00+01:00'], + dtype='datetime64[s, Europe/Amsterdam]', freq=None) + + >>> rng_tz.floor("2h", ambiguous=True) + DatetimeIndex(['2021-10-31 02:00:00+02:00'], + dtype='datetime64[s, Europe/Amsterdam]', freq=None) + """ return self._round(freq, RoundTo.NEAREST_HALF_EVEN, ambiguous, nonexistent) @Appender((_round_doc + _floor_example).format(op="floor")) @@ -2274,6 +2370,102 @@ def floor( ambiguous: TimeAmbiguous = "raise", nonexistent: TimeNonexistent = "raise", ) -> Self: + """ + Perform floor operation on the data to the specified `freq`. + + Parameters + ---------- + freq : str or Offset + The frequency level to floor the index to. Must be a fixed + frequency like 's' (second) not 'ME' (month end). See + :ref:`frequency aliases ` for + a list of possible `freq` values. + ambiguous : 'infer', bool-ndarray, 'NaT', default 'raise' + Only relevant for DatetimeIndex: + + - '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 a ValueError 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 a ValueError if there are + nonexistent times. + + Returns + ------- + DatetimeIndex, TimedeltaIndex, or Series + Index of the same type for a DatetimeIndex or TimedeltaIndex, + or a Series with the same index for a Series. + + Raises + ------ + ValueError if the `freq` cannot be converted. + + See Also + -------- + DatetimeIndex.floor : + Perform floor operation on the data to the specified `freq`. + DatetimeIndex.snap : + Snap time stamps to nearest occurring frequency. + + Notes + ----- + If the timestamps have a timezone, flooring will take place relative to the + local ("wall") time and re-localized to the same timezone. When flooring + near daylight savings time, use ``nonexistent`` and ``ambiguous`` to + control the re-localization behavior. + + Examples + -------- + **DatetimeIndex** + + >>> rng = pd.date_range("1/1/2018 11:59:00", periods=3, freq="min") + >>> rng + DatetimeIndex(['2018-01-01 11:59:00', '2018-01-01 12:00:00', + '2018-01-01 12:01:00'], + dtype='datetime64[ns]', freq='min') + + >>> rng.floor("h") + DatetimeIndex(['2018-01-01 11:00:00', '2018-01-01 12:00:00', + '2018-01-01 12:00:00'], + dtype='datetime64[ns]', freq=None) + + **Series** + + >>> pd.Series(rng).dt.floor("h") + 0 2018-01-01 11:00:00 + 1 2018-01-01 12:00:00 + 2 2018-01-01 12:00:00 + dtype: datetime64[ns] + + When rounding near a daylight savings time transition, use ``ambiguous`` or + ``nonexistent`` to control how the timestamp should be re-localized. + + >>> rng_tz = pd.DatetimeIndex(["2021-10-31 03:30:00"], tz="Europe/Amsterdam") + + >>> rng_tz.floor("2h", ambiguous=False) + DatetimeIndex(['2021-10-31 02:00:00+01:00'], + dtype='datetime64[s, Europe/Amsterdam]', freq=None) + + >>> rng_tz.floor("2h", ambiguous=True) + DatetimeIndex(['2021-10-31 02:00:00+02:00'], + dtype='datetime64[s, Europe/Amsterdam]', freq=None) + """ return self._round(freq, RoundTo.MINUS_INFTY, ambiguous, nonexistent) @Appender((_round_doc + _ceil_example).format(op="ceil")) @@ -2283,6 +2475,102 @@ def ceil( ambiguous: TimeAmbiguous = "raise", nonexistent: TimeNonexistent = "raise", ) -> Self: + """ + Perform ceil operation on the data to the specified `freq`. + + Parameters + ---------- + freq : str or Offset + The frequency level to ceil the index to. Must be a fixed + frequency like 's' (second) not 'ME' (month end). See + :ref:`frequency aliases ` for + a list of possible `freq` values. + ambiguous : 'infer', bool-ndarray, 'NaT', default 'raise' + Only relevant for DatetimeIndex: + + - '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 a ValueError 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 a ValueError if there are + nonexistent times. + + Returns + ------- + DatetimeIndex, TimedeltaIndex, or Series + Index of the same type for a DatetimeIndex or TimedeltaIndex, + or a Series with the same index for a Series. + + Raises + ------ + ValueError if the `freq` cannot be converted. + + See Also + -------- + DatetimeIndex.floor : + Perform floor operation on the data to the specified `freq`. + DatetimeIndex.snap : + Snap time stamps to nearest occurring frequency. + + Notes + ----- + If the timestamps have a timezone, ceiling will take place relative to the + local ("wall") time and re-localized to the same timezone. When ceiling + near daylight savings time, use ``nonexistent`` and ``ambiguous`` to + control the re-localization behavior. + + Examples + -------- + **DatetimeIndex** + + >>> rng = pd.date_range("1/1/2018 11:59:00", periods=3, freq="min") + >>> rng + DatetimeIndex(['2018-01-01 11:59:00', '2018-01-01 12:00:00', + '2018-01-01 12:01:00'], + dtype='datetime64[ns]', freq='min') + + >>> rng.ceil("h") + DatetimeIndex(['2018-01-01 12:00:00', '2018-01-01 12:00:00', + '2018-01-01 13:00:00'], + dtype='datetime64[ns]', freq=None) + + **Series** + + >>> pd.Series(rng).dt.ceil("h") + 0 2018-01-01 12:00:00 + 1 2018-01-01 12:00:00 + 2 2018-01-01 13:00:00 + dtype: datetime64[ns] + + When rounding near a daylight savings time transition, use ``ambiguous`` or + ``nonexistent`` to control how the timestamp should be re-localized. + + >>> rng_tz = pd.DatetimeIndex(["2021-10-31 01:30:00"], tz="Europe/Amsterdam") + + >>> rng_tz.ceil("h", ambiguous=False) + DatetimeIndex(['2021-10-31 02:00:00+01:00'], + dtype='datetime64[s, Europe/Amsterdam]', freq=None) + + >>> rng_tz.ceil("h", ambiguous=True) + DatetimeIndex(['2021-10-31 02:00:00+02:00'], + dtype='datetime64[s, Europe/Amsterdam]', freq=None) + """ return self._round(freq, RoundTo.PLUS_INFTY, ambiguous, nonexistent) # -------------------------------------------------------------- From 7eb63bda45be76b1980f14d1e9bc17a6f2a42288 Mon Sep 17 00:00:00 2001 From: cloudboat <15851404+cloudboat111@user.noreply.gitee.com> Date: Tue, 11 Nov 2025 22:32:27 +0800 Subject: [PATCH 2/4] REF: Replace @Substitution with hardcoded docstring in strftime --- pandas/core/arrays/datetimelike.py | 11 +---------- 1 file changed, 1 insertion(+), 10 deletions(-) diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py index 7ff1130b6c95a..3df12c106dfb7 100644 --- a/pandas/core/arrays/datetimelike.py +++ b/pandas/core/arrays/datetimelike.py @@ -81,8 +81,6 @@ PerformanceWarning, ) from pandas.util._decorators import ( - Appender, - Substitution, cache_readonly, ) from pandas.util._exceptions import find_stack_level @@ -1774,10 +1772,6 @@ class DatelikeOps(DatetimeLikeArrayMixin): Common ops for DatetimeIndex/PeriodIndex, but not TimedeltaIndex. """ - @Substitution( - URL="https://docs.python.org/3/library/datetime.html" - "#strftime-and-strptime-behavior" - ) def strftime(self, date_format: str) -> npt.NDArray[np.object_]: """ Convert to Index using specified date_format. @@ -1785,7 +1779,7 @@ def strftime(self, date_format: str) -> npt.NDArray[np.object_]: Return an Index of formatted strings specified by date_format, which supports the same string format as the python standard library. Details of the string format can be found in `python string format - doc <%(URL)s>`__. + doc `__. Formats supported by the C `strftime` API but not by the python string format doc (such as `"%%R"`, `"%%r"`) are not officially supported and should be @@ -2258,7 +2252,6 @@ def _round(self, freq, mode, ambiguous, nonexistent): result = result.view(self._ndarray.dtype) return self._simple_new(result, dtype=self.dtype) - @Appender((_round_doc + _round_example).format(op="round")) def round( self, freq, @@ -2363,7 +2356,6 @@ def round( """ return self._round(freq, RoundTo.NEAREST_HALF_EVEN, ambiguous, nonexistent) - @Appender((_round_doc + _floor_example).format(op="floor")) def floor( self, freq, @@ -2468,7 +2460,6 @@ def floor( """ return self._round(freq, RoundTo.MINUS_INFTY, ambiguous, nonexistent) - @Appender((_round_doc + _ceil_example).format(op="ceil")) def ceil( self, freq, From 372e8fea1ed7a76ee2ded6a3b97f50b719c347d2 Mon Sep 17 00:00:00 2001 From: cloudboat <15851404+cloudboat111@user.noreply.gitee.com> Date: Tue, 11 Nov 2025 23:09:41 +0800 Subject: [PATCH 3/4] chang int the correct url --- pandas/core/arrays/datetimelike.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py index 3df12c106dfb7..4c1897082af5f 100644 --- a/pandas/core/arrays/datetimelike.py +++ b/pandas/core/arrays/datetimelike.py @@ -1779,7 +1779,8 @@ def strftime(self, date_format: str) -> npt.NDArray[np.object_]: Return an Index of formatted strings specified by date_format, which supports the same string format as the python standard library. Details of the string format can be found in `python string format - doc `__. + doc `__. Formats supported by the C `strftime` API but not by the python string format doc (such as `"%%R"`, `"%%r"`) are not officially supported and should be From 6fcd50d629a437c1d924f39e6f80d6994c14c129 Mon Sep 17 00:00:00 2001 From: cloudboat <15851404+cloudboat111@user.noreply.gitee.com> Date: Wed, 12 Nov 2025 14:44:30 +0800 Subject: [PATCH 4/4] remove %% --- pandas/core/arrays/datetimelike.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py index 3948dd539345a..adf94e62979f6 100644 --- a/pandas/core/arrays/datetimelike.py +++ b/pandas/core/arrays/datetimelike.py @@ -1788,9 +1788,9 @@ def strftime(self, date_format: str) -> npt.NDArray[np.object_]: #strftime-and-strptime-behavior>`__. Formats supported by the C `strftime` API but not by the python string format - doc (such as `"%%R"`, `"%%r"`) are not officially supported and should be - preferably replaced with their supported equivalents (such as `"%%H:%%M"`, - `"%%I:%%M:%%S %%p"`). + doc (such as `"%R"`, `"%r"`) are not officially supported and should be + preferably replaced with their supported equivalents (such as `"%H:%M"`, + `"%I:%M:%S %p"`). Note that `PeriodIndex` support additional directives, detailed in `Period.strftime`. @@ -1817,7 +1817,7 @@ def strftime(self, date_format: str) -> npt.NDArray[np.object_]: Examples -------- >>> rng = pd.date_range(pd.Timestamp("2018-03-10 09:00"), periods=3, freq="s") - >>> rng.strftime("%%B %%d, %%Y, %%r") + >>> rng.strftime("%B %d, %Y, %r") Index(['March 10, 2018, 09:00:00 AM', 'March 10, 2018, 09:00:01 AM', 'March 10, 2018, 09:00:02 AM'], dtype='str')