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DOC: fix pandas.TimedeltaIndex.to_pytimedelta RT03,SA01 #59903

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2283ae7
seperate examples for pandas.str.is methods
saldanhad Sep 20, 2024
f19163c
pre-commit checks done
saldanhad Sep 20, 2024
db61289
refactor docstrings for ismethods
saldanhad Sep 26, 2024
99d79d8
Merge branch 'main' into dev1
saldanhad Sep 26, 2024
4e9935c
resolve conflicts code_checks.sh
saldanhad Sep 26, 2024
42fc0a3
code_checks.sh
saldanhad Sep 26, 2024
cf4271d
fix docstrings -TimedeltIndex.to_pytimedelta
saldanhad Sep 26, 2024
24f6844
Merge branch 'main' into timedeltas
saldanhad Sep 27, 2024
484000d
Merge branch 'main' into timedeltas
saldanhad Sep 28, 2024
9cbc962
Merge branch 'main' into dev1
saldanhad Sep 28, 2024
756b4cc
remove duplicated line for isdecimal
saldanhad Sep 28, 2024
3a25b9e
Merge branch 'dev1' of https://github.com/saldanhad/pandas-repo into …
saldanhad Sep 28, 2024
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14 changes: 13 additions & 1 deletion ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -70,8 +70,10 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
--format=actions \
-i ES01 `# For now it is ok if docstrings are missing the extended summary` \
-i "pandas.Series.dt PR01" `# Accessors are implemented as classes, but we do not document the Parameters section` \
-i "pandas.NA SA01" \
-i "pandas.Period.freq GL08" \
-i "pandas.Period.ordinal GL08" \
-i "pandas.PeriodDtype.freq SA01" \
-i "pandas.RangeIndex.from_range PR01,SA01" \
-i "pandas.Series.cat.add_categories PR01,PR02" \
-i "pandas.Series.cat.as_ordered PR01" \
Expand Down Expand Up @@ -101,14 +103,14 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.Timedelta.max PR02" \
-i "pandas.Timedelta.min PR02" \
-i "pandas.Timedelta.resolution PR02" \
-i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
-i "pandas.Timestamp.max PR02" \
-i "pandas.Timestamp.min PR02" \
-i "pandas.Timestamp.nanosecond GL08" \
-i "pandas.Timestamp.resolution PR02" \
-i "pandas.Timestamp.tzinfo GL08" \
-i "pandas.Timestamp.year GL08" \
-i "pandas.api.types.is_dict_like PR07,SA01" \
-i "pandas.api.types.is_extension_array_dtype SA01" \
-i "pandas.api.types.is_file_like PR07,SA01" \
-i "pandas.api.types.is_float PR01,SA01" \
-i "pandas.api.types.is_hashable PR01,RT03,SA01" \
Expand All @@ -120,6 +122,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.api.types.pandas_dtype PR07,RT03,SA01" \
-i "pandas.arrays.ArrowExtensionArray PR07,SA01" \
-i "pandas.arrays.DatetimeArray SA01" \
-i "pandas.arrays.FloatingArray SA01" \
-i "pandas.arrays.IntegerArray SA01" \
-i "pandas.arrays.IntervalArray.left SA01" \
-i "pandas.arrays.IntervalArray.length SA01" \
Expand All @@ -133,12 +136,16 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.groups SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.hist RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.max SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.min SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.ohlc SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.sum SA01" \
-i "pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.agg RT03" \
-i "pandas.core.groupby.SeriesGroupBy.aggregate RT03" \
Expand All @@ -147,10 +154,13 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.groupby.SeriesGroupBy.indices SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.max SA01" \
-i "pandas.core.groupby.SeriesGroupBy.min SA01" \
-i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
-i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
-i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
-i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
-i "pandas.core.groupby.SeriesGroupBy.sum SA01" \
-i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \
-i "pandas.core.resample.Resampler.get_group RT03,SA01" \
-i "pandas.core.resample.Resampler.groups SA01" \
Expand All @@ -176,6 +186,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.errors.IntCastingNaNError SA01" \
-i "pandas.errors.InvalidIndexError SA01" \
-i "pandas.errors.InvalidVersion SA01" \
-i "pandas.errors.MergeError SA01" \
-i "pandas.errors.NullFrequencyError SA01" \
-i "pandas.errors.NumExprClobberingError SA01" \
-i "pandas.errors.NumbaUtilError SA01" \
Expand Down Expand Up @@ -367,6 +378,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.tseries.offsets.Week.n GL08" \
-i "pandas.tseries.offsets.Week.normalize GL08" \
-i "pandas.tseries.offsets.Week.weekday GL08" \
-i "pandas.tseries.offsets.WeekOfMonth SA01" \
-i "pandas.tseries.offsets.WeekOfMonth.is_on_offset GL08" \
-i "pandas.tseries.offsets.WeekOfMonth.n GL08" \
-i "pandas.tseries.offsets.WeekOfMonth.normalize GL08" \
Expand Down
24 changes: 23 additions & 1 deletion pandas/core/arrays/timedeltas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -789,7 +789,20 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:

Returns
-------
numpy.ndarray
**numpy.ndarray**
A NumPy ``timedelta64`` object representing the same duration as the
original pandas ``Timedelta`` object. The precision of the resulting
object is in nanoseconds, which is the default
time resolution used by pandas for ``Timedelta`` objects, ensuring
high precision for time-based calculations.

See Also
--------
to_timedelta : Convert argument to timedelta format.
Timedelta : Represents a duration between two dates or times.
DatetimeIndex: Index of datetime64 data.
Timedelta.components : Return a components namedtuple-like
of a single timedelta.

Examples
--------
Expand All @@ -800,7 +813,16 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
>>> tdelta_idx.to_pytimedelta()
array([datetime.timedelta(days=1), datetime.timedelta(days=2),
datetime.timedelta(days=3)], dtype=object)

>>> tidx = pd.TimedeltaIndex(data=["1 days 02:30:45", "3 days 04:15:10"])
>>> tidx
TimedeltaIndex(['1 days 02:30:45', '3 days 04:15:10'],
dtype='timedelta64[ns]', freq=None)
>>> tidx.to_pytimedelta()
array([datetime.timedelta(days=1, seconds=9045),
datetime.timedelta(days=3, seconds=15310)], dtype=object)
"""

return ints_to_pytimedelta(self._ndarray)

days_docstring = textwrap.dedent(
Expand Down
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