DEPR: to_pytimedelta return Index[object]

doc/source/whatsnew/v3.0.0.rst

@@ -199,6 +199,7 @@ Other Deprecations
 - Deprecated allowing non-keyword arguments in :meth:`DataFrame.all`, :meth:`DataFrame.min`, :meth:`DataFrame.max`, :meth:`DataFrame.sum`, :meth:`DataFrame.prod`, :meth:`DataFrame.mean`, :meth:`DataFrame.median`, :meth:`DataFrame.sem`, :meth:`DataFrame.var`, :meth:`DataFrame.std`, :meth:`DataFrame.skew`, :meth:`DataFrame.kurt`, :meth:`Series.all`,  :meth:`Series.min`, :meth:`Series.max`, :meth:`Series.sum`, :meth:`Series.prod`, :meth:`Series.mean`, :meth:`Series.median`, :meth:`Series.sem`, :meth:`Series.var`, :meth:`Series.std`, :meth:`Series.skew`, and :meth:`Series.kurt`. (:issue:`57087`)
 - Deprecated allowing non-keyword arguments in :meth:`Series.to_markdown` except ``buf``. (:issue:`57280`)
 - Deprecated allowing non-keyword arguments in :meth:`Series.to_string` except ``buf``. (:issue:`57280`)
+- Deprecated behavior of :meth:`Series.dt.to_pytimedelta`, in a future version this will return a :class:`Series` containing python ``datetime.timedelta`` objects instead of an ``ndarray`` of timedelta; this matches the behavior of other :meth:`Series.dt` properties. (:issue:`57463`)
 - Deprecated using ``epoch`` date format in :meth:`DataFrame.to_json` and :meth:`Series.to_json`, use ``iso`` instead. (:issue:`57063`)
 -
 

pandas/conftest.py

@@ -157,6 +157,7 @@ def pytest_collection_modifyitems(items, config) -> None:
         ("SeriesGroupBy.fillna", "SeriesGroupBy.fillna is deprecated"),
         ("SeriesGroupBy.idxmin", "The behavior of Series.idxmin"),
         ("SeriesGroupBy.idxmax", "The behavior of Series.idxmax"),
+        ("to_pytimedelta", "The behavior of TimedeltaProperties.to_pytimedelta"),
         # Docstring divides by zero to show behavior difference
         ("missing.mask_zero_div_zero", "divide by zero encountered"),
         (

pandas/core/indexes/accessors.py

@@ -9,10 +9,12 @@
     NoReturn,
     cast,
 )
+import warnings
 
 import numpy as np
 
 from pandas._libs import lib
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_integer_dtype,
@@ -210,6 +212,15 @@ def _delegate_method(self, name: str, *args, **kwargs):
         return result
 
     def to_pytimedelta(self):
+        # GH 57463
+        warnings.warn(
+            f"The behavior of {type(self).__name__}.to_pytimedelta is deprecated, "
+            "in a future version this will return a Series containing python "
+            "datetime.timedelta objects instead of an ndarray. To retain the "
+            "old behavior, call `np.array` on the result",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         return cast(ArrowExtensionArray, self._parent.array)._dt_to_pytimedelta()
 
     def to_pydatetime(self) -> Series:
@@ -462,6 +473,15 @@ def to_pytimedelta(self) -> np.ndarray:
         datetime.timedelta(days=2), datetime.timedelta(days=3),
         datetime.timedelta(days=4)], dtype=object)
         """
+        # GH 57463
+        warnings.warn(
+            f"The behavior of {type(self).__name__}.to_pytimedelta is deprecated, "
+            "in a future version this will return a Series containing python "
+            "datetime.timedelta objects instead of an ndarray. To retain the "
+            "old behavior, call `np.array` on the result",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         return self._get_values().to_pytimedelta()
 
     @property

pandas/tests/extension/test_arrow.py

@@ -2861,12 +2861,16 @@ def test_dt_to_pytimedelta():
     data = [timedelta(1, 2, 3), timedelta(1, 2, 4)]
     ser = pd.Series(data, dtype=ArrowDtype(pa.duration("ns")))
 
-    result = ser.dt.to_pytimedelta()
+    msg = "The behavior of ArrowTemporalProperties.to_pytimedelta is deprecated"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        result = ser.dt.to_pytimedelta()
     expected = np.array(data, dtype=object)
     tm.assert_numpy_array_equal(result, expected)
     assert all(type(res) is timedelta for res in result)
 
-    expected = ser.astype("timedelta64[ns]").dt.to_pytimedelta()
+    msg = "The behavior of TimedeltaProperties.to_pytimedelta is deprecated"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        expected = ser.astype("timedelta64[ns]").dt.to_pytimedelta()
     tm.assert_numpy_array_equal(result, expected)
 
 

pandas/tests/series/accessors/test_cat_accessor.py

@@ -200,6 +200,9 @@ def test_dt_accessor_api_for_categorical(self, idx):
             if func == "to_period" and getattr(idx, "tz", None) is not None:
                 # dropping TZ
                 warn_cls.append(UserWarning)
+            elif func == "to_pytimedelta":
+                # GH 57463
+                warn_cls.append(FutureWarning)
             if warn_cls:
                 warn_cls = tuple(warn_cls)
             else:

pandas/tests/series/accessors/test_dt_accessor.py

@@ -192,7 +192,9 @@ def test_dt_namespace_accessor_timedelta(self):
             assert isinstance(result, DataFrame)
             tm.assert_index_equal(result.index, ser.index)
 
-            result = ser.dt.to_pytimedelta()
+            msg = "The behavior of TimedeltaProperties.to_pytimedelta is deprecated"
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                result = ser.dt.to_pytimedelta()
             assert isinstance(result, np.ndarray)
             assert result.dtype == object