@@ -790,6 +790,19 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
790790 Returns
791791 -------
792792 numpy.ndarray
793+ A NumPy ``timedelta64`` object representing the same duration as the
794+ original pandas ``Timedelta`` object. The precision of the resulting
795+ object is in nanoseconds, which is the default
796+ time resolution used by pandas for ``Timedelta`` objects, ensuring
797+ high precision for time-based calculations.
798+
799+ See Also
800+ --------
801+ to_timedelta : Convert argument to timedelta format.
802+ Timedelta : Represents a duration between two dates or times.
803+ DatetimeIndex: Index of datetime64 data.
804+ Timedelta.components : Return a components namedtuple-like
805+ of a single timedelta.
793806
794807 Examples
795808 --------
@@ -800,6 +813,14 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
800813 >>> tdelta_idx.to_pytimedelta()
801814 array([datetime.timedelta(days=1), datetime.timedelta(days=2),
802815 datetime.timedelta(days=3)], dtype=object)
816+
817+ >>> tidx = pd.TimedeltaIndex(data=["1 days 02:30:45", "3 days 04:15:10"])
818+ >>> tidx
819+ TimedeltaIndex(['1 days 02:30:45', '3 days 04:15:10'],
820+ dtype='timedelta64[ns]', freq=None)
821+ >>> tidx.to_pytimedelta()
822+ array([datetime.timedelta(days=1, seconds=9045),
823+ datetime.timedelta(days=3, seconds=15310)], dtype=object)
803824 """
804825 return ints_to_pytimedelta (self ._ndarray )
805826
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