Move to maybe_downcast_to_dtype

Author: yuanx749

doc/source/whatsnew/v3.0.0.rst

@@ -611,6 +611,7 @@ Categorical
 Datetimelike
 ^^^^^^^^^^^^
 - Bug in :attr:`is_year_start` where a DateTimeIndex constructed via a date_range with frequency 'MS' wouldn't have the correct year or quarter start attributes (:issue:`57377`)
+- Bug in :class:`DataFrame` raising ``ValueError`` when ``dtype`` is ``timedelta64`` and ``data`` is a list containing ``None`` (:issue:`60064`)
 - Bug in :class:`Timestamp` constructor failing to raise when ``tz=None`` is explicitly specified in conjunction with timezone-aware ``tzinfo`` or data (:issue:`48688`)
 - Bug in :func:`date_range` where the last valid timestamp would sometimes not be produced (:issue:`56134`)
 - Bug in :func:`date_range` where using a negative frequency value would not include all points between the start and end values (:issue:`56147`)
@@ -758,7 +759,6 @@ Styler
 
 Other
 ^^^^^
-- Bug in :class:`DataFrame` raising ``ValueError`` when ``dtype`` is ``timedelta64`` and ``data`` is a list containing ``None`` (:issue:`60064`)
 - Bug in :class:`DataFrame` when passing a ``dict`` with a NA scalar and ``columns`` that would always return ``np.nan`` (:issue:`57205`)
 - Bug in :func:`eval` on :class:`ExtensionArray` on including division ``/`` failed with a ``TypeError``. (:issue:`58748`)
 - Bug in :func:`eval` where the names of the :class:`Series` were not preserved when using ``engine="numexpr"``. (:issue:`10239`)

pandas/core/arrays/timedeltas.py

@@ -1111,7 +1111,7 @@ def sequence_to_td64ns(
         else:
             mask = np.isnan(data)
 
-        data = cast_from_unit_vectorized(data.ravel(), unit or "ns").reshape(data.shape)
+        data = cast_from_unit_vectorized(data, unit or "ns")
         data[mask] = iNaT
         data = data.view("m8[ns]")
         copy = False

pandas/core/dtypes/cast.py

@@ -1225,6 +1225,9 @@ def maybe_cast_to_datetime(
     _ensure_nanosecond_dtype(dtype)
 
     if lib.is_np_dtype(dtype, "m"):
+        if getattr(value, "ndim", 1) == 2 and value.shape[1] == 1:
+            res = TimedeltaArray._from_sequence(value.ravel(), dtype=dtype)
+            return res.reshape(value.shape)
         res = TimedeltaArray._from_sequence(value, dtype=dtype)
         return res
     else: