BUG: fix DataFrame(data=[None, 1], dtype='timedelta64[ns]') raising ValueError

doc/source/whatsnew/v3.0.0.rst

@@ -613,6 +613,7 @@ 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`)

pandas/core/construction.py

@@ -807,6 +807,12 @@ def _try_cast(
         )
 
     elif dtype.kind in "mM":
+        if is_ndarray:
+            arr = cast(np.ndarray, arr)
+            if arr.ndim == 2 and arr.shape[1] == 1:
+                # GH#60081: DataFrame Constructor converts 1D data to array of
+                # shape (N, 1), but maybe_cast_to_datetime assumes 1D input
+                return maybe_cast_to_datetime(arr[:, 0], dtype).reshape(arr.shape)
         return maybe_cast_to_datetime(arr, dtype)
 
     # GH#15832: Check if we are requesting a numeric dtype and

pandas/core/dtypes/cast.py

@@ -1205,7 +1205,7 @@ def maybe_infer_to_datetimelike(
 
 def maybe_cast_to_datetime(
     value: np.ndarray | list, dtype: np.dtype
-) -> ExtensionArray | np.ndarray:
+) -> DatetimeArray | TimedeltaArray | np.ndarray:
     """
     try to cast the array/value to a datetimelike dtype, converting float
     nan to iNaT

pandas/tests/frame/test_constructors.py

@@ -2772,6 +2772,14 @@ def test_construction_datetime_resolution_inference(self, cons):
         res_dtype2 = tm.get_dtype(obj2)
         assert res_dtype2 == "M8[us, US/Pacific]", res_dtype2
 
+    def test_construction_nan_value_timedelta64_dtype(self):
+        # GH#60064
+        result = DataFrame([None, 1], dtype="timedelta64[ns]")
+        expected = DataFrame(
+            ["NaT", "0 days 00:00:00.000000001"], dtype="timedelta64[ns]"
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 class TestDataFrameConstructorIndexInference:
     def test_frame_from_dict_of_series_overlapping_monthly_period_indexes(self):