BUG: Fix cast_pointwise_result with all-NA values

doc/source/whatsnew/v3.0.0.rst

@@ -943,7 +943,6 @@ Numeric
 
 Conversion
 ^^^^^^^^^^
-- Bug in :meth:`BaseMaskedArray._cast_pointwise_result` with all-NA values results returned ``object`` dtype instead of preserving the original dtype (:issue:`62344`)
 - Bug in :meth:`DataFrame.astype` not casting ``values`` for Arrow-based dictionary dtype correctly (:issue:`58479`)
 - Bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
 - Bug in :meth:`Series.astype` might modify read-only array inplace when casting to a string dtype (:issue:`57212`)

pandas/_libs/lib.pyi

@@ -94,6 +94,7 @@ def maybe_convert_objects(
     convert_numeric: bool = ...,
     convert_non_numeric: Literal[False] = ...,
     convert_to_nullable_dtype: Literal[False] = ...,
+    dtype_if_all_na: DtypeObj | None = ...,
     dtype_if_all_nat: DtypeObj | None = ...,
 ) -> npt.NDArray[np.object_ | np.number]: ...
 @overload
@@ -105,6 +106,7 @@ def maybe_convert_objects(
     convert_numeric: bool = ...,
     convert_non_numeric: bool = ...,
     convert_to_nullable_dtype: Literal[True] = ...,
+    dtype_if_all_na: DtypeObj | None = ...,
     dtype_if_all_nat: DtypeObj | None = ...,
 ) -> ArrayLike: ...
 @overload
@@ -116,6 +118,7 @@ def maybe_convert_objects(
     convert_numeric: bool = ...,
     convert_non_numeric: bool = ...,
     convert_to_nullable_dtype: bool = ...,
+    dtype_if_all_na: DtypeObj | None = ...,
     dtype_if_all_nat: DtypeObj | None = ...,
 ) -> ArrayLike: ...
 @overload

pandas/_libs/lib.pyx

@@ -2545,6 +2545,7 @@ def maybe_convert_objects(ndarray[object] objects,
                           bint convert_numeric=True,  # NB: different default!
                           bint convert_to_nullable_dtype=False,
                           bint convert_non_numeric=False,
+                          object dtype_if_all_na=None,
                           object dtype_if_all_nat=None) -> "ArrayLike":
     """
     Type inference function-- convert object array to proper dtype
@@ -2566,6 +2567,8 @@ def maybe_convert_objects(ndarray[object] objects,
         encountered, whether to convert and return an Boolean/IntegerArray.
     convert_non_numeric : bool, default False
         Whether to convert datetime, timedelta, period, interval types.
+    dtype_if_all_na : np.dtype, ExtensionDtype, or None, default None
+        Dtype to cast to if we have all-NA or all-None.
     dtype_if_all_nat : np.dtype, ExtensionDtype, or None, default None
         Dtype to cast to if we have all-NaT.
 
@@ -2838,6 +2841,16 @@ def maybe_convert_objects(ndarray[object] objects,
         else:
             seen.object_ = True
 
+    elif seen.null_:
+        if not seen.object_ and not seen.numeric_ and not seen.bool_:
+            # all NaT, None, or nan (at least one NA or None)
+            dtype = dtype_if_all_na
+            if dtype is not None:
+                cls = dtype.construct_array_type()
+                obj = cls._from_sequence([], dtype=dtype)
+                taker = -np.ones((<object>objects).shape, dtype=np.intp)
+                return obj.take(taker, allow_fill=True)
+
     if not convert_numeric:
         # Note: we count "bool" as numeric here. This is because
         #  np.array(list_of_items) will convert bools just like it will numeric

pandas/core/arrays/masked.py

@@ -149,10 +149,10 @@ def _from_sequence(cls, scalars, *, dtype=None, copy: bool = False) -> Self:
         return cls(values, mask)
 
     def _cast_pointwise_result(self, values) -> ArrayLike:
-        if isna(values).all():
-            return type(self)._from_sequence(values, dtype=self.dtype)
         values = np.asarray(values, dtype=object)
-        result = lib.maybe_convert_objects(values, convert_to_nullable_dtype=True)
+        result = lib.maybe_convert_objects(
+            values, convert_to_nullable_dtype=True, dtype_if_all_na=self.dtype
+        )
         lkind = self.dtype.kind
         rkind = result.dtype.kind
         if (lkind in "iu" and rkind in "iu") or (lkind == rkind == "f"):

pandas/tests/extension/test_masked.py

@@ -364,19 +364,13 @@ def check_accumulate(self, ser: pd.Series, op_name: str, skipna: bool):
     def test_loc_setitem_with_expansion_preserves_ea_index_dtype(self, data, request):
         super().test_loc_setitem_with_expansion_preserves_ea_index_dtype(data)
 
-    @pytest.mark.parametrize(
-        "arr, values",
-        [
-            (pd.array([True, False]), [pd.NA, pd.NA]),
-            (pd.array([1, 2]), [pd.NA, pd.NA]),
-        ],
-    )
-    def test_cast_pointwise_result_all_na_respects_dtype(self, arr, values):
-        """
-        GH#62344
-        Ensure that _cast_pointwise_result respects the original dtype
-        even when the result consists entirely of NA values.
-        """
-        result = arr._cast_pointwise_result(values)
-        assert result.dtype == arr.dtype
-        assert all(x is pd.NA for x in result)
+
+@pytest.mark.parametrize(
+    "arr", [pd.array([True, False]), pd.array([1, 2]), pd.array([1.0, 2.0])]
+)
+def test_cast_pointwise_result_all_na_respects_original_dtype(arr):
+    # GH#62344
+    values = [pd.NA, pd.NA]
+    result = arr._cast_pointwise_result(values)
+    assert result.dtype == arr.dtype
+    assert all(x is pd.NA for x in result)