BUG: fix for _validate_setitem_value fails to raise for PandasArray and fix tests

doc/source/whatsnew/v3.0.0.rst

@@ -627,6 +627,7 @@ ExtensionArray
 - Bug in :meth:`.arrays.ArrowExtensionArray.__setitem__` which caused wrong behavior when using an integer array with repeated values as a key (:issue:`58530`)
 - Bug in :meth:`api.types.is_datetime64_any_dtype` where a custom :class:`ExtensionDtype` would return ``False`` for array-likes (:issue:`57055`)
 - Bug in various :class:`DataFrame` reductions for pyarrow temporal dtypes returning incorrect dtype when result was null (:issue:`59234`)
+- Bug in :class:`NumpyExtensionArray` where it did not raise any error if validated value to be inserted did not have the same dtype (:issue:`51044`).
 
 Styler
 ^^^^^^

pandas/core/arrays/numpy_.py

@@ -232,6 +232,85 @@ def _validate_scalar(self, fill_value):
             fill_value = self.dtype.na_value
         return fill_value
 
+    def _validate_setitem_value(self, value) -> type(value) | None:
+        """
+        Check if we have a scalar that we can cast losslessly.
+
+        Raises
+        ------
+        TypeError
+        """
+
+        kind = self.dtype.kind
+
+        if kind == "b":
+            if lib.is_bool(value) or np.can_cast(type(value), self.dtype.type):
+                return value
+            if isinstance(value, NumpyExtensionArray) and (
+                lib.is_bool_array(value.to_numpy())
+                or lib.is_bool_list(value.to_numpy())
+            ):
+                return value
+
+        elif kind == "i":
+            if lib.is_integer(value) or np.can_cast(type(value), self.dtype.type):
+                return value
+            if isinstance(value, NumpyExtensionArray) and lib.is_integer_array(
+                value.to_numpy()
+            ):
+                return value
+
+        elif kind == "u":
+            if (lib.is_integer(value) and value > -1) or np.can_cast(
+                type(value), self.dtype.type
+            ):
+                return value
+
+        elif kind == "c":
+            if lib.is_complex(value) or np.can_cast(type(value), self.dtype.type):
+                return value
+
+        elif kind == "S":
+            if isinstance(value, str) or np.can_cast(type(value), self.dtype.type):
+                return value
+            if isinstance(value, NumpyExtensionArray) and lib.is_string_array(
+                value.to_numpy()
+            ):
+                return value
+
+        elif kind == "M":
+            if isinstance(value, np.datetime64):
+                return value
+            if isinstance(value, NumpyExtensionArray) and (
+                lib.is_date_array(value.to_numpy())
+                or lib.is_datetime_array(value.to_numpy())
+                or lib.is_datetime64_array(value.to_numpy())
+                or lib.is_datetime_with_singletz_array(value.to_numpy())
+            ):
+                return value
+
+        elif kind == "m":
+            if isinstance(value, np.timedelta64):
+                return value
+            if isinstance(value, NumpyExtensionArray) and (
+                lib.is_timedelta_or_timedelta64_array(value.to_numpy())
+                or lib.is_time_array(value.to_numpy())
+            ):
+                return value
+
+        elif kind == "f":
+            if lib.is_float(value) or np.can_cast(type(value), self.dtype.type):
+                return value
+            if isinstance(value, NumpyExtensionArray) and lib.is_float_array(
+                value.to_numpy()
+            ):
+                return value
+
+        elif np.can_cast(type(value), self.dtype.type):
+            return value
+
+        raise TypeError(f"Invalid value '{value!s}' for dtype {self.dtype}")
+
     def _values_for_factorize(self) -> tuple[np.ndarray, float | None]:
         if self.dtype.kind in "iub":
             fv = None

pandas/tests/arrays/numpy_/test_numpy.py

@@ -275,12 +275,15 @@ def test_setitem_object_typecode(dtype):
 def test_setitem_no_coercion():
     # https://github.com/pandas-dev/pandas/issues/28150
     arr = NumpyExtensionArray(np.array([1, 2, 3]))
-    with pytest.raises(ValueError, match="int"):
+    with pytest.raises(TypeError):
         arr[0] = "a"
 
     # With a value that we do coerce, check that we coerce the value
     #  and not the underlying array.
-    arr[0] = 2.5
+    with pytest.raises(TypeError):
+        arr[0] = 2.5
+
+    arr[0] = 9
     assert isinstance(arr[0], (int, np.integer)), type(arr[0])
 
 
@@ -296,7 +299,10 @@ def test_setitem_preserves_views():
     assert view2[0] == 9
     assert view3[0] == 9
 
-    arr[-1] = 2.5
+    with pytest.raises(TypeError):
+        arr[-1] = 2.5
+
+    arr[-1] = 4
     view1[-1] = 5
     assert arr[-1] == 5