BUG: Fix boolean value of NA is ambiguous in iloc assignment

pandas/core/arrays/numeric.py

@@ -28,6 +28,7 @@
     BaseMaskedArray,
     BaseMaskedDtype,
 )
+from pandas.core.construction import extract_array
 
 if TYPE_CHECKING:
     from collections.abc import (
@@ -139,7 +140,10 @@ def _safe_cast(cls, values: np.ndarray, dtype: np.dtype, copy: bool) -> np.ndarr
         raise AbstractMethodError(cls)
 
 
-def _coerce_to_data_and_mask(values, dtype, copy: bool, dtype_cls: type[NumericDtype]):
+def _coerce_to_data_and_mask(
+    values, dtype, copy: bool, dtype_cls: type[NumericDtype], default_dtype: np.dtype
+):
+    values = extract_array(values, extract_numpy=True)
     checker = dtype_cls._checker
     default_dtype = dtype_cls._default_np_dtype
 

pandas/tests/indexing/test_iloc.py

@@ -1090,6 +1090,25 @@ def test_iloc_setitem_pure_position_based(self, indexer, has_ref):
         expected = DataFrame({"a": [1, 2, 3], "b": [11, 12, 13], "c": [7, 8, 9]})
         tm.assert_frame_equal(df2, expected)
 
+    def test_iloc_assignment_nullable_int_with_na(self):
+        # GH#62473
+        ser = Series(
+            [4, 6, 9, None, 10, 13, 15], index=[6, 1, 5, 0, 3, 2, 4], dtype="Int64"
+        )
+        indices = Series(
+            [6, 1, 5, 0, 3, 2, 4], index=[6, 1, 5, 0, 3, 2, 4], dtype="int64"
+        )
+        values = Series(
+            [4, 6, 9, None, 10, 13, 15], index=[4, 1, 2, 6, 0, 5, 3], dtype="Int64"
+        )
+
+        ser.iloc[indices] = values
+
+        expected = Series(
+            [NA, 6, 13, 10, 15, 9, 4], index=[6, 1, 5, 0, 3, 2, 4], dtype="Int64"
+        )
+        tm.assert_series_equal(ser, expected)
+
     @pytest.mark.parametrize("has_ref", [True, False])
     def test_iloc_setitem_dictionary_value(self, has_ref):
         # GH#37728