use _reduce method for ExtensionArrays

Author: skonda29

pandas/core/indexing.py

@@ -1610,14 +1610,15 @@ def _validate_key(self, key, axis: AxisInt) -> None:
                 raise IndexError(f".iloc requires numeric indexers, got {arr}")
 
             if len(arr):
-                # convert to numpy array for min/max with ExtensionArrays
-                if hasattr(arr, "to_numpy"):
-                    np_arr = arr.to_numpy()
+                # handle ExtensionArray safely using _reduce method else use numpy
+                if isinstance(arr.dtype, ExtensionDtype):
+                    arr_max = arr._reduce("max")
+                    arr_min = arr._reduce("min")
                 else:
-                    np_arr = np.asarray(arr)
+                    arr_max = np.max(arr)
+                    arr_min = np.min(arr)
 
-                # check that the key does not exceed the maximum size
-                if np.max(np_arr) >= len_axis or np.min(np_arr) < -len_axis:
+                if arr_max >= len_axis or arr_min < -len_axis:
                     raise IndexError("positional indexers are out-of-bounds")
         else:
             raise ValueError(f"Can only index by location with a [{self._valid_types}]")

pandas/tests/indexing/test_iloc.py

@@ -1482,10 +1482,10 @@ def test_iloc_nullable_int64_size_1_nan(self):
     def test_iloc_arrow_extension_array(self):
         # GH#61311
         pytest.importorskip("pyarrow")
-
         df = DataFrame({"a": [1, 2], "c": [0, 2], "d": ["c", "a"]})
-
-        df_arrow = df.convert_dtypes(dtype_backend="pyarrow")
+        df_arrow = DataFrame(
+            {"a": [1, 2], "c": [0, 2], "d": ["c", "a"]}
+        ).convert_dtypes(dtype_backend="pyarrow")
+        expected = df.iloc[:, df["c"]]
         result = df_arrow.iloc[:, df_arrow["c"]]
-        expected = df_arrow.iloc[:, [0, 2]]
-        tm.assert_frame_equal(result, expected)
+        tm.assert_frame_equal(result, expected, check_dtype=False)