BUG: Fix series clipping NA issue

doc/source/whatsnew/v1.3.0.rst

@@ -696,6 +696,7 @@ Numeric
 - Bug in :meth:`DataFrame.transform` would raise ``SpecificationError`` when passed a dictionary and columns were missing; will now raise a ``KeyError`` instead (:issue:`40004`)
 - Bug in :meth:`DataFrameGroupBy.rank` giving incorrect results with ``pct=True`` and equal values between consecutive groups (:issue:`40518`)
 - Bug in :meth:`Series.count` would result in an ``int32`` result on 32-bit platforms when argument ``level=None`` (:issue:`40908`)
+- Bug in :meth:`Series.clip` would fail if series contains NA values and has nullable int or float as a data type (:issue:`40851`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/generic.py

@@ -7404,10 +7404,10 @@ def _clip_with_scalar(self, lower, upper, inplace: bool_t = False):
 
         with np.errstate(all="ignore"):
             if upper is not None:
-                subset = self.to_numpy() <= upper
+                subset = (self <= upper).to_numpy()
                 result = result.where(subset, upper, axis=None, inplace=False)
             if lower is not None:
-                subset = self.to_numpy() >= lower
+                subset = (self >= lower).to_numpy()
                 result = result.where(subset, lower, axis=None, inplace=False)
 
         if np.any(mask):

pandas/tests/series/methods/test_clip.py

@@ -40,6 +40,26 @@ def test_clip_types_and_nulls(self):
             assert list(isna(s)) == list(isna(lower))
             assert list(isna(s)) == list(isna(upper))
 
+    def test_series_clipping_with_na_values(
+        self, any_nullable_numeric_dtype, nulls_fixture
+    ):
+        # Ensure that clipping method can handle NA values with out failing
+        # GH#40581
+
+        s = Series([nulls_fixture, 1.0, 3.0], dtype=any_nullable_numeric_dtype)
+        s_clipped_upper = s.clip(upper=2.0)
+        s_clipped_lower = s.clip(lower=2.0)
+
+        expected_upper = Series(
+            [nulls_fixture, 1.0, 2.0], dtype=any_nullable_numeric_dtype
+        )
+        expected_lower = Series(
+            [nulls_fixture, 2.0, 3.0], dtype=any_nullable_numeric_dtype
+        )
+
+        tm.assert_series_equal(s_clipped_upper, expected_upper)
+        tm.assert_series_equal(s_clipped_lower, expected_lower)
+
     def test_clip_with_na_args(self):
         """Should process np.nan argument as None """
         # GH#17276