address feedback

Author: jorisvandenbossche

pandas/core/arrays/string_.py

@@ -734,7 +734,11 @@ def _putmask(self, mask: npt.NDArray[np.bool_], value) -> None:
         ExtensionArray._putmask(self, mask, value)
 
     def isin(self, values: ArrayLike) -> npt.NDArray[np.bool_]:
-        if not isinstance(values, BaseStringArray):
+        if isinstance(values, BaseStringArray) or (
+            isinstance(values, ExtensionArray) and is_string_dtype(values.dtype)
+        ):
+            values = values.astype(self.dtype, copy=False)
+        else:
             if not lib.is_string_array(np.asarray(values), skipna=True):
                 values = np.array(
                     [val for val in values if isinstance(val, str) or isna(val)],
@@ -744,8 +748,6 @@ def isin(self, values: ArrayLike) -> npt.NDArray[np.bool_]:
                     return np.zeros(self.shape, dtype=bool)
 
             values = self._from_sequence(values, dtype=self.dtype)
-        else:
-            values = values.astype(self.dtype, copy=False)
 
         return isin(np.asarray(self), np.asarray(values))
 

pandas/tests/arrays/string_/test_string.py

@@ -682,6 +682,10 @@ def test_isin(dtype, fixed_now_ts):
     expected = pd.Series([True, False, False])
     tm.assert_series_equal(result, expected)
 
+    result = s.isin([fixed_now_ts])
+    expected = pd.Series([False, False, False])
+    tm.assert_series_equal(result, expected)
+
 
 def test_isin_string_array(dtype, dtype2):
     s = pd.Series(["a", "b", None], dtype=dtype)
@@ -695,6 +699,19 @@ def test_isin_string_array(dtype, dtype2):
     tm.assert_series_equal(result, expected)
 
 
+def test_isin_arrow_string_array(dtype):
+    pa = pytest.importorskip("pyarrow")
+    s = pd.Series(["a", "b", None], dtype=dtype)
+
+    result = s.isin(pd.array(["a", "c"], dtype=pd.ArrowDtype(pa.string())))
+    expected = pd.Series([True, False, False])
+    tm.assert_series_equal(result, expected)
+
+    result = s.isin(pd.array(["a", None], dtype=pd.ArrowDtype(pa.string())))
+    expected = pd.Series([True, False, True])
+    tm.assert_series_equal(result, expected)
+
+
 def test_setitem_scalar_with_mask_validation(dtype):
     # https://github.com/pandas-dev/pandas/issues/47628
     # setting None with a boolean mask (through _putmaks) should still result