BUG (string dtype): fix where() for string dtype with python storage (#60195)

Author: jorisvandenbossche

pandas/core/arrays/string_.py

@@ -757,6 +757,12 @@ def _putmask(self, mask: npt.NDArray[np.bool_], value) -> None:
         # base class implementation that uses __setitem__
         ExtensionArray._putmask(self, mask, value)
 
+    def _where(self, mask: npt.NDArray[np.bool_], value) -> Self:
+        # the super() method NDArrayBackedExtensionArray._where uses
+        # np.putmask which doesn't properly handle None/pd.NA, so using the
+        # base class implementation that uses __setitem__
+        return ExtensionArray._where(self, mask, value)
+
     def isin(self, values: ArrayLike) -> npt.NDArray[np.bool_]:
         if isinstance(values, BaseStringArray) or (
             isinstance(values, ExtensionArray) and is_string_dtype(values.dtype)

pandas/tests/frame/indexing/test_where.py

@@ -6,8 +6,6 @@
 
 from pandas._config import using_string_dtype
 
-from pandas.compat import HAS_PYARROW
-
 from pandas.core.dtypes.common import is_scalar
 
 import pandas as pd
@@ -940,9 +938,6 @@ def test_where_nullable_invalid_na(frame_or_series, any_numeric_ea_dtype):
             obj.mask(mask, null)
 
 
-@pytest.mark.xfail(
-    using_string_dtype() and not HAS_PYARROW, reason="TODO(infer_string)"
-)
 @given(data=OPTIONAL_ONE_OF_ALL)
 def test_where_inplace_casting(data):
     # GH 22051
@@ -1023,19 +1018,18 @@ def test_where_producing_ea_cond_for_np_dtype():
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.xfail(
-    using_string_dtype() and not HAS_PYARROW, reason="TODO(infer_string)", strict=False
-)
 @pytest.mark.parametrize(
     "replacement", [0.001, True, "snake", None, datetime(2022, 5, 4)]
 )
-def test_where_int_overflow(replacement, using_infer_string, request):
+def test_where_int_overflow(replacement, using_infer_string):
     # GH 31687
     df = DataFrame([[1.0, 2e25, "nine"], [np.nan, 0.1, None]])
     if using_infer_string and replacement not in (None, "snake"):
-        request.node.add_marker(
-            pytest.mark.xfail(reason="Can't set non-string into string column")
-        )
+        with pytest.raises(
+            TypeError, match="Cannot set non-string value|Scalar must be NA or str"
+        ):
+            df.where(pd.notnull(df), replacement)
+        return
     result = df.where(pd.notnull(df), replacement)
     expected = DataFrame([[1.0, 2e25, "nine"], [replacement, 0.1, replacement]])