BUG (string dtype): let fillna with invalid value upcast to object dtype (pandas-dev#60296)

* BUG (string dtype): let fillna with invalid value upcast to object dtype

* fix fillna limit case + update tests for no longer raising

Author: jorisvandenbossche

pandas/core/internals/blocks.py

@@ -108,6 +108,7 @@
     PeriodArray,
     TimedeltaArray,
 )
+from pandas.core.arrays.string_ import StringDtype
 from pandas.core.base import PandasObject
 import pandas.core.common as com
 from pandas.core.computation import expressions
@@ -1336,7 +1337,7 @@ def fillna(
             return [self.copy(deep=False)]
 
         if limit is not None:
-            mask[mask.cumsum(self.ndim - 1) > limit] = False
+            mask[mask.cumsum(self.values.ndim - 1) > limit] = False
 
         if inplace:
             nbs = self.putmask(mask.T, value)
@@ -1684,7 +1685,7 @@ def where(self, other, cond) -> list[Block]:
             res_values = arr._where(cond, other).T
         except (ValueError, TypeError):
             if self.ndim == 1 or self.shape[0] == 1:
-                if isinstance(self.dtype, IntervalDtype):
+                if isinstance(self.dtype, (IntervalDtype, StringDtype)):
                     # TestSetitemFloatIntervalWithIntIntervalValues
                     blk = self.coerce_to_target_dtype(orig_other, raise_on_upcast=False)
                     return blk.where(orig_other, orig_cond)
@@ -1854,9 +1855,9 @@ def fillna(
         limit: int | None = None,
         inplace: bool = False,
     ) -> list[Block]:
-        if isinstance(self.dtype, IntervalDtype):
+        if isinstance(self.dtype, (IntervalDtype, StringDtype)):
             # Block.fillna handles coercion (test_fillna_interval)
-            if limit is not None:
+            if isinstance(self.dtype, IntervalDtype) and limit is not None:
                 raise ValueError("limit must be None")
             return super().fillna(
                 value=value,

pandas/tests/frame/indexing/test_where.py

@@ -1025,15 +1025,9 @@ def test_where_producing_ea_cond_for_np_dtype():
 @pytest.mark.parametrize(
     "replacement", [0.001, True, "snake", None, datetime(2022, 5, 4)]
 )
-def test_where_int_overflow(replacement, using_infer_string):
+def test_where_int_overflow(replacement):
     # GH 31687
     df = DataFrame([[1.0, 2e25, "nine"], [np.nan, 0.1, None]])
-    if using_infer_string and replacement not in (None, "snake"):
-        with pytest.raises(
-            TypeError, match=f"Invalid value '{replacement}' for dtype '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]])
 

pandas/tests/series/indexing/test_setitem.py

@@ -839,11 +839,6 @@ def test_series_where(self, obj, key, expected, raises, val, is_inplace):
         obj = obj.copy()
         arr = obj._values
 
-        if raises and obj.dtype == "string":
-            with pytest.raises(TypeError, match="Invalid value"):
-                obj.where(~mask, val)
-            return
-
         res = obj.where(~mask, val)
 
         if val is NA and res.dtype == object: