BUG: setting non-string value into StringArray raises ValueError instead of TypeError

doc/source/whatsnew/v2.0.0.rst

@@ -1324,6 +1324,7 @@ ExtensionArray
 - Bug in :meth:`api.types.is_numeric_dtype` where a custom :class:`ExtensionDtype` would not return ``True`` if ``_is_numeric`` returned ``True`` (:issue:`50563`)
 - Bug in :meth:`api.types.is_integer_dtype`, :meth:`api.types.is_unsigned_integer_dtype`, :meth:`api.types.is_signed_integer_dtype`, :meth:`api.types.is_float_dtype` where a custom :class:`ExtensionDtype` would not return ``True`` if ``kind`` returned the corresponding NumPy type (:issue:`50667`)
 - Bug in :class:`Series` constructor unnecessarily overflowing for nullable unsigned integer dtypes (:issue:`38798`, :issue:`25880`)
+- Bug in setting non-string value into ``StringArray`` raising ``ValueError`` instead of ``TypeError`` (:issue:`49632`)
 
 Styler
 ^^^^^^

pandas/core/arrays/string_.py

@@ -414,14 +414,14 @@ def __setitem__(self, key, value):
             if isna(value):
                 value = libmissing.NA
             elif not isinstance(value, str):
-                raise ValueError(
+                raise TypeError(
                     f"Cannot set non-string value '{value}' into a StringArray."
                 )
         else:
             if not is_array_like(value):
                 value = np.asarray(value, dtype=object)
             if len(value) and not lib.is_string_array(value, skipna=True):
-                raise ValueError("Must provide strings.")
+                raise TypeError("Must provide strings.")
 
             value[isna(value)] = libmissing.NA
 

pandas/core/arrays/string_arrow.py

@@ -163,13 +163,13 @@ def _maybe_convert_setitem_value(self, value):
             if isna(value):
                 value = None
             elif not isinstance(value, str):
-                raise ValueError("Scalar must be NA or str")
+                raise TypeError("Scalar must be NA or str")
         else:
             value = np.array(value, dtype=object, copy=True)
             value[isna(value)] = None
             for v in value:
                 if not (v is None or isinstance(v, str)):
-                    raise ValueError("Scalar must be NA or str")
+                    raise TypeError("Scalar must be NA or str")
         return super()._maybe_convert_setitem_value(value)
 
     def isin(self, values) -> npt.NDArray[np.bool_]:

pandas/tests/arrays/string_/test_string.py

@@ -53,14 +53,14 @@ def test_setitem_validates(cls):
         msg = "Cannot set non-string value '10' into a StringArray."
     else:
         msg = "Scalar must be NA or str"
-    with pytest.raises(ValueError, match=msg):
+    with pytest.raises(TypeError, match=msg):
         arr[0] = 10
 
     if cls is pd.arrays.StringArray:
         msg = "Must provide strings."
     else:
         msg = "Scalar must be NA or str"
-    with pytest.raises(ValueError, match=msg):
+    with pytest.raises(TypeError, match=msg):
         arr[:] = np.array([1, 2])
 
 
@@ -403,12 +403,10 @@ def test_fillna_args(dtype, request):
     tm.assert_extension_array_equal(res, expected)
 
     if dtype.storage == "pyarrow":
-        err = TypeError
         msg = "Invalid value '1' for dtype string"
     else:
-        err = ValueError
         msg = "Cannot set non-string value '1' into a StringArray."
-    with pytest.raises(err, match=msg):
+    with pytest.raises(TypeError, match=msg):
         arr.fillna(value=1)
 
 
@@ -574,7 +572,7 @@ def test_setitem_scalar_with_mask_validation(dtype):
         msg = "Cannot set non-string value"
     else:
         msg = "Scalar must be NA or str"
-    with pytest.raises(ValueError, match=msg):
+    with pytest.raises(TypeError, match=msg):
         ser[mask] = 1