TST (string dtype): clean-up assorted xfails

pandas/core/reshape/encoding.py

@@ -13,6 +13,10 @@
 from pandas._libs import missing as libmissing
 from pandas._libs.sparse import IntIndex
 
+from pandas.core.dtypes.cast import (
+    find_common_type,
+    infer_dtype_from_scalar,
+)
 from pandas.core.dtypes.common import (
     is_integer_dtype,
     is_list_like,
@@ -567,7 +571,13 @@ def from_dummies(
             )
         else:
             data_slice = data_to_decode.loc[:, prefix_slice]
-        cats_array = data._constructor_sliced(cats, dtype=data.columns.dtype)
+        dtype = data.columns.dtype
+        if default_category:
+            default_category_dtype = infer_dtype_from_scalar(default_category[prefix])[
+                0
+            ]
+            dtype = find_common_type([dtype, default_category_dtype])
+        cats_array = data._constructor_sliced(cats, dtype=dtype)
         # get indices of True entries along axis=1
         true_values = data_slice.idxmax(axis=1)
         indexer = data_slice.columns.get_indexer_for(true_values)

pandas/tests/reshape/test_from_dummies.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 from pandas import (
     DataFrame,
     Series,
@@ -330,14 +328,10 @@ def test_no_prefix_string_cats_contains_get_dummies_NaN_column():
         ),
     ],
 )
-def test_no_prefix_string_cats_default_category(
-    default_category, expected, using_infer_string
-):
+def test_no_prefix_string_cats_default_category(default_category, expected):
     dummies = DataFrame({"a": [1, 0, 0], "b": [0, 1, 0]})
     result = from_dummies(dummies, default_category=default_category)
     expected = DataFrame(expected)
-    if using_infer_string:
-        expected[""] = expected[""].astype("str")
     tm.assert_frame_equal(result, expected)
 
 
@@ -364,7 +358,6 @@ def test_with_prefix_contains_get_dummies_NaN_column():
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 @pytest.mark.parametrize(
     "default_category, expected",
     [
@@ -390,7 +383,7 @@ def test_with_prefix_contains_get_dummies_NaN_column():
         ),
         pytest.param(
             {"col2": None, "col1": False},
-            {"col1": ["a", "b", False], "col2": [None, "a", "c"]},
+            {"col1": ["a", "b", False], "col2": Series([None, "a", "c"], dtype=object)},
             id="default_category is a dict with bool and None values",
         ),
         pytest.param(

pandas/tests/strings/test_find_replace.py

@@ -293,23 +293,12 @@ def test_startswith_endswith_validate_na(any_string_dtype):
         dtype=any_string_dtype,
     )
 
-    dtype = ser.dtype
-    if (isinstance(dtype, pd.StringDtype)) or dtype == np.dtype("object"):
-        msg = "Allowing a non-bool 'na' in obj.str.startswith is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            ser.str.startswith("kapow", na="baz")
-        msg = "Allowing a non-bool 'na' in obj.str.endswith is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            ser.str.endswith("bar", na="baz")
-    else:
-        # TODO(infer_string): don't surface pyarrow errors
-        import pyarrow as pa
-
-        msg = "Could not convert 'baz' with type str: tried to convert to boolean"
-        with pytest.raises(pa.lib.ArrowInvalid, match=msg):
-            ser.str.startswith("kapow", na="baz")
-        with pytest.raises(pa.lib.ArrowInvalid, match=msg):
-            ser.str.endswith("kapow", na="baz")
+    msg = "Allowing a non-bool 'na' in obj.str.startswith is deprecated"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        ser.str.startswith("kapow", na="baz")
+    msg = "Allowing a non-bool 'na' in obj.str.endswith is deprecated"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        ser.str.endswith("bar", na="baz")
 
 
 @pytest.mark.parametrize("pat", ["foo", ("foo", "baz")])