un-xfail tests for replace/fillna downcasting

Author: jorisvandenbossche

pandas/tests/frame/methods/test_combine_first.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import is_dtype_equal
 
@@ -32,7 +30,6 @@ def test_combine_first_mixed(self):
         combined = f.combine_first(g)
         tm.assert_frame_equal(combined, exp)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_combine_first(self, float_frame, using_infer_string):
         # disjoint
         head, tail = float_frame[:5], float_frame[5:]

pandas/tests/frame/methods/test_fillna.py

@@ -126,7 +126,6 @@ def test_fillna_empty(self, using_copy_on_write):
                 df.x.fillna(method=m, inplace=True)
                 df.x.fillna(method=m)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_fillna_different_dtype(self, using_infer_string):
         # with different dtype (GH#3386)
         df = DataFrame(
@@ -371,7 +370,6 @@ def test_fillna_dictlike_value_duplicate_colnames(self, columns):
         expected["A"] = 0.0
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_fillna_dtype_conversion(self, using_infer_string):
         # make sure that fillna on an empty frame works
         df = DataFrame(index=["A", "B", "C"], columns=[1, 2, 3, 4, 5])

pandas/tests/frame/methods/test_replace.py

@@ -624,7 +624,6 @@ def test_replace_mixed_int_block_splitting(self):
         result = df.replace(0, 0.5)
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_replace_mixed2(self, using_infer_string):
         # to object block upcasting
         df = DataFrame(
@@ -1444,7 +1443,6 @@ def test_replace_ea_ignore_float(self, frame_or_series, value):
         result = obj.replace(1.0, 0.0)
         tm.assert_equal(expected, result)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_replace_value_category_type(self):
         """
         Test for #23305: to ensure category dtypes are maintained
@@ -1540,7 +1538,6 @@ def test_replace_with_compiled_regex(self):
         expected = DataFrame(["z", "b", "c"])
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_replace_intervals(self, using_infer_string):
         # https://github.com/pandas-dev/pandas/issues/35931
         df = DataFrame({"a": [pd.Interval(0, 1), pd.Interval(0, 1)]})

pandas/tests/series/methods/test_replace.py

@@ -760,7 +760,6 @@ def test_replace_value_none_dtype_numeric(self, val):
         expected = pd.Series([1, None], dtype=object)
         tm.assert_series_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_replace_change_dtype_series(self, using_infer_string):
         # GH#25797
         df = pd.DataFrame.from_dict({"Test": ["0.5", True, "0.6"]})