more xfails

Author: jorisvandenbossche

pandas/tests/apply/test_frame_apply.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas.core.dtypes.dtypes import CategoricalDtype
 
 import pandas as pd
@@ -61,6 +63,7 @@ def test_apply(float_frame, engine, request):
         assert result.index is float_frame.index
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 @pytest.mark.parametrize("axis", [0, 1])
 @pytest.mark.parametrize("raw", [True, False])
 @pytest.mark.parametrize("nopython", [True, False])
@@ -1213,6 +1216,7 @@ def test_agg_with_name_as_column_name():
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
 def test_agg_multiple_mixed():
     # GH 20909
     mdf = DataFrame(
@@ -1338,6 +1342,7 @@ def test_named_agg_reduce_axis1_raises(float_frame):
             float_frame.agg(row1=(name1, "sum"), row2=(name2, "max"), axis=axis)
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
 def test_nuiscance_columns():
     # GH 15015
     df = DataFrame(
@@ -1514,6 +1519,7 @@ def test_apply_datetime_tz_issue(engine, request):
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 @pytest.mark.parametrize("df", [DataFrame({"A": ["a", None], "B": ["c", "d"]})])
 @pytest.mark.parametrize("method", ["min", "max", "sum"])
 def test_mixed_column_raises(df, method, using_infer_string):

pandas/tests/apply/test_str.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas.compat import WASM
 
 from pandas.core.dtypes.common import is_number
@@ -79,6 +81,7 @@ def test_apply_np_transformer(float_frame, op, how):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 @pytest.mark.parametrize(
     "series, func, expected",
     chain(
@@ -137,6 +140,7 @@ def test_agg_cython_table_series(series, func, expected):
         assert result == expected
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
 @pytest.mark.parametrize(
     "series, func, expected",
     chain(

pandas/tests/arrays/categorical/test_analytics.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas.compat import PYPY
 
 from pandas import (
@@ -294,6 +296,7 @@ def test_nbytes(self):
         exp = 3 + 3 * 8  # 3 int8s for values + 3 int64s for categories
         assert cat.nbytes == exp
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_memory_usage(self):
         cat = Categorical([1, 2, 3])
 

pandas/tests/arrays/categorical/test_api.py

@@ -3,6 +3,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas.compat import PY311
 
 from pandas import (
@@ -149,6 +151,7 @@ def test_reorder_categories_raises(self, new_categories):
         with pytest.raises(ValueError, match=msg):
             cat.reorder_categories(new_categories)
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_add_categories(self):
         cat = Categorical(["a", "b", "c", "a"], ordered=True)
         old = cat.copy()

pandas/tests/arrays/categorical/test_constructors.py

@@ -735,6 +735,7 @@ def test_interval(self):
         tm.assert_numpy_array_equal(cat.codes, expected_codes)
         tm.assert_index_equal(cat.categories, idx)
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_categorical_extension_array_nullable(self, nulls_fixture):
         # GH:
         arr = pd.arrays.StringArray._from_sequence(

pandas/tests/arrays/masked/test_function.py

@@ -1,6 +1,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas.core.dtypes.common import is_integer_dtype
 
 import pandas as pd
@@ -58,6 +60,7 @@ def test_tolist(data):
     tm.assert_equal(result, expected)
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
 def test_to_numpy():
     # GH#56991
 

pandas/tests/dtypes/test_dtypes.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
 
 from pandas.core.dtypes.base import _registry as registry
@@ -959,6 +961,7 @@ def test_same_categories_different_order(self):
         c2 = CategoricalDtype(["b", "a"], ordered=True)
         assert c1 is not c2
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
     @pytest.mark.parametrize("ordered2", [True, False, None])
     def test_categorical_equality(self, ordered, ordered2):
         # same categories, same order

pandas/tests/extension/test_string.py

@@ -22,13 +22,19 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 import pandas as pd
 import pandas._testing as tm
 from pandas.api.types import is_string_dtype
 from pandas.core.arrays import ArrowStringArray
 from pandas.core.arrays.string_ import StringDtype
 from pandas.tests.extension import base
 
+pytestmark = pytest.mark.xfail(
+    using_string_dtype(), reason="TODO(infer_string)", strict=False
+)
+
 
 def maybe_split_array(arr, chunked):
     if not chunked:

pandas/tests/frame/indexing/test_coercion.py

@@ -8,6 +8,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -82,6 +84,7 @@ def test_6942(indexer_al):
     assert df.iloc[0, 0] == t2
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
 def test_26395(indexer_al):
     # .at case fixed by GH#45121 (best guess)
     df = DataFrame(index=["A", "B", "C"])

pandas/tests/frame/indexing/test_indexing.py

@@ -9,6 +9,8 @@
 import numpy as np
 import pytest
 
+from pandas._config import using_string_dtype
+
 from pandas._libs import iNaT
 from pandas.errors import InvalidIndexError
 
@@ -174,6 +176,7 @@ def test_getitem_boolean(self, mixed_float_frame, mixed_int_frame, datetime_fram
                 if bif[c].dtype != bifw[c].dtype:
                     assert bif[c].dtype == df[c].dtype
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_getitem_boolean_casting(self, datetime_frame):
         # don't upcast if we don't need to
         df = datetime_frame.copy()
@@ -501,6 +504,7 @@ def test_setitem_ambig(self, using_infer_string):
         else:
             assert dm[2].dtype == np.object_
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_setitem_None(self, float_frame, using_infer_string):
         # GH #766
         float_frame[None] = float_frame["A"]
@@ -1121,6 +1125,7 @@ def test_setitem_with_unaligned_tz_aware_datetime_column(self):
         df.loc[[0, 1, 2], "dates"] = column[[1, 0, 2]]
         tm.assert_series_equal(df["dates"], column)
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_loc_setitem_datetimelike_with_inference(self):
         # GH 7592
         # assignment of timedeltas with NaT
@@ -1143,6 +1148,7 @@ def test_loc_setitem_datetimelike_with_inference(self):
         )
         tm.assert_series_equal(result, expected)
 
+    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
     def test_getitem_boolean_indexing_mixed(self):
         df = DataFrame(
             {
@@ -1871,6 +1877,7 @@ def test_adding_new_conditional_column_with_string(dtype, infer_string) -> None:
     tm.assert_frame_equal(df, expected)
 
 
+@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)")
 def test_add_new_column_infer_string():
     # GH#55366
     pytest.importorskip("pyarrow")