diff --git a/pandas/_config/__init__.py b/pandas/_config/__init__.py
index e746933ac0bf7..80d9ea1b364f3 100644
--- a/pandas/_config/__init__.py
+++ b/pandas/_config/__init__.py
@@ -30,6 +30,6 @@
from pandas._config.display import detect_console_encoding
-def using_pyarrow_string_dtype() -> bool:
+def using_string_dtype() -> bool:
_mode_options = _global_config["future"]
return _mode_options["infer_string"]
diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index b78ff19bcfd53..2650d60eb3cef 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -37,7 +37,7 @@ from cython cimport (
floating,
)
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs.missing import check_na_tuples_nonequal
@@ -2699,7 +2699,7 @@ def maybe_convert_objects(ndarray[object] objects,
seen.object_ = True
elif seen.str_:
- if using_pyarrow_string_dtype() and is_string_array(objects, skipna=True):
+ if using_string_dtype() and is_string_array(objects, skipna=True):
from pandas.core.arrays.string_ import StringDtype
dtype = StringDtype(storage="pyarrow_numpy")
diff --git a/pandas/core/construction.py b/pandas/core/construction.py
index 360e1d5ddd3ff..32792aa7f0543 100644
--- a/pandas/core/construction.py
+++ b/pandas/core/construction.py
@@ -16,7 +16,7 @@
import numpy as np
from numpy import ma
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas._libs.tslibs import (
@@ -571,11 +571,7 @@ def sanitize_array(
if not is_list_like(data):
if index is None:
raise ValueError("index must be specified when data is not list-like")
- if (
- isinstance(data, str)
- and using_pyarrow_string_dtype()
- and original_dtype is None
- ):
+ if isinstance(data, str) and using_string_dtype() and original_dtype is None:
from pandas.core.arrays.string_ import StringDtype
dtype = StringDtype("pyarrow_numpy")
@@ -609,7 +605,7 @@ def sanitize_array(
subarr = data
if data.dtype == object and infer_object:
subarr = maybe_infer_to_datetimelike(data)
- elif data.dtype.kind == "U" and using_pyarrow_string_dtype():
+ elif data.dtype.kind == "U" and using_string_dtype():
from pandas.core.arrays.string_ import StringDtype
dtype = StringDtype(storage="pyarrow_numpy")
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index f2af69fcc9d84..21e45505b40fc 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -18,7 +18,7 @@
import numpy as np
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import (
Interval,
@@ -798,7 +798,7 @@ def infer_dtype_from_scalar(val) -> tuple[DtypeObj, Any]:
# coming out as np.str_!
dtype = _dtype_obj
- if using_pyarrow_string_dtype():
+ if using_string_dtype():
from pandas.core.arrays.string_ import StringDtype
dtype = StringDtype(storage="pyarrow_numpy")
diff --git a/pandas/core/internals/construction.py b/pandas/core/internals/construction.py
index 0d149f47fd08c..c31479b3011e5 100644
--- a/pandas/core/internals/construction.py
+++ b/pandas/core/internals/construction.py
@@ -14,7 +14,7 @@
import numpy as np
from numpy import ma
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
@@ -301,7 +301,7 @@ def ndarray_to_mgr(
bp = BlockPlacement(slice(len(columns)))
nb = new_block_2d(values, placement=bp, refs=refs)
block_values = [nb]
- elif dtype is None and values.dtype.kind == "U" and using_pyarrow_string_dtype():
+ elif dtype is None and values.dtype.kind == "U" and using_string_dtype():
dtype = StringDtype(storage="pyarrow_numpy")
obj_columns = list(values)
diff --git a/pandas/io/feather_format.py b/pandas/io/feather_format.py
index 16d4e1f9ea25d..3df3e77a851a3 100644
--- a/pandas/io/feather_format.py
+++ b/pandas/io/feather_format.py
@@ -8,7 +8,7 @@
)
import warnings
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas.compat._optional import import_optional_dependency
@@ -131,7 +131,7 @@ def read_feather(
with get_handle(
path, "rb", storage_options=storage_options, is_text=False
) as handles:
- if dtype_backend is lib.no_default and not using_pyarrow_string_dtype():
+ if dtype_backend is lib.no_default and not using_string_dtype():
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
@@ -155,7 +155,7 @@ def read_feather(
elif dtype_backend == "pyarrow":
return pa_table.to_pandas(types_mapper=pd.ArrowDtype)
- elif using_pyarrow_string_dtype():
+ elif using_string_dtype():
return pa_table.to_pandas(types_mapper=arrow_string_types_mapper())
else:
raise NotImplementedError
diff --git a/pandas/io/orc.py b/pandas/io/orc.py
index 3bca8ea7ef1df..b297164d5d108 100644
--- a/pandas/io/orc.py
+++ b/pandas/io/orc.py
@@ -9,7 +9,7 @@
Literal,
)
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas.compat._optional import import_optional_dependency
@@ -136,7 +136,7 @@ def read_orc(
df = pa_table.to_pandas(types_mapper=mapping.get)
return df
else:
- if using_pyarrow_string_dtype():
+ if using_string_dtype():
types_mapper = arrow_string_types_mapper()
else:
types_mapper = None
diff --git a/pandas/io/parquet.py b/pandas/io/parquet.py
index 306b144811898..77a9cc3fca644 100644
--- a/pandas/io/parquet.py
+++ b/pandas/io/parquet.py
@@ -15,7 +15,7 @@
filterwarnings,
)
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas.compat._optional import import_optional_dependency
@@ -257,7 +257,7 @@ def read(
to_pandas_kwargs["types_mapper"] = mapping.get
elif dtype_backend == "pyarrow":
to_pandas_kwargs["types_mapper"] = pd.ArrowDtype # type: ignore[assignment]
- elif using_pyarrow_string_dtype():
+ elif using_string_dtype():
to_pandas_kwargs["types_mapper"] = arrow_string_types_mapper()
path_or_handle, handles, filesystem = _get_path_or_handle(
diff --git a/pandas/io/parsers/arrow_parser_wrapper.py b/pandas/io/parsers/arrow_parser_wrapper.py
index cffdb28e2c9e4..86bb5f190e403 100644
--- a/pandas/io/parsers/arrow_parser_wrapper.py
+++ b/pandas/io/parsers/arrow_parser_wrapper.py
@@ -3,7 +3,7 @@
from typing import TYPE_CHECKING
import warnings
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas.compat._optional import import_optional_dependency
@@ -301,7 +301,7 @@ def read(self) -> DataFrame:
dtype_mapping = _arrow_dtype_mapping()
dtype_mapping[pa.null()] = pd.Int64Dtype()
frame = table.to_pandas(types_mapper=dtype_mapping.get)
- elif using_pyarrow_string_dtype():
+ elif using_string_dtype():
frame = table.to_pandas(types_mapper=arrow_string_types_mapper())
else:
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 1420ce84b4db8..4b569fb7e39e2 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -30,7 +30,7 @@
from pandas._config import (
config,
get_option,
- using_pyarrow_string_dtype,
+ using_string_dtype,
)
from pandas._libs import (
@@ -3294,7 +3294,7 @@ def read(
index = self.read_index("index", start=start, stop=stop)
values = self.read_array("values", start=start, stop=stop)
result = Series(values, index=index, name=self.name, copy=False)
- if using_pyarrow_string_dtype() and is_string_array(values, skipna=True):
+ if using_string_dtype() and is_string_array(values, skipna=True):
result = result.astype("string[pyarrow_numpy]")
return result
@@ -3363,7 +3363,7 @@ def read(
columns = items[items.get_indexer(blk_items)]
df = DataFrame(values.T, columns=columns, index=axes[1], copy=False)
- if using_pyarrow_string_dtype() and is_string_array(values, skipna=True):
+ if using_string_dtype() and is_string_array(values, skipna=True):
df = df.astype("string[pyarrow_numpy]")
dfs.append(df)
@@ -4735,9 +4735,9 @@ def read(
else:
# Categorical
df = DataFrame._from_arrays([values], columns=cols_, index=index_)
- if not (using_pyarrow_string_dtype() and values.dtype.kind == "O"):
+ if not (using_string_dtype() and values.dtype.kind == "O"):
assert (df.dtypes == values.dtype).all(), (df.dtypes, values.dtype)
- if using_pyarrow_string_dtype() and is_string_array(
+ if using_string_dtype() and is_string_array(
values, # type: ignore[arg-type]
skipna=True,
):
diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index 41b368c9b05c2..4fd7de7a28855 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -31,7 +31,7 @@
import numpy as np
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas.compat._optional import import_optional_dependency
@@ -2197,7 +2197,7 @@ def read_table(
from pandas.io._util import _arrow_dtype_mapping
mapping = _arrow_dtype_mapping().get
- elif using_pyarrow_string_dtype():
+ elif using_string_dtype():
from pandas.io._util import arrow_string_types_mapper
arrow_string_types_mapper()
diff --git a/pandas/tests/arithmetic/test_object.py b/pandas/tests/arithmetic/test_object.py
index 4ffd76722286a..884e6e002800e 100644
--- a/pandas/tests/arithmetic/test_object.py
+++ b/pandas/tests/arithmetic/test_object.py
@@ -8,7 +8,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas.util._test_decorators as td
@@ -303,7 +303,7 @@ def test_iadd_string(self):
index += "_x"
assert "a_x" in index
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="add doesn't work")
+ @pytest.mark.xfail(using_string_dtype(), reason="add doesn't work")
def test_add(self):
index = pd.Index([str(i) for i in range(10)])
expected = pd.Index(index.values * 2)
diff --git a/pandas/tests/arrays/categorical/test_constructors.py b/pandas/tests/arrays/categorical/test_constructors.py
index 1069a9e5aaa90..6752a503016f8 100644
--- a/pandas/tests/arrays/categorical/test_constructors.py
+++ b/pandas/tests/arrays/categorical/test_constructors.py
@@ -6,7 +6,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.core.dtypes.common import (
is_float_dtype,
@@ -442,7 +442,7 @@ def test_constructor_str_unknown(self):
with pytest.raises(ValueError, match="Unknown dtype"):
Categorical([1, 2], dtype="foo")
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="Can't be NumPy strings")
+ @pytest.mark.xfail(using_string_dtype(), reason="Can't be NumPy strings")
def test_constructor_np_strs(self):
# GH#31499 Hashtable.map_locations needs to work on np.str_ objects
cat = Categorical(["1", "0", "1"], [np.str_("0"), np.str_("1")])
diff --git a/pandas/tests/arrays/categorical/test_repr.py b/pandas/tests/arrays/categorical/test_repr.py
index ef0315130215c..e2e5d47f50209 100644
--- a/pandas/tests/arrays/categorical/test_repr.py
+++ b/pandas/tests/arrays/categorical/test_repr.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
Categorical,
@@ -78,7 +78,7 @@ def test_print_none_width(self):
assert exp == repr(a)
@pytest.mark.skipif(
- using_pyarrow_string_dtype(),
+ using_string_dtype(),
reason="Change once infer_string is set to True by default",
)
def test_unicode_print(self):
diff --git a/pandas/tests/base/test_misc.py b/pandas/tests/base/test_misc.py
index f6a4396ca5be0..bbd9b150b88a8 100644
--- a/pandas/tests/base/test_misc.py
+++ b/pandas/tests/base/test_misc.py
@@ -3,7 +3,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.compat import PYPY
@@ -82,7 +82,7 @@ def test_ndarray_compat_properties(index_or_series_obj):
@pytest.mark.skipif(
- PYPY or using_pyarrow_string_dtype(),
+ PYPY or using_string_dtype(),
reason="not relevant for PyPy doesn't work properly for arrow strings",
)
def test_memory_usage(index_or_series_memory_obj):
diff --git a/pandas/tests/base/test_unique.py b/pandas/tests/base/test_unique.py
index 3a8ed471f9dc0..42730519b32fd 100644
--- a/pandas/tests/base/test_unique.py
+++ b/pandas/tests/base/test_unique.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
import pandas._testing as tm
@@ -100,7 +100,7 @@ def test_nunique_null(null_obj, index_or_series_obj):
@pytest.mark.single_cpu
-@pytest.mark.xfail(using_pyarrow_string_dtype(), reason="decoding fails")
+@pytest.mark.xfail(using_string_dtype(), reason="decoding fails")
def test_unique_bad_unicode(index_or_series):
# regression test for #34550
uval = "\ud83d" # smiley emoji
diff --git a/pandas/tests/extension/base/ops.py b/pandas/tests/extension/base/ops.py
index 5cd66d8a874c7..fad2560265d21 100644
--- a/pandas/tests/extension/base/ops.py
+++ b/pandas/tests/extension/base/ops.py
@@ -5,7 +5,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.core.dtypes.common import is_string_dtype
@@ -37,7 +37,7 @@ def _get_expected_exception(
else:
result = self.frame_scalar_exc
- if using_pyarrow_string_dtype() and result is not None:
+ if using_string_dtype() and result is not None:
import pyarrow as pa
result = ( # type: ignore[assignment]
diff --git a/pandas/tests/extension/test_categorical.py b/pandas/tests/extension/test_categorical.py
index 09662f7b793a9..8f8af607585df 100644
--- a/pandas/tests/extension/test_categorical.py
+++ b/pandas/tests/extension/test_categorical.py
@@ -19,7 +19,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
from pandas import Categorical
@@ -99,7 +99,7 @@ def test_contains(self, data, data_missing):
continue
assert na_value_obj not in data
# this section suffers from super method
- if not using_pyarrow_string_dtype():
+ if not using_string_dtype():
assert na_value_obj in data_missing
def test_empty(self, dtype):
diff --git a/pandas/tests/frame/constructors/test_from_dict.py b/pandas/tests/frame/constructors/test_from_dict.py
index 60a8e688b3b8a..4237e796e052e 100644
--- a/pandas/tests/frame/constructors/test_from_dict.py
+++ b/pandas/tests/frame/constructors/test_from_dict.py
@@ -3,7 +3,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
DataFrame,
@@ -44,9 +44,7 @@ def test_constructor_single_row(self):
)
tm.assert_frame_equal(result, expected)
- @pytest.mark.skipif(
- using_pyarrow_string_dtype(), reason="columns inferring logic broken"
- )
+ @pytest.mark.skipif(using_string_dtype(), reason="columns inferring logic broken")
def test_constructor_list_of_series(self):
data = [
OrderedDict([["a", 1.5], ["b", 3.0], ["c", 4.0]]),
diff --git a/pandas/tests/frame/constructors/test_from_records.py b/pandas/tests/frame/constructors/test_from_records.py
index ed2f0aa9c4679..ed3f9ac611405 100644
--- a/pandas/tests/frame/constructors/test_from_records.py
+++ b/pandas/tests/frame/constructors/test_from_records.py
@@ -8,7 +8,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.compat import is_platform_little_endian
@@ -58,7 +58,7 @@ def test_from_records_with_datetimes(self):
tm.assert_frame_equal(result, expected)
@pytest.mark.skipif(
- using_pyarrow_string_dtype(), reason="dtype checking logic doesn't work"
+ using_string_dtype(), reason="dtype checking logic doesn't work"
)
def test_from_records_sequencelike(self):
df = DataFrame(
diff --git a/pandas/tests/frame/methods/test_fillna.py b/pandas/tests/frame/methods/test_fillna.py
index 1b852343266aa..5d18b5ed1f7cd 100644
--- a/pandas/tests/frame/methods/test_fillna.py
+++ b/pandas/tests/frame/methods/test_fillna.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
Categorical,
@@ -65,7 +65,7 @@ def test_fillna_datetime(self, datetime_frame):
with pytest.raises(TypeError, match=msg):
datetime_frame.fillna()
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't fill 0 in string")
+ @pytest.mark.xfail(using_string_dtype(), reason="can't fill 0 in string")
def test_fillna_mixed_type(self, float_string_frame):
mf = float_string_frame
mf.loc[mf.index[5:20], "foo"] = np.nan
@@ -537,7 +537,7 @@ def test_fillna_col_reordering(self):
filled = df.ffill()
assert df.columns.tolist() == filled.columns.tolist()
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't fill 0 in string")
+ @pytest.mark.xfail(using_string_dtype(), reason="can't fill 0 in string")
def test_fill_corner(self, float_frame, float_string_frame):
mf = float_string_frame
mf.loc[mf.index[5:20], "foo"] = np.nan
diff --git a/pandas/tests/frame/methods/test_interpolate.py b/pandas/tests/frame/methods/test_interpolate.py
index cdb9ff8a67b6b..7b206cc67d40d 100644
--- a/pandas/tests/frame/methods/test_interpolate.py
+++ b/pandas/tests/frame/methods/test_interpolate.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas.util._test_decorators as td
@@ -65,7 +65,7 @@ def test_interpolate_inplace(self, frame_or_series, request):
assert orig.squeeze()[1] == 1.5
@pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="interpolate doesn't work for string"
+ using_string_dtype(), reason="interpolate doesn't work for string"
)
def test_interp_basic(self):
df = DataFrame(
@@ -90,7 +90,7 @@ def test_interp_basic(self):
assert np.shares_memory(df["D"]._values, dvalues)
@pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="interpolate doesn't work for string"
+ using_string_dtype(), reason="interpolate doesn't work for string"
)
def test_interp_basic_with_non_range_index(self, using_infer_string):
df = DataFrame(
diff --git a/pandas/tests/frame/methods/test_replace.py b/pandas/tests/frame/methods/test_replace.py
index 3fcc4aaa6960f..0a980e5d358a5 100644
--- a/pandas/tests/frame/methods/test_replace.py
+++ b/pandas/tests/frame/methods/test_replace.py
@@ -6,7 +6,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
from pandas import (
@@ -30,9 +30,7 @@ def mix_abc() -> dict[str, list[float | str]]:
class TestDataFrameReplace:
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_inplace(self, datetime_frame, float_string_frame):
datetime_frame.loc[datetime_frame.index[:5], "A"] = np.nan
datetime_frame.loc[datetime_frame.index[-5:], "A"] = np.nan
@@ -293,9 +291,7 @@ def test_regex_replace_dict_nested_non_first_character(
expected = DataFrame({"first": [".bc", "bc.", "c.b"]}, dtype=dtype)
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_regex_replace_dict_nested_gh4115(self):
df = DataFrame({"Type": ["Q", "T", "Q", "Q", "T"], "tmp": 2})
expected = DataFrame(
@@ -304,9 +300,7 @@ def test_regex_replace_dict_nested_gh4115(self):
result = df.replace({"Type": {"Q": 0, "T": 1}})
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_regex_replace_list_to_scalar(self, mix_abc):
df = DataFrame(mix_abc)
expec = DataFrame(
@@ -332,9 +326,7 @@ def test_regex_replace_list_to_scalar(self, mix_abc):
tm.assert_frame_equal(res2, expec)
tm.assert_frame_equal(res3, expec)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_regex_replace_str_to_numeric(self, mix_abc):
# what happens when you try to replace a numeric value with a regex?
df = DataFrame(mix_abc)
@@ -350,9 +342,7 @@ def test_regex_replace_str_to_numeric(self, mix_abc):
tm.assert_frame_equal(res2, expec)
tm.assert_frame_equal(res3, expec)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_regex_replace_regex_list_to_numeric(self, mix_abc):
df = DataFrame(mix_abc)
res = df.replace([r"\s*\.\s*", "b"], 0, regex=True)
@@ -545,9 +535,7 @@ def test_replace_series_dict(self):
result = df.replace(s, df.mean())
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_convert(self):
# gh 3907
df = DataFrame([["foo", "bar", "bah"], ["bar", "foo", "bah"]])
@@ -557,9 +545,7 @@ def test_replace_convert(self):
res = rep.dtypes
tm.assert_series_equal(expec, res)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_mixed(self, float_string_frame):
mf = float_string_frame
mf.iloc[5:20, mf.columns.get_loc("foo")] = np.nan
@@ -902,9 +888,7 @@ def test_replace_input_formats_listlike(self):
with pytest.raises(ValueError, match=msg):
df.replace(to_rep, values[1:])
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_input_formats_scalar(self):
df = DataFrame(
{"A": [np.nan, 0, np.inf], "B": [0, 2, 5], "C": ["", "asdf", "fd"]}
@@ -933,9 +917,7 @@ def test_replace_limit(self):
# TODO
pass
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_dict_no_regex(self):
answer = Series(
{
@@ -957,9 +939,7 @@ def test_replace_dict_no_regex(self):
result = answer.replace(weights)
tm.assert_series_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_series_no_regex(self):
answer = Series(
{
@@ -1064,9 +1044,7 @@ def test_nested_dict_overlapping_keys_replace_str(self):
expected = df.replace({"a": dict(zip(astr, bstr))})
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
def test_replace_swapping_bug(self, using_infer_string):
df = DataFrame({"a": [True, False, True]})
res = df.replace({"a": {True: "Y", False: "N"}})
@@ -1197,9 +1175,7 @@ def test_replace_commutative(self, df, to_replace, exp):
result = df.replace(to_replace)
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
@pytest.mark.parametrize(
"replacer",
[
@@ -1492,9 +1468,7 @@ def test_regex_replace_scalar(
expected.loc[expected["a"] == ".", "a"] = expected_replace_val
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't set float into string"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set float into string")
@pytest.mark.parametrize("regex", [False, True])
def test_replace_regex_dtype_frame(self, regex):
# GH-48644
diff --git a/pandas/tests/frame/test_api.py b/pandas/tests/frame/test_api.py
index 48f51dfa981ca..e8ef0592ac432 100644
--- a/pandas/tests/frame/test_api.py
+++ b/pandas/tests/frame/test_api.py
@@ -5,7 +5,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._config.config import option_context
import pandas as pd
@@ -113,7 +113,7 @@ def test_not_hashable(self):
with pytest.raises(TypeError, match=msg):
hash(empty_frame)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="surrogates not allowed")
+ @pytest.mark.xfail(using_string_dtype(), reason="surrogates not allowed")
def test_column_name_contains_unicode_surrogate(self):
# GH 25509
colname = "\ud83d"
diff --git a/pandas/tests/frame/test_arithmetic.py b/pandas/tests/frame/test_arithmetic.py
index 91b5f905ada22..d42d1d0316892 100644
--- a/pandas/tests/frame/test_arithmetic.py
+++ b/pandas/tests/frame/test_arithmetic.py
@@ -11,7 +11,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
from pandas import (
@@ -251,9 +251,7 @@ def test_timestamp_compare(self, left, right):
with pytest.raises(TypeError, match=msg):
right_f(pd.Timestamp("nat"), df)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't compare string and int"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't compare string and int")
def test_mixed_comparison(self):
# GH#13128, GH#22163 != datetime64 vs non-dt64 should be False,
# not raise TypeError
diff --git a/pandas/tests/frame/test_constructors.py b/pandas/tests/frame/test_constructors.py
index dfcd0d7bfea54..6416ea6415eb3 100644
--- a/pandas/tests/frame/test_constructors.py
+++ b/pandas/tests/frame/test_constructors.py
@@ -21,7 +21,7 @@
from numpy.ma import mrecords
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import lib
from pandas.compat.numpy import np_version_gt2
@@ -299,14 +299,14 @@ def test_constructor_dtype_nocast_view_2d_array(self):
df2 = DataFrame(df.values, dtype=df[0].dtype)
assert df2._mgr.blocks[0].values.flags.c_contiguous
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="conversion copies")
+ @pytest.mark.xfail(using_string_dtype(), reason="conversion copies")
def test_1d_object_array_does_not_copy(self):
# https://github.com/pandas-dev/pandas/issues/39272
arr = np.array(["a", "b"], dtype="object")
df = DataFrame(arr, copy=False)
assert np.shares_memory(df.values, arr)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="conversion copies")
+ @pytest.mark.xfail(using_string_dtype(), reason="conversion copies")
def test_2d_object_array_does_not_copy(self):
# https://github.com/pandas-dev/pandas/issues/39272
arr = np.array([["a", "b"], ["c", "d"]], dtype="object")
diff --git a/pandas/tests/frame/test_reductions.py b/pandas/tests/frame/test_reductions.py
index 649c30bdec790..3f4a5f2c97b6c 100644
--- a/pandas/tests/frame/test_reductions.py
+++ b/pandas/tests/frame/test_reductions.py
@@ -6,7 +6,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.compat import (
IS64,
@@ -465,7 +465,7 @@ def test_mixed_ops(self, op):
getattr(df, op)()
@pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="sum doesn't work for arrow strings"
+ using_string_dtype(), reason="sum doesn't work for arrow strings"
)
def test_reduce_mixed_frame(self):
# GH 6806
@@ -1930,9 +1930,7 @@ def test_sum_timedelta64_skipna_false():
tm.assert_series_equal(result, expected)
-@pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="sum doesn't work with arrow strings"
-)
+@pytest.mark.xfail(using_string_dtype(), reason="sum doesn't work with arrow strings")
def test_mixed_frame_with_integer_sum():
# https://github.com/pandas-dev/pandas/issues/34520
df = DataFrame([["a", 1]], columns=list("ab"))
diff --git a/pandas/tests/frame/test_repr.py b/pandas/tests/frame/test_repr.py
index f799495d8025a..10cc86385af1b 100644
--- a/pandas/tests/frame/test_repr.py
+++ b/pandas/tests/frame/test_repr.py
@@ -7,7 +7,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
NA,
@@ -176,7 +176,7 @@ def test_repr_mixed_big(self):
repr(biggie)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="/r in")
+ @pytest.mark.xfail(using_string_dtype(), reason="/r in")
def test_repr(self):
# columns but no index
no_index = DataFrame(columns=[0, 1, 3])
diff --git a/pandas/tests/indexes/base_class/test_formats.py b/pandas/tests/indexes/base_class/test_formats.py
index 4580e00069dc1..260b4203a4f04 100644
--- a/pandas/tests/indexes/base_class/test_formats.py
+++ b/pandas/tests/indexes/base_class/test_formats.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas._config.config as cf
from pandas import Index
@@ -16,7 +16,7 @@ def test_repr_is_valid_construction_code(self):
res = eval(repr(idx))
tm.assert_index_equal(res, idx)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="repr different")
+ @pytest.mark.xfail(using_string_dtype(), reason="repr different")
@pytest.mark.parametrize(
"index,expected",
[
@@ -81,7 +81,7 @@ def test_string_index_repr(self, index, expected):
result = repr(index)
assert result == expected
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="repr different")
+ @pytest.mark.xfail(using_string_dtype(), reason="repr different")
@pytest.mark.parametrize(
"index,expected",
[
diff --git a/pandas/tests/indexes/categorical/test_category.py b/pandas/tests/indexes/categorical/test_category.py
index 87ec8289089dc..d9c9fdc62b0bc 100644
--- a/pandas/tests/indexes/categorical/test_category.py
+++ b/pandas/tests/indexes/categorical/test_category.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import index as libindex
from pandas._libs.arrays import NDArrayBacked
@@ -199,7 +199,7 @@ def test_unique(self, data, categories, expected_data, ordered):
expected = CategoricalIndex(expected_data, dtype=dtype)
tm.assert_index_equal(idx.unique(), expected)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="repr doesn't roundtrip")
+ @pytest.mark.xfail(using_string_dtype(), reason="repr doesn't roundtrip")
def test_repr_roundtrip(self):
ci = CategoricalIndex(["a", "b"], categories=["a", "b"], ordered=True)
str(ci)
diff --git a/pandas/tests/indexes/categorical/test_formats.py b/pandas/tests/indexes/categorical/test_formats.py
index 491db3a63cc0d..b1361b3e8106e 100644
--- a/pandas/tests/indexes/categorical/test_formats.py
+++ b/pandas/tests/indexes/categorical/test_formats.py
@@ -4,14 +4,14 @@
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas._config.config as cf
from pandas import CategoricalIndex
class TestCategoricalIndexRepr:
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="repr different")
+ @pytest.mark.xfail(using_string_dtype(), reason="repr different")
def test_string_categorical_index_repr(self):
# short
idx = CategoricalIndex(["a", "bb", "ccc"])
diff --git a/pandas/tests/indexes/interval/test_formats.py b/pandas/tests/indexes/interval/test_formats.py
index 3b8e18463160f..d20611a61b154 100644
--- a/pandas/tests/indexes/interval/test_formats.py
+++ b/pandas/tests/indexes/interval/test_formats.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
DataFrame,
@@ -42,7 +42,7 @@ def test_repr_missing(self, constructor, expected, using_infer_string, request):
result = repr(obj)
assert result == expected
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="repr different")
+ @pytest.mark.xfail(using_string_dtype(), reason="repr different")
def test_repr_floats(self):
# GH 32553
diff --git a/pandas/tests/indexes/test_old_base.py b/pandas/tests/indexes/test_old_base.py
index 4b8751fb3ba20..2f22c2490755e 100644
--- a/pandas/tests/indexes/test_old_base.py
+++ b/pandas/tests/indexes/test_old_base.py
@@ -6,7 +6,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs.tslibs import Timestamp
@@ -438,7 +438,7 @@ def test_insert_base(self, index):
assert index[0:4].equals(result)
@pytest.mark.skipif(
- using_pyarrow_string_dtype(),
+ using_string_dtype(),
reason="completely different behavior, tested elsewher",
)
def test_insert_out_of_bounds(self, index):
diff --git a/pandas/tests/indexing/test_coercion.py b/pandas/tests/indexing/test_coercion.py
index 84cd0d3b08b7b..f889fb0686f1d 100644
--- a/pandas/tests/indexing/test_coercion.py
+++ b/pandas/tests/indexing/test_coercion.py
@@ -9,7 +9,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.compat import (
IS64,
@@ -826,7 +826,7 @@ def replacer(self, how, from_key, to_key):
return replacer
# Expected needs adjustment for the infer string option, seems to work as expecetd
- @pytest.mark.skipif(using_pyarrow_string_dtype(), reason="TODO: test is to complex")
+ @pytest.mark.skipif(using_string_dtype(), reason="TODO: test is to complex")
def test_replace_series(self, how, to_key, from_key, replacer):
index = pd.Index([3, 4], name="xxx")
obj = pd.Series(self.rep[from_key], index=index, name="yyy")
diff --git a/pandas/tests/indexing/test_indexing.py b/pandas/tests/indexing/test_indexing.py
index 58255edb8e6df..67b3445e413f0 100644
--- a/pandas/tests/indexing/test_indexing.py
+++ b/pandas/tests/indexing/test_indexing.py
@@ -8,7 +8,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.errors import IndexingError
@@ -426,9 +426,7 @@ def test_set_index_nan(self):
)
tm.assert_frame_equal(result, df)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="can't multiply arrow strings"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="can't multiply arrow strings")
def test_multi_assign(self):
# GH 3626, an assignment of a sub-df to a df
# set float64 to avoid upcast when setting nan
@@ -654,7 +652,7 @@ def test_loc_setitem_fullindex_views(self):
df.loc[df.index] = df.loc[df.index]
tm.assert_frame_equal(df, df2)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't set int into string")
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set int into string")
def test_rhs_alignment(self):
# GH8258, tests that both rows & columns are aligned to what is
# assigned to. covers both uniform data-type & multi-type cases
diff --git a/pandas/tests/indexing/test_loc.py b/pandas/tests/indexing/test_loc.py
index bd1c378642924..07cb76adcaa10 100644
--- a/pandas/tests/indexing/test_loc.py
+++ b/pandas/tests/indexing/test_loc.py
@@ -13,7 +13,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas._libs import index as libindex
from pandas.errors import IndexingError
@@ -1204,7 +1204,7 @@ def test_loc_reverse_assignment(self):
tm.assert_series_equal(result, expected)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't set int into string")
+ @pytest.mark.xfail(using_string_dtype(), reason="can't set int into string")
def test_loc_setitem_str_to_small_float_conversion_type(self):
# GH#20388
diff --git a/pandas/tests/io/excel/test_readers.py b/pandas/tests/io/excel/test_readers.py
index 5591f8ec710e2..0c62b7df8e2cc 100644
--- a/pandas/tests/io/excel/test_readers.py
+++ b/pandas/tests/io/excel/test_readers.py
@@ -17,7 +17,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas.util._test_decorators as td
@@ -691,9 +691,7 @@ def test_dtype_backend_and_dtype(self, read_ext, tmp_excel):
)
tm.assert_frame_equal(result, df)
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="infer_string takes precedence"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="infer_string takes precedence")
def test_dtype_backend_string(self, read_ext, string_storage, tmp_excel):
# GH#36712
if read_ext in (".xlsb", ".xls"):
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index b12cfc6876a8e..af7b04d66096a 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -11,7 +11,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
from pandas import (
@@ -1347,9 +1347,7 @@ def test_unicode_name_in_footer(self):
sf = fmt.SeriesFormatter(s, name="\u05e2\u05d1\u05e8\u05d9\u05ea")
sf._get_footer() # should not raise exception
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="Fixup when arrow is default"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="Fixup when arrow is default")
def test_east_asian_unicode_series(self):
# not aligned properly because of east asian width
@@ -1724,9 +1722,7 @@ def chck_ncols(self, s):
ncolsizes = len({len(line.strip()) for line in lines})
assert ncolsizes == 1
- @pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="change when arrow is default"
- )
+ @pytest.mark.xfail(using_string_dtype(), reason="change when arrow is default")
def test_format_explicit(self):
test_sers = gen_series_formatting()
with option_context("display.max_rows", 4, "display.show_dimensions", False):
diff --git a/pandas/tests/io/formats/test_to_string.py b/pandas/tests/io/formats/test_to_string.py
index ed871577d677f..5731f74a03852 100644
--- a/pandas/tests/io/formats/test_to_string.py
+++ b/pandas/tests/io/formats/test_to_string.py
@@ -10,7 +10,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
CategoricalIndex,
@@ -849,7 +849,7 @@ def test_to_string(self):
frame.to_string()
# TODO: split or simplify this test?
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="fix when arrow is default")
+ @pytest.mark.xfail(using_string_dtype(), reason="fix when arrow is default")
def test_to_string_index_with_nan(self):
# GH#2850
df = DataFrame(
diff --git a/pandas/tests/io/json/test_pandas.py b/pandas/tests/io/json/test_pandas.py
index a34c0adc69821..3c551e80ef00b 100644
--- a/pandas/tests/io/json/test_pandas.py
+++ b/pandas/tests/io/json/test_pandas.py
@@ -10,7 +10,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.compat import IS64
import pandas.util._test_decorators as td
@@ -1573,7 +1573,7 @@ def test_from_json_to_json_table_dtypes(self):
# TODO: We are casting to string which coerces None to NaN before casting back
# to object, ending up with incorrect na values
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="incorrect na conversion")
+ @pytest.mark.xfail(using_string_dtype(), reason="incorrect na conversion")
@pytest.mark.parametrize("orient", ["split", "records", "index", "columns"])
def test_to_json_from_json_columns_dtypes(self, orient):
# GH21892 GH33205
@@ -1854,7 +1854,7 @@ def test_to_json_indent(self, indent):
assert result == expected
@pytest.mark.skipif(
- using_pyarrow_string_dtype(),
+ using_string_dtype(),
reason="Adjust expected when infer_string is default, no bug here, "
"just a complicated parametrization",
)
diff --git a/pandas/tests/reshape/test_pivot.py b/pandas/tests/reshape/test_pivot.py
index 2872b1e29d629..476ec2fc76488 100644
--- a/pandas/tests/reshape/test_pivot.py
+++ b/pandas/tests/reshape/test_pivot.py
@@ -9,7 +9,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.compat.numpy import np_version_gte1p25
@@ -2656,7 +2656,7 @@ def test_pivot_columns_not_given(self):
with pytest.raises(TypeError, match="missing 1 required keyword-only argument"):
df.pivot()
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="None is cast to NaN")
+ @pytest.mark.xfail(using_string_dtype(), reason="None is cast to NaN")
def test_pivot_columns_is_none(self):
# GH#48293
df = DataFrame({None: [1], "b": 2, "c": 3})
@@ -2672,7 +2672,7 @@ def test_pivot_columns_is_none(self):
expected = DataFrame({1: 3}, index=Index([2], name="b"))
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="None is cast to NaN")
+ @pytest.mark.xfail(using_string_dtype(), reason="None is cast to NaN")
def test_pivot_index_is_none(self):
# GH#48293
df = DataFrame({None: [1], "b": 2, "c": 3})
@@ -2686,7 +2686,7 @@ def test_pivot_index_is_none(self):
expected = DataFrame(3, index=[1], columns=Index([2], name="b"))
tm.assert_frame_equal(result, expected)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="None is cast to NaN")
+ @pytest.mark.xfail(using_string_dtype(), reason="None is cast to NaN")
def test_pivot_values_is_none(self):
# GH#48293
df = DataFrame({None: [1], "b": 2, "c": 3})
diff --git a/pandas/tests/series/indexing/test_where.py b/pandas/tests/series/indexing/test_where.py
index 7718899ff234b..053c290999f2f 100644
--- a/pandas/tests/series/indexing/test_where.py
+++ b/pandas/tests/series/indexing/test_where.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas.core.dtypes.common import is_integer
@@ -231,7 +231,7 @@ def test_where_ndframe_align():
tm.assert_series_equal(out, expected)
-@pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't set ints into string")
+@pytest.mark.xfail(using_string_dtype(), reason="can't set ints into string")
def test_where_setitem_invalid():
# GH 2702
# make sure correct exceptions are raised on invalid list assignment
diff --git a/pandas/tests/series/methods/test_reindex.py b/pandas/tests/series/methods/test_reindex.py
index 831c2338045ff..8901330108cb1 100644
--- a/pandas/tests/series/methods/test_reindex.py
+++ b/pandas/tests/series/methods/test_reindex.py
@@ -1,7 +1,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
from pandas import (
NA,
@@ -22,9 +22,7 @@
import pandas._testing as tm
-@pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="share memory doesn't work for arrow"
-)
+@pytest.mark.xfail(using_string_dtype(), reason="share memory doesn't work for arrow")
def test_reindex(datetime_series, string_series):
identity = string_series.reindex(string_series.index)
diff --git a/pandas/tests/series/methods/test_replace.py b/pandas/tests/series/methods/test_replace.py
index 90654df155cf0..0df5b5a5d0108 100644
--- a/pandas/tests/series/methods/test_replace.py
+++ b/pandas/tests/series/methods/test_replace.py
@@ -3,7 +3,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
import pandas._testing as tm
@@ -359,7 +359,7 @@ def test_replace_mixed_types_with_string(self):
expected = pd.Series([1, np.nan, 3, np.nan, 4, 5], dtype=object)
tm.assert_series_equal(expected, result)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't fill 0 in string")
+ @pytest.mark.xfail(using_string_dtype(), reason="can't fill 0 in string")
@pytest.mark.parametrize(
"categorical, numeric",
[
@@ -620,7 +620,7 @@ def test_replace_nullable_numeric(self):
with pytest.raises(TypeError, match="Invalid value"):
ints.replace(1, 9.5)
- @pytest.mark.xfail(using_pyarrow_string_dtype(), reason="can't fill 1 in string")
+ @pytest.mark.xfail(using_string_dtype(), reason="can't fill 1 in string")
@pytest.mark.parametrize("regex", [False, True])
def test_replace_regex_dtype_series(self, regex):
# GH-48644
diff --git a/pandas/tests/series/test_formats.py b/pandas/tests/series/test_formats.py
index c001e0f9b028a..78be4843f7a4d 100644
--- a/pandas/tests/series/test_formats.py
+++ b/pandas/tests/series/test_formats.py
@@ -6,7 +6,7 @@
import numpy as np
import pytest
-from pandas._config import using_pyarrow_string_dtype
+from pandas._config import using_string_dtype
import pandas as pd
from pandas import (
@@ -144,7 +144,7 @@ def test_tidy_repr_name_0(self, arg):
assert "Name: 0" in rep_str
@pytest.mark.xfail(
- using_pyarrow_string_dtype(), reason="TODO: investigate why this is failing"
+ using_string_dtype(), reason="TODO: investigate why this is failing"
)
def test_newline(self):
ser = Series(["a\n\r\tb"], name="a\n\r\td", index=["a\n\r\tf"])