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TST (string dtype): fix xfails in test_algos.py #60119

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TST (string dtype): fix xfails in test_algos.py #60119

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8 changes: 2 additions & 6 deletions pandas/tests/test_algos.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,6 @@
import numpy as np
import pytest

from pandas._config import using_string_dtype

from pandas._libs import (
algos as libalgos,
hashtable as ht,
Expand Down Expand Up @@ -1684,7 +1682,6 @@ def test_unique_complex_numbers(self, array, expected):


class TestHashTable:
@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
@pytest.mark.parametrize(
"htable, data",
[
Expand All @@ -1697,7 +1694,7 @@ class TestHashTable:
)
def test_hashtable_unique(self, htable, data, writable):
# output of maker has guaranteed unique elements
s = Series(data)
s = Series(data, dtype=object if isinstance(data, list) else None)
if htable == ht.Float64HashTable:
# add NaN for float column
s.loc[500] = np.nan
Expand All @@ -1724,7 +1721,6 @@ def test_hashtable_unique(self, htable, data, writable):
reconstr = result_unique[result_inverse]
tm.assert_numpy_array_equal(reconstr, s_duplicated.values)

@pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string)", strict=False)
@pytest.mark.parametrize(
"htable, data",
[
Expand All @@ -1737,7 +1733,7 @@ def test_hashtable_unique(self, htable, data, writable):
)
def test_hashtable_factorize(self, htable, writable, data):
# output of maker has guaranteed unique elements
s = Series(data)
s = Series(data, dtype=object if isinstance(data, list) else None)
if htable == ht.Float64HashTable:
# add NaN for float column
s.loc[500] = np.nan
Expand Down