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1 change: 1 addition & 0 deletions doc/source/whatsnew/v3.0.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -1192,6 +1192,7 @@ Other
- Bug in :func:`eval` where method calls on binary operations like ``(x + y).dropna()`` would raise ``AttributeError: 'BinOp' object has no attribute 'value'`` (:issue:`61175`)
- Bug in :func:`eval` where the names of the :class:`Series` were not preserved when using ``engine="numexpr"``. (:issue:`10239`)
- Bug in :func:`eval` with ``engine="numexpr"`` returning unexpected result for float division. (:issue:`59736`)
- Bug in :func:`test_query_duplicate_column_name` raising ``doc-formatting`` error and causing pipelines to fail (:issue:`62701`)
- Bug in :func:`to_numeric` raising ``TypeError`` when ``arg`` is a :class:`Timedelta` or :class:`Timestamp` scalar. (:issue:`59944`)
- Bug in :func:`unique` on :class:`Index` not always returning :class:`Index` (:issue:`57043`)
- Bug in :meth:`DataFrame.apply` raising ``RecursionError`` when passing ``func=list[int]``. (:issue:`61565`)
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20 changes: 5 additions & 15 deletions pandas/tests/frame/test_query_eval.py
Original file line number Diff line number Diff line change
Expand Up @@ -160,21 +160,13 @@ def test_query_empty_string(self):
df.query("")

def test_query_duplicate_column_name(self, engine, parser):
df = DataFrame(
{
"A": range(3),
"B": range(3),
"C": range(3)
}
).rename(columns={"B": "A"})
df = DataFrame({"A": range(3), "B": range(3), "C": range(3)}).rename(
columns={"B": "A"}
)

res = df.query("C == 1", engine=engine, parser=parser)

expect = DataFrame(
[[1, 1, 1]],
columns=["A", "A", "C"],
index=[1]
)
expect = DataFrame([[1, 1, 1]], columns=["A", "A", "C"], index=[1])

tm.assert_frame_equal(res, expect)

Expand Down Expand Up @@ -1140,9 +1132,7 @@ def test_query_with_nested_special_character(self, parser, engine):
[">=", operator.ge],
],
)
def test_query_lex_compare_strings(
self, parser, engine, op, func
):
def test_query_lex_compare_strings(self, parser, engine, op, func):
a = Series(np.random.default_rng(2).choice(list("abcde"), 20))
b = Series(np.arange(a.size))
df = DataFrame({"X": a, "Y": b})
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