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@santhoshbethi santhoshbethi commented Oct 13, 2025

^^^^^
- Bug in :class:`DataFrame` when passing a ``dict`` with a NA scalar and ``columns`` that would always return ``np.nan`` (:issue:`57205`)
- Bug in :class:`Series` ignoring errors when trying to convert :class:`Series` input data to the given ``dtype`` (:issue:`60728`)
- Bug in :func:`assert_frame_equal` fails when comparing two DFs containing pd.NA that only differ in dtype and dtype is false (:issue:`61473`)
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"in dtype and dtype is false" is odd phrasing

DFs -> ```:class:DataFrames````
fails -> failing

Second Series to compare.
check_dtype : bool, default True
Whether to check the Series dtype is identical.
check_dtype : bool, if False
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check_dtype is already there 2 lines up

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also the default is still True

if not check_dtype and (left.dtype != right.dtype):
# checks only when check_dtype is False #GH #61473
lv, rv = left._values, right._values
lv = np.asarray(lv, dtype=object)
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this is going to be really expensive. no other alternatives?

).rename(columns={"B": "A"})
df = DataFrame({"A": range(3), "B": range(3), "C": range(3)}).rename(
columns={"B": "A"}
)
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these changes look unrelated. please revert

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I am closing this PR

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BUG: assert_frame_equal(check_dtype=False) fails when comparing two DFs containing pd.NA that only differ in dtype (object vs Int32)

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