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REGR: check_flags not respected in assert_frame_equal #45565

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Merged
merged 5 commits into from
Jan 28, 2022
Merged

REGR: check_flags not respected in assert_frame_equal #45565

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c8c95e2
REGR: check_flags not respected in assert_frame_equal
phofl Jan 23, 2022
a45dbce
Check passed kwarg
phofl Jan 23, 2022
271c674
Fix comment
phofl Jan 23, 2022
4f23b86
Merge branch 'main' into 45554
jreback Jan 26, 2022
789b8e6
Merge branch 'main' into 45554
jreback Jan 27, 2022
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.4.1.rst
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Expand Up @@ -15,7 +15,7 @@ including other versions of pandas.
Fixed regressions
~~~~~~~~~~~~~~~~~
- Regression in :meth:`Series.mask` with ``inplace=True`` and ``PeriodDtype`` and an incompatible ``other`` coercing to a common dtype instead of raising (:issue:`45546`)
-
- Regression in :func:`.assert_frame_equal` not respecting ``check_flags=False``(:issue:`45554`)
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again. I don't understand fully since have not investigated but this issue is not actually a regression if the flag was not propagated before? As with check_flags=True I assume it did not raise if the flags were different.


.. ---------------------------------------------------------------------------

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1 change: 1 addition & 0 deletions pandas/_testing/asserters.py
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Expand Up @@ -1344,6 +1344,7 @@ def assert_frame_equal(
rtol=rtol,
atol=atol,
check_index=False,
check_flags=check_flags,
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@simonjayhawkins simonjayhawkins Jan 23, 2022 •
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right. I think I am starting to get my head round this. This should be check_flags=False to override the default checking in assert_series_equal and be consistent with check_index=False in the line above.

the flags check is already performed on the DataFrame.

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Yep you are correct. Passing in False is the way to go here

)


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15 changes: 14 additions & 1 deletion pandas/tests/util/test_assert_frame_equal.py
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Expand Up @@ -323,9 +323,22 @@ def test_frame_equal_mixed_dtypes(frame_or_series, any_numeric_ea_dtype, indexer
tm.assert_equal(obj1, obj2, check_exact=True, check_dtype=False)


def test_assert_series_equal_check_like_different_indexes():
def test_assert_frame_equal_check_like_different_indexes():
# GH#39739
df1 = DataFrame(index=pd.Index([], dtype="object"))
df2 = DataFrame(index=pd.RangeIndex(start=0, stop=0, step=1))
with pytest.raises(AssertionError, match="DataFrame.index are different"):
tm.assert_frame_equal(df1, df2, check_like=True)


def test_assert_frame_equal_checking_allow_dups_flag():
# GH#45554
left = DataFrame([[1, 2], [3, 4]])
left.flags.allows_duplicate_labels = False

right = DataFrame([[1, 2], [3, 4]])
right.flags.allows_duplicate_labels = True
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do we also need to test for DataFrames with the same flags with check_flags=True/False. I find it odd (without investigation) that the reported issue was not picked up before. The flag is on the DataFrame so why not check that instead of on the Series?

tm.assert_frame_equal(left, right, check_flags=False)

with pytest.raises(AssertionError, match="allows_duplicate_labels"):
tm.assert_frame_equal(left, right, check_flags=True)