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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) #61473

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#61748
#61525
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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)#61473
#61748
#61525
Labels
BugExtensionArrayExtending pandas with custom dtypes or arrays.Testingpandas testing functions or related to the test suitegood first issue
@michiel-de-muynck

Description

@michiel-de-muynck
michiel-de-muynck
opened on May 21, 2025
Contributor

Pandas version checks

  • I have checked that this issue has not already been reported.

    I have confirmed this bug exists on the latest version of pandas.

    I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
from pandas.testing import assert_frame_equal

df1 = pd.DataFrame(
    {
        "x": pd.Series([pd.NA], dtype="Int32"),
    }
)
df2 = pd.DataFrame(
    {
        "x": pd.Series([pd.NA], dtype="object"),
    }
)

assert_frame_equal(df1, df2, check_dtype=False) # fails, but should succeed

Issue Description

Output of the above example:

AssertionError: DataFrame.iloc[:, 0] (column name="x") are different

DataFrame.iloc[:, 0] (column name="x") values are different (100.0 %)
[index]: [0]
[left]:  [nan]
[right]: [<NA>]

When comparing DataFrames containing pd.NA using check_dtype=False, the test incorrectly fails despite the only difference being the dtype (Int32 vs object).

Note that the values in the dataframe really are the same:

print(type(df1["x"][0])) # prints <class 'pandas._libs.missing.NAType'>
print(type(df2["x"][0])) # prints <class 'pandas._libs.missing.NAType'>

Related issues:

Expected Behavior

The test should succeed, since the only difference is the dtypes, and check_dtype=False.

Installed Versions

pandas : 2.2.3
numpy : 1.26.4
pytz : 2025.2
dateutil : 2.9.0.post0
pip : 24.0
Cython : None
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 19.0.1
pyreadstat : None
pytest : 8.3.5
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.41
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : 0.23.0
tzdata : 2025.2
qtpy : None
pyqt5 : None

Activity

michiel-de-muynck
added
Bug
Needs TriageIssue that has not been reviewed by a pandas team member
on May 21, 2025
rhshadrach

rhshadrach commented on May 21, 2025

@rhshadrach
rhshadrach
on May 21, 2025
Member

Thanks for the report, this would pass if when converting the EA to a NumPy array we cast to object dtype. I haven't looked to see if this might cause issues in other cases. Since this is aimed at tests, I'm wondering if changing to object dtype is okay here.

cc @jbrockmendel @mroeschke for any thoughts.

rhshadrach
added
Testingpandas testing functions or related to the test suite
Needs DiscussionRequires discussion from core team before further action
ExtensionArrayExtending pandas with custom dtypes or arrays.
and removed
Needs TriageIssue that has not been reviewed by a pandas team member
on May 21, 2025
jbrockmendel

jbrockmendel commented on May 21, 2025

@jbrockmendel
jbrockmendel
on May 21, 2025
Member

this would pass if when converting the EA to a NumPy array we cast to object dtype

Yah I'm pretty sure that the behavior of df1['x'].to_numpy() casting to a float dtype was a much-discussed intentional decision. Changing that would be a can of worms.

I'm inclined to just discourage the use of a) check_dtype=False and b) using pd.NA in an object dtype column (note that df1 == df2 raises)

rhshadrach

rhshadrach commented on May 23, 2025

@rhshadrach
rhshadrach
on May 23, 2025 · edited by rhshadrach
Member

@jbrockmendel - sorry, I wasn't clear. I meant just inside assert_frame_equal to use .to_numpy(dtype="object") when check_dtype=False rather than just .to_numpy(). Agreed changing the behavior of .to_numpy() is off the table.

jbrockmendel

jbrockmendel commented on May 23, 2025

@jbrockmendel
jbrockmendel
on May 23, 2025
Member

Gotcha, fine by me

rhshadrach
added
good first issue
and removed
Needs DiscussionRequires discussion from core team before further action
on May 30, 2025
iabhi4
added a commit that references this issue on May 31, 2025

BUG: Fix assert_frame_equal dtype handling when check_dtype=False (pa…

3577b05
iabhi4
linked a pull request that will close this issue on May 31, 2025
venturero

venturero commented on Jun 1, 2025

@venturero
venturero
on Jun 1, 2025

how can i make contribution to solve this, can you please give advice to me? @iabhi4 @rhshadrach

iabhi4
added 2 commits that reference this issue on Jun 1, 2025

BUG: Fix assert_frame_equal dtype handling when check_dtype=False (pa…

1aff954

BUG: Fix assert_frame_equal dtype handling when check_dtype=False (pa…

ad74d18
iabhi4

iabhi4 commented on Jun 1, 2025

@iabhi4
iabhi4
on Jun 1, 2025
Contributor

Hi @venturero

I already raised a PR for this based on the above discussion. You can checkout other issues from the Issues tab and follow the contribution guide to submit a clean fix for the issue you're tackling.

iabhi4
added 3 commits that reference this issue on Jun 1, 2025

BUG: Fix assert_frame_equal dtype handling when check_dtype=False (pa…

e738953

BUG: Fix assert_frame_equal dtype handling when check_dtype=False (pa…

5e422e4

BUG: Fix assert_frame_equal dtype handling when check_dtype=False (pa…

fcac82c
gamzeozgul
added a commit that references this issue on Jun 30, 2025

FIX: Handle pd.NA values in assert_frame_equal when check_dtype=False (…

f7a6c92
gamzeozgul
linked a pull request that will close this issue on Jun 30, 2025
gamzeozgul
added a commit that references this issue on Jul 1, 2025

FIX: Handle pd.NA values in assert_frame_equal when check_dtype=False (…

c4e123a
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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) · Issue #61473 · pandas-dev/pandas