BUG: assert_frame_equal failed on comparing two not equal Sets ('set' object is not subscriptable) · Issue #51727 · pandas-dev/pandas (original) (raw)

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({'set_column': [{1, 2, 3}, {4, 5, 6}]}) # last number is different. df2 = pd.DataFrame({'set_column': [{1, 2, 3}, {4, 5, 7}]})

assert_frame_equal(df1, df2)

Issue Description

Exception:

pandas/_libs/testing.pyx:53: in pandas._libs.testing.assert_almost_equal
    ???
pandas/_libs/testing.pyx:159: in pandas._libs.testing.assert_almost_equal
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   TypeError: 'set' object is not subscriptable

pandas/_libs/testing.pyx:159: TypeError

It was raised in assert_series_equal in last else statement:

_testing.assert_almost_equal(
            left._values,
            right._values,
            rtol=rtol,
            atol=atol,
            check_dtype=bool(check_dtype),
            obj=str(obj),
            index_values=np.asarray(left.index),
        )

Expected Behavior

assert not equal error will be shown.

Installed Versions

INSTALLED VERSIONS

commit : 66e3805
python : 3.9.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-1028-aws
Version : #32~20.04.1-Ubuntu SMP Mon Jan 9 18:02:08 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.5
numpy : 1.22.2
pytz : 2022.7.1
dateutil : 2.8.0
pip : 22.3
setuptools : 65.5.0
Cython : 0.29.33
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.8
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.5.4
sqlalchemy : 1.4.46
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

But also was able to reproduce on latest version pandas==1.5.3.