TST: GH20676 Verify equals operator for list of Numpy arrays

[avinashpancham]

• closes pd.Series.equals() fails for Series containing iterable objects #20676
• [ x ] tests added / passed
• [ x ] passes black pandas
• [ x ] passes git diff upstream/master -u -- "*.py" | flake8 --diff
• [ x ] whatsnew entry

[mroeschke]

You can in-line this data in the test since is parameterizing over 1 value

[simonjayhawkins]

Thanks @avinashpancham lgtm. as a follow-up test_equals in pandas\tests\generic\test_generic.py could be split and the Series tests moved here.

[avinashpancham]

@simonjayhawkins Moved the Series.equals tests from generic/test_generic.py to series/methods/test_equals.py. But I think I found a bug while restructuring the tests such that they are in the same style. This raises a ValueError instead of False. If this is a bug that should be addressed then I would like to help (if possible given my little experience).

Code Sample, a copy-pastable example if possible

arr = np.array([1, 2])
s1 = pd.Series([arr, arr])
s2 = s1.copy()

s1[1] = 9
s1.equals(s2)

Problem description
Series.qquals operation fails when comparing two Series that have a single value and list at the same position.

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Expected Output
False

Output of pd.show_versions()
INSTALLED VERSIONS

commit : 33df259
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.5.0
Version : Darwin Kernel Version 19.5.0: Tue May 26 20:41:44 PDT 2020; root:xnu-6153.121.2~2/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

Output of pd.show_versions()
pandas : 1.1.0.dev0+2090.g33df25994.dirty
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.1.1.post20200710
Cython : 0.29.21
pytest : 5.4.3
hypothesis : 5.19.0
sphinx : 3.1.1
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : 0.7.4
fastparquet : 0.4.0
gcsfs : 0.6.2
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.0
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.1
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.50.1

[jreback]

@simonjayhawkins Moved the Series.equals tests from generic/test_generic.py to series/methods/test_equals.py. But I think I found a bug while restructuring the tests such that they are in the same style. This raises a ValueError instead of False. If this is a bug that should be addressed then I would like to help (if possible given my little experience).

Code Sample, a copy-pastable example if possible

arr = np.array([1, 2])
s1 = pd.Series([arr, arr])
s2 = s1.copy()

s1[1] = 9
s1.equals(s2)

Problem description
Series.qquals operation fails when comparing two Series that have a single value and list at the same position.

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Expected Output
False

Output of pd.show_versions()

INSTALLED VERSIONS
commit : 33df259
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.5.0
Version : Darwin Kernel Version 19.5.0: Tue May 26 20:41:44 PDT 2020; root:xnu-6153.121.2~2/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

Output of pd.show_versions()
pandas : 1.1.0.dev0+2090.g33df25994.dirty
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.1.1.post20200710
Cython : 0.29.21
pytest : 5.4.3
hypothesis : 5.19.0
sphinx : 3.1.1
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : 0.7.4
fastparquet : 0.4.0
gcsfs : 0.6.2
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.0
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.1
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.50.1

@avinashpancham can you file a new issue about this on master. thanks.

[jreback]

thanks @avinashpancham