Closed
Description
Code Sample, a copy-pastable example if possible
import numpy as np
import pandas as pd
from pandas.util.testing import assert_almost_equal
e1 = np.array([0.5831076580182805, -0.9083518696779991], 'd')
e2 = np.array([0.5831076580182805, -0.9083518696779992], 'd')
e1z = np.asanyarray(e1, np.complex128)
e2z = np.asanyarray(e2, np.complex128)
assert_almost_equal(pd.Series(e1), pd.Series(e2)) # gives True as expected
assert_almost_equal(pd.Series(e1z), pd.Series(e2z)) # unexpectedly fails
# both of equivalent tests on NumPy side pass
np.testing.assert_almost_equal(e1, e2)
np.testing.assert_almost_equal(e1z, e2z)Problem description
When running tests on MacOSX with Pandas 0.25.1, the test pandas.tests.computation.test_eval.TestMathNumExprPandas::test_result_complex128 fails because of this issue.
Expected Output
It is expected that pandas._lib.testing.assert_almost_equal would use np.testing.assert_almost_equal for all np.floating and np.complexfloating dtypes.
Output of pd.show_versions()
In [4]: pd.show_versions()
INSTALLED VERSIONS
------------------
commit : None
python : 3.6.9.final.0
python-bits : 64
OS : Darwin
OS-release : 15.4.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.1
numpy : 1.17.1
pytz : 2019.1
dateutil : 2.8.0
pip : 19.1.1
setuptools : 41.0.1.post20190716
Cython : None
pytest : 3.8.1
hypothesis : 3.68.0
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 6.3.1
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None