Equality between DataFrames misbehaves if columns contain NaN #18455
Description
Code Sample, a copy-pastable example if possible
In [2]: s = pd.DataFrame(-1, index=[1, np.nan, 2,], ...: columns=[3, np.nan, 1]) ...: In [3]: s + s # good Out[3]: 3.0 NaN 1.0 1.0 -2 -2 -2 NaN -2 -2 -2 2.0 -2 -2 -2 In [4]: s == s # bad Out[4]: 3.0 NaN 1.0 1.0 True NaN True NaN True NaN True 2.0 True NaN TrueProblem description
While it is true that np.nan != np.nan, pandas disregards this in indexes (indeed, s.loc[:, np.nan] works), so it should be coherent.
Expected Output
In [4]: s == s Out[4]: 3.0 NaN 1.0 1.0 True True True NaN True True True 2.0 True True TrueOutput of pd.show_versions()
INSTALLED VERSIONS
commit: b45325e
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-3-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8
pandas: 0.22.0.dev0+201.gb45325e28.dirty
pytest: 3.2.3
pip: 9.0.1
setuptools: 36.7.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.0
openpyxl: None
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: None
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1