Inconsistent handling of nan-float64 in Series.isin() · Issue #22205 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example if possible

N=10**6 s=pd.Series(np.full(N, np.nan, dtype=np.float64), copy=False) s.isin([np.nan]).all()

results in True, however

s=pd.Series(np.full(N+1, np.nan, dtype=np.float64), copy=False) s.isin([np.nan]).all()

results in False, even more s.isin([np.nan]).any() results in False

Problem description

Obviously, the result should be the same in both cases.

Expected Output

IMO True is more consistent with the behavior of Pandas in other functions (such as pd.unique()).

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-53-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.2.1
pip: 10.0.1
setuptools: 36.5.0.post20170921
Cython: 0.28.3
numpy: 1.13.1
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 0.9.8
lxml: 3.8.0
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: 0.1.3
fastparquet: None
pandas_gbq: None
pandas_datareader: None