isin() returns different results than eq() when mixing dtypes of comparators

Expected correct behavior for the same compartor dtypes

s = pd.Series([1.2, 2.3])
s.eq(1.2) == s.isin([1.2]) # True, True

s32 = pd.Series([1.2, 2.3], dtype="float32")
s32.eq(np.float32(1.2)) == s32.isin([np.float32(1.2)]) # True, True

Non expected behavior for mixed comparator dtypes

s32.eq(1.2) == s32.isin([1.2]) # False, True

# in detail
s32.eq(1.2) # True, False
s32.isin([1.2]) # False, False

In summary, eq() and isin() return different results when mixing comparator dtypes.

Problem description

Both methods eq() and isin() should return the same result. Here is the related SO article.

This issue might originate in numpy and perhaps is not directly pandas related (see here for more). Scalar comparison (equivalent to eq()) and array comparison (equivalent to isin()) comparison yield different results for mixed comparator dtypes in numpy, too.

Output of `pd.show_versions()`

INSTALLED VERSIONS ------------------ commit: None python: 3.6.1.final.0 python-bits: 64 OS: Linux OS-release: 4.8.0-58-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 pandas: 0.20.2 pytest: None pip: 9.0.1 setuptools: 36.0.1 Cython: 0.25.2 numpy: 1.13.1 scipy: 0.19.1 xarray: None IPython: 6.1.0 sphinx: None patsy: None dateutil: 2.6.0 pytz: 2017.2 blosc: None bottleneck: None tables: None numexpr: None feather: None matplotlib: 2.0.2 openpyxl: None xlrd: None xlwt: None xlsxwriter: None lxml: None bs4: None html5lib: 0.999999999 sqlalchemy: None pymysql: None psycopg2: None jinja2: 2.9.6 s3fs: None pandas_gbq: None pandas_datareader: None

pandas-dev / pandas