Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import numpy as np
pd.Series([635554097106142143],dtype="UInt64").isin(np.array([635554097106142079]))Issue Description
The isin check returns True, although clearly 635554097106142143 ≠ 635554097106142079
Presumably during the check the values are converted to a dtype with smaller precision.
Expected Behavior
Not using the UInt64 dtype as well as not checking against a numpy array produce the expected result
I.e. both
pd.Series([635554097106142143],dtype="int64").isin(np.array([635554097106142079]))and
pd.Series([635554097106142143],dtype="UInt64").isin([635554097106142079])Evaluate to False
Installed Versions
NSTALLED VERSIONS
commit : d9cdd2e
python : 3.12.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.0-46-generic
Version : #47~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Wed Jun 21 15:35:31 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.2.2
numpy : 2.0.0
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 24.0
Cython : None
pytest : 7.4.3
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.2.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.18.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2023.10.0
gcsfs : None
matplotlib : 3.9.1
numba : 0.60.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 17.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.14.0
sqlalchemy : None
tables : None
tabulate : None
xarray : 2024.1.1
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None