Pandas version checks
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[x] I have checked that this issue has not already been reported.
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[x] I have confirmed this bug exists on the latest version of pandas.
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[x] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import numpy as np
test_df = pd.DataFrame([{'a': 1378774140726870442}], dtype=np.int64)
print(test_df['a'].isin([np.uint64(1378774140726870528)])[0])
#True
Issue Description
The latest version of Pandas fixes the implicit conversion to float64 only when dtypes are uint64 vs int64. Int64 vs uint64 needs also to be fixed.
Expected Behavior
import pandas as pd import numpy as np test_df = pd.DataFrame([{'a': 1378774140726870442}], dtype=np.int64)
print(test_df['a'].isin([np.uint64(1378774140726870528)])[0])
False
Installed Versions
INSTALLED VERSIONS
------------------
commit : 0691c5cf90477d3503834d983f69350f250a6ff7
python : 3.11.2
python-bits : 64
OS : Linux
OS-release : 6.1.0-31-amd64
Version : #1 SMP PREEMPT_DYNAMIC Debian 6.1.128-1 (2025-02-07)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : fr_FR.UTF-8
LOCALE : fr_FR.UTF-8
pandas : 2.2.3
numpy : 1.26.0
pytz : 2023.3.post1
dateutil : 2.8.2
pip : 23.0.1
Cython : 3.0.12
sphinx : None
IPython : 8.17.2
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2023.10.0
html5lib : None
hypothesis : 6.131.0
gcsfs : None
jinja2 : 3.1.2
lxml.etree : None
matplotlib : 3.8.2
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 14.0.1
pyreadstat : None
pytest : 8.3.5
python-calamine : None
pyxlsb : None
s3fs : 2023.10.0
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None
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