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Description
Pandas version checks
I have checked that this issue has not already been reported.
I have confirmed this bug exists on thelatest version of pandas.
I have confirmed this bug exists on themain branch of pandas.
Reproducible Example
In [1]:importpandasaspdIn [2]:importnumpy.maasmaIn [3]:mx=ma.masked_array([4873214862074861312,4875446630161458944,4824652147895424384,0,3526420114272476800],mask=[0,0,0,1,0])In [4]:pd.Series(mx,dtype='Int64')Out[4]:0487321486207486156814875446630161459200248246521478954240003<NA>43526420114272476672dtype:Int64In [5]:mx.data-pd.Series(mx,dtype='Int64')Out[5]:0-2561-25623843<NA>4128dtype:Int64
Issue Description
While creating a series object from a masked array of large-ish integers (less than max ofInt64), the output doesn't match the input. This has probably something to do with float downcast/upcast somewhere.
Probably related (?)#30268,#50757
Expected Behavior
mx.data - pd.Series(mx, dtype='Int64') should be all zero with<NA> for the mask.
Installed Versions
INSTALLED VERSIONS
commit :a671b5a
python : 3.11.6.final.0
python-bits : 64
OS : Darwin
OS-release : 23.2.0
Version : Darwin Kernel Version 23.2.0: Wed Nov 15 21:53:18 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.4
numpy : 1.26.1
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : 3.0.5
pytest : 7.4.3
hypothesis : 6.88.3
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.17.2
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.12.2
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 14.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None