Closed
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 numpy as np
import pandas as pd
s = pd.Series([10000000000000000000], dtype="uint64")
s.sum() # -8446744073709551616
s.to_numpy().sum() # 10000000000000000000
s = pd.Series([10000000000000000000], dtype="uint64[pyarrow]")
s.sum() # 10000000000000000000Issue Description
The summation of a series of uint64 is converted to int64.
Expected Behavior
The result would be a uint64.
Installed Versions
INSTALLED VERSIONS
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commit : 37ea63d540fd27274cad6585082c91b1283f963d
python : 3.11.3.final.0
python-bits : 64
OS : Linux
OS-release : 6.2.6-76060206-generic
Version : #202303130630~1683753207~22.04~77c1465 SMP PREEMPT_DYNAMIC Wed M
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.0.1
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.7.2
pip : 23.1.2
Cython : None
pytest : 7.3.1
hypothesis : None
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.13.2
pandas_datareader: None
bs4 : 4.12.2
bottleneck : None
brotli :
fastparquet : 2023.4.0
fsspec : 2023.5.0
gcsfs : None
matplotlib : 3.7.1
numba : 0.57.0
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
snappy :
sqlalchemy : 1.4.46
tables : None
tabulate : 0.9.0
xarray : 2023.5.0
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None