BUG: DataFrame.convert_dtype(convert_integer=True) with int64_t limits throws Warning #58485
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 pyarrow as pa print(pd.__version__) print(pa.__version__) df = pd.DataFrame({ 'a': [-9223372036854775808, 4611686018427387904, 9223372036854775807, None], 'b': [-9223372036854775808, 4611686018427387904, 9223372036854775807, None], 'c': [-9223372036854775808, 4611686018427387904, 9223372036854775807, None], }) pa_df = df.convert_dtypes(dtype_backend='pyarrow') print(pa_df)2.2.2 16.0.0 /Users/User/.pyenv/versions/3.12.1/lib/python3.12/site-packages/pandas/core/dtypes/cast.py:1057: RuntimeWarning: invalid value encountered in cast if (arr.astype(int) == arr).all(): /Users/User/.pyenv/versions/3.12.1/lib/python3.12/site-packages/pandas/core/dtypes/cast.py:1081: RuntimeWarning: invalid value encountered in cast if (arr.astype(int) == arr).all(): a b c 0 -9223372036854775808 -9223372036854775808 -9223372036854775808 1 4611686018427387904 4611686018427387904 4611686018427387904 2 9223372036854775807 9223372036854775807 9223372036854775807 3 <NA> <NA> <NA> Issue Description
Throwing a warning when converting
Expected Behavior
It should not throw a warning, it looks like the conversion happens successfully in spite of the warning.
Installed Versions
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.5.1
pip : 23.2.1
Cython : None
pytest : 8.1.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.3.1
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 16.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.29
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None