Pandas version checks

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Reproducible Example

all(pd.Series([None, 3,5], dtype=float) > 3)
all(pd.Series([None, 3,5], dtype='float[pyarrow]') > 3)

Issue Description

Do to the pyarrow nullable bool type, there is a TypeError and the behaviour is inconsistent:

all(pd.Series([None, 3,5], dtype=float) > 3)

Out[10]: False`

all(pd.Series([None, 3,5], dtype='float[pyarrow]') > 3)

Traceback (most recent call last): File "C:\Users\Schleehauf\PycharmProjects\viodata\viotools.venv\Lib\site-packages\IPython\core\interactiveshell.py", line 3672, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "", line 1, in all(pd.Series([None, 3,5], dtype='float[pyarrow]') > 3) File "pandas/_libs/missing.pyx", line 392, in pandas._libs.missing.NAType.bool TypeError: boolean value of NA is ambiguous

Expected Behavior

Be consitant, fill the bool NA value with False for the next xxx releases and maybe add a DeprecationWarning

Installed Versions

INSTALLED VERSIONS ------------------ commit : 2cc37625532045f4ac55b27176454bbbc9baf213 python : 3.12.10 python-bits : 64 OS : Windows OS-release : 11 Version : 10.0.26100 machine : AMD64 processor : Intel64 Family 6 Model 186 Stepping 2, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : de_DE.cp1252 pandas : 2.3.0 numpy : 2.2.6 pytz : 2025.2 dateutil : 2.9.0.post0 pip : None Cython : None sphinx : None IPython : 9.3.0 adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : 4.13.4 blosc : None bottleneck : 1.5.0 dataframe-api-compat : None fastparquet : None fsspec : 2025.5.1 html5lib : None hypothesis : None gcsfs : None jinja2 : 3.1.6 lxml.etree : 5.4.0 matplotlib : 3.10.3 numba : 0.61.2 numexpr : 2.11.0 odfpy : None openpyxl : 3.1.5 pandas_gbq : None psycopg2 : None pymysql : None pyarrow : 20.0.0 pyreadstat : None pytest : 8.4.1 python-calamine : None pyxlsb : 1.0.10 s3fs : 2025.5.1 scipy : None sqlalchemy : None tables : None tabulate : 0.9.0 xarray : None xlrd : 2.0.2 xlsxwriter : 3.2.5 zstandard : 0.23.0 tzdata : 2025.2 qtpy : None pyqt5 : None

Comment From: rhshadrach

Thanks for the report!

Be consitant, fill the bool NA value with False

I think you're asking for pandas to somehow override the behavior of just all(...) and not impact bool(pd.NA). I do not think this is possible.

On the other hand, there are many issues and discussions about bool(pd.NA), I do not think it is useful to have another one. Closing.