Pandas version checks

  • [X] I have checked that this issue has not already been reported.

  • [X] I have confirmed this bug exists on the latest version of pandas.

  • [ ] I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

ser_a = pd.Series([1, 2], dtype=pd.Int64Dtype())
ser_b = pd.Series([3, pd.NA], dtype=pd.Int64Dtype())
ser_a.clip(lower=ser_b)

# TypeError: Invalid value '-inf' for dtype Int64

ser_c = pd.Series([3, pd.NA])
ser_c.dtype
# dtype('O')

ser_a.clip(lower=ser_c)
# 0    3
# 1    2
# dtype: Int64

Issue Description

Hi all,

When using extension array dtypes, clip throws a TypeError if the upper / lower series contains a pd.NA. This does not happen if we downcast the upper / lower series to type object.

Thanks

Expected Behavior

import pandas as pd

ser_a = pd.Series([1, 2], dtype=pd.Int64Dtype())
ser_b = pd.Series([3, pd.NA], dtype=pd.Int64Dtype())
ser_a.clip(lower=ser_b)
# 0    3
# 1    2
# dtype: Int64

Installed Versions

>>> pd.show_versions() C:\BD\TPD\Miniconda3-py37_4.10.3\envs\pandasdev\lib\site-packages\_distutils_hack\__init__.py:33: UserWarning: Setuptools is replacing distutils. warnings.warn("Setuptools is replacing distutils.") INSTALLED VERSIONS ------------------ commit : 478d340667831908b5b4bf09a2787a11a14560c9 python : 3.10.10.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19044 machine : AMD64 processor : Intel64 Family 6 Model 165 Stepping 3, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United Kingdom.1252 pandas : 2.0.0 numpy : 1.24.2 pytz : 2023.3 dateutil : 2.8.2 setuptools : 66.0.0 pip : 23.0.1 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : None IPython : None pandas_datareader: None bs4 : None bottleneck : None brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : None snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None zstandard : None tzdata : 2023.3 qtpy : None pyqt5 : None

Comment From: ryanyao2002

take