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
>>> s = pd.Series([1, None], dtype="int16[pyarrow]")
>>> def my_udf(value):
... return str(value)
...
>>> s.apply(my_udf)
0 1.0
1 nan
dtype: object
>>>Issue Description
NaN is passed to udf instead of pd.NA, NaN should be impossible for integral type to hold
Expected Behavior
Expected behavior is behavior from pandas 2.1.4:
>>> s = pd.Series([1, None], dtype="int16[pyarrow]")
>>> def my_udf(value):
... return str(value)
...
>>> s.apply(my_udf)
0 1
1 <NA>
dtype: object
>>>
UDF receives pd.NA instead of NaN
Installed Versions
INSTALLED VERSIONS
commit : d4c8d82
python : 3.11.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 151 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 2.2.0rc0
numpy : 1.26.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 69.0.2
pip : 23.3.1
Cython : None
pytest : 7.0.1
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.19.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.2
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 14.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None