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
# Create a Series with dtype category which contains a None value
my_series = pd.Series([1, None], dtype="category")
my_series.apply(pd.isnull)
# This will output
# 0 False
# 1 NaN <------------------ I would expect this to be True
# dtype: category
# Categories (1, bool): [False]Issue Description
When applying pd.isnull to a Series of dtype category which contains None like values (None, np.nan, pd.NA, etc.), the output doesn't contain a boolean but a float nan instead.
Expected Behavior
The output should contain only boolean values and all None, pd.NA etc. values should be evaluated as True.
Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.11.3.final.0
python-bits : 64
OS : Darwin
OS-release : 23.6.0
Version : Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:21 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T8103
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 2.2.2
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.6.1
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 : 8.13.2
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 12.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None