BUG: The isna function returns False for NaN values in a column of type 'double [pyarrow]'.

[zhengchl]

Pandas version checks

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

• 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

df_arrow = pd.DataFrame([[0, 0]], dtype="double[pyarrow]", columns=['a', 'b'])
df_arrow['c'] = df_arrow.a / df_arrow.b
df_arrow.isna()

Issue Description

The isna function returns False for NaN values in the column c, which is of type double [pyarrow]. The output of reproducible example is:

       a      b      c
0  False  False  False

It is clear that column c is 0/0, which is NaN, so it should be True.

Furthermore, if I assign the variable n to reference to column c and call pd.isna, it returns True.

n = df_arrow.iloc[0,2]
pd.isna(n)

Output of this case is True.

Expected Behavior

If I take use of numpy instead of pyarrow as dtype backend, it's as expected.
Expected behavior is:

import pandas as pd
df_np = pd.DataFrame([[0, 0]], columns=['a', 'b'])
df_np['c'] = df_np.a / df_np.b
df_np.isna()

The output is:

       a      b     c
0  False  False  True

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.12.6
python-bits : 64
OS : Darwin
OS-release : 23.6.0
Version : Darwin Kernel Version 23.6.0: Fri Nov 15 15:12:37 PST 2024; root:xnu-10063.141.1.702.7~1/RELEASE_ARM64_T6030
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : zh_CN.UTF-8
LOCALE : zh_CN.UTF-8

pandas : 2.2.3
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
pip : 24.0
Cython : None
sphinx : None
IPython : 8.24.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.4
lxml.etree : None
matplotlib : 3.9.0
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.3
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 17.0.0
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.14.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report. Closing as a duplicate of #53887.