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
df_test = pd.DataFrame({'col': [pd._libs.missing.NAType(), pd._libs.missing.NAType(), pd._libs.missing.NAType()]})
df_test.col = df_test.col.astype(pd.Int64Dtype())
df_test.fillna(1, limit=1)
Issue Description
The fillna method called on 3rd row should only replace the first NA value in the dataframe with 1, but it replaces the whole column
Note: if the second code line is remove, it works as expected, so it is something related to dtypes
Expected Behavior
It should only replace the first row
Installed Versions
/usr/local/lib/python3.10/dist-packages/_distutils_hack/init.py:33: UserWarning: Setuptools is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.10.12.final.0
python-bits : 64
OS : Linux
OS-release : 6.1.85+
Version : #1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.2.2
numpy : 1.25.2
pytz : 2023.4
dateutil : 2.8.2
setuptools : 67.7.2
pip : 23.1.2
Cython : 3.0.10
pytest : 7.4.4
hypothesis : None
sphinx : 5.0.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.4
html5lib : 1.1
pymysql : None
psycopg2 : 2.9.9
jinja2 : 3.1.4
IPython : 7.34.0
pandas_datareader : 0.10.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2023.6.0
gcsfs : 2023.6.0
matplotlib : 3.7.1
numba : 0.58.1
numexpr : 2.10.0
odfpy : None
openpyxl : 3.1.3
pandas_gbq : 0.19.2
pyarrow : 14.0.2
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : 2.0.30
tables : 3.8.0
tabulate : 0.9.0
xarray : 2023.7.0
xlrd : 2.0.1
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None