BUG: pd.DataFrame.replace() with value=pd.NA in pandas v1.5.0 and v1.5.1 crushes python kernel

[romanov-o]

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

pd.DataFrame([0,1,2,3]).replace(0, pd.NA)

Issue Description

pd.DataFrame.replace() with value=pd.NA in pandas v1.5.0 and v1.5.1 crushes python kernel:

RecursionError: maximum recursion depth exceeded while calling a Python object

Expected Behavior

      0
0    <NA>
1     1
2     2
3     3

Installed Versions

INSTALLED VERSIONS

commit : 91111fd
python : 3.10.0.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17763
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1251

pandas : 1.5.1
numpy : 1.21.4
pytz : 2021.3
dateutil : 2.8.2
setuptools : 57.4.0
pip : 22.3
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 7.30.1
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.0
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
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
xlwt : None
zstandard : None
tzdata : None

[phofl]

Hi, thanks for your report.
Duplicate of #45725

[gusutabopb]

@phofl This issue is still present in 1.5.2 (worked fine in 1.4.x):

pd.Series([0.0, 1.0]).replace(0.0, pd.NA)

throws

RecursionError: maximum recursion depth exceeded while calling a Python object

Current work around I found is to cast to object before replace:

pd.Series([0.0, 1.0]).astype(object).replace(0.0, pd.NA)