BUG: pd.DataFrame.replace integer/float value to pd.NA causes RecursionError

[chAngeZhaoZhanBo]

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] (https://pandas.pydata.org/docs/dev/getting_started/install.html#installing-the-development-version-of-pandas) of pandas.

Reproducible Example

import pandas as pd

pd.DataFrame([0, 1]).replace(0, pd.NA)
pd.DataFrame([0.5, 1.5]).replace(0.5, pd.NA)

Issue Description

pd.DataFrame.replace integer/float value to pd.NA causes RecursionError

I know this issue was reported in #49439, but it was mistakenly judged as duplication of #45725

However, #45725 only fixed the case that Dataframe replaces np.nan to pd.NA. In pandas 1.5.2, replacing integer/float value to pd.NA still crushes python kernel

Expected Behavior

      0
0    <NA>
1     1

      0
0    <NA>
1     1.5

Installed Versions

INSTALLED VERSIONS

commit : 8dab54d
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.16.3-microsoft-standard-WSL2
Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.2
numpy : 1.24.1
pytz : 2022.7
dateutil : 2.8.2
setuptools : 45.2.0
pip : 20.0.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
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