BUG: pd.replace changes dtype when using a dict to replace values even when there are no matches

[sergiykhan]

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 = pd.DataFrame(
    {'a': [1, 2], 'b': [3, 4]},
    dtype='object',
)

df1 = df.replace(
    {5: 0},
)

df2 = df.replace(
    to_replace=5,
    value=0,
)

print(df1.dtypes)
print(df2.dtypes)

Issue Description

pd.replace changes the dtype of the columns whether there is a match or not.

The output of the example above:

a    int64
b    int64
dtype: object
a    object
b    object
dtype: object

Expected Behavior

Expected output:

a    object
b    object
dtype: object
a    object
b    object
dtype: object

Installed Versions

INSTALLED VERSIONS

commit : 965ceca
python : 3.9.16.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
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 : 2.0.2
numpy : 1.24.2
pytz : 2023.3
dateutil : 2.8.2
setuptools : 58.1.0
pip : 23.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 8.12.0
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
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[ABizzinotto]

take

[phofl]

This is intended behavior unfortunately. We can't change this without deprecating.

You should not use object to store numbers in general

[sergiykhan]

Just to clarify, are you saying that the inconsistent behavior between {5: 0} and to_replace=5, value=0 is intended behaviour?

[phofl]

Nope the inconsistency is not intended. But the dict case is fine