Description
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