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BUG: DataFrame.select_dtypes returns reference to original DataFrame #48090
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@jorisvandenbossche thanks for looking into this issue and fixing it! FWIW, PR reviewed and approved 👍 |
I noticed this broke our code in 1.5 since we are depending on the https://pandas.pydata.org/pandas-docs/stable/whatsnew/v1.5.0.html#backwards-incompatible-api-changes Can we also put there? |
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
Issue Description
On Pandas 1.3.4 and previously, mutating the
DataFrame
returned byselect_dtypes
didn't change the originalDataFrame
. However, on 1.4.3, it appears mutating the selectedDataFrame
changes the original one. I suspect this is the PR that has caused the change in behavior: #42611On 1.4.3, the original
DataFrame
is mutated:Expected Behavior
on 1.3.4, the original
DataFrame
is unchanged:Installed Versions
pandas : 1.4.3
numpy : 1.23.2
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 63.2.0
pip : 22.2.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : 2.1.1
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 : 0.8.10
xarray : None
xlrd : None
xlwt : None
zstandard : None
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