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 seaborn as sns
import matplotlib.pyplot as plt
# Sample data
tips = sns.load_dataset("tips")
# Faceted distribution plot
sns.displot(data=tips, x="total_bill", palette="viridis")
plt.show()Issue Description
When using faceted distributions with Seaborn and passing the palette parameter without assigning hue, a FutureWarning is raised. The warning suggests assigning hue and setting legend=False to avoid deprecation in future versions (v0.14.0). This behavior needs clarification or adjustment in Pandas' integration with Seaborn plotting functions.
observed behavior:
FutureWarning: Passing palette without assigning hue is deprecated and will be removed in v0.14.0. Assign the y variable to hue and set legend=False for the same effect.
Expected Behavior
The warning should either be suppressed or handled gracefully within Pandas' plotting functions when interfacing with Seaborn.
Installed Versions
/usr/local/lib/python3.11/dist-packages/_distutils_hack/init.py:31: UserWarning: Setuptools is replacing distutils. Support for replacing an already imported distutils is deprecated. In the future, this condition will fail. Register concerns at https://github.com/pypa/setuptools/issues/new?template=distutils-deprecation.yml
warnings.warn(
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.11.12.final.0
python-bits : 64
OS : Linux
OS-release : 6.1.85+
Version : #1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
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 : 2.2.2
numpy : 2.0.2
pytz : 2025.2
dateutil : 2.8.2
setuptools : 75.2.0
pip : 24.1.2
Cython : 3.0.12
pytest : 8.3.5
hypothesis : None
sphinx : 8.2.3
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.3.1
html5lib : 1.1
pymysql : None
psycopg2 : 2.9.10
jinja2 : 3.1.6
IPython : 7.34.0
pandas_datareader : 0.10.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.3
bottleneck : 1.4.2
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.3.2
gcsfs : 2025.3.2
matplotlib : 3.10.0
numba : 0.60.0
numexpr : 2.10.2
odfpy : None
openpyxl : 3.1.5
pandas_gbq : 0.28.0
pyarrow : 18.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.14.1
sqlalchemy : 2.0.40
tables : 3.10.2
tabulate : 0.9.0
xarray : 2025.1.2
xlrd : 2.0.1
zstandard : 0.23.0
tzdata : 2025.2
qtpy : None
pyqt5 : None
