Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import plotly.express as px
df = px.data.iris()
#Works
px.scatter(df, x="sepal_width", y="sepal_length", color="species")
#doesn't work as expected in 1.5.x
df.plot.scatter(x="sepal_width", y="sepal_length", color="species")Issue Description
Plotly (and perhaps other backends) take a color argument that is a column name to use to make distinct colors for each variable (or even continuous color.) This is very convenient compared to the c variable in the pandas backend that takes a list of colors.
In Pandas 1.5, color and c in the back end code become the same, or rather color is an alias of c:
In addition, the code pops out the color argument so that it no longer exists in kwargs so the color information (expected to be a list of columns) is now absent. Changing the line to
color = kwargs.get('color')
would leave the variable in place, but then other plotting back ends would get color and presumably crash on an expected keyword, and would have to use c instead.
I think it would be best to not alias color to c for scatter plots and let backends like plotly continue to work as they did prior to 1.5.x
Expected Behavior
Plotly color kwarg should behave as expected prior to 1.5.x and pass through a column name to the plotly backend, not remove the kwarg and alias it to the c kwarg.
Installed Versions
/usr/local/opt/miniforge3/lib/python3.10/site-packages/_distutils_hack/init.py:33: UserWarning:
Setuptools is replacing distutils.
INSTALLED VERSIONS
commit : 91111fd
python : 3.10.6.final.0
python-bits : 64
OS : Darwin
OS-release : 22.1.0
Version : Darwin Kernel Version 22.1.0: Sun Oct 9 20:14:30 PDT 2022; root:xnu-8792.41.9~2/RELEASE_ARM64_T8103
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.5.1
numpy : 1.23.4
pytz : 2022.1
dateutil : 2.8.2
setuptools : 65.5.1
pip : 22.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.6.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
brotli :
fastparquet : None
fsspec : 2022.5.0
gcsfs : None
matplotlib : 3.5.3
numba : 0.56.3
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 9.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.0
snappy : None
sqlalchemy : 1.4.44
tables : None
tabulate : 0.8.10
xarray : None
xlrd : 2.0.1
xlwt : None
zstandard : None
tzdata : 2022.6