<jupyter_start><jupyter_text>Most examples work across multiple plotting backends, this example is also available for:* [Bokeh - autompg_violins](../bokeh/autompg_violins.ipynb)<jupyter_code>import numpy as np
import holoviews as hv

from  bokeh.sampledata.autompg import autompg
hv.extension('matplotlib')
%output size=300 fig='svg'<jupyter_output><empty_output><jupyter_text>Declaring data<jupyter_code>violin = hv.Violin(autompg, ('yr', 'Year'), ('mpg', 'Miles per Gallon')).redim.range(mpg=(8, 45))<jupyter_output><empty_output><jupyter_text>Plot<jupyter_code>%%opts Violin [aspect=1.5] (facecolors=hv.Cycle('tab20'))
violin<jupyter_output><empty_output>
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{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '241009', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 264, 'n_tokens_neox': 253, 'n_words': 43, 'path': 'examples/gallery/demos/matplotlib/autompg_violins.ipynb', 'repo_name': 'laleph/holoviews', 'size': '658'}