from hvplot.sample_data import us_crime

import hvplot.pandas  # This import automatically loads the Bokeh extension.

hvplot.extension('matplotlib', 'plotly')  # This call loads the Matplotlib (the active one) and Plotly extensions.

us_crime.hvplot(x='Year', y='Violent Crime rate')

hvplot.output(backend='plotly')

us_crime.hvplot(x='Year', y='Violent Crime rate')

hvplot.output(backend='bokeh')
us_crime.hvplot(x='Year', y='Violent Crime rate', line_dash='dashed')

hvplot.output(backend='matplotlib')
us_crime.hvplot(x='Year', y='Violent Crime rate', linestyle='dashed')

hvplot.extension('matplotlib', compatibility='bokeh')
violent_crime = us_crime.hvplot(x='Year', y='Violent Crime rate', line_dash='dashed')
violent_crime

violent_crime.opts.info()

violent_crime = us_crime.hvplot(x='Year', y='Violent Crime rate')

from bokeh.io import show

bk_fig = hvplot.render(violent_crime, backend='bokeh')
bk_fig.title = 'Violent crime'
show(bk_fig)

%matplotlib inline
mpl_fig = hvplot.render(violent_crime, backend='matplotlib')
axes = mpl_fig.get_axes()
axes[0].set_title('Violent crime')
mpl_fig

from plotly.graph_objects import Figure

plotly_fig = hvplot.render(violent_crime, backend='plotly')
fig = Figure(plotly_fig).update_layout(title='Violent crime')
fig