< area_chart | back to Gallery | cat_heatmap_chart >
from bokeh.charts import BoxPlot, output_file, show
from bokeh.sampledata.autompg import autompg as df
from bokeh.charts import defaults, vplot, hplot
defaults.width = 450
defaults.height = 350
box_plot = BoxPlot(df, label='cyl', values='mpg',
title="label='cyl', values='mpg'")
box_plot2 = BoxPlot(df, label=['cyl', 'origin'], values='mpg',
title="label=['cyl', 'origin'], values='mpg'")
box_plot3 = BoxPlot(df, label='cyl', values='mpg', color='cyl',
title="label='cyl' values='mpg'")
# use constant fill color
box_plot4 = BoxPlot(df, label='cyl', values='displ',
title="label='cyl' color='blue'",
color='blue')
# color by one dimension and label by two dimensions
box_plot5 = BoxPlot(df, label=['cyl', 'origin'], values='mpg',
title="label=['cyl', 'origin'] color='cyl'",
color='cyl')
# specify custom marker for outliers
box_plot6 = BoxPlot(df, label='cyl', values='mpg', marker='cross',
title="label='cyl', values='mpg', marker='cross'")
# color whisker by cylinder
box_plot7 = BoxPlot(df, label='cyl', values='mpg', whisker_color='cyl',
title="label='cyl', values='mpg', whisker_color='cyl'")
# remove outliers
box_plot8 = BoxPlot(df, label='cyl', values='mpg', outliers=False,
title="label='cyl', values='mpg', outliers=False")
# collect and display
output_file("boxplot.html")
show(
vplot(
hplot(box_plot, box_plot2, box_plot3),
hplot(box_plot4, box_plot5, box_plot6),
hplot(box_plot7, box_plot8)
)
)