Ridgeline plot

Preparation

import pandas as pd

from lets_plot import *
from lets_plot.mapping import as_discrete
LetsPlot.setup_html()

iris_df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/iris.csv")
print(iris_df.shape)
iris_df.head()

(150, 5)

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

mpg_df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv")
print(mpg_df.shape)
mpg_df.head()

(234, 12)

	Unnamed: 0	manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
0	1	audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
1	2	audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
2	3	audi	a4	2.0	2008	4	manual(m6)	f	20	31	p	compact
3	4	audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
4	5	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact

Plots

Default plot

ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges()

min_height parameter

df = pd.DataFrame({
    "x": [1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7],
    "y": [-.4, -.4, -.4, -.4, -.4, -.4, -.4, -.8, -.8, -.8, -.8, -.8, -.8, -.8],
    "h": [.4, -.2, .6, -.8, .3, .1, .7, .1, .3, .1, -.6, -.1, -.3, -.1],
})

ggplot(df) + \
    geom_area_ridges(aes("x", "y", height="h"), stat='identity', color="black", fill="#3182bd", min_height=-.4)

trim and tails_cutoff parameters

width, height = 400, 300
bunch = GGBunch()
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(trim=False, tails_cutoff=None) + \
    ggtitle("Default: trim=False, tails_cutoff=None"),
    0, 0, width, height)
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(trim=False, tails_cutoff=0) + \
    ggtitle("trim=False, tails_cutoff=0"),
    width, 0, width, height)
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(trim=False, tails_cutoff=3) + \
    ggtitle("trim=False, tails_cutoff=3"),
    0, height, width, height)
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(trim=True) + \
    ggtitle("trim=True"),
    width, height, width, height)
bunch.show()

scale parameter

ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(scale=1.5)

Quantiles

quantiles = [.05, .25, .5, .75, .95]
width, height = 400, 300
bunch = GGBunch()
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(quantiles=quantiles, color='black'),
    0, 0, width, height)
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(quantiles=quantiles, quantile_lines=True, color='black'),
    width, 0, width, height)
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(aes(fill="..quantile.."), quantiles=quantiles, color='black', show_legend=False),
    0, height, width, height)
bunch.add_plot(ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(aes(fill="..quantile.."), quantiles=quantiles, quantile_lines=True, color='black', show_legend=False),
    width, height, width, height)
bunch.show()

Other

ggplot(iris_df, aes("sepal_length", "species")) + \
    geom_area_ridges(kernel="triangular", adjust=.8, quantile_lines=True, trim='all', \
                     color="#993404", fill="#fe9929", tooltips=layer_tooltips().line("height|@..height..")\
                    .format("@..density..", ".2f").line("density|@..density..")\
                    .line("quantile|@..quantile.."))

ggplot(mpg_df, aes("hwy", as_discrete("year"), fill="drv")) + \
    geom_area_ridges(color="white", alpha=.5) + \
    scale_fill_brewer(type='qual', palette='Set1') + \
    facet_grid(x="drv") + \
    theme_bw() + flavor_darcula()