JoyPy is a one-function Python package based on matplotlib + pandas
with a single purpose: drawing joyplots (a.k.a. ridgeline plots).

Joyplots are stacked, partially overlapping density plots, simple as
that. They are a nice way to plot data to visually compare
distributions, especially those that change across one dimension
(e.g., over time).  Though hardly a new technique, they have become
very popular lately thanks to the R package ggjoy
(https://github.com/clauswilke/ggjoy) (which is much better
developed/maintained than this one -- and I strongly suggest you use
that if you can use R and ggplot.)  **Update**: the ggjoy package has
now been renamed ggridges (https://github.com/clauswilke/ggridges).

A minimal example is the following:

import joypy
import pandas as pd

iris = pd.read_csv("data/iris.csv")
fig, axes = joypy.joyplot(iris)

By default, `joypy.joyplot()` will draw joyplot with a density subplot
for each numeric column in the dataframe. The density is obtained with
the `gaussian_kde` function of scipy.
