Scatterplot with point colors representing a continuous variable in seaborn FacetGrid

Question

I am trying to generate multi-panel figure using seaborn in python and I want the color of the points in my multi-panel figure to be specified by a continuous variable. Here's an example of what I am trying to do with the "iris" dataset:

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib as mpl
import matplotlib.pyplot as plt
iris = sns.load_dataset('iris')

g = sns.FacetGrid(iris, col = 'species', hue = 'petal_length', palette = 'seismic')
g = g.map(plt.scatter, 'sepal_length', 'sepal_width', s = 100, alpha = 0.5)
g.add_legend()

This makes the following figure:

Which is nice, but the legend is way too long. I'd like to sample out like 1/4 of these values (ideally) or barring that display a colorbar instead. For instance, something like this might be acceptable, but I'd still want to split it over the three species.

plt.scatter(iris.sepal_length, iris.sepal_width, alpha = .8, c = iris.petal_length, cmap = 'seismic')
cbar = plt.colorbar()

Any idea about how I can get the best of both of these plots?

Edit: This topic seems like a good start.

https://github.com/mwaskom/seaborn/issues/582

Somehow, for this user, simply appending plt.colorbar after everything else ran seemed to somehow work. Doesn't seem to help in this case though.

Answer 1

Since you were asking about a legend for the scatter, one may adapt @mwaskom's solution to produce a legend with scatter points like so:

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
iris = sns.load_dataset('iris')

g = sns.FacetGrid(iris, col='species', palette = 'seismic')

def facet_scatter(x, y, c, **kwargs):
    kwargs.pop("color")
    plt.scatter(x, y, c=c, **kwargs)

vmin, vmax = 0, 7
cmap = plt.cm.viridis

norm=plt.Normalize(vmin=vmin, vmax=vmax)

g = g.map(facet_scatter, 'sepal_length', 'sepal_width', "petal_length",
          s=100, alpha=0.5, norm=norm, cmap=cmap)

# Make space for the colorbar
g.fig.subplots_adjust(right=.9)

lp = lambda i: plt.plot([], color=cmap(norm(i)), marker="o", ls="", ms=10, alpha=0.5)[0]
labels = np.arange(0,7.5,0.5)
h = [lp(i) for i in labels]
g.fig.legend(handles=h, labels=labels, fontsize=9)

plt.show()