matplotlibseabornloglog

log-log plot with seaborn jointgrid


I'm trying to create a loglog plot with a KDE and histogram associated with each axis using a seaborn JointGrid object. This gets me pretty close, but the histogram bins do not translate well into logspace. Is there a way to do this easily without having to recreate the marginal axes?

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

data = sns.load_dataset('tips')
g = sns.JointGrid('total_bill', 'tip', data)
g.plot_marginals(sns.distplot, hist=True, kde=True, color='blue')
g.plot_joint(plt.scatter, color='black', edgecolor='black')
ax = g.ax_joint
ax.set_xscale('log')
ax.set_yscale('log')
g.ax_marg_x.set_xscale('log')
g.ax_marg_y.set_yscale('log')

Output of plot


Solution

  • For log histograms I find generally useful to set your own bins with np.logspace().

    mybins=np.logspace(0,np.log(100),100)
    

    Then just set bins= in _marginals

    data = sns.load_dataset('tips')
    g = sns.JointGrid('total_bill', 'tip', data,xlim=[1,100],ylim=[0.01,100])
    g.plot_marginals(sns.distplot, hist=True, kde=True, color='blue',bins=mybins)
    g.plot_joint(plt.scatter, color='black', edgecolor='black')
    ax = g.ax_joint
    ax.set_xscale('log')
    ax.set_yscale('log')
    g.ax_marg_x.set_xscale('log')
    g.ax_marg_y.set_yscale('log')
    

    enter image description here