title: Seaborn: kdeplots with marginal histograms
body: <p>I'm using a <a href="https://seaborn.pydata.org/generated/seaborn.kdeplot.html" rel="nofollow noreferrer">kdeplot</a> to plot the densities of two bivariate distributions like this, where <code>df_c</code> and <code>df_n</code> are two Pandas DataFrames:</p>
  
  <pre><code>f, ax = plt.subplots(figsize=(6, 6))
  sns.kdeplot(df_c['attr1'], df_c['attr2'], ax=ax, cmap='Blues', shade_lowest=False)
  sns.kdeplot(df_n['attr1'], df_n['attr2'], ax=ax, cmap='Reds',  shade_lowest=False)
  </code></pre>
  
  <p>I would like to also include marginal histograms like those generated by <a href="https://seaborn.pydata.org/generated/seaborn.jointplot.html" rel="nofollow noreferrer">jointplot</a> (<a href="https://seaborn.pydata.org/tutorial/distributions.html#kernel-density-estimation" rel="nofollow noreferrer">example plot</a>). However, I cannot use jointplot (because it is appearantly not possible to plot two different distributions with jointplot, as it will generate a new Figure every time it is called), and I cannot find any information on how to reproduce the marginal histograms it produces.</p>
  
  <p>Is there an easy way to produce a kdeplot with marginal histograms using Seaborn / matplotlib? Alternatively, did I overlook a way to plot two separate distributions using a jointplot?</p>