suggestion: set current ax to g.ax_joint at end of jointplot

Tested with seaborn 0.11.1

jointplot (or JointGrid in general) leaves ax_marg_y as current axis. Some people try to use plt.xlim() or similar and are changing the marginal subplot instead of the main one. It could be nice to automatically set plt.sca(g.ax_joint) when finishing the jointplot.

Example code:

import matplotlib.pyplot as plt
import seaborn as sns

tips = sns.load_dataset('tips')
g = sns.jointplot(data=tips, x='total_bill', y='tip')
# plt.sca(g.ax_joint)
plt.axhline(tips['tip'].mean(), ls='--', c='r')
plt.axhspan(tips['tip'].quantile(.25), tips['tip'].quantile(.75), color='y', alpha=.3)
plt.show()

[jhncls]

It probably would make sense to do the same for ax_heatmap of sns.clustermap. That way e.g. plt.xlabel('features') would affect the main subplot instead of the colorbar.

[mwaskom]

I think the easiest change would be to do it at the end of jointplot . People who are using JointGrid directly are probably less likely to get bitten by this. That said, calling plt.gca at the end of the JointGrid constructor is probably fine too; but I would worry about the unintended consequences of changing the direction of axis sharing so I’d be -1 on the second proposal.

By the way, a simple test of a non-seaborn function called with plot_marginals isn’t trivial.

A simple case would be:

g = sns.JointGrid(data=penguins, x="bill_length_mm", y="bill_depth_mm")
g.plot_marginals(plt.hist)

But yes, without an established API pattern for “which axis to draw the distribution on”, it’s harder to be generic in that function.