Seaborn jointplot组颜色编码（用于散点图和密度图）

Question

I would like to use sns.jointplot to visualise the association between X and Y in the presence of two groups. However, in

tips = sns.load_dataset("tips")
sns.jointplot("total_bill", "tip", data=tips) 

there is no "hue" option as in other sns plots such as sns.scatterplot. How could one assign different colours for different groups (eg hue="smoker") in both the scatter plot, as well as the two overlapping density plots.

In R this could be done by creating a scatter plot with two marginal density plots as shown in here .

What is the equivalent in sns? If this is not possible in sns, is there another python package that can be used for this?

Answer 1

jointplot is a simple wrapper around sns.JointGrid . If you create a JointGrid object and add plots to it manually, you will have much more control over the individual plots.

In this case, your desired jointplot is simply a scatterplot combined with a kdeplot , and what you want to do is pass hue='smoker' (for example) to scatterplot .

The kdeplot is more complex; seaborn doesn't really support one KDE for each class, AFAIK, so I was forced to plot them individually (you could use a for loop with more classes).

Accordingly, you can do this:

import seaborn as sns

tips = sns.load_dataset('tips')
grid = sns.JointGrid(x='total_bill', y='tip', data=tips)

g = grid.plot_joint(sns.scatterplot, hue='smoker', data=tips)
sns.kdeplot(tips.loc[tips['smoker']=='Yes', 'total_bill'], ax=g.ax_marg_x, legend=False)
sns.kdeplot(tips.loc[tips['smoker']=='No', 'total_bill'], ax=g.ax_marg_x, legend=False)
sns.kdeplot(tips.loc[tips['smoker']=='Yes', 'tip'], ax=g.ax_marg_y, vertical=True, legend=False)
sns.kdeplot(tips.loc[tips['smoker']=='No', 'tip'], ax=g.ax_marg_y, vertical=True, legend=False)