Seaborn: How to add vertical lines to a distribution plot (sns.distplot)

Question

Using the examples from seaborn.pydata.org and the Python DataScience Handbook, I'm able to produce a combined distribution plot with the following snippet:

Code:

import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt  # some settings sns.set_style("darkgrid")  # Create some data data = np.random.multivariate_normal([0, 0], [[5, 2], [2, 2]], size=2000) data = pd.DataFrame(data, columns=['x', 'y'])  # Combined distributionplot sns.distplot(data['x']) sns.distplot(data['y']) 

Plot:

How can I combine this setup with vertical lines so that I can illustrate thresholds like this:

I know I can do it with matplotlib like here Dynamic histogram subplots with line to mark target, but I really like the simplicity of seaborn plots and would like to know if it's possible to do it more elegantly (and yes, I know that seaborn builds on top of matplotlib).

Thank you for any suggestions!

Answer 1

Just use

plt.axvline(2.8, 0,0.17) 

And the same for the other line

Here instead of 0.17 you can put the maxima of your distribution using some variable such as maxx = max(data) or something similar. 2.8 is the position on the x-axis. Oh remember that the y-value has to be in between 0 and 1 where 1 is the top of the plot. You can rescale your values accordingly. Another obvious option is simply

plt.plot([2.8, 2.8], [0, max(data)])