[ 常見問題 ] Seaborn: How to add vertical lines to a distribution plot (sns.distplot)

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Quesiton
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:

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1. import pandas as pd  
2. import numpy as np  
3. import seaborn as sns  
4. import matplotlib.pyplot as plt  
5.   
6. # some settings  
7. sns.set_style("darkgrid")  
8.   
9. # Create some data  
10. data = np.random.multivariate_normal([0, 0], [[5, 2], [2, 2]], size=2000)  
11. data = pd.DataFrame(data, columns=['x', 'y'])  
12.   
13. # Combined distributionplot  
14. sns.distplot(data['x'])  
15. sns.distplot(data['y'])  

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).

How-To
Just use matplotlib.axes.Axes.axvline:

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1. 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

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