如何在seaborn.distplot中填充不同颜色的区域

Question

Is it possible to fill with a color the area outside the two threshold lines (line1 and line2) and limited in Y-axis by the KDE curve drawn by distplot ?(that represents 3-sigmas for my application)

import pylab as pl
import seaborn as sns
#plotting the two lines
p1 = pl.axvline(x=line1,color='#EF9A9A')
p2 = pl.axvline(x=line2,color='#EF9A9A')
#plotting the PDF
sns.distplot(stat, hist=True,color='#388E3C')

Answer 1

You may use fill_between to fill the area underneath a curve. To get access to the KDE curve from the seaborn plot, you can draw that one first, such that ax.lines only has a single element, which is the curve of interest. Its data is obtained via kde_x, kde_y = ax.lines[0].get_data() .

Then using ax.fill_between() allows to fill the area under the curve. To restrict this to be outside some given data range, the where keyword argument may be used (and interpolate=True should be set to have the area go up to the points in question).

ax.fill_between(kde_x, kde_y, where=(kde_x<x0) | (kde_x>x1) , 
                interpolate=True, color='#EF9A9A')

Full example:

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

stat=np.random.randn(100)
x0 = -1
x1 = 1

#plotting the PDF (do this before plotting anything else)
ax = sns.distplot(stat, hist=True,color='#388E3C')
kde_x, kde_y = ax.lines[0].get_data()

#plotting the two lines
p1 = plt.axvline(x=x0,color='#EF9A9A')
p2 = plt.axvline(x=x1,color='#EF9A9A')


ax.fill_between(kde_x, kde_y, where=(kde_x<x0) | (kde_x>x1) , 
                interpolate=True, color='#EF9A9A')

plt.show()

---

Old answer to initial question:

You may use an axvspan , starting at the left x limit and going to the position of the first line and another one starting at the position of the second line and going to the right x limit.

 import numpy as np import matplotlib.pyplot as plt import seaborn as sns stat=np.random.randn(100) x0 = -1 x1 = 1 #plotting the two lines p1 = plt.axvline(x=x0,color='#EF9A9A') p2 = plt.axvline(x=x1,color='#EF9A9A') #plotting the PDF ax = sns.distplot(stat, hist=True,color='#388E3C') xlim = ax.get_xlim() ax.axvspan(xlim[0], x0, color='#EF9A9A', alpha=0.5) ax.axvspan(x1, xlim[1], color='#EF9A9A', alpha=0.5) #reset xlim ax.set_xlim(xlim) plt.show() 

Here, we need to adjust the xlimits after setting spans; the reason is that with the spans in place the autoscaling would add another 5% padding to both ends of the axes, resulting in white space. Alternatively you could use zero margin for the xaxis, ax.margins(x=0) .