How to manually add a legend with a color box on a matplotlib figure ?

To manually add a legend with a color box on a matplotlib figure a solution is to use patches, exemple:

import matplotlib.patches as mpatches
import matplotlib.pyplot as plt

red_patch = mpatches.Patch(color='red', label='The red data')
plt.legend(handles=[red_patch])

plt.savefig("proxy_artists.png")
plt.show()

Another example:

import matplotlib.pyplot as plt
import scipy.stats
import numpy as np

x_min = 0.0
x_max = 30.0

#----------------------------------------------------------------------------------------#
# Population B

mean = 9.0 
std = 2.0

x = np.linspace(x_min, x_max, 100)

y = scipy.stats.norm.pdf(x,mean,std)

plt.plot(x,y, color='black')

plt.fill_between(x, y, color='#89bedc', alpha='1.0')

#----------------------------------------------------------------------------------------#
# Population A

mean = 15.0 
std = 4.0

x = np.linspace(x_min, x_max, 100)

y = scipy.stats.norm.pdf(x,mean,std)

plt.plot(x,y, color='black')

plt.fill_between(x, y, color='#0b559f', alpha='1.0')

#----------------------------------------------------------------------------------------#
# legend

import matplotlib.patches as mpatches

pop_a = mpatches.Patch(color='#0b559f', label='Population A')
pop_b = mpatches.Patch(color='#89bedc', label='Population B')

plt.legend(handles=[pop_a,pop_b])

#----------------------------------------------------------------------------------------#

plt.grid()

plt.xlim(x_min,x_max)
plt.ylim(0,0.25)

plt.title('How to use ROC curve to test a dicrete classifier ?',fontsize=10)

plt.xlabel('x')
plt.ylabel('Probability Density Function')

plt.savefig("roc_curve_discrete_classifier_02.png")
plt.show()

References