Matplotlib histogram with multiple legend entries

Question

I have this code that produces a histogram, identifying three types of fields; "Low", "medium" , and "high":

import pylab as plt import pandas as pd   df = pd.read_csv('April2017NEW.csv', index_col =1) df1 = df.loc['Output Energy, (Wh/h)']  # choose index value and Average df1['Average'] = df1.mean(axis=1)  N, bins, patches = plt.hist(df1['Average'], 30)  cmap = plt.get_cmap('jet') low = cmap(0.5) medium =cmap(0.25) high = cmap(0.8)   for i in range(0,4):     patches[i].set_facecolor(low) for i in range(4,11):     patches[i].set_facecolor(medium) for i in range(11,30):     patches[i].set_facecolor(high)  plt.xlabel("Watt Hours", fontsize=16)   plt.ylabel("Households", fontsize=16) plt.xticks(fontsize=14)   plt.yticks(fontsize=14) ax = plt.subplot(111)   ax.spines["top"].set_visible(False)   ax.spines["right"].set_visible(False)  plt.show() 

that produces this:

How do I get a legend in there for the three different colors?

Answer 1

You would need to create the legend yourself. To this end, create some rectangles, which are not shown in the figure (so called proxy artists).

#create legend handles = [Rectangle((0,0),1,1,color=c,ec="k") for c in [low,medium, high]] labels= ["low","medium", "high"] plt.legend(handles, labels) 

Complete example:

import matplotlib.pyplot as plt import numpy as np from matplotlib.patches import Rectangle  data = np.random.rayleigh(size=1000)*35  N, bins, patches = plt.hist(data, 30, ec="k")  cmap = plt.get_cmap('jet') low = cmap(0.5) medium =cmap(0.25) high = cmap(0.8)   for i in range(0,4):     patches[i].set_facecolor(low) for i in range(4,11):     patches[i].set_facecolor(medium) for i in range(11,30):     patches[i].set_facecolor(high)  #create legend handles = [Rectangle((0,0),1,1,color=c,ec="k") for c in [low,medium, high]] labels= ["low","medium", "high"] plt.legend(handles, labels)  plt.xlabel("Watt Hours", fontsize=16)   plt.ylabel("Households", fontsize=16) plt.xticks(fontsize=14)   plt.yticks(fontsize=14)  plt.gca().spines["top"].set_visible(False)   plt.gca().spines["right"].set_visible(False)  plt.show()