A legend is basically an area in the plot which describes the elements present in the graph. Matplotlib provides an inbuilt method named legend() for this purpose. The syntax of the method is below :
Example: Adding Simple legend
Python3
# Import librariesimport matplotlib.pyplot as plt # Creating plotplt.plot([1, 2, 3, 4]) plt.title('simple legend example ') # Creating legendplt.legend(['simple legend example']) # Show plotplt.show() |
Output:
Creating legend with color box
To create a legend with a color box, patches are used provided by the matplotlib.patches module. A patch nothing but a 2D artist with face color and edge color. Below is a simple example of this:
Example 1:
Python3
# Import librariesimport matplotlib.patches as mpatchesimport matplotlib.pyplot as plt # Creating plotplt.plot([1, 2, 3, 4], color='blue') plt.title('simple legend example ') # Creating legend with color boxblue_patch = mpatches.Patch(color='blue', label='blue legend')plt.legend(handles=[blue_patch]) # Show plotplt.show() |
Output:
Example 2:
Python3
# Import librariesimport matplotlib.pyplot as pltimport matplotlib.patches as mpatchesimport scipy.statsimport numpy as np # Setting limit for x valuesx_min = 0.0x_max = 50.0 # Setting figure sizefig = plt.figure(figsize = (16, 9)) # Creating first datasetmean = 12.0 std = 3.0 x = np.linspace(x_min, x_max, 100)y = scipy.stats.norm.pdf(x,mean,std) # Plotting first datasetplt.plot(x,y, color='red')plt.fill_between(x, y, color='#CE5D45', alpha=1.0) # Creating second datasetmean = 18.0 std = 6.0 x = np.linspace(x_min, x_max, 100)y = scipy.stats.norm.pdf(x,mean,std) # Plotting second datasetplt.plot(x,y, color='green')plt.fill_between(x, y, color='#5DC83F', alpha=1.0) # Creating legend with color boxpop_a = mpatches.Patch(color='#5DC83F', label='Population Dataset 1')pop_b = mpatches.Patch(color='#CE5D45', label='Population Dataset 2')plt.legend(handles=[pop_a,pop_b]) # Adding grid to plotplt.grid() # Adding X and Y limitsplt.xlim(x_min,x_max)plt.ylim(0,0.25) # Adding titleplt.title('simple legend example',fontsize=12) # Adding labelsplt.xlabel('')plt.ylabel('Probability Distribution') # Showing plotplt.show() |
Output:
