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Matplotlib.pyplot.legend() in Python

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  • Difficulty Level : Basic
  • Last Updated : 12 Apr, 2020

Matplotlib is one of the most popular Python packages used for data visualization. It is a cross-platform library for making 2D plots from data in arrays. Pyplot is a collection of command style functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.

Matplotlib.pyplot.legend()

A legend is an area describing the elements of the graph. In the matplotlib library, there’s a function called legend() which is used to Place a legend on the axes.

The attribute Loc in legend() is used to specify the location of the legend.Default value of loc is loc=”best” (upper left). The strings ‘upper left’, ‘upper right’, ‘lower left’, ‘lower right’ place the legend at the corresponding corner of the axes/figure.

The attribute bbox_to_anchor=(x, y) of legend() function is used to specify the coordinates of the legend, and the attribute ncol represents the number of columns that the legend has.It’s default value is 1.

Syntax:

matplotlib.pyplot.legend([“blue”, “green”], bbox_to_anchor=(0.75, 1.15), ncol=2)

The Following are some more attributes of function legend() :

  • shadow: [None or bool] Whether to draw a shadow behind the legend.It’s Default value is None.
  • markerscale: [None or int or float] The relative size of legend markers compared with the originally drawn ones.The Default is None.
  • numpoints: [None or int] The number of marker points in the legend when creating a legend entry for a Line2D (line).The Default is None.
  • fontsize: The font size of the legend.If the value is numeric the size will be the absolute font size in points.
  • facecolor: [None or “inherit” or color] The legend’s background color.
  • edgecolor: [None or “inherit” or color] The legend’s background patch edge color.

Ways to use legend() function in Python –

Example 1:




import numpy as np
import matplotlib.pyplot as plt
  
# X-axis values
x = [1, 2, 3, 4, 5]
  
# Y-axis values 
y = [1, 4, 9, 16, 25]
  
# Function to plot  
plt.plot(x, y)
  
# Function add a legend  
plt.legend(['single element'])
  
# function to show the plot
plt.show()


Output :
graph

Example 2:




# importing modules
import numpy as np
import matplotlib.pyplot as plt
  
# Y-axis values
y1 = [2, 3, 4.5]
  
# Y-axis values 
y2 = [1, 1.5, 5]
  
# Function to plot  
plt.plot(y1)
plt.plot(y2)
  
# Function add a legend  
plt.legend(["blue", "green"], loc ="lower right")
  
# function to show the plot
plt.show()


Output :
graph

Example 3:




import numpy as np
import matplotlib.pyplot as plt
  
# X-axis values
x = np.arange(5)
  
# Y-axis values
y1 = [1, 2, 3, 4, 5]
  
# Y-axis values 
y2 = [1, 4, 9, 16, 25]
  
# Function to plot  
plt.plot(x, y1, label ='Numbers')
plt.plot(x, y2, label ='Square of numbers')
  
# Function add a legend  
plt.legend()
  
# function to show the plot
plt.show()


Output :
graph

Example 4:




import numpy as np
import matplotlib.pyplot as plt
  
x = np.linspace(0, 10, 1000)
fig, ax = plt.subplots()
  
ax.plot(x, np.sin(x), '--b', label ='Sine')
ax.plot(x, np.cos(x), c ='r', label ='Cosine')
ax.axis('equal')
  
leg = ax.legend(loc ="lower left");


Output:

Example 5:




# importing modules
import numpy as np
import matplotlib.pyplot as plt
   
# X-axis values
x = [0, 1, 2, 3, 4, 5, 6, 7, 8]
   
# Y-axis values
y1 = [0, 3, 6, 9, 12, 15, 18, 21, 24]
# Y-axis values 
y2 = [0, 1, 2, 3, 4, 5, 6, 7, 8]
   
# Function to plot  
plt.plot(y1, label ="y = x")
plt.plot(y2, label ="y = 3x")
   
# Function add a legend  
plt.legend(bbox_to_anchor =(0.75, 1.15), ncol = 2)
   
# function to show the plot
plt.show()


Output:
graph


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