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 npimport matplotlib.pyplot as plt # X-axis valuesx = [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 plotplt.show() |
Output :
Example 2:
# importing modulesimport numpy as npimport matplotlib.pyplot as plt # Y-axis valuesy1 = [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 plotplt.show() |
Output :
Example 3:
import numpy as npimport matplotlib.pyplot as plt # X-axis valuesx = np.arange(5) # Y-axis valuesy1 = [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 plotplt.show() |
Output :
Example 4:
import numpy as npimport 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 modulesimport numpy as npimport matplotlib.pyplot as plt # X-axis valuesx = [0, 1, 2, 3, 4, 5, 6, 7, 8] # Y-axis valuesy1 = [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 plotplt.show() |
Output:
