A legend is an area describing the elements of the graph. In theMatplotlib library, there’s a function called legend() which is used to place a legend on the axes. In this article, we will learn about the Matplotlib Legends.

Python Matplotlib.pyplot.legend() Syntax

Syntax: matplotlib.pyplot.legend(["blue", "green"], bbox_to_anchor=(0.75, 1.15), ncol=2)

Attributes:

• 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.

Matplotlib.pyplot.legend() in Python

Matplotlib.pyplot.legend() function is a utility given in the Matplotlib library forPythonthat gives a way to label and differentiate between multiple plots in the same figure

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

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

Python Matplotlib legend() Function Examples

Below are some examples that can see the Matplotlib interactive mode setup using Matplotlib.pyplot.legend() inPython:

Add a Legend to a Matplotlib

In this example, a simple quadratic function \( y = x^2 \) is plotted against the x-values [1, 2, 3, 4, 5]. A legend labeled "single element" is added to the plot, clarifying the plotted data.

importnumpyasnpimportmatplotlib.pyplotasplt# X-axis valuesx=[1,2,3,4,5]# Y-axis valuesy=[1,4,9,16,25]# Function to plotplt.plot(x,y)# Function add a legendplt.legend(['single element'])# function to show the plotplt.show()

Output :

Change the Position of the Legend

In this example, two data series, represented by `y1` and `y2`, are plotted. Each series is differentiated by a specific color, and the legend provides color-based labels "blue" and "green" for clarity.

# importing modulesimportnumpyasnpimportmatplotlib.pyplotasplt# Y-axis valuesy1=[2,3,4.5]# Y-axis valuesy2=[1,1.5,5]# Function to plotplt.plot(y1)plt.plot(y2)# Function add a legendplt.legend(["blue","green"],loc="lower right")# function to show the plotplt.show()

Output :

Combine Multiple labels in legend

In this example, two curves representing `y1` and `y2` are plotted against the `x` values. Each curve is labeled with a distinct legend entry, "Numbers" and "Square of numbers", respectively, providing clarity to the viewer.

importnumpyasnpimportmatplotlib.pyplotasplt# X-axis valuesx=np.arange(5)# Y-axis valuesy1=[1,2,3,4,5]# Y-axis valuesy2=[1,4,9,16,25]# Function to plotplt.plot(x,y1,label='Numbers')plt.plot(x,y2,label='Square of numbers')# Function add a legendplt.legend()# function to show the plotplt.show()

Output :

Plotting Sine and Cosine Functions with Legends in Matplotlib

In this example, both thesine and cosine functions are plotted against the range [0, 10] on the x-axis. The plot includes legends distinguishing the sine and cosine curves, enhancing visual clarity.

importnumpyasnpimportmatplotlib.pyplotaspltx=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:

Place the Legend Outside the Plot in Matplotlib

In this example, two functionsy = x andy = 3x are plotted against the x-values. The legend is strategically positioned above the plot with two columns for improved layout and clarity.

# importing modulesimportnumpyasnpimportmatplotlib.pyplotasplt# 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 valuesy2=[0,1,2,3,4,5,6,7,8]# Function to plotplt.plot(y1,label="y = x")plt.plot(y2,label="y = 3x")# Function add a legendplt.legend(bbox_to_anchor=(0.75,1.15),ncol=2)plt.show()

Output:

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