How to Display A Legend With Matplotlib?

8 minutes read

To display a legend with Matplotlib, you can use the plt.legend() function after plotting your data. This function takes an optional labels parameter where you can specify the names of the labels you want to display in the legend. You can also customize the location of the legend using the loc parameter, which takes values such as "upper right", "lower left", "center", etc. Additionally, you can adjust the size and styling of the legend using parameters like fontsize, title, and shadow. Legends are useful for identifying different elements within a plot, such as lines, markers, or colors, and can enhance the understanding of your data visualizations.

Best Matlab Books to Read in 2024

1
MATLAB for Engineers

Rating is 5 out of 5

MATLAB for Engineers

2
Essential MATLAB for Engineers and Scientists

Rating is 4.9 out of 5

Essential MATLAB for Engineers and Scientists

3
MATLAB and Simulink Crash Course for Engineers

Rating is 4.8 out of 5

MATLAB and Simulink Crash Course for Engineers

4
MATLAB: A Practical Introduction to Programming and Problem Solving

Rating is 4.7 out of 5

MATLAB: A Practical Introduction to Programming and Problem Solving

5
MATLAB For Dummies (For Dummies (Computer/Tech))

Rating is 4.6 out of 5

MATLAB For Dummies (For Dummies (Computer/Tech))

6
Differential Equations with Matlab

Rating is 4.5 out of 5

Differential Equations with Matlab

7
Matlab: A Practical Introduction to Programming and Problem Solving

Rating is 4.4 out of 5

Matlab: A Practical Introduction to Programming and Problem Solving

8
Matlab: A Practical Introduction to Programming and Problem Solving

Rating is 4.3 out of 5

Matlab: A Practical Introduction to Programming and Problem Solving

9
MATLAB and Simulink In-Depth: Model-based Design with Simulink and Stateflow, User Interface, Scripting, Simulation, Visualization and Debugging

Rating is 4.2 out of 5

MATLAB and Simulink In-Depth: Model-based Design with Simulink and Stateflow, User Interface, Scripting, Simulation, Visualization and Debugging


How to add a legend without labels in matplotlib?

You can add a legend without labels in matplotlib by creating a custom legend handler function and specifying it when creating the legend. Here is an example code snippet to do this:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
import matplotlib.pyplot as plt
import matplotlib.lines as mlines

# Create a custom legend handler function
def no_label_legend(color, linestyle):
    line = mlines.Line2D([], [], color=color, linestyle=linestyle)
    return line

# Plot some data
plt.plot([1, 2, 3], label='Line 1', color='blue')
plt.plot([3, 2, 1], label='Line 2', color='red', linestyle='dashed')

# Add legend without labels
plt.legend(handles=[no_label_legend('blue', '-'), no_label_legend('red', '--')], loc='upper left')

plt.show()


In this code snippet, the no_label_legend function creates a custom legend handler that simply creates a colored line with the specified color and linestyle. This function is then used when creating the legend by passing the desired color and linestyle for each line. This will create a legend with colored lines but without any labels.


How to hide a legend in matplotlib?

To hide the legend in a matplotlib plot, you can simply call the legend() function with no arguments. Here's an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
import matplotlib.pyplot as plt

# Create some data
x = [1, 2, 3, 4, 5]
y = [10, 15, 13, 18, 16]

# Plot the data
plt.plot(x, y)

# Hide the legend
plt.legend()

plt.show()


This will plot the data without displaying a legend.


How to create a custom legend handler in matplotlib?

To create a custom legend handler in matplotlib, you can use the HandlerBase class to define a new handler function. Here is an example of how you can create a custom legend handler for a scatter plot:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
import matplotlib.pyplot as plt
from matplotlib.legend_handler import HandlerBase

class CustomLegendHandler(HandlerBase):
    def create_artists(self, legend, orig_handle,
                        xdescent, ydescent, width, height, fontsize, trans):
        size = orig_handle.get_sizes()[0]
        marker = orig_handle.get_paths()[0]
        handle = plt.Line2D([0],[0], marker=marker, markersize=size, color='black')
        return [handle]

# Create a scatter plot
x = [1, 2, 3, 4, 5]
y = [2, 3, 4, 5, 6]
sizes = [20, 40, 60, 80, 100]
paths = [plt.Circle((0, 0), s) for s in sizes]

fig, ax = plt.subplots()
sc = ax.scatter(x, y, s=sizes, marker=paths)

# Create custom legend handler
plt.legend([sc], ['Data'], handler_map={type(sc): CustomLegendHandler()})

plt.show()


In this example, we create a custom legend handler CustomLegendHandler that creates a Line2D object with the same marker shape and size as the original scatter plot. We then use this custom legend handler when creating the legend for the scatter plot.


You can customize the create_artists method in the CustomLegendHandler class to create different types of artists for your legend, depending on your specific requirements.

Facebook Twitter LinkedIn Telegram Whatsapp Pocket

Related Posts:

When working with d3.js, you may need to display legend labels that are longer than the available space. In such cases, you can use the following approach to word wrap legend labels:Determine the maximum width for each legend label. This can be done by setting...
To plot a scatter pie chart using matplotlib, first import the necessary libraries such as matplotlib.pyplot. Next, create the data points for the scatter plot and specify the labels for the pie chart. Then, use the plt.scatter() function to plot the scatter p...
To animate a PNG image with Matplotlib, you can use the FuncAnimation class to create a sequence of frames and then save them as a video or gif. First, you need to import the necessary libraries such as Matplotlib and NumPy. Next, load your PNG image using Mat...