Animated Scatter Plot with Python

Introduction

This lab is designed to teach you how to create an animated scatter plot using Python's Matplotlib library. We will cover everything from setting up the plot to saving the animation as a GIF. By the end of this lab, you will have a working animated scatter plot that you can use to visualize your data.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlottingDataGroup(["`Plotting Data`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/AdvancedTopicsGroup(["`Advanced Topics`"]) python(("`Python`")) -.-> python/BasicConceptsGroup(["`Basic Concepts`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/FunctionsGroup(["`Functions`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) matplotlib/BasicConceptsGroup -.-> matplotlib/importing_matplotlib("`Importing Matplotlib`") matplotlib/BasicConceptsGroup -.-> matplotlib/figures_axes("`Understanding Figures and Axes`") matplotlib/PlottingDataGroup -.-> matplotlib/scatter_plots("`Scatter Plots`") matplotlib/AdvancedTopicsGroup -.-> matplotlib/animation_creation("`Animation Creation`") python/BasicConceptsGroup -.-> python/booleans("`Booleans`") python/DataStructuresGroup -.-> python/lists("`Lists`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/FunctionsGroup -.-> python/function_definition("`Function Definition`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/DataScienceandMachineLearningGroup -.-> python/numerical_computing("`Numerical Computing`") python/DataScienceandMachineLearningGroup -.-> python/data_visualization("`Data Visualization`") python/FunctionsGroup -.-> python/build_in_functions("`Build-in Functions`") subgraph Lab Skills matplotlib/importing_matplotlib -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} matplotlib/figures_axes -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} matplotlib/scatter_plots -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} matplotlib/animation_creation -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/booleans -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/lists -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/tuples -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/function_definition -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/importing_modules -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/numerical_computing -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/data_visualization -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} python/build_in_functions -.-> lab-48944{{"`Matplotlib Animated Scatter Plot`"}} end

Setting up the Plot

The first step in creating an animated scatter plot is to set up the plot itself. This involves importing the necessary libraries and creating a figure and axes object.

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()

Defining the Data

Next, we need to define the data that we will be using for our scatter plot. In this example, we will be using a simple array of numbers ranging from 0 to 10.

x = np.linspace(0, 10)

Creating the Scatter Plot

Now that we have our data, we can create the scatter plot. We do this by calling the scatter function on our axes object and passing in our x data.

scat = ax.scatter(1, 0)

Creating the Animation

The final step is to create the animation. We do this using the FuncAnimation function from the animation module. This function takes a few arguments, including the figure object, the function that will update the plot, and the number of frames to use.

def animate(i):
    scat.set_offsets((x[i], 0))
    return scat,

ani = animation.FuncAnimation(fig, animate, repeat=True,
                                    frames=len(x) - 1, interval=50)

Displaying the Plot

We can now display the plot by calling the show function from the pyplot module.

plt.show()

Summary

In this lab, we learned how to create an animated scatter plot using Python's Matplotlib library. We covered everything from setting up the plot to saving the animation as a GIF. With this knowledge, you can now create your own animated scatter plots to visualize your data.

Matplotlib Animated Scatter Plot