18 best Python Animation libraries in 2023

We can create any animation with suitable libraries or combinations of libraries that are well-known for their functionalities using Python Animation Libraries. For developers looking for options with less complex code with maximum customization options, users can customize their plots and designs depending on their preferences.  

Choosing a suitable library plays a key role in any machine learning or data science project, and we should do it properly to avoid other related issues which may arise. Some libraries offer an interactive plot to attract playing with the graph and visualize it uniquely. It will allow you to edit videos, create animations, and create a map or geological animations where we can analyze the geological data. 

Here is the list of handpicked 18 best Python Animation Libraries in 2023 which will help you with your animation requirements: 

manim - 3b1b

• Is a Python library for creating mathematical animations and educational videos that Grant Sanderson develops.  
• Is an open source library that allows users to create high-quality animations which visualize mathematical concepts like animations of graphs, functions, fractals, and more.   
• Uses Python code for creating animations which we can export to animated GIFs or video files. 

PythonRobotics

• Is a Python library for implementing different robotics simulations, visualizations, and algorithms. 
• Offers various resources and tools for robotics developers, like algorithms for path planning, localization, motion control, mapping, and many more.   
• Includes simulation environments like 2D and 3D simulators, that will allow developers to test their algorithms in virtual environments before deploying them on real robots.   

matplotlib

• Is a comprehensive library for creating animated, interactive visualizations and static in Python. 
• Produces publication-quality figures in different interactive environments and hardcopy formats across platforms. 
• Can be used in Python Scripts, web application servers, various graphical user interface toolkits, and Python/IPython shells. 

manim - ManimCommunity

• Is an animation engine for explanatory math videos used for programmatically creating precise animations. 
• Includes various tools for creating animations like support for vector graphics, 3D objects, and complex mathematical equations. 
• Also includes features for creating animations with custom fonts, styles, and colors. 

plotly.py 

• Is a Python library used to create interactive data visualizations, built on the plotly JavaScript library that allows developers to create various interactive plots.   
• Is designed to be easy to use and includes different resources and tools for creating high-quality visualizations. 
• Includes support for complex data structures like pandas DataFrames and offers various customization options for fonts, styles, and colors. 

seaborn

• Is a Python data visualization library based on Matplotlib, offering a high-level interface to create attractive and informative statistical graphics.  
• Offers various plotting functions for visualizing various data types like continuous data, data distribution, and categorial data.  
• Its the ability to create visually appealing plots with minimal effort and supports the customization of plot elements like axes, titles, legends, and labels. 

moviepy

• Is a Python library for video editing, concatenations, cutting, video composting, title insertions, creation of custom effects, and video processing. 
• Has the ability to add audio to video clips easily and offers various filters and audio effects like changing pitch and speed, adding sound effects, and adjusting volume.  
• Includes support for creating animations like moving text, images, and shapes and allows users to export their video clips to different file formats. 

termtosvg 

• Is a Python library that allows users to record terminal sessions and save them as SVG animations.  
• Produces clean-looking and lightweight still frames embeddable on the project page or animations.  
• Includes support for recording multiple terminal sessions, allowing users to control the size and speed of the resulting animation.   

altair

• Is a declarative statistical visualization library that can help you spend more time understanding your data and its meaning. 
• Offers a simple syntax for creating different visualizations, like line charts, histograms, scatterplots, and bar charts. 
• Its declarative syntax lets user's express visualizations as a series of high-level mappings between visual and data properties like color, size, and position. 

PathPlanning

• Is a Python library used for path and motion planning applications designed to be accessible to beginners and experts with a straightforward API. 
• Offers various algorithms for computing collision-free paths for drones, mobile robots, and manipulators in 2D and 3D environments. 
• Also offers tools for trajectory generation, motion control, and obstacle avoidance and supports simulation and visualization of robot motion. 

alive-progress 

• Is a Python library for displaying spinners and progress bars in command-line applications designed to offer a customizable way of showing progress indicators for long-running processes or tasks. 
• Supports for pausing and resuming progress indicators, nested spinners, and progress bars. 
• Designed to be intuitive and simple with various default settings and a straightforward API for customizing the behavior and appearance of spinners and progress bars. 

asciimatics 

• Is a package for helping people create full-screen text UIs on any platform and offers a single cross-platform Python class to do all the low-level console functions. 
• Includes cursor positioning, mouse input, screen scraping, colored/styled text, detecting and handling if the console resizes, and keyboard input like Unicode support. 
• Is a Python library for creating text-based animations and user interfaces in the terminal. 

pygal 

• Is a Python library for creating interactive Scalable Vector Graphics (SVG) graphs and charts. 
• Offers various tools for generating customizable charts, graphs, and high-quality for use in presentations, reports, and web applications. 
• Includes built-in support for data/time axis labeling, responsive design, and integration with web frameworks and interactive charts elements.   

GANimation 

• Is a Python implementation of the GANimation research project, which offers various tools for generating animations from still images using Generative Adversarial Networks (GANs).  
• Includes tools for augmenting and preprocessing input data, customizable GAN training parameters and architecture, and support for evaluating and visualizing GAN models.  
• Offers various tools for fine-tuning GAN models and generating high-quality animations for various applications. 

deep-motion-editing 

• Offers advanced and fundamental functions to work with 3D character animations in deep learning with Pytorch. 
• Is a Python implementation of the research project of the same name, which offers tools for editing the motion of human characters in video sequences using deep learning methods.  
• Its ability to generate realistic, high-quality animations for various applications offers tools for fine-tuning the deep learning model and editing the generated motions to achieve the desired results. 

geoplotlib 

• Is a Python library for creating geographical maps and visualizations and offers an easy-to-use interface for creating maps with different data types, like polygons, heatmaps, lines, and points. 
• Includes support for different tile providers and map projections, customizable styling options for data layers like size, transparency, and color. 
• Designed for creating interactive maps and visualizations and is suitable for various applications like data analysis, presentation, and exploration. 

Linux-Fake-Background-Webcam 

• Is a Python library that will allow users to replace their webcam background with a custom video or image on Linux systems.  
• Works by creating a virtual webcam device that can be selected as the input source in video conferencing applications, allowing users to appear as if they are in various environments and locations.   
• Includes the ability to control the position and size of the custom background video or image and support for replacing the webcam background with a custom video or audio. 

celluloid 

• Is a Python library that offers a simple interface for creating visualizations and animations in Matplotlib   
• Designed to make it easy for users to create animations without having to write to deal with low-level details and complex code.  
• Includes a simple interface for adding and updating data in the animation, the ability to save the animation as an MP4 or GIF video file, and support for customizing the animation style and appearance. 

FAQ

What are the best data visualizations for Python animation libraries?  

The Python Animation libraries create amazing visuals that can move and change. Here are the best data visualization libraries:  

• Matplotlib  
• Bokeh  
• Plotly  
• Pygal  
• Plotnine  
• Seaborn  
• Holoviews  

Which animation library is most used by Python coders today?  

Matplotlib is a powerful 2D plotting library. It supports various visualizations. It is used in the scientific and data analysis communities. The 'FuncAnimation' class provides its animation capabilities. It allows coders to create dynamic and interactive visualizations. Its popularity is due to its advanced development, clear documentation, and reliability. Other higher-level visualization libraries use it as the backend.  

How can I create explanatory math videos using a Python animation library?  

You can use a Python Animation library to make math videos that show concepts visually. You should follow the below steps:  

• Choose a Python animation library  
• Plan your content  
• Write the Python code  
• Animate with time  
• Narrate or annotate  
• Export the video  
• Edit and visualize  
• Share your video  

What does the code for a basic Python animation look like?  

You can make a simple animation in Python with different libraries. Many people like using the matplotlib library. Matplotlib, a strong Python library, can make plots and do basic animations.   

Here's an example of a basic Python animation using matplotlib:   

import numpy as np   

import matplotlib.pyplot as plt   

from matplotlib.animation import FuncAnimation   

# Function to update the plot in each animation frame   

def update(frame):   

   # Clear the previous plot   

   plt.cla()   

   # Generate some data points for the animation   

   x = np.linspace(0, 2*np.pi, 100)   

   y = np.sin(x + 2*np.pi*frame/100)   

   # Plot the data   

   plt.plot(x, y)   

   plt.xlabel('X')   

   plt.ylabel('Y')   

   plt.title('Basic Python Animation')   

   plt.grid(True)   

# Create a blank figure   

fig, ax = plt.subplots()   

# Create the animation with the update function, 100 frames, and 100ms delay between frames   

animation = FuncAnimation(fig, update, frames=100, interval=100)    

# If you want to save the animation as a video file, you can use the following line:   

# animation.save('basic_animation.mp4', writer='ffmpeg', fps=30)   

 # Display the animation   

plt.show()   

This code creates a simple animation that displays a sine wave. The update function makes new data points and updates the plot in each animation frame. The FuncAnimation class controls the animation. It calls the update function many times with different frame values.  

In this example, the animation has 100 frames with a delay of 100 milliseconds between frames.

To save the animation as a video file: 

1. Remove the comment from the animation. 
2. Save line. 
3. Make sure you have ffmpeg installed. 
4. Before running the code, ensure you have installed matplotlib in your Python setup. You can install it using pip install matplotlib.  

Using an animation library, how can you make line charts with various colors in Python?  

You can use different libraries in Python to make line charts with colors and animations. I will teach you how to use Matplotlib's FuncAnimation to animate graphs.   

Here's a step-by-step guide:   

#Install the required libraries (if you haven't already)   

pip install matplotlib   

# Import the necessary modules   

import numpy as np   

import matplotlib.pyplot as plt   

from matplotlib.animation import FuncAnimation   

# Generate your data: Create multiple datasets with different colors. For this example, let's consider two datasets, data1 and data2   

x = np.linspace(0, 10, 100)   

data1 = np.sin(x)   

data2 = np.cos(x)   

# Create a figure and an axis to plot the data   

fig, ax = plt.subplots()   

# Define the line objects for each dataset and set their properties   

line1, = ax.plot([], [], color='red', label='Data 1')   

line2, = ax.plot([], [], color='blue', label='Data 2')   

# Define the initialization function for the animation   

def init():   

   line1.set_data([], [])   

   line2.set_data([], [])   

   return line1, line2   

# Define the update function for the animation   

def update(frame):   

   line1.set_data(x[:frame], data1[:frame])   

   line2.set_data(x[:frame], data2[:frame])   

   return line1, line2   

# Create the animation using FuncAnimation   

frames = len(x)   

animation = FuncAnimation(fig, update, frames=frames, init_func=init, blit=True)   

# Display the animation or save it to a file (optional)   

plt.legend()   

plt.xlabel('X-axis')   

plt.ylabel('Y-axis')   

plt.title('Animated Line Chart with Different Colors')   

plt.show()   

This code makes a line chart that shows two datasets using different colors. You can customize the colors, data, and other properties per your requirements. To add more datasets, make new line objects and update their data in the update function.   

Can FuncAnimation be used to animate 3D objects and 2D shapes in Python?  

Yes, 'FuncAnimation' can animate both 3D objects and 2D shapes. But 'FuncAnimation' is a part of the Matplotlib library. It is primarily known for 2D plotting. Matplotlib's 3D plotting toolkit makes 3D objects, and visualizations come to life.  

Are there any tips or tricks to improve creating animations with Python libraries?  

To improve your animations, follow these helpful tips and tricks for efficient engineering. Here are some valuable tips to help you with it:  

• Plan your animation  
• Keep it simple  
• Use subplots  
• Choose the right library  
• Optimize data processing  
• Minimize redrawing  
• Control animation speed  
• Add labels and annotations  
• User color thoughtfully  
• Consider interactivity  
• Test on a smaller subset  

Can I find open-source projects to practice coding with a Python animation library?  

Yes, there are many open-source projects available that use Python animation libraries. These resources help you practice animation libraries before starting your own project. Here are some places where you can find such projects:  

• Matplotlib Examples Gallery  
• GitHub Repositories  
• Plotly Examples Gallery  
• Kaggle Notebooks  
• Bokeh Examples Gallery  
• Data Science Blogs  
• YouTube Tutorials