Matplotlib 3.6.0 improves 3D plots for data science

Matplotlib, the Python plotting library, has a new release out and ready for download. Let’s explore what’s included in the new update and how you can get started and implement it into your machine learning and data science projects.

New in 3.6.0

Matplotlib released version 3.6.0 on September 15, 2022.

Matplot 3.6.0 mainly focuses on new features and improvements for 3D plots. It added an equal aspect ratio for 3D plots, as well as a new custom focal length for 3D cameras that more closely mimics real-world camera movement, and a “roll” camera angle. With the “roll” camera angle, you will now be able to view 3D plots in any angle you wish, rotate it, and visually interact with your data.

Some other highlights in the newest version include:

• New modules: tight_layout and constrained_layout layout engines
• Support added for WebP as an output format
• Plenty of new updates for plotting methods, including the new (experimental) striped lines.
• Changes have been made to how Matplotlib handles garbage collection. Garbage collection will no longer be performed on closed figures.
• The ncol keyword argument has been renamed to ncols.
• New customization options for cap style, join styles, and arbitrary transforms.
• Improvements for dark theme UI.
• Fullscreen support and better animations for macOS.

View a list of the new changes for version 3.6.0 in the documentation. This is now currently the most up-to-date stable version and can be used in production.

Data visualization at your fingertips

Originally created by John D. Hunter, Matplotlib has a surprising medical background. Hunter, a neurobiologist, originally created the library in order to monitor patients with epilepsy.

Now, Matplotlib is used in data science visualization, providing interactive 3D plots, line plots, scatter plots, and much more.

From the GitHub repo:

“Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, Python/IPython shells, web application servers, and various graphical user interface toolkits.”

Matplotlib is also extensible with third-party packages and toolkits that can add new functionality to the library for more specialized usage. This includes adding interactions with Microsoft Excel, new colormaps and styling, tools for high-end physics projects, interactive widgets, new plot types, and much more. (There’s even a third-party package library for plotting football pitches.)

Getting started

Follow the installation instructions here. Matplotlib is available on Windows devices, for macOS, and Linux.

Check out the repository on GitHub and be sure to follow it so you don’t miss out on any upcoming updates. (Or even sponsor the project and lend the developers your support.)