Live training with Max Humber starts on October 22nd at 12 PM (ET)

Training duration is 2 hours

Regular Price: $210.00

20% discount ends soon

Price with 20% discount

Instructor

Max Humber is the creator of gazpacho, the author of Personal Finance with Python, and a Distinguished Faculty Member at General Assembly.

Max Humber

Distinguished Faculty Member | General Assembly

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What will you learn?

  • When and why to use motion inside of a visualization

  • How to turn any Matplotlib into an animated plot in just two steps

  • How to format and save plots as animated gifs

Course Abstract

A good visualization should capture the interest of the audience and make an impression. Few things capture interest more than bright colors and movement. Unfortunately, adding motion to a static plot generated with a tool like Matplotlib has traditionally been cumbersome and confusing. And so, few people ever get around to playing with motion in their visualizations… until now.


In this course, Max will help you turn any Matplotlib plot into an animated visualization with just a couple of extra lines of code. Whereas animation used to be something that required fancy tooling, Max will show you how to use simple Python decorators to stitch together multiple plots like frames in a movie. By the end of this session, you’ll be able to capture interest and make an impression with any presentation or spot of data analysis!

Course Schedule

Introduction ( 10 | 10 minutes )

  • Who am I, and who are you?

  • Discussion: Have you ever tried to animate a plot?

  • Basic Review of Matplotlib


Plot Prep ( 15 | 25 minutes )

  • Making sure that we have the right data

  • Tweaking figure and canvas sizes

  • Adjusting backgrounds

  • Turning Matplotlib plots into functions


Animation Basics ( 25 | 50 minutes )

  • Overview of the Matplotlib.animation module

  • Using FuncAnimation to animate plots

  • Using the gif.frame decorator to animate plots

  • Exercise: Turn a simple Matplotlib plot into an animated gif


Q&A and Break ( 10 | 60 minutes ) 


Animation Examples ( 25 | 85 minutes )

  • How to style animated gifs

  • How to using 3D inside of animated gifs

  • How to recreate popular /r/dataisbeautiful plots

  • Exercise: Recreate an animated gif with Matplotlib


Animated ML ( 25 | 110 minutes ) 

  • How to visualize machine learning hyperparameters

  • How to visualize model diagnostics

  • How to tell a convincing machine learning story

  • Exercise: Create an animated machine learning model diagnostic plot


Q&A and Conclusion ( 10 | 120 minutes )

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Who will be interested in this course?

  • Data Scientists / Data Engineers

  • Those that work with data that has a temporal dimension

  • Those that find Matplotlib endlessly frustrating and confusing

Which knowledge and skills you should have?

  • Required: Experience with Python

  • Required: Some experience with Matplotlib

What is included in your ticket?

  • Access to the live training and a QA session with the Instructor

  • Access to the on-demand recording

  • Certificate of completion