Code and run your first Python script with Matplotlib in minutes without installing anything!
This course is designed for learners with some Python experience, and provides a crash course in Matplotlib. This enables the learners to delve into core data visualization topics that can be transferred to other languages. In this course, you will learn how to use Jupyter, generate and choose the best graphs to represent your data.
To allow for a truly hands-on, self-paced learning experience, this course is video-free.
Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.
Overview
Syllabus
- Intro to Matplotlib
- Welcome to Week 1 of the Select Topics in Python: Matplotlib course. These assignments cover the basics of Jupyter notebooks and Matplotlib, customizing a visualization, as well as box plots and histograms. The module ends with graded coding exercises.
- Intermediate Matplotlib
- Welcome to Week 2 of the Select Topics in Python: Matplotlib course. These assignments extend the previous module by introducing line charts, area charts, scatter plots, bubble charts, pie charts, and donut charts. The module ends with graded coding exercises.
- Advanced Matplotlib
- Welcome to Week 3 of the Select Topics in Python: Matplotlib course. These assignments cover specialized visualizations, configuring layout and presentation, and adding animations. The module ends with graded coding exercises.
Taught by
Patrick Ester