Textbook in PDF format

This book is written for frustrated and reluctant Matplotlib users who care about crafting good data visuals. Matplotlib can be a blank canvas, offering more room for customization than you might find in Microsoft Excel, and offers the advantages of reproducibility and automation that come from working with Python. Still, becoming comfortable with matplotlib requires a lot of patience. I wrote this book to help make that easier and put some essentials in one place.
This book itself doesn't show you how to make particular chart types. The idea is you already have a bar chart, line plot, histogram, etc, but that it's ugly. The book helps you figure out how to beautify your charts and helps make those steps seem less mysterious.
Why Matplotlib? Though a bit aged, matplotlib is the standard in Python. Matplotlib is integrated with pandas and Seaborn is based off Matplotlib. You might prefer Plotnine if you already know R’s ggplot2. You might prefer to leave Python and use D3 if you know JavaScript. You might prefer Microsoft Excel if you want consultants in your audience to feel at home. I recommend Matplotlib to anyone who is already committed to working in Python (and with the Python community) and values reproducibility and customizability. By the time we get to Part III, we’ll be drawing more than plotting. This allows for more creativity than Excel allows and we’ll maintain a reproducible Python-only workflow.
The Object-oriented Interface
Axes Appearance, Ticks, and Grids
Elements and Coordinate Systems
Text and Titles
Dates
Colors
Multiple Axes and Plots
Style and Configuration
Math Interlude
Math Interlude - Applications
Artist Objects
Artist Objects - Applications
Special Topics - Multi-dimensional Scaling
Special Topics - Intro Stats Graphs
Special Topics - Ternary Plots