Book Image

Mastering Matplotlib 2.x

By : Benjamin Walter Keller
Book Image

Mastering Matplotlib 2.x

By: Benjamin Walter Keller

Overview of this book

In this book, you’ll get hands-on with customizing your data plots with the help of Matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more about tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this book. You’ll delve into niche plots and visualize ordinal and tabular data. In this book, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you’ll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook
Table of Contents (7 chapters)

Interactive Plotting

Until now, we have studied how to plot on 3D axes and how to make various different kinds of plots within those 3D axes. We also studied how to use basemap to generate map projections. Interactive plotting defines a discussion on interactivity wherein Matplotlib plots aren't just static images but dynamic updated figures that can change the way they are displayed based on the changes in real time to actual data in order to build apps using Matplotlib. In this chapter, we will learn about the following topics:

  • How to use the ipywidgets module with the Jupyter Notebook to make easy, interactive widgets
  • How to add callbacks to plots for interactivity
  • How to generate GUI neutral widgets for use in different kinds of Matplotlib applications
  • How to make movies and animations