Book Image

Matplotlib 2.x By Example

By : Allen Yu, Claire Chung, Aldrin Yim
Book Image

Matplotlib 2.x By Example

By: Allen Yu, Claire Chung, Aldrin Yim

Overview of this book

Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization. Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts. By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Table of Contents (15 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback

Interactive backends

Matplotlib can build interactive figures that are far more engaging for readers. Sometimes, a plot might be overwhelmed with graphical elements, making it hard to discern individual data points. On other occasions, some data points may appear so similar that it becomes hard to spot the differences with the naked eye. An interactive plot can address these two scenarios by allowing us to zoom in, zoom out, pan, and explore the plot in the way we want.

Through the use of interactive backends, plots in Matplotlib can be embedded in Graphical User Interface (GUI) applications. By default, Matplotlib supports the pairing of the Agg raster graphics renderer with a wide variety of GUI toolkits, including wxWidgets (Wx), GIMP Toolkit (GTK+), Qt, and Tkinter (Tk). As Tkinter is the de facto standard GUI for Python, which is built on top of Tcl/Tk, we can create an interactive plot just by calling in a standalone Python script.

Tkinter-based backend 

Let's try to copy the...