Book Image

Matplotlib for Python Developers - Second Edition

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

Matplotlib for Python Developers - Second Edition

By: Aldrin Yim, Claire Chung, Allen Yu

Overview of this book

Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Chapter 2. Getting Started with Matplotlib

Now that we are familiar with the capabilities and functionalities of Matplotlib and all geared up with the Python environment, let's go straight ahead and create our first plots.

In this chapter, we will learn how to:

  • Draw basic line and scatter plots
  • Overlay multiple data series on the same plots
  • Adjust grids, axes, and labels
  • Add a title and legend
  • Save created plots as separate files
  • Configure Matplotlib global settings