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

Configuring Matplotlib


We have learned to tweak a few major elements in a Matplotlib plot. When we recurrently generate figures of similar style, it would be nice to have a way to store and apply the persistent global settings. Matplotlib offers a few options for configuration.

Configuring within Python code

To keep settings throughout the current session, we can execute matplotlib.rcParams to override configuration file settings.

For instance, we can set the font size of all text in plots to 18 with the following:

matplotlib.rcParams['font.size'] = 18

Alternatively we can call the matplotlib.rc() function. As matplotlib.rc() just changes one property, to change multiple settings, we can use the function matplotlib.rcParams.update(), and pass parameters in the form of a dictionary of key-value pairs:

matplotlib.rcParams.update({'font.size': 18, 'font.family': 'serif'})

Reverting to default settings

To revert to default settings, you can call matplotlib.rcdefaults() or matplotlib.style.use('default...