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

Text and annotations


To enhance the understanding of plot details, we may sometimes add in text annotations for explanation. We will now introduce the methods of adding and adjusting text in Matplotlib plots.

Adding text annotations

We can add text to our plot by calling plt.text(x,y,text); we specify the x and y coordinates and the text string. Here is a quick example:

plt.text(0.25,0.5,'Hello World!',fontsize=30)
plt.show()

You can see in this figure the Hello World! message appearing in the center of the plot:

Font

Here are some of the common font properties adjustable in Matplotlib:

  • Font size: Float or relative size, for example, smaller and x-large
  • Font weight: For example, bold or semibold
  • Font style: For example, italic
  • Font family: For example, Arial
  • Rotation: Angle in degrees; it is vertical or horizontal

Note

Matplotlib now supports unicode and emoji.

Mathematical notations

As a plotting tool, mathematical notations are common. We can use the in-built mathtext or LaTeX to render mathematical...