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

Using style sheets


We have learned to style our plots step by step so far. For more persistent and portable settings, we can apply a predefined global style via the matplotlib.style module:

## Available styles
 Matplotlib provides a number of pre-built style sheets. You can check them out by with `matplotlib.style.available`.


import matplotlib as mpl
mpl.style.available

Out[1]: ['seaborn-talk',
'seaborn-poster',
'_classic_test',
'seaborn-ticks',
'seaborn-paper',
'ggplot',
'seaborn',
'seaborn-dark',
'seaborn-bright',
'seaborn-pastel',
'fivethirtyeight',
'Solarize_Light2',
'classic',
'grayscale',
'bmh',
'seaborn-dark-palette',
'seaborn-whitegrid',
'seaborn-white',
'dark_background',
'seaborn-muted',
'fast',
'seaborn-notebook',
'seaborn-darkgrid',
'seaborn-colorblind',
'seaborn-deep']

Applying a style sheet

We can call plt.style.use(stylename) to apply a style. This function takes in built-in style sheets, local paths, and URLs.

Creating own style sheet

You can also create your own style sheet...