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

Introducing Seaborn

Seaborn by Michael Waskom is a statistical visualization library that is built on top of Matplotlib. It comes with handy functions for visualizing categorical variables, univariate distributions, and bivariate distributions. For more complex plots, various statistical methods such as linear regression models and clustering algorithms are available. Like Matplotlib, Seaborn also supports Pandas dataframes as input, plus automatically performing the necessary slicing, grouping, aggregation, and statistical model fitting to produce informative figures.

These Seaborn functions aim to bring publication-quality figures through an API with a minimal set of arguments, while maintaining the full customization capabilities of Matplotlib. In fact, many functions in Seaborn return a Matplotlib axis or grid object when invoked. Therefore, Seaborn is a great companion of Matplotlib. To install Seaborn through PyPI, you can issue the following command in the terminal:

pip install pandas...