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 pandas

Beside NumPy and SciPy, pandas is one of the most common scientific computing libraries for Python. Its authors aim to make pandas the most powerful and flexible open source data analysis and manipulation tool available in any language, and in fact they are almost achieving that goal. Its powerful and efficient library is a perfect match for data scientists. Like other Python packages, Pandas can easily be installed via PyPI:

pip install pandas

First introduced in version 1.5, Matplotlib supports the use of pandas DataFrame as the input in various plotting classes. Unlike the simpler examples in previous chapters, where Python lists were supplied as the source of data, Pandas DataFrame is a powerful two-dimensional labeled data structure that supports indexing, querying, grouping, merging, and some other common relational database operations. DataFrame is similar to spreadsheets in the sense that each row of the DataFrame contains different variables of an instance, while...