Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

Overview of this book

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.
Table of Contents (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Importing data from a JSON resource


This recipe will show us how we can read the JSON data format. Moreover, we'll be using a remote resource in this recipe. It will add a tiny level of complexity to the recipe, but it will also make it much more useful because in real life we will encounter more remote resources than local ones.

JavaScript Object Notation (JSON) is widely used as a platform-independent format to exchange data between systems or applications.

A resource, in this context, is anything we can read, be it a file or a URL endpoint (which can be the output of a remote process/program or just a remote static file). In short, we don't care who produced a resource and how they did it; we just need it to be in a known format like JSON.

Getting ready

In order to get started with this recipe, we need the requests module installed and importable (in PYTHONPATH) in our virtual environment. We have installed this module in Chapter 1, Preparing Your Working Environment.

We also need Internet...