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

Installing a requests module


Most of the data that we need now is available over HTTP or similar protocol, so we need something to get it. Python library requests make the job easy.

Even though Python comes with the urllib2 module for work with remote resources and supporting HTTP capabilities, it requires a lot of work to get the basic tasks done.

A requests module brings a new API that makes the use of web services seamless and pain free. Lots of the HTTP 1.1 stuff is hidden away and exposed only if you need it to behave differently than default.

How to do it...

Using pip is the best way to install requests. Use the following command for the same:

$ pip install requests

That's it. This can also be done inside your virtualenv, if you don't need requests for every project or want to support different requests versions for each project.

Just to get you ahead quickly, here's a small example on how to use requests:

import requests
r = requests.get('http://github.com/timeline.json')
print r.content

How it works...

We sent the GET HTTP request to a URI at www.github.com that returns a JSON-formatted timeline of activity on GitHub (you can see HTML version of that timeline at https://github.com/timeline). After the response is successfully read, the r object contains content and other properties of the response (response code, cookies set, header metadata, and even the request we sent in order to get this response).