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Python Data Visualization Cookbook

You're reading from  Python Data Visualization Cookbook

Product type Book
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Pages 280 pages
Edition 1st Edition
Languages
Author (1):
Igor Milovanovic Igor Milovanovic
Profile icon Igor Milovanovic

Table of Contents (15) Chapters

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using Right Plots to Understand Data 8. More on matplotlib Gems 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 makes that 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.

Requests module brings new API that makes the use of web services seamless and pain free. Lot 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 response is successfully read, the r object contains content and other properties of the response (response code, cookies set, header metadata, even the request we sent in order to get this response).

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Python Data Visualization Cookbook
Published in: Nov 2013 Publisher: Packt ISBN-13: 9781782163367
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