Learning Python Data Visualization

✍ Scribed by Chad Adams

• Year: 2014
• Tongue: English
• Leaves: 212
• Category: Library

✦ Synopsis

If you are a Python novice or an experienced developer and want to explore data visualization libraries, then this is the book for you. No prior charting or graphics experience is needed.

✦ Table of Contents

Cover
Copyright
Credits
About the Author
About the Reviewers
www.PacktPub.com
Table of Contents
Preface
Chapter 1: Setting Up Your Development Environment
Introduction
Setting up Python on Windows
Installation
Exploring the Python installation in Windows
Python editors
Setting up Python on Mac OS X
Setting up Python on Ubuntu
Summary
Chapter 2: Python Refresher
Python basics
Importing modules and libraries
Input and output
Generating an image
Creating SVG graphics using svgwrite
For Windows users using VSPT
For Eclipse or other editors on Windows
For Eclipse on Mac and Linux
Summary
Chapter 3: Getting Started with pygal
Why use pygal?
Installing pygal using pip
Installing pygal using Python Tools for Visual Studio
Building a line chart
Stacked line charts
Simple bar charts
Stacked bar charts
Horizontal bar charts
XY charts
Scatter plots
DateY charts
Summary
Chapter 4: Advanced Charts
Pie charts
Stacked pie charts
Radar charts
Box plots
Dot charts
Funnel charts
Gauge charts
Pyramid charts
Worldmap charts
Summary
Chapter 5 : Tweaking pygal
Country charts
Parameters
Legend at the bottom
Legend settings
Label settings
Chart title settings
Displaying no data
pygal themes
Summary
Chapter 6: Importing Dynamic Data
Pulling data from the Web
The XML refresher
RSS and the ATOM
Understanding HTTP
Using HTTP in Python
Parsing XML in Python with HTTP
About JSON
Parsing JSON in Python with HTTP
About JSONP
JSONP with Python
Summary
Chapter 7 : Putting ItAll Together
Chart usage for a blog
Getting our data in order
Converting date strings to dates
Using strptime
Saving the output as a counted array
Counting the array
Python modules
Building the main method
Modifying our RSS to return values
Building our chart module
Building a portable configuration for our chart
Setting up our chart for data
Configuring our main function to pass data
Project improvements
Summary
Chapter 8: Further Resources
The matplotlib library
Installing the matplotlib library
matplotlib's library download page
Creating simple matplotlib charts
Plotly
Pyvot
Summary
Appendix: References and Resources
Links for help and support
Charting libraries
Editors and IDEs for Python
Other libraries and Python alternative shells
Index