Learning Python Data Visualization

Master how to build dynamic HTML5-ready SVG charts using Python and the pygal library
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Learning Python Data Visualization

Chad R. Adams

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Master how to build dynamic HTML5-ready SVG charts using Python and the pygal library
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Book Details

ISBN 139781783553334
Paperback212 pages

Book Description

The best applications use data and present it in a meaningful, easy-to-understand way. Packed with sample code and tutorials, this book will walk you through installing common charts, graphics, and utility libraries for the Python programming language.

Firstly you will discover how to install and reference libraries in Visual Studio or Eclipse. We will then go on to build simple graphics and charts that allow you to generate HTML5-ready SVG charts and graphs, along with testing and validating your data sources. We will also cover parsing data from the Web and offline sources, and building a Python charting application using dynamic data. Lastly, we will review other popular tools and frameworks used to create charts and import/export chart data. By the end of this book, you will be able to represent complex sets of data using Python.

Table of Contents

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
Creating SVG graphics using svgwrite
Summary
Chapter 3: Getting Started with pygal
Why use pygal?
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
Radar charts
Box plots
Dot charts
Funnel charts
Gauge charts
Pyramid charts
Worldmap charts
Summary
Chapter 5: Tweaking pygal
Country charts
Parameters
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
Parsing XML in Python with HTTP
About JSON
Parsing JSON in Python with HTTP
About JSONP
JSONP with Python
Summary
Chapter 7: Putting It All Together
Chart usage for a blog
Python modules
Modifying our RSS to return values
Project improvements
Summary
Chapter 8: Further Resources
The matplotlib library
Plotly
Pyvot
Summary

What You Will Learn

  • Build different types of Python charts and graphs
  • Master how to build Python graphics libraries
  • Test and validate your data sources
  • Explore common Python libraries for charts and graphics
  • Build charts using dynamic data from offline and online sources
  • Use CSS to modify embedded SVG images in HTML pages
  • Install and write Python code on Windows, Mac, or Linux
  • Discover how to install and reference libraries in Visual Studio or Eclipse

Authors

Table of Contents

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
Creating SVG graphics using svgwrite
Summary
Chapter 3: Getting Started with pygal
Why use pygal?
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
Radar charts
Box plots
Dot charts
Funnel charts
Gauge charts
Pyramid charts
Worldmap charts
Summary
Chapter 5: Tweaking pygal
Country charts
Parameters
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
Parsing XML in Python with HTTP
About JSON
Parsing JSON in Python with HTTP
About JSONP
JSONP with Python
Summary
Chapter 7: Putting It All Together
Chart usage for a blog
Python modules
Modifying our RSS to return values
Project improvements
Summary
Chapter 8: Further Resources
The matplotlib library
Plotly
Pyvot
Summary

Book Details

ISBN 139781783553334
Paperback212 pages
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