Learning Python data visualization: master how to build dynamic HTML5-ready SVG charts using Python and the pygal library

Learning Python data visualization: master how to build dynamic HTML5-ready SVG charts using Python and the pygal library

Author
Adams, Chad
Publisher
Packt Publishing Ltd
Language
English
Year
2014
Page
iii, 195 pages : illustrations ; 24 cm
ISBN
9781783553334,1783553332
File Type
azw3
File Size
5.6 MiB

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

About This Book
A practical guide that helps you break into the world of data visualization with Python Understand the fundamentals of building charts in Python Packed with easy-to-understand tutorials for developers who are new to Python or charting in Python

Who This Book Is For

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.

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

In Detail

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.

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