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Mastering Python Data Visualization

You're reading from   Mastering Python Data Visualization Generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783988327
Length 372 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. A Conceptual Framework for Data Visualization 2. Data Analysis and Visualization FREE CHAPTER 3. Getting Started with the Python IDE 4. Numerical Computing and Interactive Plotting 5. Financial and Statistical Models 6. Statistical and Machine Learning 7. Bioinformatics, Genetics, and Network Models 8. Advanced Visualization A. Go Forth and Explore Visualization Index

Chapter 8. Advanced Visualization

Visualization methods have transformed from the traditional bar and pie graphs several decades ago to much more creative forms lately. Designing visualization is not as straightforward as picking one from the many choices that a particular tool offers. The right visualization conveys the right message, and the wrong visualization may distort, confuse, or convey the wrong message.

Computers and storage devices within them are useful in not only storing large chunks of data using data structures, but also to use the power of computing via algorithms. According to Michael Bostock, the creator of D3.js and a leading visualization expert, we should visualize the algorithm and not just the data that feeds into it. An algorithm is the core engine behind any process or computational model; therefore, this algorithm has become an important use case for visualization.

Visualizing algorithms has only been recognized in the recent past few years, and one interesting...

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