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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

A sports example


To illustrate another example, and how a specific visualization method works better than another, let us consider a different question: What are the top five record touchdowns by quarterbacks in American Football as of Feb 2015? The original source of data for this are the Len Dawson NFL and AFL Statistics. (Data source: http://www.pro-football-reference.com/players/D/DawsLe00.htm.)

The data contains information about the top 22 quarterbacks: Peyton Manning, Brett Favre, Dan Marino, Drew Brees, Tom Brady, Frank Tarkenton, John Elway, Warren Moon, John Unitas, Vinny Testaverda, Joe Montana, Dave Krieg, Eli Manning, Sonny Jurgensen, Dan Fouts, Philip Rivers, Ben Roethlisberger, Drew Bledsoe, Boomer Esiason, John Hadle, Tittle, and Tony Romo:

Before we think of a visualization method, a little bit of analysis needs to be done. These quarterbacks had played in different time periods. For example, Brett Favre played from 1991 to 2010, and Dan Marino played from 1983 to 1999. The...

You have been reading a chapter from
Mastering Python Data Visualization
Published in: Oct 2015
Publisher:
ISBN-13: 9781783988327
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