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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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Author (1):
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Kirthi Raman Kirthi Raman
Author Profile Icon Kirthi Raman
Kirthi Raman
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Table of Contents (16) Chapters Close

Mastering Python Data Visualization
Credits
About the Author
About the Reviewers
www.PacktPub.com
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 Go Forth and Explore Visualization Index

Interactive visualization


For a visualization to be considered interactive, it must satisfy two criteria:

  • Human input: The control of some aspect of the visual representation of information must be available to humans

  • Response time: The changes made by humans must be incorporated into the visualization in a timely manner

When large amounts of data must be processed to create a visualization, this becomes very hard, sometimes impossible, even with the current technology; therefore, "interactive visualization" is usually applied to systems that provide feedback to the users within several seconds of input. Many interactive visualization systems support a metaphor of navigation, analogous to navigation through the physical world.

The benefit of interaction is that people can explore a larger information space in a shorter time, which can be understood through one platform. However, a disadvantage to this interaction is that it requires a lot of time to exhaustively check every possibility to...

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Mastering Python Data Visualization
Published in: Oct 2015
Publisher:
ISBN-13: 9781783988327
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