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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

Perception and presentation methods

In the past, data size and variety did not impose much of a challenge; therefore, perceiving and analyzing data was straightforward. Today there are large quantities of data in innumerable fields, and visualization can provide valuable assistance to humans for perceiving and interacting with visualization of the data. Human factors contribute significantly to the whole visualization process in order to better understand data and aid in decision-making tasks.

Visualization techniques can be categorized into two areas:

  • Scientific visualization: This involves scientific data with an inherent physical entity
  • Information visualization: This involves abstract data (spatial or non-spatial)

Most visualization systems are designed so that humans and computers can cooperate, each performing the following tasks:

  • Visually representing data to enhance data analysis
  • Visually displaying models, interpretations of data, ideas, hypotheses, and insight
  • Helping users to improve...
You have been reading a chapter from
Mastering Python Data Visualization
Published in: Oct 2015
Publisher:
ISBN-13: 9781783988327
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