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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

Why does visualization require planning?

The whole process of visualization involves people with different skill sets and domain expertise. Data wranglers diligently collect data and analyze it. Mathematicians and statisticians understand the visual design principles and communicate their data using those principles. Designers or artists (in some cases, frontend developers) have the skills necessary for visualization, while business analysts look out for things like customer behavioral patterns, outliers, or a sudden unusual trend. However, it always starts with either acquiring or gathering data, and with the following steps:

  • Acquire or gather data from an external source, a website, or from a file on a disk
  • Parse and filter data using programming methods to parse, clean, and reduce the data
  • Analyze and refine to remove noise and unnecessary dimensions and find patterns
  • Represent and interact to present the data in ways that are more accessible and understandable

How much of this process is...

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