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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
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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 2. Data Analysis and Visualization

Most visualization stories begin with some question that is oriented towards a topic where the data is being either explored or collected. The question contains the premise to the story and leads us to the point at which the data takes an expedition over the storyline. Such data expeditions that start with a question, for example, How many Ebola deaths were reported in the year 2014? are implemented by a group of people by collaborating with each other. The role of data communicators should be to create an information experience that transforms how their audiences think about their story.

The key parts of the story relate to the process of placing the visualization in a meaningful context. The context provides knowledge that answers questions such as the following:

  • Is there sufficient data?
  • Is there a time frame within which this data exists?
  • Which associable events around the globe will influence this data?

To reiterate, it is important to...

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