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Interactive Data Visualization with Python - Second Edition

You're reading from  Interactive Data Visualization with Python - Second Edition

Product type Book
Published in Apr 2020
Publisher
ISBN-13 9781800200944
Pages 362 pages
Edition 2nd Edition
Languages
Authors (4):
Abha Belorkar Abha Belorkar
Profile icon Abha Belorkar
Sharath Chandra Guntuku Sharath Chandra Guntuku
Profile icon Sharath Chandra Guntuku
Shubhangi Hora Shubhangi Hora
Profile icon Shubhangi Hora
Anshu Kumar Anshu Kumar
Profile icon Anshu Kumar
View More author details

Table of Contents (9) Chapters

Preface 1. Introduction to Visualization with Python – Basic and Customized Plotting 2. Static Visualization – Global Patterns and Summary Statistics 3. From Static to Interactive Visualization 4. Interactive Visualization of Data across Strata 5. Interactive Visualization of Data across Time 6. Interactive Visualization of Geographical Data 7. Avoiding Common Pitfalls to Create Interactive Visualizations Appendix

Static versus Interactive Visualization

While static data visualizations are a giant leap forward toward the goal of extracting and explaining the value and information that datasets hold, the addition of interactivity takes these visualizations a step ahead.

Interactive data visualizations have the following qualities:

  • They are easier to explore as they allow you to interact with data by changing colors, parameters, and plots.
  • They can be manipulated easily and instantly. Since you can interact with them, the graphs can be changed in front of you. For example, in the exercises and activities in this chapter, you will create an interactive slider. When the position of this slider is altered and the graph you see changes, you will also be able to create checkboxes that allow you to select the parameters you wish to see.
  • They enable access to real-time data and the insights they provide. This allows for the efficient and quick analysis of trends.
  • They are easier...
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