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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

Data Visualization

The actual visualization is as important as the data that is being visualized, obviously, since it is the end product of the process. Thus, paying close attention to creating the best possible visualization for the data at hand is crucial.

Interactive visualizations have multiple elements/parts. Let's take a closer look at each element to understand what can go wrong and how to prevent such mistakes.

Choosing a Visualization

Once your data has been cleaned and prepared, and the features that you want to visualize have been chosen, the first step in creating a visualization is selecting the graph or plot that is going to display your data. This decision impacts the efficiency and ease with which your visualization can explain your data, and thus you need to ensure that you're picking a visualization that can accurately explain and describe your data.

In the previous chapters, we looked at three types of data – stratified, temporal...

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