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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 Formatting and Interpretation

The purpose of interactive data visualization is to visually and interactively present data so that it is easy to comprehend. Thus, naturally, data is the most important factor of any visualization. Hence, the first phase of data visualization is understanding the data in front of you – understanding what it is, what it means, and what it's conveying. Only when you understand the data will you be able to design a visualization that will help others understand it.

Additionally, it is important to ensure that your data makes sense and contains enough information – be it categorical, numerical, or a mix of both – to be visualized. So, if you are dealing with erroneous or dirty data, you're bound to end up with a faulty visualization.

In the next section, we'll look at a few ways to avoid common mistakes that are typically made in this phase of data and how to avoid them.

Avoiding Common Pitfalls while Dealing...

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