Interactive Web-Based Data Visualization (Chapman & Hall)
Friday, 14 February 2020

This richly illustrated book that covers R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. Carson Sievert writes for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Many R code examples illustrate how to tap the extensive functionality of these tools to enhance the presentation and exploration of data, and how to use these concepts and tools to generate more informative, engaging, and reproducible interactive graphics using free and open source software.


Author: Carson Sievert Publisher: Chapman and Hall
Date: January 2020
Pages: 448
ISBN: 978-1138331457
Print: 1138331457
Kindle: B084C5L8W5
Audience: data users and developers
Level: Introductory/Intermediate
Category: Data Science

Key features:

  • Convert static ggplot2 graphics to an interactive web-based form
  • Link, animate, and arrange multiple plots in standalone HTML from R
  • Embed, modify, and respond to plotly graphics in a shiny app
  • Learn best practices for visualizing continuous, discrete, and multivariate data
  • Learn numerous ways to visualize geo-spatial data

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.


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Foundational Python For Data Science

Author: Kennedy Behrman
Publisher: Pearson
ISBN: 978-0136624356
Print: 0136624359
Kindle: B095Y6G2QV
Audience: Data scientists
Rating: 4.5
Reviewer: Kay Ewbank

This book sets out to be a simple introduction to Python, specifically how to use it to work with data.

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Author: Pierre-Yves Saumont
Publisher: Manning
Date: April 2019
Pages: 480
ISBN: 978-1617295362
Print: 1617295361
Audience: Functional programming afficianados wanting to use Kotlin
Rating: 4
Reviewer: Alex Armstrong
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