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Interactive Web-Based Data Visualization with R, plotly, and shiny Chapman & Hall/CRC The R Series

Langue : Anglais

Auteur :

Couverture de l’ouvrage Interactive Web-Based Data Visualization with R, plotly, and shiny

The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Through many R code examples, you will learn how to tap the extensive functionality of these tools to enhance the presentation and exploration of data. By mastering these concepts and tools, you will impress your colleagues with your ability to quickly generate more informative, engaging, and reproducible interactive graphics using free and open source software that you can share over email, export to pdf, and more.

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

This book makes heavy use of plotly for graphical rendering, but you will also learn about other R packages that support different phases of a data science workflow, such as tidyr, dplyr, and tidyverse. Along the way, you will gain insight into best practices for visualization of high-dimensional data, statistical graphics, and graphical perception. The printed book is complemented by an interactive website where readers can view movies demonstrating the examples and interact with graphics.

1. Why interactive data visualization? 2. The plotly for R ecosystem. 3. The plot_ly() toolbox. 4. Plotly extension packages.

Carson Sievert is the author and maintainer of the plotly R package, a recipient of the American Statistical Association’s 2017 John Chambers award, and Program Chair of the Section on Statistical Graphics. After receiving a PhD in statistics from Iowa State, Carson joined RStudio as a software engineer to work on software that bridges R and web technologies such as shiny, plotly, and rmarkdown.

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