Visualize Data with R

Learning Objectives

After completing this section, an individual will be able to visualize data with annotated plots.

• understand key components of the grammar of graphics
• visualize data with the ggplot2 package
• develop interactive graphics (plotly, ggvis)
• examine related packages (cowplot, GGally, grid viewports)
• create heatmaps (pheatmap)
• network observations in connected graphs
• use shiny to share results on the web

Contents

• ggplot2 and related stuff
• shiny apps
• Visualize Links
• Graphics Links
• Network Observatins in Connected Graphs
• Additional Pages
  • R4DS Book
    • Data Visualization
    • Graphics for Communication

References

• Lattice Book Figures with R Code (Deepayan Sarkar)
  • Lattice Demo (John Gillett) with R Code
  • Lattice Graphics (inside-R)
  • Lattice Graphics (Weka Learn Studios)
• ggplot2 Plotting System for R
  • Grammar of Graphics (Weka Learn Studios)
  • ggplot2 and the grammar of graphics (Revolution Analytics)
  • Graphics with ggplot2 (r4stats.com)
  • History of ggplot2 (Wikipedia)
  • Vince Vu’s Dynamic FPS Presentation: Each frame of Vince’s talk animations corresponds to a different estimate along the solution path of the FPS estimator, plotted as biplots using ggbiplot. Each frame was saved as a PNG file, and the sequence converted using ffmpeg into a movie file as described in the WikiBooks ffmpeg Guide. [FPS package to be posted on Vince Vu’s Software Page when completed.]
• R Graph Gallery on Facebook
• Revolution Analytics Graph Gallery
• R Graphics Gallery (Alastair Sanderson)
• William S Cleveland’s Visualizing Data Book
• A Comprehensive Guide to the Grammar of Graphics for Effective Visualization of Multi-dimensional Data by Depanjan Sarkar

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Table of contents

• Network Observatins in Connected Graphs
• Visualization & Graphics Links