- produce handsome, publication-quality plots with automatic legends created from the plot specification
- superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales
- add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression
- save any ggplot2 plot (or part thereof) for later modification or reuse
- create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots
- approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot
This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.
About the author
Carson Sievert is a PhD student in the Department of Statistics at Iowa State University. His work includes R packages for acquiring data from the Web (pitchRx, bbscrapeR, XML2R), designing interactive Web graphics (animint, plotly), and visualizations for exploring statistical models (LDAvis).