O'Reilly logo

R Data Analysis Cookbook by Shanthi Viswanathan, Viswa Viswanathan

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Generating standard plots such as histograms, boxplots, and scatterplots

Before even embarking on any numerical analyses, you may want to get a good idea about the data through a few quick plots. Although the base R system supports powerful graphics, we will generally turn to other plotting options like lattice and ggplot for more advanced plots. Therefore, we cover only the simplest forms of basic graphs.

Getting ready

If you have not already done so, download the data files for this chapter and ensure that they are available in your R environment's working directory and run the following commands:

> auto <- read.csv("auto-mpg.csv") > > auto$cylinders <- factor(auto$cylinders, levels = c(3,4,5,6,8), labels = c("3cyl", "4cyl", "5cyl", "6cyl", "8cyl")) ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required