**SAS and R**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Pairs plots (section 5.1.17) are a useful way of displaying the pairwise relations between variables in a dataset. But the default display is unsatisfactory when the variables aren’t all continuous. In this entry, we discuss ways to improve these displays that have been proposed by John Emerson, Walton Green, Barret Schloerke, Dianne Cook, Heike Hofmann, and Hadley Wickham in a manuscript under review entitled *The Generalized Pairs Plot*. http://www.blogger.com/img/blank.gif

Implementations of the methods in the paper are available in the `gpairs` and `GGally` packages; here we use the latter, which is based on the grammar of graphics and the ggplot2 package. This is an R-only entry: we are unaware of efforts to replicate this approach in SAS.

New users may find it easier to break process down into steps, rather than to do everything at once, as the R language allows. One way to do that is to make a smaller version of a dataset, with just the analysis variables included. here we use the HELP data set and choose two categorical variables (gender and housing status) and two continuous ones (the number of drinks per day and a measure of depressive symptoms). Once this new subset is created, the call to `ggpairs()` is straightforward.

**R**

library(GGally)

ds = read.csv("http://www.math.smith.edu/r/data/help.csv")

ds$sex = as.factor(ifelse(ds$female==1, "female", "male"))

ds$housing = as.factor(ifelse(ds$homeless==1, "homeless", "housed"))

smallds = subset(ds, select=c("housing", "sex", "i1", "cesd"))

ggpairs(smallds, diag=list(continuous="density", discrete="bar"), axisLabels="show")

For users more comfortable with R, the `ggpairs` function allows you to select variables to include, via its `columns` option. The following line produces a plot identical to the above, without the `subset()`.

ggpairs(ds, columns=c("housing", "sex", "i1", "cesd"),

diag=list(continuous="density", discrete="bar"), axisLabels="show")

Various options are available for the diagonal elements of the plot matrix, and the off-diagonals can be controlled with `upper` and `lower` options. The `examples(ggpairs)` command is very helpful for visualizing some of the possibilities.

**leave a comment**for the author, please follow the link and comment on their blog:

**SAS and R**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.