# Five ways to visualize your pairwise comparisons

March 5, 2011
By

(This article was first published on Recology, and kindly contributed to R-bloggers)

In data analysis it is often nice to look at all pairwise combinations of continuous variables in scatterplots. Up until recently, I have used the function splom in the package lattice, but ggplot2 has superior aesthetics, I think anyway.

Here a few ways to accomplish the task:

```require(lattice)
require(ggplot2)
```

1) Using base graphics, function “pairs”

`pairs(iris[1:4], pch = 21)`

2) Using lattice package, function “splom”

`splom(~iris[1:4])`

3) Using package ggplot2, function “plotmatrix”

`plotmatrix(iris[1:4])`

4) a function called ggcorplot by Mike Lawrence at Dalhousie University

-get ggcorplot function at this link

```ggcorplot(
data = iris[1:4],
var_text_size = 5,
cor_text_limits = c(5,10))```

5) panel.cor function using pairs, similar to ggcorplot, but using base graphics. Not sure who wrote this function, but here is where I found it.

```panel.cor <- function(x, y, digits=2, prefix="", cex.cor)
{
usr <- par("usr"); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- abs(cor(x, y))
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep="")
if(missing(cex.cor)) cex <- 0.8/strwidth(txt)

test <- cor.test(x,y)
# borrowed from printCoefmat
Signif <- symnum(test\$p.value, corr = FALSE, na = FALSE,
cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1),
symbols = c("***", "**", "*", ".", " "))

text(0.5, 0.5, txt, cex = cex * r)
text(.8, .8, Signif, cex=cex, col=2)
}
```
`pairs(iris[1:4], lower.panel=panel.smooth, upper.panel=panel.cor)`

A comparison of run times…

```> system.time(pairs(iris[1:4]))
user  system elapsed
0.138   0.008   0.156
> system.time(splom(~iris[1:4]))
user  system elapsed
0.003   0.000   0.003
> system.time(plotmatrix(iris[1:4]))
user  system elapsed
0.052   0.000   0.052
> system.time(ggcorplot(
+ data = iris[1:4],
var_text_size = 5,
cor_text_limits = c(5,10)))

user  system elapsed
0.130   0.001   0.131
> system.time(pairs(iris[1:4], lower.panel=panel.smooth, upper.panel=panel.cor))
user  system elapsed
0.170   0.011   0.200```

…shows that splom is the fastest method, with the method using the panel.cor function pulling up the rear.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

Tags: , , ,