Test

Easy: Install the GGally package from github (you might have to install the devtools package first). Run one of the examples, put the chart in a knitr/Rmarkdown document and write a paragraph to explain the chart.

GGally::ggpairs

From the example of ggpairs:

library(GGally)

## [1] TRUE

data(tips, package = "reshape")
pm <- ggpairs(tips[, 1:3])
pm

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

The plot above is a generalized pairs plot that shows the pairwise relationship between all combinations of the variables: total_bill, tip, and sex. total_bill and tip are continuous variables and display an average correlation. Their univariate densities are displayed in the first two diagonals. sex is a discrete variable. In the bottom right corner, the bar chart of sex shows that there almost twice as many males as there are females. There also appears to be a slightly higher total_bill and tip for males in the box-plots, but it can not easily be seen in the faceted-histograms in the bottom row.