Multiple lattice plots

Lattice is a package for R that makes Trellis graphics (originally developed for S by William S. Cleveland and colleagues at Bell Labs). Quick-R has an overview and examples of the different lattice plotting functions.  One quirk of the software is that lattice wants all data presented in the same format.  Quick-R: “~x|A means display numeric variable x for each level of factor A. y~x | A*B means display the relationship between numeric variables y and x separately for every combination of factor A and B levels.”

Lattice makes good looking plots, but you can’t use standard graphics parameters like mfrow=c(x,y) to show multiple plots at once. My lab mate Owen showed me a trick to get lattice to draw multiple plots for a number of numeric variables using melt() from the reshape package.  melt() expands a data frame into variable/value columns for one or more id columns.  Here’s an example of a data frame d, with 10 rows of numerical variables a,b,c and a condition factor equal to 1 or 2.

library(lattice)

library(reshape)

d <- data.frame(a=rnorm(10), b=rnorm(10), c=rnorm(10), cond=factor(sample(1:2,10,replace=TRUE)))

stripplot(value~cond|variable,melt(d, id=”cond”),scales=list(relation=”free”))

Setting the scales parameter allows the panels to have different scales for their axes; setting the parameter as.table=TRUE would have plotted from top left to bottom right.

You can also get the same plots as above using featurePlot in the caret package: featurePlot(x, y).

To get density plots of the predictor variables a,b,c:

densityplot(~value|variable,melt(d),scales=list(relation=”free”))