As part of their talk they had a little competition in visualising London Underground performance data, see their slides. Both made heavy use of the respective panelling / faceting capabilities. Additionally Rich used the
panel.groups argument of xyplot to fine control the content of each panel. Brilliant! I had never used this argument before. So, here is a silly example with the iris data set to remind myself of panel.groups in the future.
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| library(lattice) | |
| my.settings <- list( | |
| superpose.symbol=list(pch=19), | |
| plot.line=list(col="black"), | |
| plot.polygon=list(col=adjustcolor(col="steelblue", | |
| alpha.f=0.5), | |
| border="white") | |
| ) | |
| xyplot(Sepal.Length ~ Sepal.Width, groups=Species, data=iris, | |
| main="Lattice example with panel.groups", | |
| par.settings = my.settings, | |
| panel=panel.superpose, | |
| panel.groups=function(x,y, group.number,...){ | |
| specie <- levels(iris$Species)[group.number] | |
| if(specie %in% "setosa"){ | |
| panel.xyplot(x,y,...) | |
| panel.abline(lm(y~x)) | |
| } | |
| if(specie %in% "versicolor"){ | |
| panel.barchart(x, y) | |
| } | |
| if(specie %in% "virginica"){ | |
| panel.rug(x, y) | |
| } | |
| } | |
| ) |
