Figure: another plyr example quantiles (0.05, 0.25, 0.5, 0.75, 0.95) of DSC by temperature bin
There are plenty of good examples on how to use functions from the plyr package. Here is one more, demonstrating how to use ddply with a custom function. Note that there are two places where the example function may blow up if you pass in poorly formatted or strange data: calls to 1) t.test() and 2) quantile(). Also note the use of the transpose function, t(), for converting column-wise data into row-wise data-- suitable for inclusion into a dataframe containing a single row.
Example Code
#librarieslibrary(plyr)library(lattice)# simulate DSC data from several filesr <- data.frame(temp=rep(1:100, times=2), dsc=rnorm(200))r$file <- factor(rep(c('file 1','file 2'), each=100))# bin temperature in 5 degree slicesgroups <- seq(0, 100, by=5)r$group <- cut(r$temp, groups)# custom summary function# updated to work with arbitrary column namesf <- function(i, column){# conf interval# careful with this t.test -- may blow up with some datasetsi.conf <- data.frame(t(t.test(i[, column], conf.level=0.95, na.action='na.omit')$conf.int))names(i.conf) <- c('lower', 'upper')# quantilesp <- c(0.05, 0.25, 0.5, 0.75, 0.95)i.quant <- data.frame(t(quantile(i[, column], probs=p, na.rm=TRUE)))names(i.quant) <- paste('q', round(p * 100), sep='_')# make a dataframed <- data.frame(mean=mean(i[, column], na.rm=TRUE),min=min(i[, column], na.rm=TRUE),max=max(i[, column], na.rm=TRUE),sd=sd(i[, column], na.rm=TRUE),i.quant,i.conf)# give back to callerreturn(d)}# apply our function by groupsr.agg <- ddply(r, .(group), .fun=f, column='dsc')# visualization of some of the resultsxyplot(q_50 + q_5 + q_95 ~ group, data=r.agg, type='l', lty=c(1,2,2), col=1)xyplot(q_5 + q_25 + q_50 + q_75 + q_95 ~ group, data=r.agg, type='l', lty=c(3,2,1,2,3), lwd=c(1,1,2,1,1), col=1)xyplot(mean + lower + upper ~ group, data=r.agg, type='l', lty=c(1,2,2), col=1)xyplot(mean + lower + upper ~ group, data=r.agg, type='p', cex=c(1,2,2), pch=c('o','-','-'), col=1)
