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- library(lattice)
- ## load data
- connection <- url("http://bengarland.com/r/sample_data.txt")
- data <- read.table(connection, header = TRUE)
- ## process data
- data.pruned <- subset(data, select = c(-Rep, -Factor1, -SubFactor))
- data.by <- with(data, list(Factor1=Factor1, SubFactor=SubFactor))
- data.mean <- aggregate(data.pruned, data.by, mean)
- stack.SubFactor <- function(subfactor) {
- stacked <- stack(subset(data.mean.bob, SubFactor == subfactor))
- cbind(stacked, SubFactor = subfactor)
- }
- data.mean.bob <- subset(data.mean, Factor1 == "BOB")
- data.mean.bob.stacked <- do.call(rbind, lapply(levels(data.mean.bob$SubFactor),
- stack.SubFactor))
- data$Time <- c(0, 30, 40, 50)[data$Rep]
- data.bob.p <- subset(data, Factor1 == "BOB" & SubFactor == "P")
- ## graph 1
- barchart(Measurement1 ~ SubFactor | Factor1, data.mean,
- main = "Mean of Measurement1")
- ## graph 2
- xyplot(values ~ ind, data.mean.bob.stacked, group = SubFactor, type = "b")
- ## graph 3
- barchart(Measurement1 + Measurement2 + Measurement3 + Measurement4
- + Measurement5 ~ SubFactor | Factor1, data.mean,
- auto.key = TRUE)
- ## graph 4
- # assuming that rep A is T1, rep B is T2, etc.
- xyplot(Measurement1 + Measurement2 + Measurement3 + Measurement4
- + Measurement5 ~ Time, data.bob.p, type = "b", auto.key = TRUE)
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