library(cluster)
library(fpc)
data1 = read.table(file='data.csv', sep=',', header=T)
group <- data1$group
data1$group <- NULL
wdata <- na.omit(data1) 
wdata <- scale(wdata)
fit <- hclust(dist(wdata), method='ward')
plot(fit, labels=FALSE)

par(ask=TRUE)
choose.clust <- function(){readline("What clustering solution would you like to use? ")} 
clust.level <- as.integer(choose.clust())

groups <- cutree(fit, clust.level)
rect.hclust(fit, clust.level, border='red')

clust.out <- as.matrix(groups)
colnames(clust.out) <- c("cluster")
wclust <- as.matrix(cbind(clust.out, data1))
write.table(wclust, file="ward_out.csv", sep=",")
print('Applying cluster level and appending files')

par(ask=TRUE)
print('Creating bar chart of clusters by Group')
b.plot <- table(clust.out, group)
b.plot.mat <- as.matrix(b.plot)
b.plot.per <- prop.table(b.plot.mat, margin=2)*100
barplot(b.plot.per, main="Clusters by Group", ylim=c(0,100), ylab="Percent", beside=TRUE, cex.names=0.5, col=rainbow(clust.level))

print('Sending all output to PDF file')
pdf(file="ward_output.pdf")
plot(fit, labels=FALSE)
rect.hclust(fit, clust.level, border='red')
barplot(b.plot.per, main="Clusters by Group", ylim=c(0,100), ylab="Percent", beside=TRUE, cex.names=0.5, col=rainbow(clust.level))
dev.off()