## -----------------------------------------------------------------------------
m <- matrix(1:15, nrow=5, ncol=3)
m


## -----------------------------------------------------------------------------
# sum values in each row
apply(m, 1, sum)

# get mean for each column
apply(m, 2, mean)


## -----------------------------------------------------------------------------
rowSums(m)


## -----------------------------------------------------------------------------
colnames(m) <- c('v1', 'v2', 'v3')
d <- data.frame(name=c('Yi', 'Yi', 'Yi', 'Er', 'Er'), m, stringsAsFactors=FALSE)
d$v2[1] <- NA
d


## -----------------------------------------------------------------------------
tapply(d$v1, d$name, mean)
tapply(d$v1, d$name, max)
tapply(d$v2, d$name, mean)
tapply(d$v2, d$name, mean, na.rm=TRUE)


## -----------------------------------------------------------------------------
aggregate(d[, c("v1", "v2", "v3")], d$name, mean, na.rm=TRUE)


## -----------------------------------------------------------------------------
aggregate(d[, c("v1", "v2", "v3")], d[, "name", drop=FALSE], mean, na.rm=TRUE)
# or 
aggregate(d[, c("v1", "v2", "v3")], list(d$name), mean, na.rm=TRUE)


## -----------------------------------------------------------------------------
names <- list("Antoinette", "Mary", "Duncan", "Obalaya", "Jojo")
nchar("Jim")

lapply(names, nchar)
sapply(names, nchar)


## -----------------------------------------------------------------------------
shortname <- function(name) {
	if (nchar(name) < 5) {
		name <- toupper(name)
		return(name)
	} else {
		name <- substr(name,1,5)
		return(name)
	}
}

sapply(names, shortname)