df <- data.frame(group=rep(LETTERS, each=2), value=1:52)
res <- unlist(lapply(unique(df$group), function(x) mean(subset(df, group==x)$value)))
names(res) <- unique(df$group)

A    B    C    D    E    F    G    H    I    J    K    L    M    N    O    P
 1.5  3.5  5.5  7.5  9.5 11.5 13.5 15.5 17.5 19.5 21.5 23.5 25.5 27.5 29.5 31.5
   Q    R    S    T    U    V    W    X    Y    Z
33.5 35.5 37.5 39.5 41.5 43.5 45.5 47.5 49.5 51.5

unique(c("B","B","A","C","C","C","B","A"))

[1] "B" "A" "C"

x[!duplicated(x)]

k = 0;
switch (TYPEOF(x)) {
case LGLSXP:
case INTSXP:
for (i = 0; i < n; i++)
    if (LOGICAL(dup)[i] == 0)
    INTEGER(ans)[k++] = INTEGER(x)[i];
break;

df <- data.frame(group=rep(LETTERS, each=2), value=1:52)
a1 <- aggregate(df$value,list(df$group),mean)

setNames(a1[,2],a1[,1])

library(plyr)
unlist(daply(df,"group",summarise,val=mean(value)))

example <- raster(xmn = 0, xmx = 100, ymn = 0, ymx = 100, nrow = 100, ncol = 100)
example[] <- sample(x <- 1:100, 10000, replace = TRUE)

plot(example)

vals <- values(example)[x]
identical(vals, x)

uniques <- unique(example)
identical(uniques, x)