I want to split data in R by varying block sizes but each observation is unique -

i have managed read in data file, , subset out 2 columns of info want work with. stuck because need split data chunks of varying sizes , apply function (mean, sd) them, save chunks , plot sd each. otherwise known block averaging. right have data frame 2 columns , 10005 rows. head of looks this:

frame    ca     1 0.773 

is there efficient way subset pieces of data a:b can dictate how data broken "frame" column? have found answers on here not sure mean or if work.

chunk <- function(x, n)  (mapply(function(a, b) (x[a:b]), seq.int(from=1, to=length(x), by=n),        pmin(seq.int(from=1, to=length(x), by=n)+(n-1),            length(x)), simplify=false)) 

i'm not sure if you're looking closure, data frame can subsetted arbitrary indices.

(if frame can subsetted a:b, sequence , subset may made row index?)

df <- data.frame(group = sample(c("a", "b"), 20, replace = t),                  val = rnorm(20))  # closure - returns function accepts , subsetter <- function(from, to) {     function(x) {         x[from:to, ]     } }  # , specified sub1 <- subsetter(2, 4) sub2 <- subsetter(1, 5)  # data split to sub1(df) #group        val #2      0.5518802 #3     b  1.5955093 #4     -0.8132578  sub2(df) #  group        val #1     b  0.4780080 #2      0.5518802 #3     b  1.5955093 #4     -0.8132578 #5     b  0.4449554