R: Comparing values in vector to column in data frame - r

Question

Apologies if this has been asked before, but I've searched for a while and can't find anything to answer my question. I'm somewhat comfortable using R but never really learned the fundamentals. Here's what I'm trying to do.
I've got a vector (call it "responseTimes") that looks something like this:
150 50 250 200 100 150 250
(It's actually much longer, but I'm truncating it here.)
I've also got a data frame where one column, timeBin, is essentially counting up by 50 from 0 (so 0 50 100 150 200 250 etc).
What I'm trying to do is to count how many values in responseTimes are less than or equal to each row in the data frame. I want to store these counts in a new column of my data frame. My output should look something like this:
timeBin counts
0 0
50 1
100 2
150 4
200 5
250 7
I know I can use the sum function to compare vector elements to some constant (e.g., sum(responseTimes>100) would give me 5 for the data I've shown here) but I don't know how to do this to compare to a changing value (that is, to compare to each row in the timeBin column).
I'd prefer not to use a loop, as I'm told those can be particularly slow in R and I have quite a large data set that I'm working with. Any suggestions would be much appreciated! Thanks in advance.

Answer 1

You can use sapply this way:
> timeBin <- seq(0, 250, by=50)
> responseTimes <- c(150, 50, 250, 200, 100, 150, 250 )
>
> # using sapply (after all `sapply` is a loop)
> ans <- sapply(timeBin, function(x) sum(responseTimes<=x))
> data.frame(timeBin, counts=ans) # your desired output.
timeBin counts
1 0 0
2 50 1
3 100 2
4 150 4
5 200 5
6 250 7

Answer 2

That might help:
responseTimes <- c(150, 50, 250, 200, 100, 150, 250)
bins1 <- seq(0, 250, by = 50)
sahil1 <- function(input = responseTimes, binsx = bins1) {
tablem <- table(cut(input, binsx)) # count of input across bins
tablem <- cumsum(tablem) # cumulative sums
return(as.data.frame(tablem)) # table to data frame
}