Calculation in a loop in R - r

Question

Consider the following data:
library(Benchmarking)
x <- c(2, 3, 8)
y <- c(1, 5, 10)
k <- 25
d <- data.frame(x,y,k)
x <- c(5, 2, 3, 4)
y <- c(3, 5, 9, 10)
k <- 30
d2 <- data.frame(x,y,k)
d3 <- replicate(3, rbind(d, d2[sample(seq_len(nrow(d2)), 3), , drop=FALSE]), simplify = FALSE)
So now I have a list of 3 data.frame. For each of these 3 data.frame I want to perform the following calculation:
e1 <- with(subset(d3[[1]], k == 25), dea(d3[[1]]$x, d3[[1]]$y, XREF = x, YREF = y))
e2 <- with(subset(d3[[1]], k == 30), dea(d3[[1]]$x, d3[[1]]$y, XREF = x, YREF = y))
we1 <- weighted.mean(eff(e1), d3[[1]]$y)
we2 <- weighted.mean(eff(e2), d3[[1]]$y)
va <- we2/we1
But instead of using that code three times, where I change [[1]] to [[2]] and [[3]], can I instead use a loop, where it does the calculation for all 3 data.frame and create a new data.frame where it list va for the three calculations?

Answer 1

We create a function and then loop through the list and apply the function
f1 <- function(dat) {
d1 <- subset(dat, k == 25)
e1 <- with(d1, dea(dat$x, dat$y, XREF = x, YREF = y))
d2 <- subset(dat, k == 30)
e2 <- with(d2, dea(dat$x, dat$y, XREF = x, YREF = y))
we1 <- weighted.mean(eff(e1), dat$y)
we2 <- weighted.mean(eff(e2), dat$y)
we2/we1
}
sapply(d3, f1)