优化 R 中的双循环

Question

I have this double loop working:

for (i in 1:nrow(doe)) {
  for (j in 1:nrow(rsm)) {
    if (rsm[j,2] == doe[i,2] & rsm[j,3] == doe[i,3] & rsm[j,4] == doe[i,4]) {
      out <- cbind(doe[i,6], rsm[j,6])
      matching_out <- rbind(matching_out, out)
      break
    }
  }
}

As you can see, I have to match three columns together in two dataset (# 2, 3, 4 in this case), and then cbind column 6 of the two data frame in another one.

The question is: since this is quite slow, how can I optimise it? I suppose I could use an apply -like approach, but I can't figure out.

Answer 1

您可以简单地使用基本R单线执行此操作：

merge(rsm, doe, by.x=names(rsm)[2:4],by.y=names(doe)[2:4])[-(1:3)]