How to remove rows based on the column values

Question

I have a large data.frame, example:

> m <- matrix(c(3,6,2,5,3,3,2,5,4,3,5,3,6,3,6,7,5,8,2,5,5,4,9,2,2), nrow=5, ncol=5)
> colnames(m) <- c("A", "B", "C", "D", "E")
> rownames(m) <- c("a", "b", "c", "d", "e")
> m
  A B C D E
a 3 3 5 7 5
b 6 2 3 5 4
c 2 5 6 8 9
d 5 4 3 2 2
e 3 3 6 5 2

I would like to remove all rows, where A and/or B columns have greater value than C D and E columns. So in this case rows b, d, e should be removed and I should get this:

  A B C D E
a 3 3 5 7 5
c 2 5 6 8 9

Can not remove them one by one because the data.frame has more than a million rows. Thanks

Answer 1

Use subsetting, together with pmin() and pmax() to retain the values that you want. I'm not sure that I fully understand your criteria (you said "C D and E" but since you want to throw away row e, I think that you meant C, D or E ), but the following seems to do what you want:

> m[pmax(m[,"A"],m[,"B"])<=pmin(m[,"C"],m[,"D"],m[,"E"]),]
  A B C D E
a 3 3 5 7 5
c 2 5 6 8 9