As mentioned in this comment, the standard suggestions for re-ordering columns in a data.frame are generally cumbersome and error-prone, especially if you have a lot of columns.
This function allows to re-arrange columns by position: specify a variable name and the desired position, and don't worry about the other columns.
##arrange df vars by position
##'vars' must be a named vector, e.g. c("var.name"=1)
arrange.vars <- function(data, vars){
##stop if not a data.frame (but should work for matrices as well)
stopifnot(is.data.frame(data))
##sort out inputs
data.nms <- names(data)
var.nr <- length(data.nms)
var.nms <- names(vars)
var.pos <- vars
##sanity checks
stopifnot( !any(duplicated(var.nms)),
!any(duplicated(var.pos)) )
stopifnot( is.character(var.nms),
is.numeric(var.pos) )
stopifnot( all(var.nms %in% data.nms) )
stopifnot( all(var.pos > 0),
all(var.pos <= var.nr) )
##prepare output
out.vec <- character(var.nr)
out.vec[var.pos] <- var.nms
out.vec[-var.pos] <- data.nms[ !(data.nms %in% var.nms) ]
stopifnot( length(out.vec)==var.nr )
##re-arrange vars by position
data <- data[ , out.vec]
return(data)
}
Now the OP's request becomes as simple as this:
table <- data.frame(Time=c(1,2), In=c(2,3), Out=c(3,4), Files=c(4,5))
table
## Time In Out Files
##1 1 2 3 4
##2 2 3 4 5
arrange.vars(table, c("Out"=2))
## Time Out In Files
##1 1 3 2 4
##2 2 4 3 5
To additionally swap Time and Files columns you can do this:
arrange.vars(table, c("Out"=2, "Files"=1, "Time"=4))
## Files Out In Time
##1 4 3 2 1
##2 5 4 3 2