r - find highest proportion in data.frame -


i have dataframe looks this:

x <- data.frame(sector=rep(1:5, each=2),                 subspecies=rep(c("type a", "type b"), 5),                 proportion= c(.2, 1-.2, .3, 1-.3, .4,                                1-.4, .5, 1-.5, .6, 1-.6))  x$dominance <- na  x[,1] <- sort(x[,1])  x    sector subspecies proportion dominance 1       1     type        0.2        na 2       1     type b        0.8        na 3       2     type        0.3        na 4       2     type b        0.7        na 5       3     type        0.4        na 6       3     type b        0.6        na 7       4     type        0.5        na 8       4     type b        0.5        na 9       5     type        0.6        na 10      5     type b        0.4        na

in each sector 1-5, if type highest proportion, need add 'a dominant' 'dominance' column, or if type b highest proportion, need add 'b dominant' 'dominance' column. if there tie, need add 'tie' 'dominance' column.

this should output dataframe:

x$dominance <- c("b dominant", "b dominant", "b dominant", "b dominant", "b dominant",                   "b dominant", "tie", "tie", "a dominant", "a dominant") x    sector subspecies proportion  dominance 1       1     type        0.2 b dominant 2       1     type b        0.8 b dominant 3       2     type        0.3 b dominant 4       2     type b        0.7 b dominant 5       3     type        0.4 b dominant 6       3     type b        0.6 b dominant 7       4     type        0.5        tie 8       4     type b        0.5        tie 9       5     type        0.6 dominant 10      5     type b        0.4 dominant

here base r solution

compare <- function(x) {   ## return subspecies of max proportion   res <- x[which(x$proportion == max(x$proportion)), "subspecies"]   if(length(res) > 1l) { ## if tied length(res) == 2     out <- "tie"   } else { ## simple string replacement     out <- paste(sub("type ", "", res), "dominant")     ## or use     #out <- if(res == "type a") {"a dominant"} else {"b dominant")}   }   out }  x$dominance <- unsplit(lapply(split(x, x$sector), compare), x$sector)  > x    sector subspecies proportion  dominance 1       1     type        0.2 b dominant 2       1     type b        0.8 b dominant 3       2     type        0.3 b dominant 4       2     type b        0.7 b dominant 5       3     type        0.4 b dominant 6       3     type b        0.6 b dominant 7       4     type        0.5        tie 8       4     type b        0.5        tie 9       5     type        0.6 dominant 10      5     type b        0.4 dominant

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