r - 在 data.frame 中找到最高比例

Question

我有一个如下所示的数据框:

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 A        0.2        NA
2       1     Type B        0.8        NA
3       2     Type A        0.3        NA
4       2     Type B        0.7        NA
5       3     Type A        0.4        NA
6       3     Type B        0.6        NA
7       4     Type A        0.5        NA
8       4     Type B        0.5        NA
9       5     Type A        0.6        NA
10      5     Type B        0.4        NA

在1-5的每个扇区中，如果A型比例最高，那么我需要在'dominance'列中添加'A dominant'，或者如果B型比例最高，那么我需要添加'B显性”到“支配”列。如果有平局，我需要在“优势”列中添加“平局”。

这应该是输出数据框:

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 A        0.2 B dominant
2       1     Type B        0.8 B dominant
3       2     Type A        0.3 B dominant
4       2     Type B        0.7 B dominant
5       3     Type A        0.4 B dominant
6       3     Type B        0.6 B dominant
7       4     Type A        0.5        tie
8       4     Type B        0.5        tie
9       5     Type A        0.6 A dominant
10      5     Type B        0.4 A dominant

Answer 1

 library(data.table)
 DT <- data.table(x)

 DT[, dominance := {p.a <- proportion[subspecies =="Type A"]
                    p.b <- proportion[subspecies =="Type B"] 
                   if (p.a > p.b) "A dominant" else if (p.b > p.a) "B dominant" else "tie"}
                  , by=sector]


    sector subspecies proportion  dominance
 1:      1     Type A        0.2 B dominant
 2:      1     Type B        0.8 B dominant
 3:      2     Type A        0.3 B dominant
 4:      2     Type B        0.7 B dominant
 5:      3     Type A        0.4 B dominant
 6:      3     Type B        0.6 B dominant
 7:      4     Type A        0.5        tie
 8:      4     Type B        0.5        tie
 9:      5     Type A        0.6 A dominant
10:      5     Type B        0.4 A dominant