R 计算列的值之间的差值

我认为聚合函数应该可以工作，但我不知道如何定义组合并将它们传递给函数参数。

如果您愿意使用dplyr这样的函数应该可以工作

s  diff  c2  c3
1  w-x   m   -1
1  w-y   m   -2
1  w-z   m   -3
1  x-y   m   -1
etc

datc1.y）%>%
转换（s，diff=粘贴（c1.y，c1.x，sep=“-”），c2，c3=c3.y-c3.x）
dat2
##s diff c2 c3
##11w-xm-1
##2 1 w-y m-2
##3.1 x-y m-1
##4 1 w-z m-3
##51x-zm-2
##6y-zm-1
##7 2 w-x f-1
##8 2 w-y f-2
##9.2 x-y f-1
##10 2 w-z f-3
##11.2 x-z f-2
##12 2 y-z f-1
##13 3宽x米-1
##14 3 w-y m-2
##15.3 x-y m-1
##16 3 w-z m-3
##173x-zm-2
##18.3 y-z m-1
s
和
c2
的意义是什么？您是否真的对
s&c1&c2
与其他
s&c1&c2
s的区别感兴趣？
s  diff  c2  c3
1  w-x   m   -1
1  w-y   m   -2
1  w-z   m   -3
1  x-y   m   -1
etc

dat <- data.frame(s=c(1,1,1,1,2,2,2,2,3,3,3,3), c1=c("w","x","y","z","w","x","y","z","w","x","y","z"), c2=c("m","m","m","m","f","f","f","f","m","m","m","m"), c3=c(1,2,3,4,5,6,7,8,9,10,11,12))

library(dplyr)
dat$c1 <- as.character(dat$c1)
dat2 <- dat %>%
  left_join(dat, by = c("s", "c2")) %>%
  filter(c1.x > c1.y) %>%
  transmute(s, diff = paste(c1.y, c1.x, sep = "-"), c2, c3 = c3.y - c3.x)

dat2

##    s diff c2 c3
## 1  1  w-x  m -1
## 2  1  w-y  m -2
## 3  1  x-y  m -1
## 4  1  w-z  m -3
## 5  1  x-z  m -2
## 6  1  y-z  m -1
## 7  2  w-x  f -1
## 8  2  w-y  f -2
## 9  2  x-y  f -1
## 10 2  w-z  f -3
## 11 2  x-z  f -2
## 12 2  y-z  f -1
## 13 3  w-x  m -1
## 14 3  w-y  m -2
## 15 3  x-y  m -1
## 16 3  w-z  m -3
## 17 3  x-z  m -2
## 18 3  y-z  m -1

do.call(rbind, lapply(split(dat, dat$s), function(a){
    a$c1 = as.character(a$c1)
    d = setNames(data.frame(t(combn(unique(a$c1), 2, FUN = function(x){
        list(x[1], x[2], a$c3[a$c1 == x[1]] - a$c3[a$c1 == x[2]])
    }))), c("col1", "col2", "val"))
    d$s = a$s[1]
    d$c2 = a$c2[1]
    d
}))
#    col1 col2 val s c2
#1.1    w    x  -1 1  m
#1.2    w    y  -2 1  m
#1.3    w    z  -3 1  m
#1.4    x    y  -1 1  m
#1.5    x    z  -2 1  m
#1.6    y    z  -1 1  m
#2.1    w    x  -1 2  f
#2.2    w    y  -2 2  f
#2.3    w    z  -3 2  f
#2.4    x    y  -1 2  f
#2.5    x    z  -2 2  f
#2.6    y    z  -1 2  f
#3.1    w    x  -1 3  m
#3.2    w    y  -2 3  m
#3.3    w    z  -3 3  m
#3.4    x    y  -1 3  m
#3.5    x    z  -2 3  m
#3.6    y    z  -1 3  m