查找R中DF中每行的最大值和第二最大值

假设我有一个包含ID、性别和几个数字变量的df。见下文

    set.seed(123)
    ID <- c(1,2,3,4,5,6,7,8,9,10)
    gender <- c("m", "m", "m", "f", "f", "m", "m", "f", "f", "m")
    x1 <- rnorm(10, 0, 1)
    x2 <- rnorm(10, 0, 1)
    x3 <- rnorm(10, 0, 1)
    x4 <- rnorm(10, 0, 1)
    x5 <- rnorm(10, 0, 1)
    df <- data.frame(ID, gender, x1, x2, x3, x4, x5)

set.seed（123）
ID这里有一个简单的解决方案：

maxes <- t(sapply(1:nrow(df), function(i) {
    names(sort(df[i,3:7], decreasing=T)[1:2])
}))
colnames(maxes) <- c("MAX1","MAX2")
df <- cbind(df, maxes)

   ID gender          x1         x2         x3          x4          x5
1   1      m -0.56047565  1.2240818 -1.0678237  0.42646422 -0.69470698
2   2      m -0.23017749  0.3598138 -0.2179749 -0.29507148 -0.20791728
3   3      m  1.55870831  0.4007715 -1.0260044  0.89512566 -1.26539635
4   4      f  0.07050839  0.1106827 -0.7288912  0.87813349  2.16895597
5   5      f  0.12928774 -0.5558411 -0.6250393  0.82158108  1.20796200
6   6      m  1.71506499  1.7869131 -1.6866933  0.68864025 -1.12310858
7   7      m  0.46091621  0.4978505  0.8377870  0.55391765 -0.40288484
8   8      f -1.26506123 -1.9666172  0.1533731 -0.06191171 -0.46665535
9   9      f -0.68685285  0.7013559 -1.1381369 -0.30596266  0.77996512
10 10      m -0.44566197 -0.4727914  1.2538149 -0.38047100 -0.08336907
        MAX1        MAX2 MAX1 MAX2
1   1.224082   0.4264642   x2   x4
2  0.3598138  -0.2079173   x2   x5
3   1.558708   0.8951257   x1   x4
4   2.168956   0.8781335   x5   x4
5   1.207962   0.8215811   x5   x4
6   1.786913    1.715065   x2   x1
7   0.837787   0.5539177   x3   x4
8  0.1533731 -0.06191171   x3   x4
9  0.7799651   0.7013559   x5   x2
10  1.253815 -0.08336907   x3   x5

最大值非常接近