Question

I am trying to write some code which identifies the greatest two values for each row and provides their column number and value.

df = data.frame( car = c (2,1,1,1,0), bus = c (0,2,0,1,0),
                 walk = c (0,3,2,0,0), bike = c(0,4,0,0,1))

I’ve managed to get it to do this for the maximum value using the max and max.col functions.

df$max = max.col(df,ties.method="first")
df$val = apply(df[ ,1:4], 1, max)

As far as I know there are no equivalent functions for the second highest value so doing this has made things a little trickier. Using this code provides the second highest value but (importantly) not in situations with ties. Also it looks risky.

sec.fun <- function (x) {
  max( x[x!=max(x)] )
}

df$val2 <- apply(df[ ,1:4], 1, sec.fun)

Ideally the solution would not involve removing any original data and could be used to find the third, fourth… highest value but neither of these are essential requirements.

Answer 1

try this:

# a function that returns the position of n-th largest
maxn <- function(n) function(x) order(x, decreasing = TRUE)[n]

this is a closure, so you can use like this:

> # position of the largest
> apply(df, 1, maxn(1))
[1] 1 4 3 1 4
> # position of the 2nd largest
> apply(df, 1, maxn(2))
[1] 2 3 1 2 1
> 
> # value of the largest
> apply(df, 1, function(x)x[maxn(1)(x)])
[1] 2 4 2 1 1
> # value of the 2nd largest
> apply(df, 1, function(x)x[maxn(2)(x)])
[1] 0 3 1 1 0

Updated

Why using closure here?

One reason is that you can define a function such as:

max2 <- maxn(2)
max3 <- maxn(3)

then, use it

> apply(df, 1, max2)
[1] 2 3 1 2 1
> apply(df, 1, max3)
[1] 3 2 2 3 2

I’m not sure if the advantage is obvious, but I like this way, since this is more functional-ish way.