Ranking and Counting Matrix Elements in R

Question

I know there are similar questions but I couldn't find an answer to my question. I'm trying to rank elements in a matrix and then extract data of 5 highest elements.

Here is my attempt.

set.seed(20)
d<-matrix(rnorm(100),nrow=10,ncol=10)
start<-d[1,1]
for (i in 1:10) {
for (j in 1:10) {
  if (start < d[i,j])
  {high<-d[i,j]
  rowind<-i
  colind<-j
  }
  }
}

Although this gives me the data of the highest element, including row and column numbers, I can't think of a way to do the same for elements ranked from 2 to 5. I also tried

  rank(d, ties.method="max")

But it wasn't helpful because it just spits out the rank in vector format. What I ultimately want is a data frame (or any sort of table) that contains rank, column name, row name, and the data(number) of highest 5 elements in matrix.

Edit

set.seed(20)
d<-matrix(rnorm(100),nrow=10,ncol=10)
d[1,2]<-5
d[2,1]<-5 
d[1,3]<-4
d[3,1]<-4

Thanks for the answers. Those perfectly worked for my purpose, but as I'm running this code for correlation chart -where there will be duplicate numbers for every pair- I want to count only one of the two numbers for ranking purpose. Is there any way to do this? Thanks.

Answer 1

Here's a very crude way:

DF = data.frame(row = c(row(d)), col = c(col(d)), v = c(d))
DF[order(DF$v, decreasing=TRUE), ][1:5, ]

   row col        v
91   1  10 2.208443
82   2   9 1.921899
3    3   1 1.785465
32   2   4 1.590146
33   3   4 1.556143

It would be nice to only have to partially sort, but in ?order, it looks like this option is only available for sort, not for order.

---

If the matrix has row and col names, it might be convenient to see them instead of numbers. Here's what I might do:

dimnames(d) <- list(letters[1:10], letters[1:10])
DF = data.frame(as.table(d))

DF[order(DF$Freq, decreasing=TRUE), ][1:5, ]

   Var1 Var2     Freq
91    a    j 2.208443
82    b    i 1.921899
3     c    a 1.785465
32    b    d 1.590146
33    c    d 1.556143

The column names don't make much sense here, unfortunately, but you can change them with names(DF) <- as usual.

Answer 2

Here is one option with Matrix

library(Matrix)
m1 <- summary(Matrix(d, sparse=TRUE))
head(m1[order(-m1[,3]),],5)
#   i  j        x
#93 3 10 2.359634
#31 1  4 2.234804
#23 3  3 1.980956
#55 5  6 1.801341
#16 6  2 1.678989

---

Or use melt

library(reshape2)
m2 <- melt(d)
head(m2[order(-m2[,3]), ], 5)

Answer 3

Here is something quite simple in base R.

# set.seed(20)
# d <- matrix(rnorm(100), nrow = 10, ncol = 10)

d.rank <- matrix(rank(-d), nrow = 10, ncol = 10)

which(d.rank <= 5, arr.ind=TRUE)
     row col
[1,]   3   1
[2,]   2   4
[3,]   3   4
[4,]   2   9
[5,]   1  10

d[d.rank <= 5]
[1] 1.785465 1.590146 1.556143 1.921899 2.208443

Results can (easily) be made clearer (see comment from Frank):

cbind(which(d.rank <= 5, arr.ind=TRUE), v = d[d.rank <= 5], rank = rank(-d[d.rank <= 5]))

     row col        v rank
[1,]   3   1 1.785465    3
[2,]   2   4 1.590146    4
[3,]   3   4 1.556143    5
[4,]   2   9 1.921899    2
[5,]   1  10 2.208443    1