r - Finding cooccurences between two variables within a group

Question

I am hoping to efficiently compute a co-occurence matrix by finding the co-occurences between two different variables within a group, ideally without using a complex loop that iterates through all possible combinations.

Given that my dataframe looks as follows:

df = data.frame(group = c(1,1,1,2,2,2),var1 = c(1,2,4,2,2,4),var2 = c(4,1,2,1,3,2))

> df
  group var1 var2
1     1    1    4
2     1    2    1
3     1    4    2
4     2    2    1
5     2    2    3
6     2    4    2

I am hoping to turn this into a new co-occurence matrix, where the rows represent var1 and columns var2.

EDIT: For those unfamiliar with co-occurences, I am interested in pairs of values that occur simultaneously in a group. For example, the combination of "2" and "1" happens once in group 1, and other time in group 2, thus implying 2 co-occurences. In my example, I put the combination next two each other, but they could occur anywhere within the group.

It should look like the following:

> cooc
  1 2 3 4
1 0 2 0 1
2 2 0 1 2
3 0 1 0 0
4 1 2 0 0

I have done this before when dealing with co-occurences using just one variable within a group by using the xtabs function, but not sure how to apply it to multiple columns. For example, if I was interested in finding the co-occurences for var1 within the different groups, I would do the following:

> td = xtabs(~group + var1,data = df)
> cooc = crossprod(td,td)
> diag(cooc) = 0

Answer 1

if i am understanding your question correctly, I believe this should work:

# i only use data.table here in case we need to do this "by group"
# but in this solution I do not use it as i did not see the significance
# of grouping
###library(data.table)
###df <-  data.table(df)

# this creates the pair of values "a_b"
df$ID <- paste(df$var1,df$var2,sep="_")
# we enumerate all the unique values that way we can create 
# a map to later match the data and map
uniqval <- sort(unique(c(df$var1,df$var2)))
grid <- expand.grid(uniqval,uniqval)
grid$ID <- paste(grid$Var1,grid$Var2,sep="_")
# match our data to this map
matches <- sort(match(df$ID,grid$ID))
# tabulate our results into a dataframe
tab <- data.frame(table(grid$ID[matches]))
# split up our ID back into values
tab$Var2 <- substr(tab$Var1,3,3)
tab$Var1 <- substr(tab$Var1,1,1)
# create our empty result matrix
cooc <- matrix(0,nrow=length(uniqval),ncol=length(uniqval))
rownames(cooc) <- uniqval
colnames(cooc) <- uniqval

# there are other ways to do this
# but this seemed simple enough of a loop for me
# we just need to replace the tabulation results
# into our desired location in the matrix
# namely, "a_b" frequencies into [a,b] and [b,a] positions
for(m in 1:nrow(tab)){

  i <- tab$Var1[m]
  j <- tab$Var2[m]

# by adding this to the previous value
# we are accounting for "a_b" equiv. to "b_a"
  cooc[i,j] <- cooc[i,j]+tab$Freq[m]
  cooc[j,i] <- cooc[i,j]

}