How to calculate a table of pairwise counts from long-form data frame

Question

I have a \'long-form\' data frame with columns id (the primary key) and featureCode (categorical variable). Each record has between 1 and 9 values

Answer 1

If you don't need that exact structure, but just need to get the pairwise counts, you can try this approach:

Here's your data:

dat <- read.table(header = TRUE, 
       text = "id  featureCode
                5         PPLC
                5         PCLI
                6         PPLC
                6         PCLI
                7          PPL
                7         PPLC
                7         PCLI
                8         PPLC
                9         PPLC
               10         PPLC")

We're only interested in ids where there is more than one featureCode:

dat2 <- dat[ave(dat$id, dat$id, FUN=length) > 1, ]

Having this data as a list is going to be useful since it will let us use lapply to get the pairwise combinations.

dat2 <- split(dat2$featureCode, dat2$id)

This next step can be broken down into its intermediate sections if you prefer, but the basic idea is to create combinations of the vectors in each list item and then tabulate the unlisted output.

table(unlist(lapply(dat2, function(x) 
  combn(sort(x), 2, FUN = function(y) 
    paste(y, collapse = "+")))))
# 
#  PCLI+PPL PCLI+PPLC  PPL+PPLC 
#         1         3         1

Update: A better answer at another question

With a little bit of modification, @flodel's answer to another question is applicable here. It requires the igraph package to be installed (install.packages("igraph")).

dat2 <- dat[ave(dat$id, dat$id, FUN=length) > 1, ]
dat2 <- split(dat2$featureCode, dat2$id)
library(igraph)
g <- graph.edgelist(matrix(unlist(lapply(dat2, function(x) 
  combn(as.character(x), 2, simplify = FALSE))), ncol = 2, byrow=TRUE), 
                    directed=FALSE)
get.adjacency(g)
# 3 x 3 sparse Matrix of class "dgCMatrix"
#      PPLC PCLI PPL
# PPLC    .    3   1
# PCLI    3    .   1
# PPL     1    1   .