I am trying to convert an edgelist to an adjacent matrix.
Below is the sample data
#Sample Data
User<-c("1","1","2","3","4")
v1 <- c("b", "b", "a", "d", "c")
v2 <- c("c", "d", "c", "a", "a")
v3 <- c(0, 0, "d", 0, "b")
v4 <- c(0, 0, 0, 0, 0)
v5 <- c(0, 0, 0, 0, 0)
my_data<-data.frame(User, v1, v2, v3, v4, v5)
my_data
If you run this code you will get the below as output,
User v1 v2 v3 v4 v5
1 b c 0 0 0
1 b d 0 0 0
2 a c d 0 0
3 d a 0 0 0
4 c a b 0 0
Using the data, I want to create an adjacent matrix that looks like follows:
a b c d
a 0 0 2 2
b 0 0 1 1
c 2 1 0 1
d 2 1 1 0
Basically, the desired output diplays the count how many times each pair appeared in column v1~v5 in the sample data frame.
I have tried to use AdjacencyFromEdgelist function from dils library, also tried to create a matrix shell with NAs and fill out the matrix by looping through the dataframe.
However, I could not get neither way to work.
I think this may be close to what you have in mind. In the rows where there are more than 2 vertices, I considered every existing pairs:
library(igraph)
do.call(rbind, my_data[-1] |>
apply(1, \(x) x[x != 0]) |>
lapply(\(x) t(combn(x, m = 2)))) |>
graph_from_edgelist(directed = FALSE) %>%
as_adjacency_matrix()
4 x 4 sparse Matrix of class "dgCMatrix"
b c d a
b . 2 1 1
c 2 . 1 2
d 1 1 . 2
a 1 2 2 .
Or without the pip operator in base R:
tmp <- apply(my_data[-1], 1, function(x) x[x != 0])
tmp <- do.call(rbind, lapply(tmp, function(x) t(combn(x, m = 2))))
my_graph <- graph_from_edgelist(tmp, directed = FALSE)
adj_mat <- as_adjacency_matrix(my_graph)
adj_mat