Create Weighted edges in igraph instead of multiple single connections

Question

I'm trying to visualize the connections between the institutions in a medical faculty and just can't get the edges to be weighted and displayed thicker or thinner depending on the number of connections.

I've tried to combine the answers I found here playing around with edge.width = E(g)$weight and trying graph.strength(g). But honestly I have no idea what I'm doing. This is the first time I have to use R and I have no experience in programming whatsoever.

library(igraph)
D3 <- read.csv(file.choose(),header=TRUE,row.names = 1)
g <- graph.data.frame(D3, directed=FALSE)
plot(g, 
     vertex.size=20, 
     vertex.label.dist=1, 
     vertex.label.degree=-pi/2, 
     layout=layout_with_kk)

Igraph plots a network where every single connection is shown. Some institutions have multiple connections between each other which make the graph quite unattractive to look at. Only a Part of the table was used for this picture

My data looks like this and has about 1500 rows:

"1","NEUROLOGIE","MEDINF" 

my data

Any help is much appreciated!

Answer 1

Using edge.width = E(g)$weight is the right idea, but you need to get the right weight. graph.strength(g) is a property of the vertices, but you need a weight for the edges. I don't know of a function that directly calculates how many edges there are between two vertices, but it is not hard to write one.

First, get a version of the graph with just one edge between each pair of connected vertices.

g2 = simplify(g)

Now we need to get the right weight for the edges of g2. If an edge connects two vertices, all shortest paths connecting those two vertices will be single edges, so for each edge of the simplified g2, we need to find the number of shortest paths (edges) between those vertices in the original g. Then we can plot.

E(g2)$weight = sapply(E(g2), function(e) { 
    length(all_shortest_paths(g, from=ends(g2, e)[1], to=ends(g2, e)[2])$res) } )
plot(g2, 
     vertex.size=15, 
     vertex.label.dist=0.5, 
     vertex.label.cex=0.8,
     vertex.label.degree=-pi/2, 
     edge.width=E(g2)$weight,
     layout=layout_with_kk,
     margin=-0.2)

(I have slightly modified your plot statement to improve readability.)