Is there a way to convert a graph network to a relational dataset in R?

Question

I have a dataset that consists of linked nodes, that I'm trying to convert to a simple relational table. The structure is like this:

Key1 Key2
A    A
A    B
A    C
B    A
B    B
B    C
C    A
C    B
C    C
D    D
D    E
E    D
E    E
F    F

At the end of the day, I'm trying to figure out if there's a way in R (outside of a loop, which would be too slow given the size of the set) to get every possible related values under a new unique master ID. The final dataset would like something like this:

Master   Key
1        A
1        B
1        C
2        D
2        E
3        F

I can't find anything on the topic because I'm likely asking the question without the proper terminology.

Any help is appreciated!

Answer 1

This is simply getting the connected components of the graph.

Using your data:

Dat = read.table(text="Key1 Key2
A    A
A    B
A    C
B    A
B    B
B    C
C    A
C    B
C    C
D    D
D    E
E    D
E    E
F    F", 
header=TRUE)

We turn the edges into a graph and get the connected components.

library(igraph)
g = graph_from_edgelist(as.matrix(Dat), directed=FALSE)
components(g)$membership
A B C D E F 
1 1 1 2 2 3 

Note that components(g)$membership is a vector with named components. The A,B,C,D,E,F can be accessed with names(components(g)$membership)