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I've the following dataset: 

**Strenght  Movie1  Movie2** 
  23            2        3 
  80            1        2  
  10            4        3

And I want to create a graph with the relationships between movies having the first column as the strenght of the relationship. How can I do this using R?

Many thanks!

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  • $\begingroup$ There are several ways how graphs can be represented. Which representation you need depends on what you're planning to do with the graph / what algorithms you want to run on it. $\endgroup$
    – stmax
    Commented Sep 7, 2016 at 14:01
  • $\begingroup$ I'm tryig to build a graph that shows the relationships of the movies having the first column as the strenght of the relationships. Like the graphs created in Gephi. Which algorithm I need to use? $\endgroup$
    – João_testeSW
    Commented Sep 7, 2016 at 14:04
  • $\begingroup$ Algorithm may be the wrong word. If you want a graph that demonstrates distance in a network graph as the values in the first column try the igraph package on CRAN cran.r-project.org/web/packages/igraph/igraph.pdf $\endgroup$
    – DaveRGP
    Commented Sep 8, 2016 at 14:43
  • $\begingroup$ The other part to this is you need to specify your edges, i.e. where the joins are. $\endgroup$
    – DaveRGP
    Commented Sep 8, 2016 at 14:56

1 Answer 1

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Try this R code:

library(igraph)
dfr <- data.frame(idMovie1=c(2,1,4), idMovie2=c(3, 2, 3), strength=c(23,80,10))

igr <- igraph::graph.data.frame(dfr)
plot(x = igr,
     edge.curved=FALSE, edge.width=log(edge_attr(igr)$strength), edge.label=edge_attr(igr)$strength,
     main="Graph of Movie Strengths")

Works only for small daasets. visualizations get ugly quickly.

igraph

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  • $\begingroup$ Sorry mu ignorance but is possible to make the dataframe: dfr <- data.frame(idMovie1=c(2,1,4), idMovie2=c(3, 2, 3), strength=c(23,80,10)) reading directly from my txt file? $\endgroup$
    – João_testeSW
    Commented Sep 13, 2016 at 14:08
  • 1
    $\begingroup$ Sure, but that is basic R. Use the read.csv() function or one of its variants. You might have to reorder the columns, remove duplicates, impute NAs.... standard stuff. $\endgroup$
    – knb
    Commented Sep 13, 2016 at 14:54

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