I’m an old programmer bigot, so doing things in R is always a bit weird (I’m *still* not used to “.” having no meaning). This post will (hopefully) help me later when I have to do this again. It’s actually the third time I have to relearn igraph on R =/

### Load a graph

Knowing a little R, I expect that I can load a graph in memory with just one line.

I little googling and <http://igraph.org/r/doc/read_graph.html>:

> The `read_graph` function is able to read graphs in various representations from a file, or from a http connection.

Great! How about the file format? Hmmm… edge list? Not clear what’s expected but it seems something simple like:

node1 node2

node2 node3

I wonder if it accepts weight and direction, let’s try:

node1 node2 9

node2 node3 99

G \<- read_graph(“my_file.edge”, directed = “true”)

Nah… let’s remove the weight…

node1 node2

node2 node3

Parse error again =(

Okay, let’s find something else. After some more googling I find tutorials [here](http://kateto.net/networks-r-igraph) and [there](http://www.shizukalab.com/toolkits/sna/weighted-edgelists) reading things from csv files.

<https://gist.github.com/ruliana/d32d022c389d08c0be8b042075281f9f>

*loading a directed weighted graph*

I learned that if you name a column “weight”, the function “graph.data-frame” do the right thing. Not bad, it actually took 2 lines, but that’s fair enough.

Let me try with my 8.000 nodes graph… fast and easy. Very good!

### Network descriptives

I’m interest in network descriptives, let’s try to find the most central node by degree.

The function “centr_degree(G)” looks very promising, but now I have a matrix of node degrees, how to find the biggest one?

Hmm… “degree(G)” looks better, I just need to sort it and take some at the beginning.

<https://gist.github.com/ruliana/5d0078a1a579739ae07aeb22cb48dca8>

Eeeeeasy! We also have “strength”, which is the sum of weights.

<https://gist.github.com/ruliana/bcb40ddb1b5327ecfea7adc8514936d7>

Not bad at all =)

Let’s try reciprocity, as it matter a lot to my research… Reciprocity is zero, that’s ok… wait… what?! It **can’t** be zero o_O

Ohhh… let me take some time to read the docs. Hmmm… hmmm… not helping. Maybe it thinks my graph is undirected? Let’s test with a smaller data set. Worked.

Looking for a solution I find the useful “is.mutual(G)”:

<https://gist.github.com/ruliana/68a3dd48bf12c109a6a17a28c1edde1f>

But my big graph still returns nothing…

Some hours googling and looking source codes and still nothing, must be something really obvious.

---

I find it!!! And, at this right moment, I hate “read.csv” >\_\< My csv file had a single space after each comma, even using quotes for every column, the parse ignores it and add a space before the string values. Ugh… living and learning.

<https://gist.github.com/ruliana/f8c4762999c16273d4ea43ab20bdd2c6>

I think that’s enough for now. Next time I’m going to try some more graph functions.

So far, R and igraph are really easy to work with, but for some minor inconveniences.