“[” and “[[” with the apply() functions

[ and [[ are a little bit faster (~15%) in the case below:
prefix <- sample(LETTERS, size=100, replace=TRUE)
paste(prefix, abs(100 * rnorm(100)), sep="-")
benchmark(sapply(strsplit(id, "-"), function(a) a[1]), sapply(strsplit(id, "-"), "[", 1), order="elapsed", replications=100)

The stupidest thing...

Did you know you can use "[" and "[[" as function names for subsetting with calls to the apply-type functions?

For example, suppose you have a bunch of identifier strings like "ZYY-43S-CWA3" and you want to pull off the bit before the first hyphen ("ZYY" in this case). (For code to create random IDs like that, see the end of this post.)

Suppose the IDs are in a vector of character strings, id.

If I wanted to grab the bit before the first hyphen, I would typically use strsplit and then sapply with function(a) a[1], as so:

But in place of function(a) a[1], you can use "[", 1, as follows:

I think that’s kind of cute. You can use "[[" the same way, if you’re working with lists.

Here’s some code to create random IDs of this form, to test out the above:

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R for complex network analysis

(The page is still under construction.)

Complex network analysis is quite common in biology and social network analysis. However, CRAN task views don’t provide a specific section. Here, I collect R packages for complex network analysis.

iGraph: generic purpose

iGraph is a C library for manipulating graphs, complex network analysis, social network analysis. It has R and Python interfaces. My own experience is that it runs really fast.