**Why? » R**, and kindly contributed to R-bloggers)

This morning I came across a post which discusses the differences between scala, ruby and python when trying to analyse time series data. Essentially, there is a text file consisting of times in the format HH:MM and we want to get an idea of its distribution. Tom discusses how this would be a bit clunky in ruby and gives a solution in scala.

However, I think the data is just crying out to be “analysed” in R:

require(ggplot2)#Load the plotting package

times = c("17:05", "16:53", "16:29", ...)#would be loaded from a file

times = as.POSIXct(strptime(times, "%H:%M")) #convert to POSIXct format

qplot(times, fill=I('steelblue'), col=I('black'))#Plot with nice colours

Which gives

I definitely don’t want to get into any religious wars of R vs XYZ. I just wanted to point out that when analysing data, R does a really good job.

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**Why? » R**.

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