Blog Posts by Andrew B. Collier / @datawookie

Day 17: Datasets from R

Month of Julia
Accessing R Datasets from Julia.

R has an extensive range of builtin datasets, which are useful for experimenting with the language. The RDatasets package makes many of these available within Julia. We’ll see another way of accessing R’s datasets in a couple of days’ time too. In the meantime though, check out the documentation for RDatasets and then read on below.

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urlshorteneR: A package for shortening URLs

This is a small package I put together quickly to satisfy an immediate need: generating abbreviated URLs in R. As it happens I require this functionality in a couple of projects, so it made sense to have a package to handle the details. It’s not perfect but it does the job. The code is available from github along with vague usage information. In essence the functionality is simple: first authenticate to shortening service (goo. Read More →

Day 12: Parallel Processing

Month of Julia
Doing Parallel Processing with Julia.
As opposed to many other languages, where parallel computing is bolted on as an afterthought, Julia was designed from the start with parallel computing in mind. It has a number of native features which lend themselves to efficient implementation of parallel algorithms. It also has packages which facilitate cluster computing (using MPI, for example). We won’t be looking at those, but focusing instead on coroutines, generic parallel processing and parallel loops. Read More →

Day 9: Input/Output

Month of Julia
Your code won’t be terribly interesting without ways of getting data in and out. Ways to do that with Julia will be the subject of today’s post. Console IO Direct output to the Julia terminal is done via print() and println(), where the latter appends a newline to the output. julia> print(3, " blind "); print("mice!\n") 3 blind mice! julia> println("Hello World!") Hello World! Terminal input is something that I never do, but it’s certainly possible. Read More →