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David Smith's picture
July 30, 2014

R is a very powerful language for creating custom data visualizations, but during the development process sometimes you make a mistake and things go horribly wrong. But sometime serendipity intervenes, and the (unintended) result can be quite beautiful. Accidental aRt, if you will.

by Andrie de Vries

In my previous post I wrote about how to identify and visualize package dependencies.  Within hours, Duncan Murdoch (member of R-core) identified some discrepancies between my list of dependencies and the visualisation.  Since then, I fixed the dispecrancies. In this blog post I attempt to clarify the issues involved in listing package dependencies.

As global warming causes sea levels to rise, the risk of flooding for coastal settlements also rises over time. A recent analysis by Reuters find that incidents of coastal flooding along the Eastern seaboard of the United States have surged in recent years as the sea level steadily rises.


Pearl Jam has been featuring in my playlist recently, which reminded me of this old Misheard Lyrics video for Yellow Ledbetter:


The funny think is, I don't think Yellow Ledbetter has official lyrics, so these might be as good as any. I've seen it performed a few times on stage, and each time the lyrics are different. Not as wildly divergent as these, but still: variations each time. (If anyone does know what the actual lyrics are, please point me to the source!)

That's all for this week. See you Monday!

I was honoured to be invited earlier this month to the Directions of Statistical Computing meeting in Brixen, Italy. DSC is one of two meetings run by the R Project and unlike the useR! conference, DSC is a much smaller and intimate meeting (DSC 2014 had about 30 participants).

R is a functional language, which means that your code often contains a lot of ( parentheses ). And complex code often means nesting those parentheses together, which make code hard to read and understand. But there's a very handy R package — magrittr, by Stefan Milton Bache — which lets you transform nested function calls into a simple pipeline of operations that's easier to write and understand.