Monthly Archives: April 2013

Managing memory in a list of lists data structure

April 3, 2013
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First, a confession: instead of using classes and defining methods for them, I build a lot of ad hoc data structures out of lists and then build up one-off methods that operate on those lists of lists. I think this … Continue reading →

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ISBA on INLA [webinar]

April 3, 2013
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ISBA on INLA [webinar]

If you have missed the item of information, Håvard Rue is giving an ISBA webinar tomorrow on INLA: the ISBA Webinar on INLA is scheduled for April 4th, 2013 from 8:30 - 12:30 EDT. ------------------------------------------------------- To join the online meeting (Now from mobile devices using the Cisco WebEx Meeting App) ------------------------------------------------------- 1. Go to https://www.webex.com/login/attend-a-meeting

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Automated Re-Install of Packages for R 3.0

April 3, 2013
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With the big release of R 3.0 today comes an unfortunate side effect of needing to re-install all of your packages. Luckily, R provides a pretty easy method of getting all of your packages into a list for automated re-install.  Here’s how to do it for OSX users with a default install to the Library: Automated Re-Install of...

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Hurray! An R Connections API!

April 3, 2013
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I waited until April 3 to post this, so it wouldn't be taken as an April Fool's joke! A recent R News item announces that we now have a bona fide mechanism to create custom connections in R! This makes it possible to implement a custom connection in an R package. Until now, the only

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R 3.0.0 is released!

April 3, 2013
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R 3.0.0 is released!

The new R 3.0.0 is out! You know the drill! Get the source code from here.

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Colour it up: my quest to master ggplot2 (part 2)

April 3, 2013
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Splitting a Large CSV File into Separate Smaller Files Based on Values Within a Specific Column

April 3, 2013
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Splitting a Large CSV File into Separate Smaller Files Based on Values Within a Specific Column

One of the problems with working with data files containing tens of thousands (or more) rows is that they can become unwieldy, if not impossible, to use with “everyday” desktop tools. When I was Revisiting MPs’ Expenses, the expenses data I downloaded from IPSA (the Independent Parliamentary Standards Authority) came in one large CSV file

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CFP: the 11th Australasian Data Mining Conference (AusDM 2013), submission due 15 July

April 3, 2013
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CFP: the 11th Australasian Data Mining Conference (AusDM 2013), submission due 15 July

********************************************************************* The 11th Australasian Data Mining Conference (AusDM 2013) Canberra, Australia, 13-15 November 2013, http://ausdm13.togaware.com Join us on LinkedIn: http://www.linkedin.com/groups/AusDM-4907891 ********************************************************************* Data mining, the art and science of intelligent analysis of (usually large) data sets for meaningful (and previously unknown) … Continue reading →

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Beware of grep with a list

April 2, 2013
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Beware of grep with a list

Another R tip: beware of as.character applied to a list. Really, beware of grep with a list: You might have thought that the result would be just 1, but grep expects a vector of character strings. If the input is not that, it uses as.character(). Since the result of that starts with "c(", grep finds

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apply vs for

April 2, 2013
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apply vs for

It’s widely understood that, in R programming, one should avoid for loops and always try to use apply-type functions. But this isn’t entirely true. It may have been true for Splus, back in the day: As I recall, that had to do with the entire environment from each iteration being retained in memory. Here’s a

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