You can get it here: https://github.com/slycoder/Rflim
Read this for a quick explanation: https://www.facebook.com/note.php?note_id=10150359708746212
You can get it here: https://github.com/slycoder/Rflim
Read this for a quick explanation: https://www.facebook.com/note.php?note_id=10150359708746212
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Some of you might be interested in a little analysis we did of baseball fandom on Facebook.
Baseball season is in full swing again! March 31st was opening day for Major League Baseball and while we can’t all be swinging the bat or fielding first base in Giants’ stadium, all of us can cheer on our favorite team. Many of you support your favorite teams on Facebook; in this post we’ll look at how you and your friends express your fandom and what that says about the team you love.
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The other day someone posted a link to this python package which provides a bash-style pipe operator to manipulate streams through a series of transformers. It seemed like a cool and powerful way of doing the usual data pre-processing / munging I often do in python.
But what about R? I also do a lot of processing in R and to me this pipe metaphor also seemed like a natural way of iterating over data frames. So the other day I set about trying to implement an R-thonic pipe operator and about 50 lines later I succeeded. It’s actually more robust and featureful than what I’ll describe below, but even in these simple use cases I can see it making manipulating data much easier.
Read more here: http://www.facebook.com/notes/jonathan-chang/pipes-in-r/10150174062816212
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It was mentioned to me at NIPS that not everyone is on Facebook all the time and so it behooves me to post a few links here of some stuff that’s happened over the past few months. I’ll be better about cross-posting in the future, I promise!
I’m probably forgetting a bunch of other stuff that’s happened this fall.
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Brendan (who will be joining us this summer, natch!) pointed out yesterday that we don’t have a repository for the papers we’ve published here at Facebook. We moved fast. Now you can find them by clicking on the “Papers” tab of the Facebook Data page. Happy reading everyone!
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