

Visualizing Facebook Friends: Eye Candy in R - sonabinu
http://paulbutler.org/archives/visualizing-facebook-friends/

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sonabinu
This picture is one of the biggest inspirations for learning R. For some
interesting resource to get started, take a look at
[http://datagrad.blogspot.com/2013/02/some-learning-
resources...](http://datagrad.blogspot.com/2013/02/some-learning-resources-
for-r.html)

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aeontech
Here's his full-size, zoomable visualization:
<http://fbmap.bitaesthetics.com/>

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alecdbrooks
Data visualization experts: is R a good language to learn for doing
visualizations or would something like Processing or javascript and D3 be a
better choice?

The article makes it clear that you can do nice visualizations in R, but not
if it's the best option for someone getting started.

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hazexp
It depends.

For _statistical_ graphics, it is hard to beat R simply because it has all of
the statistical functionality built right in. Want an ACF plot for your ARMA
model? No problem. To do this in D3 requires a lot more code. R also has the
great package ggplot2, which is simply brilliant for constructing plots.

Where D3 shines is the ability to add interactivity and animation to its
plots. R simply has no concept of this as it is only really capable of static
graphics.

If you know neither system, I would probably suggest D3 because you're going
to have to learn a graphics system anyway. With D3 at least you have the
ability to construct more than just static graphics. Also, it's all JS so most
people are going to find it easier to learn than R.

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gdubs
Nice little aside, that he doesn't mention in the article: he was an intern
when he made this. Great work.

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niggler
Did he ever release the commands he used to generate the plot?

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paulgb
I wasn't able to release the original code as it belonged to Facebook, but
Nathan Yao wrote a great blog post covering how to do make a similar map
(including code): [http://flowingdata.com/2011/05/11/how-to-map-connections-
wit...](http://flowingdata.com/2011/05/11/how-to-map-connections-with-great-
circles/)

To be honest, 80% of the code was getting the data into the right shape and
the other 20% was a slow implementation of the great circle calculations (I
didn't know about the geosphere package so I rolled my own). Nathan's code is
better.

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aeontech
Tufte would be proud, beautiful work!

