For those who’ve been living under a rock for the past few years and haven’t been paying attention: the interwebs are alight with the field of data visualization. Not only does it appeal to this generation’s one click fix for information need, it also represents the closing of the gap between the creative design-centric types and the data/information types. “Data Viz” has a mantra: Deliver complex information in the most efficient and beautiful way possible. A great source for the best of the best is Nathan Yau’s FlowingData. In a series of recent posts he’s made a call for something I’ve personally wanted since I was a kid. Life stats, or as he puts it, the quantified self. Since I hadn’t been keeping tabs on the minutae of my life, I decided to take a stab at it with my inbox.

It turns out, OSX users have all of their emails sitting in /Users/”user”/Library/Mail/, in parsable text form. As with all statistics, it’s key to have a large sample size in order to find trends. Lucky for me, I have a co-worker/super-friend extraordinaire, Liv. From about the second week I started working in the lab, the email exchanges have been relentless, save for Christmas breaks:

Zooming in for monthly, weekly and daily trends:

It was exciting to see some of these trends, expected (the picnic effect, why e-mail when you’re eating lunch together?) or unexpected (the reversed polarity in sender from early week, to late week). There a number of other things to do that come to mind, say, word clouds (we exchanged 13,284 exclamation marks, make it rain!!!!). While these haven’t been polished in terms of presentation, it’s great to see the stats come to life. My excitement was diminished the following week when I saw someone had done the exact same thing… only better. Argh!! Kudos to you, and congratulations on your Ph.D.!!!!!

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