My adventures analyzing personal data at Wolfram, as lead data analyst on the March 2012 quantified self blog post.
April 2014, Data Raves NYC: http://www.meetup.com/Data-Rave/events/170730922/
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Quantified Self Adventures at Wolfram
Hacker School W’
0 100 200 300 400
w o o l l f f r r a a m
s blog post (March 2012)
I was the lead data analyst for Stephen Wolfram’
s quantified self blog post:
We had about 20 years worth of personal data!
Each dot is a sent email on date X and time Y (“
The diurnal plot of keystrokes is very similar to the email plot:
phone calls and meetings
Phone call spikes on the hour? Why?
s when his meetings are (he’
s remote so all his meetings are on the phone):
on the phone peaks show he’
s often late to his meetings.)
Awesome! Show me the code!
follow-up blog posts
We wrote several follow-up posts showing detailed code for analyzing email, keystrokes, and pedometer data:
I wrote an interface for analyzing your keystrokes:
wolfram” a bunch of times, then grab the data:
Letter pair intervals when typing “
wolfram” (after 50 trials):
intervals Transpose Differences keydata All, All, 2 ;
Mesh All, PlotStyle colors, PlotLegends SwatchLegend colors, nicelabel pchars , ImageSize 500
, nicelabel "letter interval sec " , nicelabel "trial" , Left, Bottom , RotateLabel True
letter interval sec
10 20 30 40 50
letter interval distribution
My letter pair interval distribution is bimodal:
Labeled keyhistogram intervals, ChartStyle colors, ImageSize 600,
AspectRatio 1 2, PlotLabel nicelabel "Letter interval distribution Paul Jean " ,
nicelabel "interval ms " , SwatchLegend colors, nicelabel pchars , Bottom, Right , Spacings Automatic, 0
50 100 150
Letter interval distribution Paul Jean
same finger” rule?
Letter pairs on the same finger ~ 150 ms
Letter pairs on different fingers ~ 75 ms
Mean Flatten intervals 1, 3, 5, 6
Mean Flatten intervals 2, 4
Does it take about twice as long for other people too?
I got keystroke data from 42 data nerds at Wolfram:
meanswolfram Mean Transpose Differences & All, All, 2 & wolframdata;
Grid Partition keychart , ImageSize 100, ChartStyle Directive Opacity 0.6 , & colors & meanswolfram,
7, 7, 1, , SwatchLegend colors, nicelabel pchars
Wolfram nerds typing “
The Wolfram interval distribution was bimodal too, also with peaks at about 75 ms and 150 ms:
intervalswolfram Flatten Transpose Transpose Differences All, All, 2 & wolframdata ;
0 100 200
... But it’
s not just a 2x rule (the best linear model has a bias):
twofingers Transpose Differences All, All, 2 1, 3, 5, 6 & wolframdata;
onefinger Transpose Differences All, All, 2 2, 4 & wolframdata;
fingersFit LinearModelFit Transpose Mean Flatten & twofingers, Mean Flatten & onefinger , x, x
0.106044 0.490341 x
Letter intervals for Wolfram nerds in ms
50 100 150 200 250
s quantified self blog made a splash.
But people said: show me the code!
Our follow-up posts showed people how to analyze their own data.
Fun modeling keystrokes times with Mathematica.