Mixpanel Statistics
A collection of Python scripts that pull API data from Mixpanel and perform statistics on the data.
Currently supported: - Correlation Analysis - Regression Analysis
Setup
Retrieve your API key and secret from Mixpanel API Information (http://mixpanel.com/user/account/#info). Set the variables in your shell:
export MIXPANEL_API_KEY=klsj234kljSLDKFJl243jlksdjf
export MIXPANEL_API_SECRET=lkJSdlkj234lkjsdlfksjdflksjdf
Correlation Analysis
Correlation determines the relationship between two variables. To determine the correlation of different Mixpanel events, do:
./correlation.py [event1] [event2] [event3]...
./correlation.py success_view checkout_view checkout_error
Output
==============================================================================
Correlation coefficients
checkout_view x checkout_error: 0.600231
checkout_view x success_view: 0.806892
checkout_error x success_view: 0.469129
Regression Analysis
Regression analysis studies the relationship between a dependent variable and other independent variables. To perform regression analysis on your Mixpanel events, do:
./regression.py [dependent_var] [independent_var1] [independent_var2]
./regression.py success_view checkout_view checkout_error
Output
==============================================================================
Dependent Variable: success_view
Method: Least Squares
Date: Sun, 10 Jan 2010
Time: 12:23:16
# obs: 60
# variables: 3
==============================================================================
variable coefficient std. Error t-statistic prob.
==============================================================================
const 1.151644 0.767227 1.501047 0.138863
checkout_view 0.049232 0.005862 8.398709 0.000000
checkout_error -0.032332 0.133101 -0.242911 0.808946
==============================================================================
Models stats Residual stats
==============================================================================
R-squared 0.651435 Durbin-Watson stat 2.219304
Adjusted R-squared 0.639205 Omnibus stat 6.593467
F-statistic 53.263875 Prob(Omnibus stat) 0.037004
Prob (F-statistic) 0.000000 JB stat 5.678402
Log likelihood -160.875422 Prob(JB) 0.058472
AIC criterion 5.462514 Skew 0.649233
BIC criterion 5.567231 Kurtosis 3.765081
==============================================================================
Regression equation for response variable 'success_view'
success_view = 1.15164371922 + 0.04923(checkout_view) + -0.03233(checkout_error)
Contact
Web: http://bradjasper.com
Twitter: @bradjasper
Email: [email protected]