Statistics and Data Analysis in Python with pandas and statsmodels

UPDATE

NOTE: The date of this meetup has changed, it will now take place on Wed., September 14, 2011.

I am very pleased to announce that along with our usual sponsorship from Revolution Analytics, this month's meetup will also be sponsored by O'Reilly's Strata Conference (http://strataconf.com/stratany2011). This will include many wonderful things:

Shwag-tastic Revolution Analytics give-aways: stickers, t-shirts, and teddy bears--oh my! O'Reilly book give-aways: there will be copies of R in a Nutshell (http://oreilly.com/catalog/9780596801717), R Cookbook (http://oreilly.com/catalog/9780596809164), Data Analysis with Open Source Tools (http://oreilly.com/catalog/9780596802363), and Mining the Social Web (http://oreilly.com/catalog/0636920010203) Two passes to Strata Conference: we will hold a raffle for these passes Finally, and perhaps most exciting, Strata will be sponsoring our first round of drinks at The Central Bar! To accommodate what will likely be a larger the average turnout, I have reserved the upstairs of Central Bar. I hope to see you there!

Fresh off our summer recess and diving right into our new---less restrictive--- focus area, we are thrilled to host Wes McKinney.

Wes is a prominent figure in the scientific Python community, and has made tremendous contributions to several core statistical computing libraries in that language. This month, Wes will be speaking specifically about two packages he has created related to data manipulation in Python and analysis.

pandas is a Python library providing powerful and flexible data structures (similar to R's data.frame) and accompanying tools for data wrangling, time series, input / output, and visualization. statsmodels is a related Python project providing standard statistical and econometric models.

http://pandas.sourceforge.net (http://pandas.sourceforge.net/)

http://statsmodels.sourceforge.net (http://statsmodels.sourceforge.net/)

In this talk Wes will demo the features of both libraries, particularly as they relate to similar tools in R, as well as speak about planned work to create an better integrated statistical computing environment in Python. I will also touch on connections to other scientific Python projects of interest to the statistical computing community.

As usual, we will have pizza starting at about 6:15 at AOL, and Wes will begin promptly at 7pm.