Saturday 1:55 p.m.–2:25 p.m.

Diving into Open Data with IPython Notebook & Pandas

Julia Evans

Audience level:


I'll walk you through Python's best tools for getting a grip on data: IPython Notebook and pandas. I'll show you how to read in data, clean it up, graph it, and draw some conclusions, using some open data about the number of cyclists on Montréal's bike paths as an example.


Using a the example of some cyclist sensor data from Montréal, I'll explain how to - clean up data (fix date formatting issues, remove null values, ...) - graph the data - scrape weather data from the weather office website and look at the relationship between temperature & cyclists - aggregate the data to find out how many people bike on weekdays vs weekends - talk about possible directions to take the project (make a model using scikit-learn)