It’s been a few months since I’ve posted here; blogging was a bit taboo this summer at work (though it turns out I found plenty of other ways to raise red flags for the Cyber Security team using just Python + the Interwebs).
Working in an office with several other research assistants who were proficient with some statistical scripting languages (Stata, SAS), I began to think there’s probably a niche for a more general-purpose language in academic social science research (as well as in automating some of the tasks involved with casework around the office). I was already using Python in much of my work. What started out as a few trips to coworkers’ desks to help them write this or that script quickly turned into a few pages of notes, and that turned into some thirty pages of charts, explanations, and instructional tasks. (I must note, the final formatting was inspired by the style of my linear algebra lecture notes from last semester.)
I presented a version of Python for Economists to some coworkers at the FTC Bureau of Economics in July. I’ve been a student of three different college classes that taught Python from scratch, but I’ve never seen a way of teaching Python that I thought was appropriate for students already familiar with scripting languages such as Stata. I focus on two broad applications of Python I’ve found very useful in social science research: web scraping and textual processing (including regular expressions).