Tis the season to visualize election polling data!

I use the open source Python pandas library frequently for data processing and analysis and plotting and all the things.

What I’m doing:

Reformatting dates ranging from early 1900’s until now, using Python’s datetime.strptime method. Straightforward.

Or, how to take advantage of cron jobs and run code automatically.

At a PyData Meetup last week, some fellow classmates and I were introduced to Spyre, a framework for creating data-driven python web apps. It’s the simplest way I’ve found to launch a dynamic web app and not touch HTML or javascript… some days just aren’t HTML&javascript days, y’know?

Bikeshare programs around the country are pretty popular these days.

Python’s formatting method is my favorite code discovery of the week.

My latest project at Metis sought to answer the following question: Do adverse economic conditions early in an actor’s life influence his/her relative success in the future?

Today at Metis I presented on Item Response Theory (IRT), or a better way to evaluate student aptitude. The presentation was based on a blog post from Knewton, an adaptive learning company that uses IRT to evaluate performance on tests.

This week we are using BeautifulSoup to extract data from websites. Perfect timing, given that for my latest project I needed to build a database of actor information.

The first project assigned to us at Metis was based on MTA Turnstile Data.

I’ve been a Metis student for four days and I’m looking forward to a future lesson on “Creating Time out of Thin Air” because, wow!, there’s so much to do and learn and so little time.