Date: Fall 2017

As I was collecting articles on the history of the NYC subway fare, I found myself wanting a different way to save my notes. I was tired of reorganizing a Google Doc over and over. What I was looking for was:

• tagging - the ability to view subsets of a notes set
• dated - the ability to sort subsets of notes
• portable - so many online note tools seem great but don't improve or fit your ideal data model; I didn't want to get locked in
• publishable - the ability to quickly share a note I had just written

The result is a Node.js library which accepts a series of Markdown-based notes and outputs the grouped and sorted notes. The result is browseable on GitHub or through a docs integration (I used GitBooks).

notetime is on npm and GitHub. I am actively using it to compile my urban history notes.

Date: September 2017

Being new to New York City, I decided to study the history of the MTA subway fare.

I ended up collecting the New York Times articles from every fare increase since 1904 and writing up a summary of what I learned. Check out my notes and the finished post.

Date: Fall 2016

After implementing basic graph algorithms on the New York City subway network, I began exploring centrality metrics on the New York City, Boston, Paris, and Washington, DC, subway networks. This lets us see what are the most important stations in the network and compare network structure across cities.

Check out my blog posts (first and second) on the centrality adventure and check out the results in the web app.

Date: Summer 2016

While reviewing algorithms during a round of interview prep, I realized it would be fun to implement graph algorithms on a transit network!

Check out my blog post and web app about depth-first search, breadth-first search, and Dijkstra's algorithms visualized on the New York City subway network.

Date: May 2016

Wanting to familiarize myself with the GTFS-realtime specification and Node.js applications, I created a realtime map of Boston transit!

You can read the full explanation on my blog. The code is available on GitHub!

Date: March 2016

I tackled two birds with one stone on this project: 1) I learned the basics of creating and publishing my own Ruby gem, and 2) I implemented a simple algorithm to convert a GTFS feed into a GeoJSON file. I hope to be able to use this subproject in a larger transit visualization in the future!

You can read the full explanation on my blog. The code is available on GitHub and RubyGems.org!

Date: February 2016

I created a web tool to visualize New York City transit frequencies using Transitland and Mapbox. Schedule data from buses and subways (and even a few ferry routes!) is plotted for an example Friday and Saturday morning. You can view any of the layers together to understand differences in service between modes and days.

You can read the full explanation on my blog. Feel free to explore the web tool itself!

Date: July 2010

I developed a basic social network around stadium travel in an effort to learn PHP and MySQL. As you will notice, I had not yet learned how to make a website look decent in the slightest.

Stadium Fanatic was my first foray into web programming and was critical to my understanding of the modern web. Even better, it sparked my passion for stadium travel. I would not be well on my way to visiting all 30 MLB ballparks without this formative project!

The site is no longer on the web, but below is a picture of it in its prime.

Date: November 2015

I like baseball. I like stadiums. I really like transit. What better way to combine these interests than by learning vector graphics?

Click here to read my full summary and download the map as a PDF. And, as always, let me know about any recommendations you may have!

Date: January 2016

Aware of its applications to transit and urban planning, I learned the basics of Geographical Information Systems (GIS). I created the map below using QGIS and Inkscape.

Read about my study of the Transfort bus routes in Fort Collins, Colorado, in the full blog post!