Google Scholar Visualization

One of the most common images I see during science presentations is the frequency of publications within a particular field over time. It’s a great way to show the growth of the field while attempting to validate the worthiness of the research that follows. As far as I can tell, most people manually assemble this data with sequential searches on Google Scholar or Web of Science. This seemed like a straightforward opportunity for automation, so I made a little website that does just that. It takes a Google Scholar search query and a range of years and plots the number of results over time.


Taylor Swifting

I had a really random idea the other day for a simple coding project using the LastFM API: When was the last time you listened to Taylor Swift? This is obviously an extremely important statistic to know for the Taylor Swift obsessed. I already made a tool to lookup the Read more…

Foursquare Heatmap

I’m a regular user of the location-based social network Foursquare mainly as a source of recommendations for new places to try. I typically check in everywhere I go with the exception of private residences (can’t let people stalk me that easily), so I have a pretty extensive log covering my location history. While it’s not quite as extensive as the Google Maps Location History, it does a good job representing the places I visit.

In the past I’ve messed around with making heatmaps of latitude/longitude coordinate pairs without much success. It always required tedious manipulations to properly overlay on top of a Google Maps image and wasn’t really worth the effort. I recently stumbled across a Python-based heatmap tool created by Seth Golub that takes a list of coordinates and turns them into a beautiful heatmap that can be overlaid on a OpenStreetMap. Once I figured out how to get Python Image Library installed properly, I used my private Foursquare feed to grab every checkin over the past year. Extracting and exporting the GPS coordinates included with each XML element only required a few lines of code. The resulting maps, which have been limited to only show downtown and the general Austin area, are displayed below.