Having only Lat/Long of pickup data is disappointing (would have liked the dropoff data too), but the date range can be correlated to the NYC Taxi data set, which exists for all of 2014.
The Aggregate_FHV_Data.xlsx contains data on Lyft as well. In September 2014, Lyft did 115,999 total pickups in NYC, while Uber did 1,028,136 pickups. (however, Lyft didn't have any activity in NYC until the end of July.)
I love your visualizations of the NYC Taxi dataset, minimaxir =]
I was just going to mention that if people were interested in exploring this type of data, there exists a Kaggle competition[1] for "Taxi Trajectory Prediction". The data contains the full GPS paths of the taxis and comes with pre-existing scripts you can run online, including a Python script for visualizing the city via taxi paths[2].
There's even a secondary challenge for predicting travel times which include visualizations of taxi travel speed, producing "veins" on the city streets proportional to the speed you can travel along them[3].
I'm not minimaxir but anyway... that's an odd way to put it. My guess is, he/she is not the kind of software QA engineer you might be accustomed to depending on the kinds of companies you've worked at. Think of automated custom static and dynamic code analysis, continuous integration, build systems, deployment monitoring, etc. Places like Google and Stripe (and many other technical organizations with good engineering culture) have very skilled people doing these things.
I'm a normal/infrastructure engineer who reluctantly ends up focusing on test systems every once in a while. I get all the tests running, from a single script, with all results collated and machine readable, get CI set up properly, make the system reliable enough to trust, etc. Because someone has to do it! And yes I've done this in organizations where there was a QA engineer or two, who did reasonably cheap semi-automated QA, but couldn't put together a whole system and make it reliable enough to run on its own. But there are definitely a few places where QA engineer is not the "lowest rank".
General comment about QA: A lot of people do QA because they're interested in the 'story' or the 'business case' and simply find that interesting. It is not a starter-developer job.
That's enough for interesting visualizations and statistical analysis of comparisons between the two, although the original 538 article (http://fivethirtyeight.com/features/uber-is-serving-new-york... ) is pretty good. (for my own visualizations of the NYC Taxi dataset, see my blog post: http://minimaxir.com/2015/08/nyc-map/ )
The Aggregate_FHV_Data.xlsx contains data on Lyft as well. In September 2014, Lyft did 115,999 total pickups in NYC, while Uber did 1,028,136 pickups. (however, Lyft didn't have any activity in NYC until the end of July.)