Mapping a City’s Flow Using #UberData
In this #UberData post we show how the 9 major US cities “flow” — and how people move from one part to another.
- New York
- San Diego
- San Francisco
Here is San Francisco’s network visualizing the probability that a ride starts in one neighborhood and ends in another:
The neighborhoods are outlined in grey and at the centroid of each neighborhood is a circle, the size of which represents the proportion of rides that flow out of that neighborhood. The circles are colored according to which statistically-identified subnetwork they belong. Every neighborhood that sends a ride in has a line of the same color as the source neighborhood connecting it to its destination. The weight of each line represents the proportion of rides that go from the source neighborhood to its target. (Technically speaking this is a weighted digraph.)
In this case, as with before, most of the action is going on between neighborhoods in a radius around downtown San Francisco. What about the other cities?
What can we do with this information? Well we can identify networks of “related” neighborhoods that are the “hub” of the city, into and out of which the most people flow.
Here are the most tightly connected neighborhood pairs for each city:
- Boston: Back Bay-Beacon Hill / Boston Central
- Chicago: Near North Side with itself (…guess people don’t want to leave!)
- DC: Capitol Hill / Downtown
- LA: WeHo with itself
- New York: Midtown with itself
- Philadelphia: City Center West / City Center East
- San Diego: Mission Bay with itself
- San Francisco: SoMa with itself
- Seattle: Capitol Hill with itself
What’s amazing is that, in most cities, people tend to stay within a neighborhood taking relatively short rides.
What is it about Near North Side, WeHo, Midtown, Mission Bay, SoMa, and Capitol Hill that make them so popular? These neighborhoods have some kind of activity gravity keeping people within them, and that’s fascinating.
What variables account for this? Is it because people tend to live, work, and play in the same neighborhood? Do they have the most popular bars, restaurants, and cultural centers?
Cities are amazing places and #UberData can give us a peek into their style like this.
We are excited to surpass the 100th city mark by welcoming two Brazilian cities, Rio de Janeiro and Belo Horizonte, to the UberEATS family. From Atlanta to Warsaw, people have truly embraced this easy and reliable way to discover the food they love at the push of a button. Whether that’s an Indian inspired samosa, a good old-fashioned American burger or Vietnamese pho, people in 27 countries are using UberEATS to get a taste of the world’s flavors at the push of a button.
We’re excited to expand the Uber for Business platform beyond business travel, to include a world-class customer transportation solution, Uber Central. With Uber Central, organizations of all shapes and sizes can now easily provide on-demand, door-to-door transportation for their customers, clients, and guests.
A little over a year ago, we set out to put a new spin on an old classic–make reliable food delivery available at the tap of a button. Back then, we started by offering food in the UberEATS app from 1,000 pioneering restaurant partners in four cities. And today, more than 40,000 restaurants globally–from poke shops to pasta spots–are sharing food with customers through UberEATS. With a growing restaurant community comes more choices and more complexity. So we’re cooking up features to continue to make UberEATS easy and reliable. Here is a taste–