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.

  • Boston
  • Chicago
  • DC
  • LA
  • New York
  • Philadelphia
  • San Diego
  • San Francisco
  • Seattle

Here is San Francisco’s network visualizing the probability that a ride starts in one neighborhood and ends in another:

San Francisco

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?



Washington, DC


New York


San Diego


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.

Featured articles

San Francisco, your Self-Driving Uber is arriving now

In September, we introduced the world’s first Self-Driving Ubers to the Steel City. Three months later, we’re bringing Volvo XC90s to San Francisco. We’re incredibly excited to work with Volvo to pair our state-of-the-art self-driving technology with Volvo’s outstanding vehicle development and core safety capabilities. Starting today, riders who request an uberX in San Francisco […]

Uber & Disney Join Forces For “Rogue One: A Star Wars Story”

Today we announced we’re collaborating with Disney on an activation that transforms the Uber  rider app into a themed Rogue One: A Star Wars Story experience. The in-app experience, which Uber riders can opt-into, will unlock special Rogue One: A Star Wars Story features as well as access to exclusive video content. Uber riders in […]

Let’s take care of each other

This flu season, we’re delivering free flu-fighting care packages across the country. When you receive a pack, you’ll have the option to request a free flu shot from a registered nurse–for up to 5 people.