Here’s a chart from a article on the relationship between Uber and public transit in New York City, via the incomparable fivethirtyeight blog. I recommend the whole thing, but the key part of the argument centers around this grid comparing income to transit access:
Here’s how the author describes the chart:
Put another way: Given the high fixed costs of vehicle ownership, the first and most important transportation choice a New York household makes is whether to own a car. Residents who go without a car may use some combination of public transit, taxis, Ubers and other alternatives (like bicycling and carpooling) to get where they need to go. In that sense, Ubers, taxis and public transit are complements to one another instead of competitors.
But transportation options are also constrained by a commuter’s income. Our data suggests that we might place New Yorkers into about five broad categories, based on their income and ease of access to public transit.
Now these categories are specific to New York City, a unique American city to be sure. But could you make the same kind of “broad outcomes” chart for someone in the Twin Cities? If so, what would it look like?
I think that matrix would be a lot more interesting if the sizes of the income and access to transit boxes was weighted to the real sizes based on actual stats.
I wonder if someone could put something like that together by aggregating census tracts by level of transit service. Does the census include information about transit ridership vs car use too?
I know I’m talking to myself but this makes me wish I were better with gis. I’m data nerding hard here.
Thanks for sharing this. This is a fantastic graphic.
Interesting and unusual style of presentation, but the vertical contents and scale seem ambiguous: what does “access to public transit” mean, and does it reflect actual usage, as in the “private car” contents?
I just think it means, “is your housing close to quality bus or subway service”?
Then if the “private car” means having access to one, an analogous chart for the Twin Cities might look quite different. (Here, a lot of low income people own cars.)