How Chicagoans commute map: An interview with the cartographer

Chicago Commute Map by Transitized

A screenshot of the map showing Lakeview and the Brown, Red, Purple and Purple Line Express stations.

Shaun Jacobsen blogs at and yesterday published the How Chicagoans Commute map. I emailed him to get some more insight on why he made it, how, and what insights it tells about Chicago and transit. The map color-symbolizes census tracts based on the simple majority commuting transportation mode.

What got you started on this map?

It was your post about the Census data and breaking it down by ZIP code to show people how many homes have cars. I’ve used that method a few times. The method of looking up each case each time it came up took too long, so this kind of puts it in one place.

What story did you want to tell?

I wanted to demonstrate that many households in the city don’t have any cars at all, and these residents need to be planned for as well. What I really liked was how the north side transit lines stuck out. Those clearly have an impact on how people commute, but I wonder what the cause is. Are the Red and Brown Lines really good lines (in people’s opinions) so they take them, or are people deciding to live closer to the lines because they want to use it (because they work downtown, for example)?

[Find out where people are commuting to with Where We Work.]

The reason I decided to post the map on Thursday was because while I was writing the story about a proposed development in Uptown and I wanted  information on how many people had cars around that development. As the map shows, almost all of Uptown is transit-commuting, and a lot of us don’t even own any cars.

And what did you find?

I definitely did not expect to see so much of River North and Streeterville as “walk”.

I expected to see more transit use along transit lines, because only the north side lines really seem to get people on transit to commute. There are “pockets” along certain lines, but if you look at the Orange Line, for instance, there’s not as many people using it. What interests me more is finding the little “islands” where there are people commuting in ways different from the tracts around them. Like tract 622, which is right where the Brown Line branches off toward Kimball. It has higher rates of car ownership compared to the surrounding tracts, too.

I think it’s also interesting to note that no Metra station, except a few on the Electric line, seemed capable of getting most commuters on a train. [I’m going to guess because only the Electric line has a frequency that encourages its use.]

What didn’t surprise me is that the Blue Line stations northwest of Belmont, where they’re in the freeway, is that they didn’t seem to do much at all. I can’t help but think it’s because the placement of the stations is so far removed from the surrounding residences or destinations that it almost doesn’t even seem like it’s there.

I think the biggest shortfall of any sort of map like this is that you can see how people are getting to work, and where they live, but you can’t see where they finish their trip. [Shaun didn’t know about Where We Work when I interviewed him].

If you could even get the “end tract” you could look a lot further into why people might (or might not) be choosing a certain mode of transportation to work.

What data and tools did you use?

I first used the Chicago Data Portal to grab the census tract boundaries. Then I grabbed all of the census data for B08141 (“means of transportation to work by number of vehicles available”) and DP04 (“selected housing characteristics”) for each tract and combined it using the tract ID and Excel’s VLOOKUP formula.

I had to calculate the “mode share” for each from the B08141 data, showing vehicle ownership, by dividing each mode’s total by the total number of commuters. Then I just used Excel to find the highest number and coded it 1 (drive alone), 2 (carpool), 3 (transit), 4 (walk), 5 (bike), or 6 (telecommute) so that I could apply a conditional style in TileMill.

I had to clean up the census tract numbers so they were all 6 digits, appended with 0s if not 6 digits long (e.g. 170800 instead of 1708, since some tracts get split into 1709.01, 1709.02, etc), and used QGIS to join the Census data with the census shapefile. Then I exported it as a shapefile to be used in TileMill. I also grabbed the CTA lines and stations, and Metra lines and stations, from the Chicago data portal, and cleaned them up (so stations outside the city limits were removed).

To display the map and legend I used my custom CSS and Mapbox.js, along with the Leaflet Hash plugin. The tiles are hosted on MapBox.

What issues did you run into?

The Census data exports are not user friendly and I had to clean up a lot of the data. The census tract numbers were the hardest. They had to be perfect or else QGIS wouldn’t join them.

I also ran into a problem with TileMill. Earlier versions of the map I made would actually darken the tract if the dominant commute mode were responsible for more than half of all commute journeys. Many tracts closer to the center of Chicago were “blended”, so no mode was over 50%. But if any tract had a commute mode that was 50% or more, it was slightly darker. Now it doesn’t work, and I can’t figure out why.

Steven Vance

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