Got a Ride? Ridesharing Equity in Chicago

Fall 2021
Introduction to Urban Data Informatics
Columbia GSAPP
Prof. Boyeong Hong

I expected Uber and Lyft pickups to cluster in white, wealthy Chicago neighborhoods. 42 million trips later, the data said no — the pickups go where the trips are, which mostly means downtown.

Open the interactive map → →

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The Question

Hypothesis

Rideshare access tracks
income and race

42M trips · 13 months
77 Community Areas
EPSG:4326

Uber and Lyft are now a meaningful share of Chicago's transit mix. Whether they reach the neighborhoods that need them is a separate question.

Guess: pickups skew toward wealthier, whiter community areas. The test set: 42 million anonymized rideshare trips from the City of Chicago's TNP dataset (every Uber, Lyft, and Via pickup, Oct 2020 – Nov 2021), joined against Census income and race data across all 77 Community Areas.

Pickups vs. Income

Choropleth shows median household income; yellow dots scale with pickup count per community area

Choropleth of median household income across Chicago's 77 Community Areas, with yellow scatter overlay sized by rideshare pickup count

PYTHON · FOLIUM · CHOROPLETH

If pickups tracked income, the largest yellow dots would sit on the darkest-blue (highest-income) North Side tracts. They don't.

Pickups vs. Race

The same scatter overlay, this time on the percentage of white residents per community area

% WHITE

Northern lakefront and Near North Side hold the highest white population shares.

% NONWHITE

The South and West Sides — mostly nonwhite — still get plenty of pickups, especially near employment corridors.

Side by side, the maps don't track demographics. Downtown and the Near North Side dominate pickups whether you're looking at the income map or the race map — they dominate because that's where the trips originate, not because of who lives there.

Key Numbers

42M

Trips Analyzed

Community Areas

13 mo

Time Window

Pan, zoom, hover

The original Folium maps from the notebook. Click any bubble for its Community Area name and count.

Pickups. Bubble size = total rideshare pickups in that Community Area.

Median income. Bubble size = median household income.

% white. Bubble size = share of white residents. Notice it looks a lot like the income map.

All three. Pickups, income, and race on the same map. The pickup bubbles don't sit where the demographic bubbles sit.

Findings

Hypothesis: disproven. Pickup volume doesn't track income or share of white residents at the Community Area level. Whatever rideshare is doing in Chicago, it isn't quietly skewing toward whiter, richer neighborhoods.
High income can mean low demand. One of Chicago's highest-income areas had among the fewest pickups — those residents own cars and drive themselves.
Pickups follow trips, not people. The Loop, the Near North Side, and the big employment corridors dominate, full stop. That's where people actually need rides — regardless of who lives there.
Income and race are nearly the same map. The two choropleths are visual near-mirrors of each other in Chicago. Any single-variable equity test runs into that wall before it can say much.

This project was completed for Introduction to Urban Data Informatics at Columbia GSAPP (Fall 2021, Professor Boyeong Hong). Data sourced from the City of Chicago TNP dataset and US Census. Notebook and Folium HTML outputs live on GitHub; an earlier version of this writeup is on Medium.