There’s nothing better than spending an afternoon with an interesting dataset.
True, this might be a case of different strokes for different folks, but I really do enjoy digging into a big ol’ stack of numbers and seeing what I can find. My brain has always had that numerical curiosity.
Needing a break from both my basketball and COVID-19 work, I widened my circle a bit. I filtered through the list of public datasets on OpenData.Utah.Gov, found that the Utah Transit Authority had a lot of fun data that I had some questions about, and began exploring.
As you would expect, UTA keeps close tabs on its ridership numbers, across all of its various forms of transport: light rail (TRAX), FrontRunner commuter trains, buses of all forms, paratransit and so on. In fact, it even keeps data on where riders are getting on and off of buses.
Those ridership numbers absolutely plummeted as soon as the pandemic started — people, understandably, didn’t want to be in the close company of strangers anymore. I wanted to learn about that story: How much did they change? How much have they recovered? Are there any interesting trends in the data?
Here are UTA’s numbers showing average weekday ridership separated by mode of transport. In this tool, you can select the mode of transport you’re interested in looking at in the drop-down menu at the top left. Last year’s numbers are in red, 2021′s numbers are in blue, and the previous three years have their data in pale colors.
Clicking through the graphs, we see really similar patterns across nearly all types of transport: a huge drop when the pandemic hit, and slow recovery in the months since. Percentagewise, Utah saw the biggest drops in FrontRunner ridership, which plunged nearly 90%. TRAX ridership fell about 75%, and bus ridership slumped about 70%.
The biggest month-to-month recovery came in the most recent month for which we have data, from August to September 2021. But as you can see, that’s also a month in which UTA typically sees its biggest ridership in general. Overall, UTA is still seeing traffic numbers about 40% lower than usual.
It’s also interesting to note that the ski bus routes lost the lowest amount of ridership. Though numbers vary from month to month more than other routes (and remember, these are weekday numbers), by February, the ski bus had seen only a 38% drop in traffic; in that month, every other form of UTA transport was down 60%. Perhaps congestion in the canyons is pushing people toward the buses even when they’re not wanting to use them in other aspects of their lives.
Bus stop data
UTA also has the data on every bus stop in its system, of which there are thousands. Here, I’ve mapped them all for you. This is a fun map to click around in — find the nearest bus stop to you, click on it, and see how average weekday ridership has changed!
The red dots are bus stops that have seen ridership losses between February 2020 and October 2021. The blue ones are bus stops that have seen ridership gains between those same months. The more red, the bigger the losses; the more blue, the bigger the gains. And as you can see, there are more red dots than blue dots; that’s to be expected when dealing with overall losses like the ones discussed above.
I was curious to see if there were any trends I could discern regarding which bus stops saw the biggest drops. I had a hypothesis: essentially, that cushy east- and south-siders might have been more quick to stop riding the bus than their west and north-side counterparts. So I ran a calculation to see if there was a correlation between the latitude/longitude coordinate of the stop and its decline in ridership.
What did I find? Well, that my hypothesis was true, but by the tiniest margins. In fact, there was only a 0.02 correlation between a stop’s north-south coordinate and its ridership, and only a 0.05 correlation between a stop’s east-west coordinate and its ridership. In fact, this means that less than 1% of a stop’s ridership change can be attributed to its coordinates on the map.
That makes some sense, though. If you click through these maps, you’ll see wildly different numbers, even in very close bus stops. A business opening or closing near that stop, an apartment building going up, or even just a new public transit-minded family moving in or out can drastically change any individual stop’s ridership.
How about with UTA’s trains? Well, let’s look at that map:
There are two stops that have actually seen increases in their ridership. Both are on TRAX’s green line. I suspect the increases here are due to the temporary airport stop change pushing riders to get on and off that line sooner.
And on this map, because of the reduced number of stops, it’s a little easier to see trends in the data. Ridership downtown, at the University of Utah and in the south end of Salt Lake County declined the most, with decreases in the 50% to 70% range. But in the middle of the valley, the decreases are much closer to 30%. The Fairmont Station stop, the last stop of the lightly ridden streetcar line in Sugar House, has seen only 10% decreases, as that area experiences growth.
Meanwhile, decreases in FrontRunner traffic were seen least in Ogden, which has seen a 37% decline. Provo, too, seems to still rely on the train similarly. But FrontRunner traffic fell off much more in Salt Lake City proper and the suburbs, with declines of 50% to 60%.
This data takes into account both people getting on and coming off the train, so the results were a bit surprising to me: I usually think of FrontRunner as a service to get people to Salt Lake City from outlying areas and vice versa. This data indicates that might be changing somewhat, as perhaps more people are taking other trips from, say, Ogden to Farmington.
Overall, though, public use of public transit isn’t especially close to what it was just two years ago. How many of those trips have been eliminated altogether versus how many have been replaced by personal cars is a worthwhile topic of exploration — but we’ll save that for another afternoon.
Andy Larsen is a data columnist for The Salt Lake Tribune. You can reach him at firstname.lastname@example.org.