Analyzing and visualizing data from rideshare apps
I drive for Uber and Lyft as a side gig, usually at night, but my day job often revolves around data analysis and journalism.
On the docket is building a dashboard to compare Uber and Lyft prices across cities (I’ll start with the United States). I’ll also be tracking and analyzing my own rides and fares to learn more about how to become a profitable driver. You can visit our maps page for some visualizations related to real-time rideshare apps.
Below are some graphics illustrating UberX prices (base, per minute, and per mile) across the United States. The first dashboard plots the base price that everyone pays as soon as an UberX ride begins. You can see that the Hamptons, out on the east end of Long Island, is the most expensive region with a base fare of $10. Flagstaff, Arizona and Santa Fe, New Mexico are also outliers at $8, compared to the average of $2.44. I’ve also colored the bars by the cost per mile.
The scatterplot below compares per mile and per minute charges. As you would expect, there’s a pretty strong relationship between the two, but you can see there’s a lot more variation in the per mile charges than the per minute charges. I’m not sure why this is, but it’s something I’d like to explore further. Once again, the Hamptons, Flagstaff, and Santa Fe are outliers.
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