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Aaron Gordon, who is a data reporter at Bloomberg News, has been working on his coding skills. And so for absolutely no reason whatsoever, he decided to map out the life of one of New York's Citi Bikes, specifically Citi Bike #32606. The dataset is pre-pandemic because Citi Bike stopped publishing unique bike identifiers for each trip around 2020. But based on historical data and far as we know, #32606 is the most-used traditional bike (i.e. not an e-bike) in the history of the Citi Bike network.
It began its life on October 15, 2017 at 11:08am in Park Slope, Brooklyn, and then went on to accomplish 7,060 miles (~11,361 kilometers) and 8,624 trips over a period of 806 days. This works out to an average of just over 10 trips per day. In total, this bike traveled the equivalent of a return trip from New York to Los Angeles, and then a short trip up to Burlington, Vermont. And it was all done with only leg power.
Here's the visual mapping that Aaron created:
What I love about this passion project is that it starts to show just how impactful something as simple as a single shared bicycle can be for a city. These bike networks are relatively new, but they're already doing a lot of heavy lifting when it comes to urban mobility. Earlier this week, we learned that in the City of London, cyclists now make up 2x the number of people in cars. And that of the people cycling, 17% of them do so using a shared bicycle.
In the case of New York, the Citi Bike network had ~128,000 active members and ~34,000 bikes as of February 2025. What you're seeing above is the story of just one them.
Cover photo by Spenser Sembrat on Unsplash
This is an interesting map to play around with. It allows you to see how many 15-minute neighborhoods and cities there are around the world. And it works by calculating the average time it takes to walk or bike to the closest 20 points of interest in 10,000 cities. These points include all of the usual suspects like places of work, schools, healthcare institutions, grocery stores, and so on. A blue cell indicates an average walk time < 15 minutes, and a red cell indicates an average walk time > 15 minutes. The darker the color, the shorter or longer the average time in minutes.
By this measure, it's hard to beat many/most European cities. Here are Paris and Barcelona:
Boy, population densities can be so misleading. The typical approach is to just take the number of people and divide it by a given area. This then gives you something like X number of "people per square kilometer." The problem with this approach is that there are countless factors that can skew your result.
Hong Kong, for instance, is really dense. But as a city, it also has a lot of green space, mountains, and other undeveloped areas. Only about a quarter of Hong Kong's land is developed. So when you divide total people by its administrative boundary area, it is going to appear less dense than it really is.
One alternative approach is to use a method known as population-weighted density. The way this works is that you take the average densities of smaller more granular subareas and then weight them by the population of each subarea. It is a little more complicated to calculate, but the overall intent is to try and capture a density figure that more accurately reflects what the average person experiences on the ground.
And this is exactly the method that Jonathan Nolan decided to use in his new website CityDensity.com. What his site allows you to do is compare population-weighted densities across various cities, and then see how it tapers off as you move outward from their city centers.
Once again, it is hard to beat Paris' supremely dense mid-rise built form:
Well, that is, until you check out Hong Kong:
Charts: CityDensity.com
Aaron Gordon, who is a data reporter at Bloomberg News, has been working on his coding skills. And so for absolutely no reason whatsoever, he decided to map out the life of one of New York's Citi Bikes, specifically Citi Bike #32606. The dataset is pre-pandemic because Citi Bike stopped publishing unique bike identifiers for each trip around 2020. But based on historical data and far as we know, #32606 is the most-used traditional bike (i.e. not an e-bike) in the history of the Citi Bike network.
It began its life on October 15, 2017 at 11:08am in Park Slope, Brooklyn, and then went on to accomplish 7,060 miles (~11,361 kilometers) and 8,624 trips over a period of 806 days. This works out to an average of just over 10 trips per day. In total, this bike traveled the equivalent of a return trip from New York to Los Angeles, and then a short trip up to Burlington, Vermont. And it was all done with only leg power.
Here's the visual mapping that Aaron created:
What I love about this passion project is that it starts to show just how impactful something as simple as a single shared bicycle can be for a city. These bike networks are relatively new, but they're already doing a lot of heavy lifting when it comes to urban mobility. Earlier this week, we learned that in the City of London, cyclists now make up 2x the number of people in cars. And that of the people cycling, 17% of them do so using a shared bicycle.
In the case of New York, the Citi Bike network had ~128,000 active members and ~34,000 bikes as of February 2025. What you're seeing above is the story of just one them.
Cover photo by Spenser Sembrat on Unsplash
This is an interesting map to play around with. It allows you to see how many 15-minute neighborhoods and cities there are around the world. And it works by calculating the average time it takes to walk or bike to the closest 20 points of interest in 10,000 cities. These points include all of the usual suspects like places of work, schools, healthcare institutions, grocery stores, and so on. A blue cell indicates an average walk time < 15 minutes, and a red cell indicates an average walk time > 15 minutes. The darker the color, the shorter or longer the average time in minutes.
By this measure, it's hard to beat many/most European cities. Here are Paris and Barcelona:
Boy, population densities can be so misleading. The typical approach is to just take the number of people and divide it by a given area. This then gives you something like X number of "people per square kilometer." The problem with this approach is that there are countless factors that can skew your result.
Hong Kong, for instance, is really dense. But as a city, it also has a lot of green space, mountains, and other undeveloped areas. Only about a quarter of Hong Kong's land is developed. So when you divide total people by its administrative boundary area, it is going to appear less dense than it really is.
One alternative approach is to use a method known as population-weighted density. The way this works is that you take the average densities of smaller more granular subareas and then weight them by the population of each subarea. It is a little more complicated to calculate, but the overall intent is to try and capture a density figure that more accurately reflects what the average person experiences on the ground.
And this is exactly the method that Jonathan Nolan decided to use in his new website CityDensity.com. What his site allows you to do is compare population-weighted densities across various cities, and then see how it tapers off as you move outward from their city centers.
Once again, it is hard to beat Paris' supremely dense mid-rise built form:
Well, that is, until you check out Hong Kong:
Charts: CityDensity.com
The city propers are completely blue, and you have to go pretty far out (or up into mountains) to find areas that don't have 15-minute conveniences.
Toronto has a strong core and isn't terrible overall, but expectedly, we aren't as uniform and as deep blue as Paris and Barcelona:
Where things get really interesting, though, is when you look at cities like Dallas and Houston:
It's clear where these cities stand on walkability.
The city propers are completely blue, and you have to go pretty far out (or up into mountains) to find areas that don't have 15-minute conveniences.
Toronto has a strong core and isn't terrible overall, but expectedly, we aren't as uniform and as deep blue as Paris and Barcelona:
Where things get really interesting, though, is when you look at cities like Dallas and Houston:
It's clear where these cities stand on walkability.
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