cycling – ilari.scheinin.fi

Where I’ve Been and How?

Ilari Scheinin — Wed, 08 Jul 2015 12:24:44 +0000

I have been running the Moves app on my phone for almost two years. I guess its main idea is to be an activity tracker; it’ll tell you how much you’ve walked, ran, or ridden a bike, without you having to remember to turn it on before starting an “activity”. But for me the main point isn’t as much the activity part as it is the tracking part. Without me having to do anything, the app silently collects data about my movements in the background. I can then download the accumulated data and play around with it in R.

When I was at the Recurse Center, I needed a little project to work on learning ggplot2 and shiny, and chose to do a remake of this old blog post on the shares of different modes of transportation I use. The end result is packaged into a shiny app, and shows for example that in New York I walked a lot more than I used to while living in Amsterdam or Helsinki, and that last summer I spent a lot of time on boats. A more subtle difference is that in Amsterdam I seemed to use trams only for commuting to work.

I also wanted to try out some mapping with leaflet, and made another app that shows all my movement while I was in New York. If all checkboxes are turned on, four months of data seems to be a bit much to handle performance-wise, and the app becomes slow and sometimes crashes (turns gray and stops responding). Anyways, it was a fun experiment to do.

The source code is available on GitHub.

Citi Bikes and Neighborhoods

Ilari Scheinin — Wed, 08 Jul 2015 12:24:13 +0000

New York City has an excellent bike sharing system called Citi Bikes. When I was at the Recurse Center, I frequently used the bikes for commuting. What was annoying though, was that every now and then all the nearby docks were empty by the time I was leaving. I guess this was because it was mostly a residential area, so in the mornings people would grab the bikes and ride them to work, and in the evenings the bikes would flow back. A business district would naturally see the opposite pattern. (I know the operators rebalance bikes between stations, but I don’t know if this happens intra-day or just to correct slower drift patterns.)

In addition to being a convenient way to move around, another nice thing about the system is that they release their ride data publicly. I decided do a little experiment in R. I downloaded all their data and used dplyr to count the number of bikes arriving to and leaving from each station. I did that for each hour of the day and separately for weekdays and weekends.

In order to visualize the patterns, I plotted them with ggmap and made a little shiny app.

To identify neighborhoods with similar usage patterns, I used K-means clustering and put the results in another shiny app. It also contains a plot of the variance explained for assessing a suitable value for K.

The source code is available on GitHub.

How I Move

Ilari Scheinin — Thu, 02 Oct 2014 09:22:44 +0000

With 12 full months of Moves data, I thought it would be a fun experiment to make some plots. These show how I move around in terms of time spent and distance traveled, both for relative share of each mode of transport, and for the total time or distance. Flying is excluded.