When I was buying a new apartment in Helsinki, I really wanted to optimise the location. I work as a consultant so I want to be able to move around as effortlessly as possible. However, I have never seen any data on how well the public transit works in the different parts of the city. The travel time maps display the time it takes from place A to B, but in this case that’s not enough. I didn’t know where I wanted to buy the flat from. Or where I would work in the near future.



So I did my own analysis: I calculated the travel time from every address to every other address in Helsinki around 7:30-8:00am (about 30 billion searches total!). Then I calculated the (weighted) average travel time to anywhere in the city, using amount of jobs in the target area as weight.

The result is pretty interesting. You can clearly see how some expensive neighbourhoods are not actually very accessible. (Well, anybody who lives in Helsinki knows it already, but finally there is a computer software that agrees!)

I didn’t stop there. I already had a software that could quickly analyse the travel times in Helsinki so why not try to optimise the location based on the pubs that serve good beer! I used a list of “top 20 beer bars”, and created a map that displays the average travel time to home after closing time 1:30am.

Check the visualisation at helsinki.wanhala.net.

And please note that as this is a hobby project, the algorithm is not 100% tested. There may be errors in the data. I just haven’t found any.

Tech stuff

The algorithm was made from scratch in nodejs. The data I used: