Data Science meets life: finding a New York apartment

Challenge: imagine you’re moving to New York and you have a week to find a place*.  You want to live in a “hip” neighbourhoods but not get ripped off.

You find a list of 10 up and coming neighbourhoods by StreetEasy… 10 – you see!  But you only have a week! Time to use your data science skills to find the MOST up and coming neighbourhoods to focus your search on.


Solution: After a short amount of pondering, you reckon that lots of people go out in the evening in hip neighbourhoods and that’s an early indication of an awesome place to live. Think Shoreditch or Brixton for the Londoners. SO you download open data from the New York Municipal Transport Authority and look at people leaving the subway in the evening. It’s either people going out enjoying themselves or people heading home (and hopefully enjoying their homes!)

Outcome: You find that Elmhurst is trending downloads… What happened to its popularity in 2016?! (Note to self: investigate more. Murder? Really bad Zillow review?) Don’t go there! Fort Greene and Woodside seem to be the places to go! Right, now out to explore the streets of New York!

Full write-up and presentation.

* I’d actually just moved to San Francisco and encountered a similar challenge but NY has awesome open data!


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