Inspiration
We met each other for the first time at Technica, and Fannie's Mae's perfect community challenge drew us to its purpose because as students and teens, we recognize the need for a more streamlined system to help us identify areas to live. Zillow, a similar service, doesn't take into account factors beyond cost and area: we wanted to include those as well as characters of you, the user, in order to create a unique house searching experience exactly suited to you.
What it does
You can select the standard factors such as urban/rural, rent/buy, cost, state, etc. (to increase calculation speed, we used counties, schools, and zip codes from Maryland), and added education, type of accommodation, type of community (family-friendly, retirement community, etc.) to make our search engine much more personalized.
How we built it
We gathered data from the Maryland Transit Association and used API requests to Zillow to gather the Maryland-specific information of House Price Index by zip code and bus stops across the state. Using reverse geolocation and the csv library, we read this into a Suburbia object and added US Census Bureau data such as urban/urban-cluster/rural associations to our Suburbia object. We classified communities by zip code
Challenges we ran into
Few datasets are standardized in how they're formatted; US Census uses FIPS codes to identify counties, UACE to identify urban areas, school rankings are identified by counties, and transit stops are identified by lat/lng coordinates. Converting all those numbers into zipcodes where the codes are not immediately interchangable was a huge obstacle that we faced while trying to code up this project. There's simply so much data out there that centralizing them all into one portal was the most time-consuming task.
Accomplishments that we're proud of
Although half our team is made up of non-coders, we were each able to contribute according to our strengths: we had two people on data collection, researching and compiling population and demographic data onto Google Docs/Excel, one person working on Bootstrap for the first time, and one person utilizing API requests and ElementTree XML parser for the first time. We came in as newbies, but we were able to explore outside our comfort zone to create a beautiful site that we hope to build on in the future.
What's next for Suburbia
Using data that Zillow packages on their website, we think, with a bit more time, we will be able to easily add sale and rental listings to the zones that we create on the map. Currently, our website is created to highlight the top 5 zipcodes that would be the best suit for the user, as well as identifying information; in the future, Suburbia will be able to offer houses available to buy/rent in the perfect communities that we identify.
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