Inspiration
The Fannie Mae challenge inspired us to create an application for first time home buyers.
What it does
This project is a web application designed to help first-time homebuyers find the best neighborhoods based on personalized criteria. Users can adjust sliders to filter ZIP codes by factors such as school ratings, number of hospitals, average home prices, population, and available housing units. The app dynamically ranks and displays the top five ZIP codes that match the selected preferences. An interactive Mapbox map visually highlights these top ZIP codes with color-coded indicators, providing both detailed rankings and geographical context to support informed home-buying decisions.
How we built it
We used React and Next.js and TypeScript for our frontend development. We used Python and FastAPI for our backend development.
Challenges we ran into
Finding extensive and reliable zip code specific data sets to analyze, formatting our data in an appealing way, and fixing never ending bugs!
Accomplishments that we're proud of
Coloring the heat map according to the color codded zip code rankings.
What we learned
Starting with a concrete idea before development always helps.
What's next for House Hackers
We hope to scale this for the entire country!
Built With
- css3
- fastapi
- html5
- javascript
- next.js
- python
- react.js
- typescript
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