PGHNeighborhoodPicker

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  homepage

Inspiration

We want to help people moving to Pittsburgh find the best neighborhood.

What it does

It takes in some information about the user and returns a heatmap with all of the neighborhoods in Pittsburgh.

How we built it

We created a mySQL database which included all of our data for the project. We then used python to run the calculations. Then we created a React Project and used Flask to incorporate Python, which is used for generating results.

Challenges we ran into

Connecting out cloud database to our python code, connecting our front and backend together.

Accomplishments that we're proud of

We got a whole dictionary of similarity scores of neighborhoods using machine learning and database management.

What we learned

We learned that developing a project is never easy. It requires a lot of skills to get a project run and a lot of different departments.

What's next for PGHNeighborhoodPicker

Make the website fully work as specified that constantly updates.

Presentation

https://www.canva.com/design/DAGSKCvd0IA/FWJMiczj-RuLzY02XMjShg/edit?utm_content=DAGSKCvd0IA&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton

Built With

• css
• flask
• html
• javascript
• mysql
• python
• react