MuniPulse

I’ve always been interested in civics and have been curious about what it takes for a city to be maintained. I wanted to make something that could be used to address problems in my city, such as potholes. This tool identifies anomalies in 311 data, and streamlines data preparation. It also includes feature selection with assisted feature creation being a work in progress. I built it using Python and Streamlit.

Managing my time and deciding on what tools I'd use was a challenge. There was kind of a push and pull between “do I want to use this tool that I am familiar with but might not be as efficient for my goals, or do I want to use the more efficient tool that is totally new but may take time to learn?” I chose the latter because my focus is speed and learning. I'm proud for stepping out of my comfort zone. This is a learning curve that took time to embrace, but it was worth it. I learned a lot about algorithms, time management, applying statistical knowledge, and manually processing data. The next step is assisted feature creation and implementing secure user authentication with Auth0, as well as integrating RapidMiner.

Built With

• python
• streamlit