Screenshot of the map with the data

About the Project

Inspiration

The idea for this project came from a desire to analyze and visualize livability across different districts in Montreal. We wanted to create an interactive tool that could help users explore and compare different areas based on various criteria.

What We Learned

Throughout this project, we gained experience in:

Streamlit for building interactive web applications
Pydeck for visualizing geospatial data
Data analysis to calculate and interpret livability scores

Challenges Faced

Integrating Pydeck with Streamlit: Making selections on the map trigger updates in the UI was tricky.
Dynamic Filtering: Ensuring that the total score updates properly when filters change required careful handling.
Custom Styling: Streamlit doesn’t support extensive styling natively, so we had to work with HTML and CSS to format tables and legends properly.
Data Accuracy: Our data analyst had to ensure that the collected data was reliable and the calculations reflected real-world livability factors.

Final Thoughts

This project was a great opportunity to combine data visualization, interactivity, and web development. It helped us understand how to present complex data in a user-friendly way while tackling real-world challenges in UI, backend logic, and data analysis.