Inspiration
Public transit is essential, but safety is a major concern. We wanted to explore crime patterns near bus stops in Montreal to identify high-risk areas and provide insights for safer commuting.
What it does
Our project visualizes crime rates near bus stops using Montreal’s open data. We map incidents, highlight hotspots, and uncover patterns to help improve public safety and city planning.
How we built it
- Collected crime and bus stop data from Montreal’s open data portal.
- Cleaned and processed the data using Python and JavaScript.
Challenges we ran into
- Cleaning and merging datasets with different formats.
- Ensuring accurate geospatial mapping of crime incidents.
- Balancing detail and clarity in our visualizations.
Accomplishments that we're proud of
- Successfully mapped crime trends near transit stops.
- Created clear, insightful visualizations.
- Developed a data-driven approach that could assist policymakers in improving transit safety.
What we learned
- Handling and analyzing geospatial data effectively.
- Extracting meaningful insights from real-world datasets.
- The importance of clear storytelling when presenting data.
Log in or sign up for Devpost to join the conversation.