🇨🇦 MapleRadar: Toronto Survival Causality Mapping
MapleRadar is an interactive simulation and data visualization tool that maps the complex causal chains of navigating life in Toronto. From TTC service cuts to the grocery monopoly and housing crisis, this tool illustrates how urban stressors impact student mental health, academic performance, and financial stability.
The Team & Contributions Member 1:[shero233]: Lead Developer – Streamlit UI, NetworkX Graph Logic. Member 2:[alexhabbick]: Backend/Algorithm – Impact calculation and "GPA Risk" simulation.
What the Project Does Dynamic Scenarios: Simulates real-world events like "TTC Service Cuts" or "Loblaws Price Hikes."
Causality Mapping: Visualizes how one urban factor (e.g., rent increase) triggers a chain reaction affecting productivity.
Academic Risk Assessment: Tracks "GPA Risk" and "Academic Probation" status based on simulated lifestyle stressors.
Local Knowledge Base: Uses a custom North York/Toronto dataset to provide context-aware survival tips.
Tech Stack Language: Python
Frontend/UI: Streamlit
Graph Engine: NetworkX & Pyvis
Installation & Setup Ensure you have Python 3.8+ installed.
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Clone the Repository git clone [(https://github.com/shero233/MapleRadar)] cd MapleRadar
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Environment Setup It is recommended to use a virtual environment: # Windows python -m venv venv .\venv\Scripts\activate
# macOS/Linux python3 -m venv venv source venv/bin/activate -
Install Dependencies pip install streamlit networkx pyvis matplotlib
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Run the Application streamlit run app.py