An interactive Streamlit site for analyzing university student mental health patterns, academic performance, and demographics.
- Interactive Visuals: Demographics, mental health indicators, CGPA, and course-wise trends
- Mental Health Insights: Depression, anxiety, panic attack prevalence
- Academic Correlations: CGPA vs. mental health, year-wise analysis
- Data Mining: Association rules (Apriori), K-Means clustering
- Modular Code: Clean separation of preprocessing, visualization, and mining logic
student-mental-health-dashboard/
├── app.py - Streamlit app
├── data_prep.py - Data preprocessing
├── viz.py - Visualizations
├── mining.py - Apriori & K-Means
├── requirements.txt - Dependencies
├── Student-Mental-health.csv - Data
└── README.md