🎓 School Dropout Risk Analysis

This project identifies patterns that contribute to school dropout risk using both Python and Power BI. The goal is to support early intervention and informed decision-making.

📁 Files Included

• School Dropout Risk Analysis.ipynb – This Jupyter Notebook contains a complete data analysis pipeline on school dropout risk. It includes:

  • Data loading and cleaning
  • Exploratory Data Analysis (EDA) using pandas, matplotlib, seaborn
  • Statistical summaries and insights
  • Suggestions for intervention based on trends and findings

• SCHOOL DROPOUT RISK.pbix – Power BI report with:

  • Interactive dashboards
  • Risk factor visualizations
  • Demographics, performance, and correlation views

🛠 Tools Used

• Python (pandas, seaborn, matplotlib)
• Power BI
• Jupyter Notebook

---

Use this project to explore the academic and social signals linked to school dropout and support preventive measures.