Healthcare analytics case study
Why do patients miss medical appointments?
Python code, visualizations, findings, and recommendations from 110,527 public medical appointment records.

Problem
Which patient and scheduling factors are associated with missed visits?
The analysis explores appointment attendance patterns across age, gender, SMS reminder status, scholarship status, and weekday. The analysis is descriptive; it identifies patterns, not causes, and is not a clinical tool.
The public dataset is not redistributed here. The charts and the full Python code are available below so the analysis can be reproduced.
Visual analysis
Six views of appointment behavior.






Code and recommendation
Transparent, reproducible analysis.
Project reflection
Lessons Learned
This project strengthened my ability to transform public healthcare data into clear visualizations, reproducible Python analysis, and operational recommendations while respecting model and data limitations.
Related
More of my work.
Related projects, dashboards, research, and my CV.