About

This project explores factors that influence missed medical appointments using the Medical Appointment No-Shows dataset containing over 110,000 patient records. The analysis includes data cleaning, exploratory data analysis (EDA), and visualization of patient attendance patterns based on factors such as age, scholarship status, SMS reminders, and appointment weekdays. The project identifies trends associated with missed appointments and provides business recommendations to help healthcare providers reduce no-show rates and improve appointment management. Built using Python, Pandas, and Matplotlib.