No-Show Appointment Dataset Analysis

The No-Show Appointment Dataset Analysis project investigates factors influencing patient attendance for medical appointments in Brazil. Using a dataset of 110,527 appointments, the analysis explores variables such as demographics, health conditions, appointment scheduling, and SMS reminders to identify patterns related to no-shows. Key findings reveal that approximately 20% of patients miss their appointments, with higher no-show rates among younger patients and those with longer waiting times between scheduling and appointment. Surprisingly, SMS reminders did not significantly reduce no-shows, while patients with chronic conditions like hypertension and diabetes were more likely to attend. The project employs Python libraries like Pandas, Matplotlib, and Seaborn for data cleaning, exploratory analysis, and visualization, providing actionable insights to help healthcare providers improve attendance rates and optimize resource allocation.