This project aims to perform different data visualization techniques on a heart disease dataset to understand the distribution and relationships between various features. The insights gained from this analysis will help in building and evaluating a model for the early detection of heart disease.
The dataset used in this analysis contains the following features:
Age:Age of the patient in years.Sex:Gender of the patient (Male or Female).ChestPainType:Type of chest pain experienced (Typical Angina, Atypical Angina, Non-Anginal Pain, Asymptomatic).RestingBP:Resting blood pressure in mm Hg.Cholesterol:Serum cholesterol level in mg/dl.FastingBS:Fasting blood sugar level (1 if > 120 mg/dl, 0 otherwise).RestingECG:Results of the resting electrocardiogram (Normal, ST-T wave abnormality, Left ventricular hypertrophy).MaxHR:Maximum heart rate achieved.ExerciseAngina:Presence of exercise-induced angina (Yes or No).Oldpeak:Depression induced by exercise relative to rest.ST_Slope:Slope of the peak exercise ST segment (Upsloping, Flat, Downsloping).HeartDisease:Target variable indicating the presence (1) or absence (0) of heart disease.