This is an exploratory data analysis (EDA) done as a project for a data science bootcamp hosted by Hyperiondev. An EDA report, a jupyter file with the EDA was made in and the dataset can be found in this repository.

The purpose of the exploratory data analysis on heart disease was to identify what the risk factors are linked to heart disease. The EDA considers data cleaning, missing data, data stories and visualisations, and draws conclusions based on the relationships identified in the study.

The data used is called 'heart.csv' and can be found in the repository. It consists of 14 attributes related to heart disease and the information of 303 patients.

The EDA was made in a jupyter notebook using python 3, which can be found in the repository.

Amy Marais

The EDA was conducted as a project for a data science bootcamp hosted by Hyperiondev.