Cardiovascular diseases are a leading cause of mortality worldwide, making early risk assessment critical. For our project, we have chosen the Cardiovascular Disease Dataset from Kaggle to analyze the complex interplay between lifestyle choices and health outcomes. Our goal is to leverage R programming to not only predict the presence of heart disease but also to model key health indicators like blood pressure. By analyzing 70,000 patient records, we aim to demonstrate how data science can transform raw medical stats into actionable health insights.

Este relatório apresenta exercícios práticos de visualização de dados utilizando flexdashboard, agregando leitura de arquivo CSV, criação de gráficos e mapas temáticos.

A brief overview about the concept of Expected Values (EVs) and its functional usage through ioslides.

Comprehensive Data Science Analysis of Indonesia’s National Budget (APBN): Exploratory, Predictive, and Temporal Modeling