Cardiovascular Disease Dataset Description

Overview

This dataset consolidates information from two primary sources:

The primary aim is to predict the presence or absence of cardiovascular disease based on various patient metrics.

Variables

ID: Unique identifier for each patient.
age: Age of the patient in days.
age_years: Age of the patient in years (derived from age).
gender: Gender of the patient. Categorical variable (1: Female, 2: Male).
height: Height of the patient in centimeters.
weight: Weight of the patient in kilograms.
ap_hi: Systolic blood pressure.
ap_lo: Diastolic blood pressure.
cholesterol: Cholesterol levels. Categorical variable (1: Normal, 2: Above Normal, 3: Well Above Normal).
gluc: Glucose levels. Categorical variable (1: Normal, 2: Above Normal, 3: Well Above Normal).
smoke: Smoking status. Binary variable (0: Non-smoker, 1: Smoker).
alco: Alcohol intake. Binary variable (0: Does not consume alcohol, 1: Consumes alcohol).
active: Physical activity. Binary variable (0: Not physically active, 1: Physically active).
cardio: Presence or absence of cardiovascular disease. Target variable. Binary (0: Absence, 1: Presence).
bmi: Body Mass Index, derived from weight and height. Calculated as ( \text{BMI} = \frac{\text{weight (kg)}}{\text{height (m)}^2} ).
bp_category: Blood pressure category based on ap_hi and ap_lo. Categories include "Normal", "Elevated", "Hypertension Stage 1", "Hypertension Stage 2", and "Hypertensive Crisis".
bp_category_encoded: Encoded form of bp_category for machine learning purposes.

Data Source and Acknowledgment

Data was sourced from the UCI Machine Learning Repository and Kaggle.
All patient data has been anonymized to ensure privacy.

Tables

Cardio Data Processed

@kaggle.colewelkins_cardiovascular_disease.cardio_data_processed

1.04 MB
68205 rows
17 columns


CREATE TABLE cardio_data_processed (
  "id" BIGINT,
  "age" BIGINT,
  "gender" BIGINT,
  "height" BIGINT,
  "weight" DOUBLE,
  "ap_hi" BIGINT,
  "ap_lo" BIGINT,
  "cholesterol" BIGINT,
  "gluc" BIGINT,
  "smoke" BIGINT,
  "alco" BIGINT,
  "active" BIGINT,
  "cardio" BIGINT,
  "age_years" BIGINT,
  "bmi" DOUBLE,
  "bp_category" VARCHAR,
  "bp_category_encoded" VARCHAR
);