heart: Heart Disease

In Rkabacoff/qacData: Datasets for Data Science Instruction

Heart Disease

Description

Predict heart disease from lab data

Usage

heart

Format

A data frame with 303 rows and 14 variables:

age

integer. age in years.

sex

factor with 2 levels. male, female.

cp

factor with 4 levels. chest pain type (typical angina, atypical angina, non-anginal pain, asymptomatic).

testbps

integer. resting blood pressure in mm Hg on admission to the hospital.

chol

integer. serum cholestoral in mg/dl.

fbs

integer. fasting blood sugar > 120 mg/dl (1 = true; 0 = false).

restecg

factor with 3 levels. resting electrocardiographic results (normal, having ST-T wave abnormality,left ventricular hypertrophy).

thalach

integer. maximum heart rate achieved.

exang

integer. exercise induced angina (1 = yes; 0 = no).

oldpeak

double. ST depression induced by exercise relative to rest.

slope

factor with 3 levels. the slope of the peak exercise ST segment (upslope, flat, downsloping).

ca

integer. number of major vessels (0-3) colored by flourosopy.

thal

factor with 3 levels. normal, fixed defect, reversable defect.

disease

factor with 2 levels. heart disease (yes, no). This is the outcome variable of interest.

Source

Data obtained from the UCI Machine Learning Repository.

Creators:

1. Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.

2. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.

3. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.

4. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D.

Donor: David W. Aha (aha '@' ics.uci.edu) [phone]

Examples

summary(heart)

Rkabacoff/qacData documentation built on April 3, 2022, 9:21 a.m.