wine {ggbiplot}

Wine dataset

Description

Results of a chemical analysis of wines grown in the same region in Italy, derived from three different cultivars. The analysis determined the quantities of 13 chemical constituents found in each of the three types of wines.

The grape varieties (cultivars), 'barolo', 'barbera', and 'grignolino', are indicated in wine.class.

Usage

data(wine)

Format

A wine data frame consisting of 178 observations (rows) and 13 columns and vector wine.class of factors indicating the cultivars. The variables are:

Alcohol

a numeric vector

MalicAcid

Malic acid, a numeric vector

Ash

Ash, a numeric vector

AlcAsh

Alcalinity of ash, a numeric vector

Mg

Magnesium, a numeric vector

Phenols

total phenols, a numeric vector

Flav

Flavanoids, a numeric vector

NonFlavPhenols

Nonflavanoid phenols, a numeric vector

Proa

Proanthocyanins, a numeric vector

Color

Color intensity, a numeric vector

Hue

a numeric vector

OD

D280/OD315 of diluted wines, a numeric vector

Proline

a numeric vector

Source

UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Wine)

Examples

data(wine)
table(wine.class)

wine.pca <- prcomp(wine, scale. = TRUE)
ggscreeplot(wine.pca)                                               
ggbiplot(wine.pca, 
         obs.scale = 1, var.scale = 1, 
         groups = wine.class, ellipse = TRUE, circle = TRUE)