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.class
#> barolo grignolino barbera
#> 59 71 48
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)