wine {spinifex} | R Documentation |
The wine dataset from the UCI Machine Learning Repository.
Description
The wine dataset contains the results of a chemical analysis of wines grown in a specific area of Italy. Three types of wine are represented in the 178 samples, with the results of 13 chemical analyses recorded for each sample. The Type variable has been transformed into a categorical variable.
Usage
wine
Format
A data frame of 178 observations of target
class Type
and 12 numeric variables:
Type, The type of wine, the target factor, 1 (59 obs), 2(71 obs), and 3 (48 obs).
Alcohol, Alcohol
Malic, Malic acid
Ash, Ash
Alcalinity, Alcalinity of ash
Magnesium, Magnesium
Phenols, Total phenols
Flavanoids, Flavanoids
Nonflavanoids, Nonflavanoid phenols
Proanthocyanins, Proanthocyanins
Color, Color intensity
Hue, Hue
Dilution, D280/OD315 of diluted wines
Proline, Proline
Details
The data contains no missing values and consist of only numeric data, with a three class target variable (Type) for classification.
Replicating this dataset:
require("rattle") str(rattle::wine) ## save(wine, file = "./data/wine.rda")
Source
rattle, R package. G. Williams, 2020. rattle: Graphical User Interface for Data Science in R https://CRAN.R-project.org/package=rattle
PARVUS. M. Forina. et al. 1988. Elsevier, Amsterdam, PARVUS: An extendable package of programs for data exploration, classification and correlation. ISBN 0-44-430121z
Examples
library(spinifex)
str(wine)
dat <- scale_sd(wine[, 2:6])
clas <- wine$Type
bas <- basis_pca(dat)
mv <- manip_var_of(bas)
mt <- manual_tour(bas, mv)
ggt <- ggtour(mt, dat, angle = .2) +
proto_default(aes_args = list(color = clas, shape = clas))
animate_plotly(ggt)