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\name{flower}
\alias{flower}
\title{Flower Characteristics}
\usage{data(flower)}
\description{8 characteristics for 18 popular flowers.}
\format{
A data frame with 18 observations on 8 variables:
\tabular{rll}{
[ , "V1"] \tab factor \tab winters \cr
[ , "V2"] \tab factor \tab shadow \cr
[ , "V3"] \tab factor \tab tubers \cr
[ , "V4"] \tab factor \tab color \cr
[ , "V5"] \tab ordered \tab soil \cr
[ , "V6"] \tab ordered \tab preference \cr
[ , "V7"] \tab numeric \tab height \cr
[ , "V8"] \tab numeric \tab distance
}
\describe{
\item{V1}{winters, is binary and indicates whether the plant may be left
in the garden when it freezes.}
\item{V2}{shadow, is binary and shows whether the plant needs to stand
in the shadow.}
\item{V3}{tubers, is asymmetric binary and distinguishes between plants
with tubers and plants that grow in any other way.}
\item{V4}{color, is nominal and specifies the flower's color (1 = white,
2 = yellow, 3 = pink, 4 = red, 5 = blue).}
\item{V5}{soil, is ordinal and indicates whether the plant grows in dry
(1), normal (2), or wet (3) soil.}
\item{V6}{preference, is ordinal and gives someone's preference ranking
going from 1 to 18.}
\item{V7}{height, is interval scaled, the plant's height in centimeters.}
\item{V8}{distance, is interval scaled, the distance in centimeters that
should be left between the plants.}
}
}
\references{
Struyf, Hubert and Rousseeuw (1996), see \code{\link{agnes}}.
}
\examples{
data(flower)
str(flower) # factors, ordered, numeric
## "Nicer" version (less numeric more self explainable) of 'flower':
flowerN <- flower
colnames(flowerN) <- c("winters", "shadow", "tubers", "color",
"soil", "preference", "height", "distance")
for(j in 1:3) flowerN[,j] <- (flowerN[,j] == "1")
levels(flowerN$color) <- c("1" = "white", "2" = "yellow", "3" = "pink",
"4" = "red", "5" = "blue")[levels(flowerN$color)]
levels(flowerN$soil) <- c("1" = "dry", "2" = "normal", "3" = "wet")[levels(flowerN$soil)]
flowerN
## ==> example(daisy) on how it is used
}
\keyword{datasets}
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