\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}