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Flower Characteristics

flower.Rd

8 characteristics for 18 popular flowers.

Usage

data(flower)

Format

A data frame with 18 observations on 8 variables:

[ , "V1"]factorwinters
[ , "V2"]factorshadow
[ , "V3"]factortubers
[ , "V4"]factorcolor
[ , "V5"]orderedsoil
[ , "V6"]orderedpreference
[ , "V7"]numericheight
[ , "V8"]numericdistance

V1

winters, is binary and indicates whether the plant may be left in the garden when it freezes.

V2

shadow, is binary and shows whether the plant needs to stand in the shadow.

V3

tubers, is asymmetric binary and distinguishes between plants with tubers and plants that grow in any other way.

V4

color, is nominal and specifies the flower's color (1 = white, 2 = yellow, 3 = pink, 4 = red, 5 = blue).

V5

soil, is ordinal and indicates whether the plant grows in dry (1), normal (2), or wet (3) soil.

V6

preference, is ordinal and gives someone's preference ranking going from 1 to 18.

V7

height, is interval scaled, the plant's height in centimeters.

V8

distance, is interval scaled, the distance in centimeters that should be left between the plants.

References

Struyf, Hubert and Rousseeuw (1996), see agnes.

Examples

data(flower)
str(flower) # factors, ordered, numeric
#> 'data.frame':	18 obs. of  8 variables:
#>  $ V1: Factor w/ 2 levels "0","1": 1 2 1 1 1 1 1 1 2 2 ...
#>  $ V2: Factor w/ 2 levels "0","1": 2 1 2 1 2 2 1 1 2 2 ...
#>  $ V3: Factor w/ 2 levels "0","1": 2 1 1 2 1 1 1 2 1 1 ...
#>  $ V4: Factor w/ 5 levels "1","2","3","4",..: 4 2 3 4 5 4 4 2 3 5 ...
#>  $ V5: Ord.factor w/ 3 levels "1"<"2"<"3": 3 1 3 2 2 3 3 2 1 2 ...
#>  $ V6: Ord.factor w/ 18 levels "1"<"2"<"3"<"4"<..: 15 3 1 16 2 12 13 7 4 14 ...
#>  $ V7: num  25 150 150 125 20 50 40 100 25 100 ...
#>  $ V8: num  15 50 50 50 15 40 20 15 15 60 ...

## "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
#>    winters shadow tubers  color   soil preference height distance
#> 1    FALSE   TRUE   TRUE    red    wet         15     25       15
#> 2     TRUE  FALSE  FALSE yellow    dry          3    150       50
#> 3    FALSE   TRUE  FALSE   pink    wet          1    150       50
#> 4    FALSE  FALSE   TRUE    red normal         16    125       50
#> 5    FALSE   TRUE  FALSE   blue normal          2     20       15
#> 6    FALSE   TRUE  FALSE    red    wet         12     50       40
#> 7    FALSE  FALSE  FALSE    red    wet         13     40       20
#> 8    FALSE  FALSE   TRUE yellow normal          7    100       15
#> 9     TRUE   TRUE  FALSE   pink    dry          4     25       15
#> 10    TRUE   TRUE  FALSE   blue normal         14    100       60
#> 11    TRUE   TRUE   TRUE   blue    wet          8     45       10
#> 12    TRUE   TRUE   TRUE  white normal          9     90       25
#> 13    TRUE   TRUE  FALSE  white normal          6     20       10
#> 14    TRUE   TRUE   TRUE    red normal         11     80       30
#> 15    TRUE  FALSE  FALSE   pink normal         10     40       20
#> 16    TRUE  FALSE  FALSE    red normal         18    200       60
#> 17    TRUE  FALSE  FALSE yellow normal         17    150       60
#> 18   FALSE  FALSE   TRUE yellow    dry          5     25       10

## ==> example(daisy)  on how it is used