

   FFlloowweerr CChhaarraacctteerriissttiiccss

        data(flower)

   FFoorrmmaatt::

        A data frame with 18 observations on 8 variables:

         [ , 1]     factor      winters
         [ , 2]     factor      shadow
         [ , 3]     factor      tubers
         [ , 4]     factor      color
         [ , 5]     ordered     soil
         [ , 6]     ordered     preference
         [ , 7]     numeric     height
         [ , 8]     numeric     distance

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

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

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

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

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

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

        `height' is interval scaled, the plant's height in cen-
        timeters.

        `distance' is interval scaled, the distance in centime-
        ters that should be left between the plants.

   DDeessccrriippttiioonn::

        8 characteristics for 18 popular flowers.

   SSoouurrccee::

        The reference below.

   RReeffeerreenncceess::

        Anja Struyf, Mia Hubert & Peter J. Rousseeuw (1996):
        Clustering in an Object-Oriented Environment.  Journal
        of Statistical Software, 1.  <URL:
        http://www.stat.ucla.edu/journals/jss/>

   EExxaammpplleess::

        data(flower)
        ## Example 2 in ref
        daisy(flower, type = list(asymm = 3))
        daisy(flower, type = list(asymm = c(1, 3), ordratio = 7))

