Description Usage Format Details Source References Examples
A simple dataset containing 17 (mostly logical) variables on 101 animals.
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A data frame with 17 columns: hair, feathers, eggs, milk, airborne, aquatic, predator, toothed, backbone, breathes, venomous, fins, legs, tail, domestic, catsize, type.
Most variables are logical and indicate whether the corresponding
animal has the corresponsing characteristic or not. The only 2
exceptions are: legs
takes
values 0, 2, 4, 5, 6, and 8. type
is a grouping of the animals
into 7 groups, see the example section for the detailed list.
Ask the original donor of the data why girl is an animal.
The original data have been donated by Richard S. Forsyth to the UCI Repository Of Machine Learning Databases at
and were converted to R format by Friedrich Leisch.
Newman, D.J. & Hettich, S. & Blake, C.L. & Merz, C.J. (1998). UCI Repository of machine learning databases [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Department of Information and Computer Science.
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hair feathers eggs milk
Mode :logical Mode :logical Mode :logical Mode :logical
FALSE:58 FALSE:81 FALSE:42 FALSE:60
TRUE :43 TRUE :20 TRUE :59 TRUE :41
airborne aquatic predator toothed
Mode :logical Mode :logical Mode :logical Mode :logical
FALSE:77 FALSE:65 FALSE:45 FALSE:40
TRUE :24 TRUE :36 TRUE :56 TRUE :61
backbone breathes venomous fins
Mode :logical Mode :logical Mode :logical Mode :logical
FALSE:18 FALSE:21 FALSE:93 FALSE:84
TRUE :83 TRUE :80 TRUE :8 TRUE :17
legs tail domestic catsize
Min. :0.000 Mode :logical Mode :logical Mode :logical
1st Qu.:2.000 FALSE:26 FALSE:88 FALSE:57
Median :4.000 TRUE :75 TRUE :13 TRUE :44
Mean :2.842
3rd Qu.:4.000
Max. :8.000
type
mammal :41
bird :20
reptile : 5
fish :13
amphibian : 4
insect : 8
mollusc.et.al:10
$mammal
[1] "aardvark" "antelope" "bear" "boar" "buffalo" "calf"
[7] "cavy" "cheetah" "deer" "dolphin" "elephant" "fruitbat"
[13] "giraffe" "girl" "goat" "gorilla" "hamster" "hare"
[19] "leopard" "lion" "lynx" "mink" "mole" "mongoose"
[25] "opossum" "oryx" "platypus" "polecat" "pony" "porpoise"
[31] "puma" "pussycat" "raccoon" "reindeer" "seal" "sealion"
[37] "squirrel" "vampire" "vole" "wallaby" "wolf"
$bird
[1] "chicken" "crow" "dove" "duck" "flamingo" "gull"
[7] "hawk" "kiwi" "lark" "ostrich" "parakeet" "penguin"
[13] "pheasant" "rhea" "skimmer" "skua" "sparrow" "swan"
[19] "vulture" "wren"
$reptile
[1] "pitviper" "seasnake" "slowworm" "tortoise" "tuatara"
$fish
[1] "bass" "carp" "catfish" "chub" "dogfish" "haddock"
[7] "herring" "pike" "piranha" "seahorse" "sole" "stingray"
[13] "tuna"
$amphibian
[1] "frog.1" "frog.2" "newt" "toad"
$insect
[1] "flea" "gnat" "honeybee" "housefly" "ladybird" "moth" "termite"
[8] "wasp"
$mollusc.et.al
[1] "clam" "crab" "crayfish" "lobster" "octopus" "scorpion"
[7] "seawasp" "slug" "starfish" "worm"
[1] "bass" "carp" "catfish" "chub" "dogfish" "dolphin"
[7] "haddock" "herring" "pike" "piranha" "porpoise" "seahorse"
[13] "seal" "sealion" "sole" "stingray" "tuna"
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