Diverses fonctions permettent de connaître la structure des data.frames :
is.data.frame()
: prédicat pour vérifier la nature d'une variable
> is.data.frame(lenses) [1] TRUE
names()
ou colnames()
: pour récupérer un vecteur contenant les noms des colonnes :
> names(lenses); [1] "Age" "Defaut" "Astygmate" "Larmes" "Classe" > colnames(lenses) [1] "Age" "Defaut" "Astygmate" "Larmes" "Classe"
row.names()
: pour récupérer un vecteur contenant les étiquettes des lignes :
> row.names(lenses) [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" [16] "16" "17" "18" "19" "20" "21" "22" "23" "24"
length()
ou ncol()
: pour connaître le nombre de colonnes
> length(lenses) #taille de la liste
[1] 5
> ncol(lenses)
[1] 5
nrow()
pour le nombre de lignes
nrow(lenses) [1] 24>
dimnames()
pour obtenir une liste de noms de colonnes et d'étiquettes
> dimnames(iris) [[1]] [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48" [49] "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60" [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72" [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84" [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96" [97] "97" "98" "99" "100" "101" "102" "103" "104" "105" "106" "107" "108" [109] "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120" [121] "121" "122" "123" "124" "125" "126" "127" "128" "129" "130" "131" "132" [133] "133" "134" "135" "136" "137" "138" "139" "140" "141" "142" "143" "144" [145] "145" "146" "147" "148" "149" "150" [[2]] [1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" "Species"
summary()
pour résumer le contenu
summary(lenses) Age Defaut Astygmate Larmes Classe pre-presbyopic:8 hypermetrope:12 false:12 normal:12 hcl: 4 presbyopic :8 myope :12 true :12 reduce:12 ncl:15 young :8 scl: 5