Data Exploration
This page shows a basic exploration of iris data with R.
Check the dimensionality
> dim(iris)
[1] 150 5
Variable names or column names
> names(iris)
[1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" "Species"
Structure
> str(iris)
'data.frame': 150 obs. of 5 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
Attributes
> attributes(iris)
$names
[1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" "Species"
$row.names
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
[21] 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
[41] 41 42 43 44 45 46 47 48 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 74 75 76 77 78 79 80
[81] 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
[101] 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120
[121] 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140
[141] 141 142 143 144 145 146 147 148 149 150
$class
[1] "data.frame"
Get the first 5 rows
> iris[1:5,]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
Get Sepal.Length of the first 10 rows
> iris[1:10, "Sepal.Length"]
[1] 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9
Same as above
> iris$Sepal.Length[1:10]
[1] 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9
Distribution of every variable
> summary(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
Min. :4.300 Min. :2.000 Min. :1.000 Min. :0.100 setosa :50
1st Qu.:5.100 1st Qu.:2.800 1st Qu.:1.600 1st Qu.:0.300 versicolor:50
Median :5.800 Median :3.000 Median :4.350 Median :1.300 virginica :50
Mean :5.843 Mean :3.057 Mean :3.758 Mean :1.199
3rd Qu.:6.400 3rd Qu.:3.300 3rd Qu.:5.100 3rd Qu.:1.800
Max. :7.900 Max. :4.400 Max. :6.900 Max. :2.500
Frequency
> table(iris$Species)
setosa versicolor virginica
50 50 50
Pie chart
> pie(table(iris$Species))
Variance of Sepal.Length
> var(iris$Sepal.Length)
[1] 0.6856935
Covariance of two variables
> cov(iris$Sepal.Length, iris$Petal.Length)
[1] 1.274315
Correlation of two variables
> cor(iris$Sepal.Length, iris$Petal.Length)
[1] 0.8717538
Histogram
> hist(iris$Sepal.Length)
Density
> plot(density(iris$Sepal.Length))
Scatter plot
> plot(iris$Sepal.Length, iris$Sepal.Width)
Pair plot
> plot(iris)
or
> pairs(iris)
More examples on data exploration with R and other data mining techniques can be found in my book "R and Data Mining: Examples and Case Studies", which is downloadable as a .PDF file at the link.