#(1)
average_sepal_length <- mean(iris$Sepal.Length)
da1 <- subset(iris, Sepal.Length > average_sepal_length)
nrow(da1)
## [1] 70
da2 <- iris[!(iris$Sepal.Length > average_sepal_length), ]
nrow(da2)
## [1] 80
#(2)
library(ggplot2)
plot1 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_point() +labs(title = "Relationship between Sepal.Length and Petal.Length",x = "Sepal.Length", y = "Petal.Length") +theme_bw()
plot1
#(3)
plot2 <- ggplot(iris, aes(Sepal.Width, Petal.Width, color = Species)) + geom_point() +labs(title = "Relationship between Sepal.Width and Petal.Width",x = "Sepal.Width", y = "Petal.Width") + theme_bw()
plot2
#(4)
d <- cbind(iris[, 1:2], iris[, 3:5])
d
## 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
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
## 101 6.3 3.3 6.0 2.5 virginica
## 102 5.8 2.7 5.1 1.9 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 107 4.9 2.5 4.5 1.7 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginica
d1 <- cbind(iris[, 1], iris[, 2])
d1
## [,1] [,2]
## [1,] 5.1 3.5
## [2,] 4.9 3.0
## [3,] 4.7 3.2
## [4,] 4.6 3.1
## [5,] 5.0 3.6
## [6,] 5.4 3.9
## [7,] 4.6 3.4
## [8,] 5.0 3.4
## [9,] 4.4 2.9
## [10,] 4.9 3.1
## [11,] 5.4 3.7
## [12,] 4.8 3.4
## [13,] 4.8 3.0
## [14,] 4.3 3.0
## [15,] 5.8 4.0
## [16,] 5.7 4.4
## [17,] 5.4 3.9
## [18,] 5.1 3.5
## [19,] 5.7 3.8
## [20,] 5.1 3.8
## [21,] 5.4 3.4
## [22,] 5.1 3.7
## [23,] 4.6 3.6
## [24,] 5.1 3.3
## [25,] 4.8 3.4
## [26,] 5.0 3.0
## [27,] 5.0 3.4
## [28,] 5.2 3.5
## [29,] 5.2 3.4
## [30,] 4.7 3.2
## [31,] 4.8 3.1
## [32,] 5.4 3.4
## [33,] 5.2 4.1
## [34,] 5.5 4.2
## [35,] 4.9 3.1
## [36,] 5.0 3.2
## [37,] 5.5 3.5
## [38,] 4.9 3.6
## [39,] 4.4 3.0
## [40,] 5.1 3.4
## [41,] 5.0 3.5
## [42,] 4.5 2.3
## [43,] 4.4 3.2
## [44,] 5.0 3.5
## [45,] 5.1 3.8
## [46,] 4.8 3.0
## [47,] 5.1 3.8
## [48,] 4.6 3.2
## [49,] 5.3 3.7
## [50,] 5.0 3.3
## [51,] 7.0 3.2
## [52,] 6.4 3.2
## [53,] 6.9 3.1
## [54,] 5.5 2.3
## [55,] 6.5 2.8
## [56,] 5.7 2.8
## [57,] 6.3 3.3
## [58,] 4.9 2.4
## [59,] 6.6 2.9
## [60,] 5.2 2.7
## [61,] 5.0 2.0
## [62,] 5.9 3.0
## [63,] 6.0 2.2
## [64,] 6.1 2.9
## [65,] 5.6 2.9
## [66,] 6.7 3.1
## [67,] 5.6 3.0
## [68,] 5.8 2.7
## [69,] 6.2 2.2
## [70,] 5.6 2.5
## [71,] 5.9 3.2
## [72,] 6.1 2.8
## [73,] 6.3 2.5
## [74,] 6.1 2.8
## [75,] 6.4 2.9
## [76,] 6.6 3.0
## [77,] 6.8 2.8
## [78,] 6.7 3.0
## [79,] 6.0 2.9
## [80,] 5.7 2.6
## [81,] 5.5 2.4
## [82,] 5.5 2.4
## [83,] 5.8 2.7
## [84,] 6.0 2.7
## [85,] 5.4 3.0
## [86,] 6.0 3.4
## [87,] 6.7 3.1
## [88,] 6.3 2.3
## [89,] 5.6 3.0
## [90,] 5.5 2.5
## [91,] 5.5 2.6
## [92,] 6.1 3.0
## [93,] 5.8 2.6
## [94,] 5.0 2.3
## [95,] 5.6 2.7
## [96,] 5.7 3.0
## [97,] 5.7 2.9
## [98,] 6.2 2.9
## [99,] 5.1 2.5
## [100,] 5.7 2.8
## [101,] 6.3 3.3
## [102,] 5.8 2.7
## [103,] 7.1 3.0
## [104,] 6.3 2.9
## [105,] 6.5 3.0
## [106,] 7.6 3.0
## [107,] 4.9 2.5
## [108,] 7.3 2.9
## [109,] 6.7 2.5
## [110,] 7.2 3.6
## [111,] 6.5 3.2
## [112,] 6.4 2.7
## [113,] 6.8 3.0
## [114,] 5.7 2.5
## [115,] 5.8 2.8
## [116,] 6.4 3.2
## [117,] 6.5 3.0
## [118,] 7.7 3.8
## [119,] 7.7 2.6
## [120,] 6.0 2.2
## [121,] 6.9 3.2
## [122,] 5.6 2.8
## [123,] 7.7 2.8
## [124,] 6.3 2.7
## [125,] 6.7 3.3
## [126,] 7.2 3.2
## [127,] 6.2 2.8
## [128,] 6.1 3.0
## [129,] 6.4 2.8
## [130,] 7.2 3.0
## [131,] 7.4 2.8
## [132,] 7.9 3.8
## [133,] 6.4 2.8
## [134,] 6.3 2.8
## [135,] 6.1 2.6
## [136,] 7.7 3.0
## [137,] 6.3 3.4
## [138,] 6.4 3.1
## [139,] 6.0 3.0
## [140,] 6.9 3.1
## [141,] 6.7 3.1
## [142,] 6.9 3.1
## [143,] 5.8 2.7
## [144,] 6.8 3.2
## [145,] 6.7 3.3
## [146,] 6.7 3.0
## [147,] 6.3 2.5
## [148,] 6.5 3.0
## [149,] 6.2 3.4
## [150,] 5.9 3.0
d2 <- subset(iris, Species == "setosa")
d3 <- subset(iris, Species == "versicolor")
r1 <- rbind(d2, d3)
r1
## 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
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
d4 <- iris[1, 1:4]
d5 <- iris[1, 4:5]
r2 <- merge(d4, d5, by.x="Petal.Width", by.y="Petal.Width")
r2
## Petal.Width Sepal.Length Sepal.Width Petal.Length Species
## 1 0.2 5.1 3.5 1.4 setosa
#(5)
apply(iris[,1:4],2,sum)
## Sepal.Length Sepal.Width Petal.Length Petal.Width
## 876.5 458.6 563.7 179.9
lapply(iris[,1:4],mean)
## $Sepal.Length
## [1] 5.843333
##
## $Sepal.Width
## [1] 3.057333
##
## $Petal.Length
## [1] 3.758
##
## $Petal.Width
## [1] 1.199333
tapply(iris$Sepal.Length,iris$Species,sum)
## setosa versicolor virginica
## 250.3 296.8 329.4
sepallength.per.species <- aggregate(iris$Sepal.Length, by=list(iris$Species), FUN=mean)
sepallength.per.species
## Group.1 x
## 1 setosa 5.006
## 2 versicolor 5.936
## 3 virginica 6.588