###Selektiranje elemenata iz vektora ----
WHO <- read.csv("WHO.csv")
summary(WHO) #1.st quartile, (25%observation) #3rd quartilw 75%
## Country Region Population Under15
## Length:194 Length:194 Min. : 1 Min. :13.12
## Class :character Class :character 1st Qu.: 1696 1st Qu.:18.72
## Mode :character Mode :character Median : 7790 Median :28.65
## Mean : 36360 Mean :28.73
## 3rd Qu.: 24535 3rd Qu.:37.75
## Max. :1390000 Max. :49.99
##
## Over60 FertilityRate LifeExpectancy ChildMortality
## Min. : 0.81 Min. :1.260 Min. :47.00 Min. : 2.200
## 1st Qu.: 5.20 1st Qu.:1.835 1st Qu.:64.00 1st Qu.: 8.425
## Median : 8.53 Median :2.400 Median :72.50 Median : 18.600
## Mean :11.16 Mean :2.941 Mean :70.01 Mean : 36.149
## 3rd Qu.:16.69 3rd Qu.:3.905 3rd Qu.:76.00 3rd Qu.: 55.975
## Max. :31.92 Max. :7.580 Max. :83.00 Max. :181.600
## NA's :11
## CellularSubscribers LiteracyRate GNI
## Min. : 2.57 Min. :31.10 Min. : 340
## 1st Qu.: 63.57 1st Qu.:71.60 1st Qu.: 2335
## Median : 97.75 Median :91.80 Median : 7870
## Mean : 93.64 Mean :83.71 Mean :13321
## 3rd Qu.:120.81 3rd Qu.:97.85 3rd Qu.:17558
## Max. :196.41 Max. :99.80 Max. :86440
## NA's :10 NA's :91 NA's :32
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale
## Min. : 37.20 Min. : 32.50
## 1st Qu.: 87.70 1st Qu.: 87.30
## Median : 94.70 Median : 95.10
## Mean : 90.85 Mean : 89.63
## 3rd Qu.: 98.10 3rd Qu.: 97.90
## Max. :100.00 Max. :100.00
## NA's :93 NA's :93
#Postoji nekoliko nacina da selektujemo vektor u osnovnom R paketu:
#** prema poziciji
#** prema vrijednosti
#** prema imenu
#**Prema poziciji:----
WHO[5] #peta varijabla
## Over60
## 1 3.82
## 2 14.93
## 3 7.17
## 4 22.86
## 5 3.84
## 6 12.35
## 7 14.97
## 8 14.06
## 9 19.46
## 10 23.52
## 11 8.24
## 12 11.24
## 13 3.38
## 14 6.89
## 15 15.78
## 16 19.31
## 17 23.81
## 18 5.74
## 19 4.54
## 20 6.90
## 21 7.28
## 22 20.52
## 23 5.63
## 24 10.81
## 25 7.03
## 26 26.11
## 27 3.88
## 28 3.87
## 29 7.67
## 30 4.89
## 31 20.82
## 32 7.05
## 33 5.74
## 34 3.80
## 35 13.80
## 36 13.42
## 37 9.19
## 38 4.50
## 39 5.13
## 40 9.07
## 41 10.15
## 42 5.10
## 43 24.69
## 44 17.95
## 45 16.92
## 46 23.23
## 47 12.74
## 48 4.51
## 49 23.90
## 50 5.96
## 51 12.35
## 52 8.97
## 53 9.21
## 54 8.62
## 55 9.64
## 56 4.53
## 57 3.73
## 58 23.92
## 59 5.17
## 60 8.38
## 61 25.90
## 62 23.82
## 63 7.38
## 64 3.72
## 65 19.47
## 66 26.72
## 67 5.40
## 68 25.41
## 69 9.72
## 70 6.56
## 71 5.03
## 72 5.06
## 73 5.18
## 74 6.70
## 75 6.41
## 76 23.41
## 77 17.62
## 78 8.10
## 79 7.86
## 80 7.82
## 81 4.95
## 82 16.59
## 83 15.15
## 84 26.97
## 85 10.98
## 86 31.92
## 87 5.30
## 88 10.04
## 89 4.25
## 90 8.84
## 91 3.80
## 92 6.34
## 93 5.76
## 94 24.24
## 95 12.03
## 96 6.31
## 97 4.76
## 98 6.96
## 99 20.57
## 100 19.15
## 101 4.45
## 102 4.92
## 103 8.21
## 104 6.65
## 105 4.29
## 106 22.87
## 107 8.84
## 108 4.94
## 109 13.23
## 110 9.18
## 111 6.67
## 112 23.82
## 113 5.80
## 114 18.58
## 115 7.61
## 116 5.01
## 117 8.15
## 118 5.38
## 119 8.84
## 120 7.65
## 121 23.02
## 122 19.01
## 123 6.59
## 124 4.26
## 125 4.49
## 126 9.07
## 127 21.41
## 128 3.99
## 129 6.44
## 130 8.84
## 131 10.13
## 132 4.79
## 133 8.01
## 134 9.12
## 135 6.21
## 136 20.48
## 137 24.39
## 138 1.73
## 139 16.58
## 140 16.72
## 141 20.66
## 142 18.60
## 143 3.94
## 144 12.35
## 145 12.13
## 146 9.92
## 147 7.39
## 148 26.97
## 149 4.76
## 150 4.59
## 151 4.57
## 152 20.52
## 153 10.05
## 154 4.41
## 155 15.13
## 156 18.60
## 157 23.16
## 158 5.10
## 159 4.46
## 160 8.44
## 161 5.26
## 162 22.86
## 163 12.40
## 164 4.99
## 165 9.55
## 166 5.34
## 167 25.32
## 168 23.25
## 169 6.09
## 170 4.80
## 171 13.96
## 172 17.56
## 173 5.16
## 174 4.44
## 175 7.96
## 176 13.18
## 177 10.49
## 178 10.56
## 179 6.30
## 180 9.07
## 181 3.72
## 182 20.76
## 183 0.81
## 184 23.06
## 185 4.89
## 186 19.31
## 187 18.59
## 188 6.38
## 189 6.02
## 190 9.17
## 191 9.32
## 192 4.54
## 193 3.95
## 194 5.68
WHO$Region[5] #peti element/obseracija u varijabli Region
## [1] "Africa"
WHO$Region[-5] #sve osim 5 elementa
## [1] "Eastern Mediterranean" "Europe" "Africa"
## [4] "Europe" "Americas" "Americas"
## [7] "Europe" "Western Pacific" "Europe"
## [10] "Europe" "Americas" "Eastern Mediterranean"
## [13] "South-East Asia" "Americas" "Europe"
## [16] "Europe" "Americas" "Africa"
## [19] "South-East Asia" "Americas" "Europe"
## [22] "Africa" "Americas" "Western Pacific"
## [25] "Europe" "Africa" "Africa"
## [28] "Western Pacific" "Africa" "Americas"
## [31] "Africa" "Africa" "Africa"
## [34] "Americas" "Western Pacific" "Americas"
## [37] "Africa" "Africa" "Western Pacific"
## [40] "Americas" "Africa" "Europe"
## [43] "Americas" "Europe" "Europe"
## [46] "South-East Asia" "Africa" "Europe"
## [49] "Eastern Mediterranean" "Americas" "Americas"
## [52] "Americas" "Eastern Mediterranean" "Americas"
## [55] "Africa" "Africa" "Europe"
## [58] "Africa" "Western Pacific" "Europe"
## [61] "Europe" "Africa" "Africa"
## [64] "Europe" "Europe" "Africa"
## [67] "Europe" "Americas" "Americas"
## [70] "Africa" "Africa" "Americas"
## [73] "Americas" "Americas" "Europe"
## [76] "Europe" "South-East Asia" "South-East Asia"
## [79] "Eastern Mediterranean" "Eastern Mediterranean" "Europe"
## [82] "Europe" "Europe" "Americas"
## [85] "Western Pacific" "Eastern Mediterranean" "Europe"
## [88] "Africa" "Western Pacific" "Eastern Mediterranean"
## [91] "Europe" "Western Pacific" "Europe"
## [94] "Eastern Mediterranean" "Africa" "Africa"
## [97] "Eastern Mediterranean" "Europe" "Europe"
## [100] "Africa" "Africa" "Western Pacific"
## [103] "South-East Asia" "Africa" "Europe"
## [106] "Western Pacific" "Africa" "Africa"
## [109] "Americas" "Western Pacific" "Europe"
## [112] "Western Pacific" "Europe" "Eastern Mediterranean"
## [115] "Africa" "South-East Asia" "Africa"
## [118] "Western Pacific" "South-East Asia" "Europe"
## [121] "Western Pacific" "Americas" "Africa"
## [124] "Africa" "Western Pacific" "Europe"
## [127] "Eastern Mediterranean" "Eastern Mediterranean" "Western Pacific"
## [130] "Americas" "Western Pacific" "Americas"
## [133] "Americas" "Western Pacific" "Europe"
## [136] "Europe" "Eastern Mediterranean" "Western Pacific"
## [139] "Europe" "Europe" "Europe"
## [142] "Africa" "Americas" "Americas"
## [145] "Americas" "Western Pacific" "Europe"
## [148] "Africa" "Eastern Mediterranean" "Africa"
## [151] "Europe" "Africa" "Africa"
## [154] "Western Pacific" "Europe" "Europe"
## [157] "Western Pacific" "Eastern Mediterranean" "Africa"
## [160] "Eastern Mediterranean" "Europe" "South-East Asia"
## [163] "Eastern Mediterranean" "Americas" "Africa"
## [166] "Europe" "Europe" "Eastern Mediterranean"
## [169] "Europe" "South-East Asia" "Europe"
## [172] "South-East Asia" "Africa" "Western Pacific"
## [175] "Americas" "Eastern Mediterranean" "Europe"
## [178] "Europe" "Western Pacific" "Africa"
## [181] "Europe" "Eastern Mediterranean" "Europe"
## [184] "Africa" "Americas" "Americas"
## [187] "Europe" "Western Pacific" "Americas"
## [190] "Western Pacific" "Eastern Mediterranean" "Africa"
## [193] "Africa"
WHO$Region[5:10] # elemente od 5 do 10, ukljucujuci 5 i 10
## [1] "Africa" "Americas" "Americas" "Europe"
## [5] "Western Pacific" "Europe"
WHO[5:10] #kada ne stavimo zarez onda R podrazumjeva sve obzervacije i uzima komandu za varijable
## Over60 FertilityRate LifeExpectancy ChildMortality CellularSubscribers
## 1 3.82 5.40 60 98.5 54.26
## 2 14.93 1.75 74 16.7 96.39
## 3 7.17 2.83 73 20.0 98.99
## 4 22.86 NA 82 3.2 75.49
## 5 3.84 6.10 51 163.5 48.38
## 6 12.35 2.12 75 9.9 196.41
## 7 14.97 2.20 76 14.2 134.92
## 8 14.06 1.74 71 16.4 103.57
## 9 19.46 1.89 82 4.9 108.34
## 10 23.52 1.44 81 4.0 154.78
## 11 8.24 1.96 71 35.2 108.75
## 12 11.24 1.90 75 16.9 86.06
## 13 3.38 2.12 79 9.6 127.96
## 14 6.89 2.24 70 40.9 56.06
## 15 15.78 1.84 78 18.4 127.01
## 16 19.31 1.47 71 5.2 111.88
## 17 23.81 1.85 80 4.2 116.61
## 18 5.74 2.76 74 18.3 69.96
## 19 4.54 5.01 57 89.5 85.33
## 20 6.90 2.32 67 44.6 65.58
## 21 7.28 3.31 67 41.4 82.82
## 22 20.52 1.26 76 6.7 84.52
## 23 5.63 2.71 66 53.3 142.82
## 24 10.81 1.82 74 14.4 124.26
## 25 7.03 2.03 77 8.0 109.17
## 26 26.11 1.51 74 12.1 140.68
## 27 3.88 5.78 56 102.4 45.27
## 28 3.87 6.21 53 104.3 22.33
## 29 7.67 2.93 65 39.7 96.17
## 30 4.89 4.94 53 94.9 52.35
## 31 20.82 1.66 82 5.3 79.73
## 32 7.05 2.38 72 22.2 79.19
## 33 5.74 4.54 48 128.6 40.65
## 34 3.80 6.49 51 149.8 31.80
## 35 13.80 1.84 79 9.1 129.71
## 36 13.42 1.66 76 14.0 73.19
## 37 9.19 2.35 78 17.6 98.45
## 38 4.50 4.85 62 77.6 28.71
## 39 5.13 5.05 58 96.0 93.84
## 40 9.07 NA 77 10.6 NA
## 41 10.15 1.83 79 9.9 92.20
## 42 5.10 4.91 56 107.6 86.06
## 43 24.69 1.48 77 4.7 116.37
## 44 17.95 1.46 78 5.5 11.69
## 45 16.92 1.47 81 3.2 97.71
## 46 23.23 1.53 78 3.8 123.44
## 47 12.74 2.00 69 28.8 4.09
## 48 4.51 6.15 49 145.7 23.09
## 49 23.90 1.88 79 3.7 128.47
## 50 5.96 3.53 58 80.9 21.32
## 51 12.35 NA 74 12.6 164.02
## 52 8.97 2.55 73 27.1 87.22
## 53 9.21 2.62 76 23.3 104.55
## 54 8.62 2.85 73 21.0 101.08
## 55 9.64 2.24 72 15.9 133.54
## 56 4.53 5.04 54 100.3 59.15
## 57 3.73 4.88 61 51.8 4.47
## 58 23.92 1.62 76 3.6 138.98
## 59 5.17 4.77 60 68.3 16.67
## 60 8.38 2.64 70 22.4 83.72
## 61 25.90 1.85 81 2.9 166.02
## 62 23.82 1.98 82 4.1 94.79
## 63 7.38 4.18 62 62.0 117.32
## 64 3.72 5.79 58 72.9 78.89
## 65 19.47 1.82 72 19.9 102.31
## 66 26.72 1.40 81 4.1 132.30
## 67 5.40 3.99 64 72.0 84.78
## 68 25.41 1.51 81 4.8 106.48
## 69 9.72 2.22 74 13.5 NA
## 70 6.56 3.91 69 32.0 140.38
## 71 5.03 5.09 55 101.2 44.02
## 72 5.06 5.05 50 129.1 56.18
## 73 5.18 2.64 63 35.2 69.94
## 74 6.70 3.28 63 75.6 41.49
## 75 6.41 3.10 74 22.9 103.97
## 76 23.41 1.38 75 6.2 117.30
## 77 17.62 2.11 82 2.3 106.08
## 78 8.10 2.53 65 56.3 72.00
## 79 7.86 2.40 69 31.0 103.09
## 80 7.82 1.91 73 17.6 74.93
## 81 4.95 4.15 69 34.4 78.12
## 82 16.59 2.00 81 4.0 108.41
## 83 15.15 2.92 82 4.2 121.66
## 84 26.97 1.45 82 3.8 157.93
## 85 10.98 2.31 75 16.8 108.12
## 86 31.92 1.39 83 3.0 104.95
## 87 5.30 3.39 74 19.1 118.20
## 88 10.04 2.52 67 18.7 155.74
## 89 4.25 4.54 60 72.9 67.49
## 90 8.84 3.01 67 59.9 13.64
## 91 3.80 2.65 80 11.0 175.09
## 92 6.34 3.03 69 26.6 116.40
## 93 5.76 3.20 68 71.8 87.16
## 94 24.24 1.57 74 8.7 102.94
## 95 12.03 1.50 74 9.3 78.65
## 96 6.31 3.15 50 99.6 56.17
## 97 4.76 4.95 59 74.8 49.17
## 98 6.96 2.47 65 15.4 155.70
## 99 20.57 1.49 74 5.4 151.30
## 100 19.15 1.65 82 2.2 148.27
## 101 4.45 4.59 66 58.2 40.65
## 102 4.92 5.55 58 71.0 25.69
## 103 8.21 1.99 74 8.5 127.04
## 104 6.65 2.31 77 10.5 165.72
## 105 4.29 6.85 51 128.0 68.32
## 106 22.87 1.37 80 6.8 124.86
## 107 8.84 NA 60 37.9 NA
## 108 4.94 4.78 59 84.0 93.60
## 109 13.23 1.51 74 15.1 99.04
## 110 9.18 2.25 75 16.2 82.38
## 111 6.67 3.40 69 38.5 NA
## 112 23.82 NA 82 3.8 89.73
## 113 5.80 2.45 68 27.5 105.08
## 114 18.58 1.69 76 5.9 NA
## 115 7.61 2.65 72 31.1 113.26
## 116 5.01 5.34 53 89.7 32.83
## 117 8.15 1.98 65 52.3 2.57
## 118 5.38 3.17 65 38.7 96.39
## 119 8.84 NA 71 37.1 65.00
## 120 7.65 2.50 68 41.6 43.81
## 121 23.02 1.76 81 4.1 NA
## 122 19.01 2.10 81 5.7 109.19
## 123 6.59 2.59 73 24.4 82.15
## 124 4.26 7.58 56 113.5 29.52
## 125 4.49 6.02 53 123.7 58.58
## 126 9.07 NA 72 25.1 NA
## 127 21.41 1.93 81 2.8 115.62
## 128 3.99 2.90 72 11.6 168.97
## 129 6.44 3.35 67 85.9 61.61
## 130 8.84 NA 72 20.8 74.94
## 131 10.13 2.52 77 18.5 188.60
## 132 4.79 3.90 63 63.0 34.22
## 133 8.01 2.93 75 22.0 99.40
## 134 9.12 2.48 77 18.2 110.41
## 135 6.21 3.11 69 29.8 99.30
## 136 20.48 1.39 76 5.0 130.97
## 137 24.39 1.33 80 3.6 115.39
## 138 1.73 2.06 82 7.4 123.11
## 139 16.58 1.29 81 3.8 108.50
## 140 16.72 1.47 71 17.6 104.80
## 141 20.66 1.39 74 12.2 109.16
## 142 18.60 1.51 69 10.3 179.31
## 143 3.94 4.73 60 55.0 40.63
## 144 12.35 NA 74 9.2 NA
## 145 12.13 1.96 75 17.5 123.00
## 146 9.92 2.05 74 23.4 120.52
## 147 7.39 4.28 73 17.8 NA
## 148 26.97 NA 83 3.3 111.75
## 149 4.76 4.22 63 53.2 68.26
## 150 4.59 2.76 76 8.6 191.24
## 151 4.57 5.02 61 59.6 73.25
## 152 20.52 1.37 74 6.6 125.39
## 153 10.05 2.23 74 13.1 145.71
## 154 4.41 4.86 47 181.6 35.63
## 155 15.13 1.27 82 2.9 150.24
## 156 18.60 1.37 76 7.5 109.35
## 157 23.16 1.49 80 3.1 106.56
## 158 5.10 4.17 70 31.1 49.77
## 159 4.46 6.77 50 147.4 6.85
## 160 8.44 2.44 58 44.6 126.83
## 161 5.26 5.10 54 104.0 NA
## 162 22.86 1.47 82 4.5 113.22
## 163 12.40 2.35 75 9.6 87.05
## 164 4.99 4.56 62 73.1 56.14
## 165 9.55 2.32 72 20.8 178.88
## 166 5.34 3.48 50 79.7 63.70
## 167 25.32 1.93 82 2.9 118.57
## 168 23.25 1.51 83 4.3 131.43
## 169 6.09 3.04 75 15.1 63.17
## 170 4.80 3.81 68 58.3 90.64
## 171 13.96 1.43 74 13.2 111.63
## 172 17.56 1.44 75 7.4 107.24
## 173 5.16 6.11 64 56.7 53.23
## 174 4.44 4.75 56 95.5 50.45
## 175 7.96 3.86 72 12.8 52.63
## 176 13.18 1.80 71 20.7 135.64
## 177 10.49 2.04 76 16.1 116.93
## 178 10.56 2.08 76 14.2 88.70
## 179 6.30 2.38 63 52.8 68.77
## 180 9.07 NA 64 29.7 21.63
## 181 3.72 6.06 56 68.9 48.38
## 182 20.76 1.45 71 10.7 122.98
## 183 0.81 1.84 76 8.4 148.62
## 184 23.06 1.90 80 4.8 130.75
## 185 4.89 5.36 59 54.0 55.53
## 186 19.31 2.00 79 7.1 92.72
## 187 18.59 2.07 77 7.2 140.75
## 188 6.38 2.38 68 39.6 91.65
## 189 6.02 3.46 72 17.9 55.76
## 190 9.17 2.44 75 15.3 97.78
## 191 9.32 1.79 75 23.0 143.39
## 192 4.54 4.35 64 60.0 47.05
## 193 3.95 5.77 55 88.5 60.59
## 194 5.68 3.64 54 89.8 72.13
## LiteracyRate
## 1 NA
## 2 NA
## 3 NA
## 4 NA
## 5 70.1
## 6 99.0
## 7 97.8
## 8 99.6
## 9 NA
## 10 NA
## 11 NA
## 12 NA
## 13 91.9
## 14 56.8
## 15 NA
## 16 NA
## 17 NA
## 18 NA
## 19 42.4
## 20 NA
## 21 NA
## 22 97.9
## 23 84.5
## 24 NA
## 25 95.2
## 26 NA
## 27 NA
## 28 67.2
## 29 NA
## 30 NA
## 31 NA
## 32 84.3
## 33 56.0
## 34 34.5
## 35 NA
## 36 94.3
## 37 93.4
## 38 74.9
## 39 NA
## 40 NA
## 41 96.2
## 42 56.2
## 43 98.8
## 44 99.8
## 45 98.3
## 46 NA
## 47 NA
## 48 66.8
## 49 NA
## 50 NA
## 51 NA
## 52 89.5
## 53 91.9
## 54 72.0
## 55 84.5
## 56 93.9
## 57 67.8
## 58 99.8
## 59 NA
## 60 NA
## 61 NA
## 62 NA
## 63 88.4
## 64 50.0
## 65 99.7
## 66 NA
## 67 67.3
## 68 97.2
## 69 NA
## 70 75.2
## 71 41.0
## 72 54.2
## 73 NA
## 74 NA
## 75 84.8
## 76 99.0
## 77 NA
## 78 NA
## 79 NA
## 80 NA
## 81 78.2
## 82 NA
## 83 NA
## 84 98.9
## 85 86.6
## 86 NA
## 87 92.6
## 88 99.7
## 89 87.4
## 90 NA
## 91 NA
## 92 NA
## 93 NA
## 94 99.8
## 95 NA
## 96 89.6
## 97 60.8
## 98 89.2
## 99 99.7
## 100 NA
## 101 NA
## 102 74.8
## 103 93.1
## 104 NA
## 105 31.1
## 106 NA
## 107 NA
## 108 58.0
## 109 88.5
## 110 93.1
## 111 NA
## 112 NA
## 113 97.4
## 114 98.4
## 115 NA
## 116 56.1
## 117 92.3
## 118 88.8
## 119 NA
## 120 60.3
## 121 NA
## 122 NA
## 123 NA
## 124 NA
## 125 61.3
## 126 NA
## 127 NA
## 128 NA
## 129 NA
## 130 NA
## 131 94.1
## 132 60.6
## 133 93.9
## 134 NA
## 135 NA
## 136 99.5
## 137 95.2
## 138 96.3
## 139 NA
## 140 98.5
## 141 97.7
## 142 99.6
## 143 71.1
## 144 NA
## 145 NA
## 146 NA
## 147 98.8
## 148 NA
## 149 89.2
## 150 86.6
## 151 NA
## 152 97.9
## 153 91.8
## 154 42.1
## 155 95.9
## 156 NA
## 157 99.7
## 158 NA
## 159 NA
## 160 NA
## 161 NA
## 162 97.7
## 163 91.2
## 164 71.1
## 165 94.7
## 166 87.4
## 167 NA
## 168 NA
## 169 83.4
## 170 99.7
## 171 NA
## 172 97.3
## 173 58.3
## 174 NA
## 175 NA
## 176 98.8
## 177 NA
## 178 NA
## 179 99.6
## 180 NA
## 181 73.2
## 182 99.7
## 183 NA
## 184 NA
## 185 73.2
## 186 NA
## 187 98.1
## 188 99.4
## 189 82.6
## 190 NA
## 191 93.2
## 192 63.9
## 193 71.2
## 194 92.2
WHO[c(1,5)] # prva i peta varijabla a sve obzervacije
## Country Over60
## 1 Afghanistan 3.82
## 2 Albania 14.93
## 3 Algeria 7.17
## 4 Andorra 22.86
## 5 Angola 3.84
## 6 Antigua and Barbuda 12.35
## 7 Argentina 14.97
## 8 Armenia 14.06
## 9 Australia 19.46
## 10 Austria 23.52
## 11 Azerbaijan 8.24
## 12 Bahamas 11.24
## 13 Bahrain 3.38
## 14 Bangladesh 6.89
## 15 Barbados 15.78
## 16 Belarus 19.31
## 17 Belgium 23.81
## 18 Belize 5.74
## 19 Benin 4.54
## 20 Bhutan 6.90
## 21 Bolivia (Plurinational State of) 7.28
## 22 Bosnia and Herzegovina 20.52
## 23 Botswana 5.63
## 24 Brazil 10.81
## 25 Brunei Darussalam 7.03
## 26 Bulgaria 26.11
## 27 Burkina Faso 3.88
## 28 Burundi 3.87
## 29 Cambodia 7.67
## 30 Cameroon 4.89
## 31 Canada 20.82
## 32 Cape Verde 7.05
## 33 Central African Republic 5.74
## 34 Chad 3.80
## 35 Chile 13.80
## 36 China 13.42
## 37 Colombia 9.19
## 38 Comoros 4.50
## 39 Congo 5.13
## 40 Cook Islands 9.07
## 41 Costa Rica 10.15
## 42 Ivory Coast 5.10
## 43 Croatia 24.69
## 44 Cuba 17.95
## 45 Cyprus 16.92
## 46 Czech Republic 23.23
## 47 Democratic People's Republic of Korea 12.74
## 48 Democratic Republic of the Congo 4.51
## 49 Denmark 23.90
## 50 Djibouti 5.96
## 51 Dominica 12.35
## 52 Dominican Republic 8.97
## 53 Ecuador 9.21
## 54 Egypt 8.62
## 55 El Salvador 9.64
## 56 Equatorial Guinea 4.53
## 57 Eritrea 3.73
## 58 Estonia 23.92
## 59 Ethiopia 5.17
## 60 Fiji 8.38
## 61 Finland 25.90
## 62 France 23.82
## 63 Gabon 7.38
## 64 Gambia 3.72
## 65 Georgia 19.47
## 66 Germany 26.72
## 67 Ghana 5.40
## 68 Greece 25.41
## 69 Grenada 9.72
## 70 Guatemala 6.56
## 71 Guinea 5.03
## 72 Guinea-Bissau 5.06
## 73 Guyana 5.18
## 74 Haiti 6.70
## 75 Honduras 6.41
## 76 Hungary 23.41
## 77 Iceland 17.62
## 78 India 8.10
## 79 Indonesia 7.86
## 80 Iran (Islamic Republic of) 7.82
## 81 Iraq 4.95
## 82 Ireland 16.59
## 83 Israel 15.15
## 84 Italy 26.97
## 85 Jamaica 10.98
## 86 Japan 31.92
## 87 Jordan 5.30
## 88 Kazakhstan 10.04
## 89 Kenya 4.25
## 90 Kiribati 8.84
## 91 Kuwait 3.80
## 92 Kyrgyzstan 6.34
## 93 Lao People's Democratic Republic 5.76
## 94 Latvia 24.24
## 95 Lebanon 12.03
## 96 Lesotho 6.31
## 97 Liberia 4.76
## 98 Libya 6.96
## 99 Lithuania 20.57
## 100 Luxembourg 19.15
## 101 Madagascar 4.45
## 102 Malawi 4.92
## 103 Malaysia 8.21
## 104 Maldives 6.65
## 105 Mali 4.29
## 106 Malta 22.87
## 107 Marshall Islands 8.84
## 108 Mauritania 4.94
## 109 Mauritius 13.23
## 110 Mexico 9.18
## 111 Micronesia (Federated States of) 6.67
## 112 Monaco 23.82
## 113 Mongolia 5.80
## 114 Montenegro 18.58
## 115 Morocco 7.61
## 116 Mozambique 5.01
## 117 Myanmar 8.15
## 118 Namibia 5.38
## 119 Nauru 8.84
## 120 Nepal 7.65
## 121 Netherlands 23.02
## 122 New Zealand 19.01
## 123 Nicaragua 6.59
## 124 Niger 4.26
## 125 Nigeria 4.49
## 126 Niue 9.07
## 127 Norway 21.41
## 128 Oman 3.99
## 129 Pakistan 6.44
## 130 Palau 8.84
## 131 Panama 10.13
## 132 Papua New Guinea 4.79
## 133 Paraguay 8.01
## 134 Peru 9.12
## 135 Philippines 6.21
## 136 Poland 20.48
## 137 Portugal 24.39
## 138 Qatar 1.73
## 139 Republic of Korea 16.58
## 140 Republic of Moldova 16.72
## 141 Romania 20.66
## 142 Russian Federation 18.60
## 143 Rwanda 3.94
## 144 Saint Kitts and Nevis 12.35
## 145 Saint Lucia 12.13
## 146 Saint Vincent and the Grenadines 9.92
## 147 Samoa 7.39
## 148 San Marino 26.97
## 149 Sao Tome and Principe 4.76
## 150 Saudi Arabia 4.59
## 151 Senegal 4.57
## 152 Serbia 20.52
## 153 Seychelles 10.05
## 154 Sierra Leone 4.41
## 155 Singapore 15.13
## 156 Slovakia 18.60
## 157 Slovenia 23.16
## 158 Solomon Islands 5.10
## 159 Somalia 4.46
## 160 South Africa 8.44
## 161 South Sudan 5.26
## 162 Spain 22.86
## 163 Sri Lanka 12.40
## 164 Sudan 4.99
## 165 Suriname 9.55
## 166 Swaziland 5.34
## 167 Sweden 25.32
## 168 Switzerland 23.25
## 169 Syrian Arab Republic 6.09
## 170 Tajikistan 4.80
## 171 Thailand 13.96
## 172 The former Yugoslav Republic of Macedonia 17.56
## 173 Timor-Leste 5.16
## 174 Togo 4.44
## 175 Tonga 7.96
## 176 Trinidad and Tobago 13.18
## 177 Tunisia 10.49
## 178 Turkey 10.56
## 179 Turkmenistan 6.30
## 180 Tuvalu 9.07
## 181 Uganda 3.72
## 182 Ukraine 20.76
## 183 United Arab Emirates 0.81
## 184 United Kingdom 23.06
## 185 United Republic of Tanzania 4.89
## 186 United States of America 19.31
## 187 Uruguay 18.59
## 188 Uzbekistan 6.38
## 189 Vanuatu 6.02
## 190 Venezuela (Bolivarian Republic of) 9.17
## 191 Viet Nam 9.32
## 192 Yemen 4.54
## 193 Zambia 3.95
## 194 Zimbabwe 5.68
WHO[1:5,c(1,5)] #ovo je WHO[observacije,varijable] dakle lijevo od zareza biramo koje cemo redove, a desno koje cemo kolone
## Country Over60
## 1 Afghanistan 3.82
## 2 Albania 14.93
## 3 Algeria 7.17
## 4 Andorra 22.86
## 5 Angola 3.84
#zadatak 1 -----
#imajuci u vidu pravilo da je lijevo od zareza red a desno kolona kako da izlistate samo peti red (minuta)
# sacuvajte peti red baze WHO pod nazivom peti
#odgovor
WHO[5,]
## Country Region Population Under15 Over60 FertilityRate LifeExpectancy
## 5 Angola Africa 20821 47.58 3.84 6.1 51
## ChildMortality CellularSubscribers LiteracyRate GNI
## 5 163.5 48.38 70.1 5230
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale
## 5 93.1 78.2
peti <- WHO[5,]
peti
## Country Region Population Under15 Over60 FertilityRate LifeExpectancy
## 5 Angola Africa 20821 47.58 3.84 6.1 51
## ChildMortality CellularSubscribers LiteracyRate GNI
## 5 163.5 48.38 70.1 5230
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale
## 5 93.1 78.2
#**Prema vrijednosti ----
WHO[WHO$Population > 650000,] #izdvaja samo one observacije koje su imaju populaciju vecu od 650hiljada
## Country Region Population Under15 Over60 FertilityRate
## 36 China Western Pacific 1390000 17.95 13.42 1.66
## 78 India South-East Asia 1240000 29.43 8.10 2.53
## LifeExpectancy ChildMortality CellularSubscribers LiteracyRate GNI
## 36 76 14.0 73.19 94.3 8390
## 78 65 56.3 72.00 NA 3590
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale
## 36 NA NA
## 78 NA NA
WHO[WHO$Over60 < 4,] #izdvaja samo one observacije koji su manji od 4
## Country Region Population Under15 Over60
## 1 Afghanistan Eastern Mediterranean 29825 47.42 3.82
## 5 Angola Africa 20821 47.58 3.84
## 13 Bahrain Eastern Mediterranean 1318 20.16 3.38
## 27 Burkina Faso Africa 16460 45.66 3.88
## 28 Burundi Africa 9850 44.20 3.87
## 34 Chad Africa 12448 48.52 3.80
## 57 Eritrea Africa 6131 43.10 3.73
## 64 Gambia Africa 1791 45.90 3.72
## 91 Kuwait Eastern Mediterranean 3250 24.90 3.80
## 128 Oman Eastern Mediterranean 3314 24.19 3.99
## 138 Qatar Eastern Mediterranean 2051 13.28 1.73
## 143 Rwanda Africa 11458 43.56 3.94
## 181 Uganda Africa 36346 48.54 3.72
## 183 United Arab Emirates Eastern Mediterranean 9206 14.41 0.81
## 193 Zambia Africa 14075 46.73 3.95
## FertilityRate LifeExpectancy ChildMortality CellularSubscribers
## 1 5.40 60 98.5 54.26
## 5 6.10 51 163.5 48.38
## 13 2.12 79 9.6 127.96
## 27 5.78 56 102.4 45.27
## 28 6.21 53 104.3 22.33
## 34 6.49 51 149.8 31.80
## 57 4.88 61 51.8 4.47
## 64 5.79 58 72.9 78.89
## 91 2.65 80 11.0 175.09
## 128 2.90 72 11.6 168.97
## 138 2.06 82 7.4 123.11
## 143 4.73 60 55.0 40.63
## 181 6.06 56 68.9 48.38
## 183 1.84 76 8.4 148.62
## 193 5.77 55 88.5 60.59
## LiteracyRate GNI PrimarySchoolEnrollmentMale
## 1 NA 1140 NA
## 5 70.1 5230 93.1
## 13 91.9 NA NA
## 27 NA 1300 60.7
## 28 67.2 610 NA
## 34 34.5 1360 NA
## 57 67.8 580 37.2
## 64 50.0 1750 68.2
## 91 NA NA NA
## 128 NA NA NA
## 138 96.3 86440 95.7
## 143 71.1 1270 NA
## 181 73.2 1310 89.7
## 183 NA 47890 NA
## 193 71.2 1490 91.4
## PrimarySchoolEnrollmentFemale
## 1 NA
## 5 78.2
## 13 NA
## 27 55.9
## 28 NA
## 34 NA
## 57 32.5
## 64 70.4
## 91 NA
## 128 NA
## 138 96.6
## 143 NA
## 181 92.3
## 183 NA
## 193 93.9
#**Prema imenu ----
WHO [WHO$Region=="Europe",] #zarez je veoma bitan
## Country Region Population Under15 Over60
## 2 Albania Europe 3162 21.33 14.93
## 4 Andorra Europe 78 15.20 22.86
## 8 Armenia Europe 2969 20.34 14.06
## 10 Austria Europe 8464 14.51 23.52
## 11 Azerbaijan Europe 9309 22.25 8.24
## 16 Belarus Europe 9405 15.10 19.31
## 17 Belgium Europe 11060 16.88 23.81
## 22 Bosnia and Herzegovina Europe 3834 16.35 20.52
## 26 Bulgaria Europe 7278 13.53 26.11
## 43 Croatia Europe 4307 14.98 24.69
## 45 Cyprus Europe 1129 17.16 16.92
## 46 Czech Republic Europe 10660 14.56 23.23
## 49 Denmark Europe 5598 17.66 23.90
## 58 Estonia Europe 1291 15.69 23.92
## 61 Finland Europe 5408 16.42 25.90
## 62 France Europe 63937 18.26 23.82
## 65 Georgia Europe 4358 17.62 19.47
## 66 Germany Europe 82800 13.17 26.72
## 68 Greece Europe 11125 14.60 25.41
## 76 Hungary Europe 9976 14.62 23.41
## 77 Iceland Europe 326 20.71 17.62
## 82 Ireland Europe 4576 21.54 16.59
## 83 Israel Europe 7644 27.53 15.15
## 84 Italy Europe 60885 14.04 26.97
## 88 Kazakhstan Europe 16271 25.46 10.04
## 92 Kyrgyzstan Europe 5474 30.21 6.34
## 94 Latvia Europe 2060 14.57 24.24
## 99 Lithuania Europe 3028 15.13 20.57
## 100 Luxembourg Europe 524 17.46 19.15
## 106 Malta Europe 428 14.98 22.87
## 112 Monaco Europe 38 18.26 23.82
## 114 Montenegro Europe 621 19.01 18.58
## 121 Netherlands Europe 16714 17.21 23.02
## 127 Norway Europe 4994 18.64 21.41
## 136 Poland Europe 38211 14.91 20.48
## 137 Portugal Europe 10604 14.92 24.39
## 140 Republic of Moldova Europe 3514 16.52 16.72
## 141 Romania Europe 21755 15.05 20.66
## 142 Russian Federation Europe 143000 15.45 18.60
## 148 San Marino Europe 31 14.04 26.97
## 152 Serbia Europe 9553 16.45 20.52
## 156 Slovakia Europe 5446 15.00 18.60
## 157 Slovenia Europe 2068 14.16 23.16
## 162 Spain Europe 46755 15.20 22.86
## 167 Sweden Europe 9511 16.71 25.32
## 168 Switzerland Europe 7997 14.79 23.25
## 170 Tajikistan Europe 8009 35.75 4.80
## 172 The former Yugoslav Republic of Macedonia Europe 2106 16.89 17.56
## 178 Turkey Europe 73997 26.00 10.56
## 179 Turkmenistan Europe 5173 28.65 6.30
## 182 Ukraine Europe 45530 14.18 20.76
## 184 United Kingdom Europe 62783 17.54 23.06
## 188 Uzbekistan Europe 28541 28.90 6.38
## FertilityRate LifeExpectancy ChildMortality CellularSubscribers
## 2 1.75 74 16.7 96.39
## 4 NA 82 3.2 75.49
## 8 1.74 71 16.4 103.57
## 10 1.44 81 4.0 154.78
## 11 1.96 71 35.2 108.75
## 16 1.47 71 5.2 111.88
## 17 1.85 80 4.2 116.61
## 22 1.26 76 6.7 84.52
## 26 1.51 74 12.1 140.68
## 43 1.48 77 4.7 116.37
## 45 1.47 81 3.2 97.71
## 46 1.53 78 3.8 123.44
## 49 1.88 79 3.7 128.47
## 58 1.62 76 3.6 138.98
## 61 1.85 81 2.9 166.02
## 62 1.98 82 4.1 94.79
## 65 1.82 72 19.9 102.31
## 66 1.40 81 4.1 132.30
## 68 1.51 81 4.8 106.48
## 76 1.38 75 6.2 117.30
## 77 2.11 82 2.3 106.08
## 82 2.00 81 4.0 108.41
## 83 2.92 82 4.2 121.66
## 84 1.45 82 3.8 157.93
## 88 2.52 67 18.7 155.74
## 92 3.03 69 26.6 116.40
## 94 1.57 74 8.7 102.94
## 99 1.49 74 5.4 151.30
## 100 1.65 82 2.2 148.27
## 106 1.37 80 6.8 124.86
## 112 NA 82 3.8 89.73
## 114 1.69 76 5.9 NA
## 121 1.76 81 4.1 NA
## 127 1.93 81 2.8 115.62
## 136 1.39 76 5.0 130.97
## 137 1.33 80 3.6 115.39
## 140 1.47 71 17.6 104.80
## 141 1.39 74 12.2 109.16
## 142 1.51 69 10.3 179.31
## 148 NA 83 3.3 111.75
## 152 1.37 74 6.6 125.39
## 156 1.37 76 7.5 109.35
## 157 1.49 80 3.1 106.56
## 162 1.47 82 4.5 113.22
## 167 1.93 82 2.9 118.57
## 168 1.51 83 4.3 131.43
## 170 3.81 68 58.3 90.64
## 172 1.44 75 7.4 107.24
## 178 2.08 76 14.2 88.70
## 179 2.38 63 52.8 68.77
## 182 1.45 71 10.7 122.98
## 184 1.90 80 4.8 130.75
## 188 2.38 68 39.6 91.65
## LiteracyRate GNI PrimarySchoolEnrollmentMale
## 2 NA 8820 NA
## 4 NA NA 78.4
## 8 99.6 6100 NA
## 10 NA 42050 NA
## 11 NA 8960 85.3
## 16 NA 14460 NA
## 17 NA 39190 98.9
## 22 97.9 9190 86.5
## 26 NA 14160 99.3
## 43 98.8 18760 94.8
## 45 98.3 NA 99.1
## 46 NA 24370 NA
## 49 NA 41900 94.8
## 58 99.8 20850 97.7
## 61 NA 37670 97.7
## 62 NA 35910 99.1
## 65 99.7 5350 NA
## 66 NA 40230 NA
## 68 97.2 25100 98.8
## 76 99.0 20310 97.8
## 77 NA 31020 98.8
## 82 NA 34180 99.4
## 83 NA 27110 97.0
## 84 98.9 32400 99.6
## 88 99.7 11250 NA
## 92 NA 2180 95.5
## 94 99.8 17700 95.0
## 99 99.7 19640 95.6
## 100 NA 64260 93.6
## 106 NA NA 93.3
## 112 NA NA NA
## 114 98.4 13700 NA
## 121 NA 43140 NA
## 127 NA 61460 99.1
## 136 99.5 20430 96.9
## 137 95.2 24440 99.1
## 140 98.5 3640 90.1
## 141 97.7 15120 87.9
## 142 99.6 20560 NA
## 148 NA NA NA
## 152 97.9 11540 94.7
## 156 NA 22130 NA
## 157 99.7 26510 97.7
## 162 97.7 31400 99.7
## 167 NA 42200 99.7
## 168 NA 52570 98.9
## 170 99.7 2300 99.5
## 172 97.3 11090 97.3
## 178 NA 16940 99.5
## 179 99.6 8690 NA
## 182 99.7 7040 90.8
## 184 NA 36010 99.8
## 188 99.4 3420 93.3
## PrimarySchoolEnrollmentFemale
## 2 NA
## 4 79.4
## 8 NA
## 10 NA
## 11 84.1
## 16 NA
## 17 99.2
## 22 88.4
## 26 99.7
## 43 97.0
## 45 99.5
## 46 NA
## 49 96.9
## 58 97.0
## 61 97.9
## 62 99.3
## 65 NA
## 66 NA
## 68 99.3
## 76 98.3
## 77 99.2
## 82 100.0
## 83 97.8
## 84 98.5
## 88 NA
## 92 95.1
## 94 96.8
## 99 95.8
## 100 95.7
## 106 94.3
## 112 NA
## 114 NA
## 121 NA
## 127 99.2
## 136 96.7
## 137 99.7
## 140 90.1
## 141 87.3
## 142 NA
## 148 NA
## 152 94.4
## 156 NA
## 157 97.3
## 162 99.8
## 167 99.0
## 168 99.5
## 170 96.0
## 172 99.2
## 178 98.3
## 179 NA
## 182 91.5
## 184 99.6
## 188 91.0
##zadatak 5 minuta; ----
##ako je lijevo od zareza red a desno kolona, kako da opet dobijemo samo evropu ali za samo prvu, trecu i sestu varijablu?
##spasite kao WHOEurope
##odgovor
WHO [WHO$Region=="Europe",c(1,3,6)] #zarez je veoma bitan
## Country Population FertilityRate
## 2 Albania 3162 1.75
## 4 Andorra 78 NA
## 8 Armenia 2969 1.74
## 10 Austria 8464 1.44
## 11 Azerbaijan 9309 1.96
## 16 Belarus 9405 1.47
## 17 Belgium 11060 1.85
## 22 Bosnia and Herzegovina 3834 1.26
## 26 Bulgaria 7278 1.51
## 43 Croatia 4307 1.48
## 45 Cyprus 1129 1.47
## 46 Czech Republic 10660 1.53
## 49 Denmark 5598 1.88
## 58 Estonia 1291 1.62
## 61 Finland 5408 1.85
## 62 France 63937 1.98
## 65 Georgia 4358 1.82
## 66 Germany 82800 1.40
## 68 Greece 11125 1.51
## 76 Hungary 9976 1.38
## 77 Iceland 326 2.11
## 82 Ireland 4576 2.00
## 83 Israel 7644 2.92
## 84 Italy 60885 1.45
## 88 Kazakhstan 16271 2.52
## 92 Kyrgyzstan 5474 3.03
## 94 Latvia 2060 1.57
## 99 Lithuania 3028 1.49
## 100 Luxembourg 524 1.65
## 106 Malta 428 1.37
## 112 Monaco 38 NA
## 114 Montenegro 621 1.69
## 121 Netherlands 16714 1.76
## 127 Norway 4994 1.93
## 136 Poland 38211 1.39
## 137 Portugal 10604 1.33
## 140 Republic of Moldova 3514 1.47
## 141 Romania 21755 1.39
## 142 Russian Federation 143000 1.51
## 148 San Marino 31 NA
## 152 Serbia 9553 1.37
## 156 Slovakia 5446 1.37
## 157 Slovenia 2068 1.49
## 162 Spain 46755 1.47
## 167 Sweden 9511 1.93
## 168 Switzerland 7997 1.51
## 170 Tajikistan 8009 3.81
## 172 The former Yugoslav Republic of Macedonia 2106 1.44
## 178 Turkey 73997 2.08
## 179 Turkmenistan 5173 2.38
## 182 Ukraine 45530 1.45
## 184 United Kingdom 62783 1.90
## 188 Uzbekistan 28541 2.38
#sve ovo sto smo "selektirali" da bismo spasili moramo da ubacimo znak asign.
WHOEurope <- WHO [WHO$Region=="Europe",c(1,3,6)]
#podskup
WHO[WHO$Over60 %in% c(0.81,4.23,6.2,8),] #uzima samo elemente koji se nalaze u setu 0.81, 4.23, 6.2, 8. Buduci da samo Arab Emirati imaju udio stanovnistva starosti preko 60 jednak 0.81 samo je to i selektovano
## Country Region Population Under15 Over60
## 183 United Arab Emirates Eastern Mediterranean 9206 14.41 0.81
## FertilityRate LifeExpectancy ChildMortality CellularSubscribers
## 183 1.84 76 8.4 148.62
## LiteracyRate GNI PrimarySchoolEnrollmentMale
## 183 NA 47890 NA
## PrimarySchoolEnrollmentFemale
## 183 NA
#ili da vidimo samo BiH
WHO[WHO$Country %in% c ("Bosnia and Herzegovina"),] #funkcija podskupa je veoma korisna ako imamo listu odredjenu koju zelimo "izvuci" iz orginalne baze.
## Country Region Population Under15 Over60 FertilityRate
## 22 Bosnia and Herzegovina Europe 3834 16.35 20.52 1.26
## LifeExpectancy ChildMortality CellularSubscribers LiteracyRate GNI
## 22 76 6.7 84.52 97.9 9190
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale
## 22 86.5 88.4
#recimo zemlje iz razlicitog regiona: BiH, Oman, Egipat, Japan
WHO$Population
## [1] 29825 3162 38482 78 20821 89 41087 2969 23050
## [10] 8464 9309 372 1318 155000 283 9405 11060 324
## [19] 10051 742 10496 3834 2004 199000 412 7278 16460
## [28] 9850 14865 21700 34838 494 4525 12448 17465 1390000
## [37] 47704 718 4337 21 4805 19840 4307 11271 1129
## [46] 10660 24763 65705 5598 860 72 10277 15492 80722
## [55] 6297 736 6131 1291 91729 875 5408 63937 1633
## [64] 1791 4358 82800 25366 11125 105 15083 11451 1664
## [73] 795 10174 7936 9976 326 1240000 247000 76424 32778
## [82] 4576 7644 60885 2769 127000 7009 16271 43178 101
## [91] 3250 5474 6646 2060 4647 2052 4190 6155 3028
## [100] 524 22294 15906 29240 338 14854 428 53 3796
## [109] 1240 121000 103 38 2796 621 32521 25203 52797
## [118] 2259 10 27474 16714 4460 5992 17157 169000 1
## [127] 4994 3314 179000 21 3802 7167 6687 29988 96707
## [136] 38211 10604 2051 49003 3514 21755 143000 11458 54
## [145] 181 109 189 31 188 28288 13726 9553 92
## [154] 5979 5303 5446 2068 550 10195 52386 10838 46755
## [163] 21098 37195 535 1231 9511 7997 21890 8009 66785
## [172] 2106 1114 6643 105 1337 10875 73997 5173 10
## [181] 36346 45530 9206 62783 47783 318000 3395 28541 247
## [190] 29955 90796 23852 14075 13724
WHO$Population1 <- WHO$Population #dupliramo varijablu population
WHO$Population1 [c(3,8)] <- c(0,1) #na ovaj nacin mijenjamo 3 i 8 observaciju u vektoru istovremeno
#ovdje nemamo zareza jer smo vec odabrali koja je varijabla
head(WHO$Population1,8) #vidimo da smo zamjenili #8 oznacava prvih 8 redova
## [1] 29825 3162 0 78 20821 89 41087 1
### Izmjena faktora u data.frame-u
str(WHO) #vidimo da je region factor
## 'data.frame': 194 obs. of 14 variables:
## $ Country : chr "Afghanistan" "Albania" "Algeria" "Andorra" ...
## $ Region : chr "Eastern Mediterranean" "Europe" "Africa" "Europe" ...
## $ Population : int 29825 3162 38482 78 20821 89 41087 2969 23050 8464 ...
## $ Under15 : num 47.4 21.3 27.4 15.2 47.6 ...
## $ Over60 : num 3.82 14.93 7.17 22.86 3.84 ...
## $ FertilityRate : num 5.4 1.75 2.83 NA 6.1 2.12 2.2 1.74 1.89 1.44 ...
## $ LifeExpectancy : int 60 74 73 82 51 75 76 71 82 81 ...
## $ ChildMortality : num 98.5 16.7 20 3.2 163.5 ...
## $ CellularSubscribers : num 54.3 96.4 99 75.5 48.4 ...
## $ LiteracyRate : num NA NA NA NA 70.1 99 97.8 99.6 NA NA ...
## $ GNI : num 1140 8820 8310 NA 5230 ...
## $ PrimarySchoolEnrollmentMale : num NA NA 98.2 78.4 93.1 91.1 NA NA 96.9 NA ...
## $ PrimarySchoolEnrollmentFemale: num NA NA 96.4 79.4 78.2 84.5 NA NA 97.5 NA ...
## $ Population1 : num 29825 3162 0 78 20821 ...
WHO[6,2] <- "America" #mijenjamo sesti red i drugu kolonu
#prebacimo u character
WHO$Region <- as.character(WHO$Region)
WHO[6,2] <- "America" #sad smo uspijeli
head(WHO$Region)
## [1] "Eastern Mediterranean" "Europe" "Africa"
## [4] "Europe" "Africa" "America"
#ako zelimo sve Americas mijenjati u America imamo vise nacina ali cemo ih obraditi kasnije.
#1. ifelse ()
#2. gsub ()
#vratimo varijablu u factor
WHO$Region <- as.factor(WHO$Region)
str(WHO)
## 'data.frame': 194 obs. of 14 variables:
## $ Country : chr "Afghanistan" "Albania" "Algeria" "Andorra" ...
## $ Region : Factor w/ 7 levels "Africa","America",..: 4 5 1 5 1 2 3 5 7 5 ...
## $ Population : int 29825 3162 38482 78 20821 89 41087 2969 23050 8464 ...
## $ Under15 : num 47.4 21.3 27.4 15.2 47.6 ...
## $ Over60 : num 3.82 14.93 7.17 22.86 3.84 ...
## $ FertilityRate : num 5.4 1.75 2.83 NA 6.1 2.12 2.2 1.74 1.89 1.44 ...
## $ LifeExpectancy : int 60 74 73 82 51 75 76 71 82 81 ...
## $ ChildMortality : num 98.5 16.7 20 3.2 163.5 ...
## $ CellularSubscribers : num 54.3 96.4 99 75.5 48.4 ...
## $ LiteracyRate : num NA NA NA NA 70.1 99 97.8 99.6 NA NA ...
## $ GNI : num 1140 8820 8310 NA 5230 ...
## $ PrimarySchoolEnrollmentMale : num NA NA 98.2 78.4 93.1 91.1 NA NA 96.9 NA ...
## $ PrimarySchoolEnrollmentFemale: num NA NA 96.4 79.4 78.2 84.5 NA NA 97.5 NA ...
## $ Population1 : num 29825 3162 0 78 20821 ...
#zadaci ----
#izmijenite u WHO$Population1 treci element u broj 10.000
#prije ovakvih stvari savjet je da formirate novu bazu, ali i novu varijablu. Uvijek treba imati tzv master bazu koja je osnovna
#radi toga prvo formirajte WHO1 koja je identicna WHO
##odgovor
WHO1 <- WHO
WHO1$Population1 [3]
## [1] 0
WHO1$Population1 [3] <- 10000
str(WHO1)
## 'data.frame': 194 obs. of 14 variables:
## $ Country : chr "Afghanistan" "Albania" "Algeria" "Andorra" ...
## $ Region : Factor w/ 7 levels "Africa","America",..: 4 5 1 5 1 2 3 5 7 5 ...
## $ Population : int 29825 3162 38482 78 20821 89 41087 2969 23050 8464 ...
## $ Under15 : num 47.4 21.3 27.4 15.2 47.6 ...
## $ Over60 : num 3.82 14.93 7.17 22.86 3.84 ...
## $ FertilityRate : num 5.4 1.75 2.83 NA 6.1 2.12 2.2 1.74 1.89 1.44 ...
## $ LifeExpectancy : int 60 74 73 82 51 75 76 71 82 81 ...
## $ ChildMortality : num 98.5 16.7 20 3.2 163.5 ...
## $ CellularSubscribers : num 54.3 96.4 99 75.5 48.4 ...
## $ LiteracyRate : num NA NA NA NA 70.1 99 97.8 99.6 NA NA ...
## $ GNI : num 1140 8820 8310 NA 5230 ...
## $ PrimarySchoolEnrollmentMale : num NA NA 98.2 78.4 93.1 91.1 NA NA 96.9 NA ...
## $ PrimarySchoolEnrollmentFemale: num NA NA 96.4 79.4 78.2 84.5 NA NA 97.5 NA ...
## $ Population1 : num 29825 3162 10000 78 20821 ...
#dodatno indeksiranje ----
which.min(WHO$Population) #dakle indeksira nam red u kojem se nalazi najniza populacija.
## [1] 126
WHO [126,] # da nam prikaze sve varijable
## Country Region Population Under15 Over60 FertilityRate
## 126 Niue Western Pacific 1 30.61 9.07 NA
## LifeExpectancy ChildMortality CellularSubscribers LiteracyRate GNI
## 126 72 25.1 NA NA NA
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale Population1
## 126 NA NA 1
#zadatak----
# po istoj logici koja zemlja ima najvecu Populaciju?
#odgovor
which.max(WHO$Population)
## [1] 36
WHO[36,] #Kina
## Country Region Population Under15 Over60 FertilityRate
## 36 China Western Pacific 1390000 17.95 13.42 1.66
## LifeExpectancy ChildMortality CellularSubscribers LiteracyRate GNI
## 36 76 14 73.19 94.3 8390
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale Population1
## 36 NA NA 1390000