Weight and Sex traits dataframe.
Usage
data(weight_sex)Examples
# 1. Library TOmicsVis package
library(TOmicsVis)
# 2. Load example data
data(weight_sex)
# 3. View example data
weight_sex
#> Weight Sex
#> 1 36.74 Female
#> 2 38.54 Female
#> 3 44.91 Female
#> 4 43.53 Female
#> 5 39.03 Female
#> 6 26.01 Female
#> 7 29.59 Female
#> 8 33.08 Female
#> 9 45.21 Female
#> 10 38.05 Female
#> 11 39.48 Female
#> 12 32.13 Female
#> 13 41.42 Female
#> 14 30.82 Female
#> 15 37.90 Female
#> 16 33.64 Female
#> 17 39.67 Female
#> 18 45.27 Female
#> 19 34.44 Female
#> 20 33.59 Female
#> 21 46.57 Female
#> 22 34.47 Female
#> 23 46.02 Female
#> 24 26.08 Female
#> 25 46.16 Female
#> 26 28.38 Female
#> 27 32.75 Female
#> 28 39.50 Female
#> 29 42.16 Female
#> 30 29.23 Female
#> 31 43.36 Female
#> 32 36.43 Female
#> 33 25.98 Female
#> 34 31.89 Female
#> 35 31.38 Female
#> 36 31.51 Female
#> 37 32.73 Female
#> 38 39.31 Female
#> 39 34.33 Female
#> 40 36.88 Female
#> 41 37.24 Female
#> 42 33.57 Female
#> 43 33.32 Female
#> 44 48.36 Female
#> 45 29.55 Female
#> 46 34.98 Female
#> 47 30.03 Female
#> 48 32.89 Female
#> 49 42.65 Female
#> 50 40.30 Female
#> 51 35.54 Female
#> 52 41.79 Female
#> 53 28.87 Female
#> 54 33.32 Female
#> 55 43.62 Female
#> 56 40.84 Female
#> 57 47.42 Female
#> 58 46.15 Female
#> 59 33.54 Female
#> 60 38.28 Female
#> 61 34.52 Female
#> 62 47.90 Female
#> 63 27.03 Female
#> 64 28.78 Female
#> 65 29.48 Female
#> 66 32.57 Female
#> 67 27.36 Female
#> 68 45.46 Female
#> 69 38.97 Female
#> 70 36.67 Female
#> 71 35.33 Female
#> 72 34.71 Female
#> 73 46.67 Female
#> 74 36.90 Female
#> 75 32.07 Female
#> 76 39.46 Female
#> 77 25.48 Female
#> 78 36.97 Female
#> 79 47.20 Female
#> 80 37.25 Female
#> 81 44.09 Female
#> 82 43.06 Female
#> 83 34.93 Female
#> 84 36.34 Female
#> 85 28.48 Female
#> 86 29.40 Female
#> 87 26.94 Female
#> 88 41.15 Female
#> 89 33.47 Female
#> 90 28.32 Female
#> 91 40.16 Female
#> 92 30.22 Female
#> 93 29.42 Female
#> 94 25.97 Female
#> 95 34.67 Female
#> 96 27.35 Female
#> 97 46.19 Female
#> 98 30.79 Female
#> 99 43.49 Female
#> 100 35.42 Female
#> 101 48.06 Male
#> 102 36.80 Male
#> 103 39.98 Male
#> 104 39.51 Male
#> 105 42.74 Male
#> 106 31.61 Male
#> 107 38.76 Male
#> 108 34.81 Male
#> 109 45.25 Male
#> 110 39.65 Male
#> 111 44.95 Male
#> 112 29.90 Male
#> 113 30.96 Male
#> 114 36.78 Male
#> 115 43.21 Male
#> 116 40.02 Male
#> 117 35.01 Male
#> 118 34.84 Male
#> 119 44.65 Male
#> 120 47.32 Male
#> 121 45.44 Male
#> 122 39.63 Male
#> 123 28.20 Male
#> 124 42.06 Male
#> 125 42.11 Male
#> 126 42.66 Male
#> 127 30.69 Male
#> 128 39.11 Male
#> 129 38.78 Male
#> 130 43.42 Male
#> 131 27.85 Male
#> 132 36.94 Male
#> 133 39.86 Male
#> 134 35.74 Male
#> 135 33.50 Male
#> 136 27.45 Male
#> 137 45.66 Male
#> 138 48.13 Male
#> 139 33.39 Male
#> 140 43.16 Male
#> 141 29.07 Male
#> 142 34.13 Male
#> 143 42.51 Male
#> 144 43.36 Male
#> 145 33.32 Male
#> 146 45.76 Male
#> 147 28.52 Male
#> 148 30.45 Male
#> 149 31.87 Male
#> 150 30.56 Male
#> 151 32.39 Male
#> 152 29.56 Male
#> 153 39.86 Male
#> 154 45.90 Male
#> 155 31.16 Male
#> 156 25.86 Male
#> 157 41.91 Male
#> 158 35.11 Male
#> 159 27.65 Male
#> 160 29.29 Male
#> 161 29.40 Male
#> 162 43.58 Male
#> 163 37.42 Male
#> 164 43.23 Male
#> 165 43.20 Male
#> 166 41.15 Male
#> 167 29.53 Male
#> 168 26.67 Male
#> 169 45.51 Male
#> 170 44.10 Male
#> 171 30.42 Male
#> 172 38.93 Male
#> 173 44.09 Male
#> 174 34.60 Male
#> 175 43.78 Male
#> 176 27.19 Male
#> 177 30.61 Male
#> 178 38.21 Male
#> 179 37.95 Male
#> 180 46.62 Male
#> 181 46.32 Male
#> 182 40.38 Male
#> 183 44.88 Male
#> 184 28.48 Male
#> 185 38.23 Male
#> 186 36.62 Male
#> 187 39.93 Male
#> 188 31.18 Male
#> 189 47.54 Male
#> 190 42.75 Male
#> 191 48.24 Male
#> 192 37.09 Male
#> 193 36.49 Male
#> 194 43.54 Male
#> 195 46.83 Male
#> 196 34.19 Male
#> 197 34.27 Male
#> 198 33.22 Male
#> 199 42.54 Male
#> 200 44.18 Male