5 Reshaping Data
This is Chapter covers the Reshaping data – rearrange data form, not the content, of data : useing R package reshape.
Aggregating data – summarizing, reducing data :aggregate, by, tapply
5.1 Anatomy of a dataframe
ID variable – representing the unit on which measurements take place Measured variables – what is measured Values variable – the measured results
5.2 (reshape) PACKAGE
Rearrange ID and measured variables into different forms Measured variables – what is measured The reshape package extracts these information (melt) and rearranges into different forms (cast)
require("reshape2")## Loading required package: reshape2head(french_fries, n=3)## time treatment subject rep potato buttery grassy rancid painty
## 61 1 1 3 1 2.9 0.0 0 0.0 5.5
## 25 1 1 3 2 14.0 0.0 0 1.1 0.0
## 62 1 1 10 1 11.0 6.4 0 0.0 0.05.3 (melt) FUNCTION
ffm <- melt(french_fries, id=1:4, measure=5:9)
head(ffm, n=3)## time treatment subject rep variable value
## 1 1 1 3 1 potato 2.9
## 2 1 1 3 2 potato 14.0
## 3 1 1 10 1 potato 11.05.4 (cast) FUNCTION: Formula
dcast(ffm, rep~treatment) #Aggregation function missing: defaulting to length## Aggregation function missing: defaulting to length## rep 1 2 3
## 1 1 580 580 580
## 2 2 580 580 580dcast(ffm, treatment~rep) #Aggregation function missing: defaulting to length## Aggregation function missing: defaulting to length## treatment 1 2
## 1 1 580 580
## 2 2 580 580
## 3 3 580 580dcast(ffm, rep+treatment ~ .) #Aggregation function missing: defaulting to length## Aggregation function missing: defaulting to length## rep treatment .
## 1 1 1 580
## 2 1 2 580
## 3 1 3 580
## 4 2 1 580
## 5 2 2 580
## 6 2 3 5805.5 (cast) FUNCTION: Return to original form
dcast(ffm, treatment+rep+time+subject ~ variable)## treatment rep time subject potato buttery grassy rancid painty
## 1 1 1 1 3 2.9 0.0 0.0 0.0 5.5
## 2 1 1 1 10 11.0 6.4 0.0 0.0 0.0
## 3 1 1 1 15 1.2 0.1 0.0 1.1 5.1
## 4 1 1 1 16 9.0 2.6 0.4 0.1 0.2
## 5 1 1 1 19 7.0 3.2 0.0 4.9 3.2
## 6 1 1 1 31 12.2 0.0 0.0 2.5 2.0
## 7 1 1 1 51 8.6 1.7 0.1 1.4 0.1
## 8 1 1 1 52 5.8 0.0 1.7 8.5 1.1
## 9 1 1 1 63 8.3 0.0 0.0 1.1 0.4
## 10 1 1 1 78 4.9 1.2 0.0 1.1 3.5
## 11 1 1 1 79 5.1 0.0 0.0 2.0 0.0
## 12 1 1 1 86 5.2 1.2 0.0 7.9 4.9
## 13 1 1 2 3 9.0 0.3 0.1 5.8 0.3
## 14 1 1 2 10 8.0 3.1 3.1 6.2 1.7
## 15 1 1 2 15 5.3 1.4 0.1 3.9 6.5
## 16 1 1 2 16 4.1 5.1 0.0 2.8 0.0
## 17 1 1 2 19 8.7 0.0 0.0 12.8 11.3
## 18 1 1 2 31 9.7 3.3 0.0 12.1 1.1
## 19 1 1 2 51 9.4 6.7 1.5 11.1 2.8
## 20 1 1 2 52 6.5 1.6 2.8 1.1 0.0
## 21 1 1 2 63 8.9 0.0 0.0 2.3 0.0
## 22 1 1 2 78 3.3 0.0 1.3 0.0 6.3
## 23 1 1 2 79 5.9 0.0 2.3 0.5 0.0
## 24 1 1 2 86 6.7 6.0 0.0 0.0 0.0
## 25 1 1 3 3 11.8 0.2 0.0 6.0 0.0
## 26 1 1 3 10 9.3 7.0 0.0 2.6 3.8
## 27 1 1 3 15 3.4 0.2 0.2 7.2 2.6
## 28 1 1 3 16 1.5 0.2 3.0 3.8 1.7
## 29 1 1 3 19 11.2 9.6 3.6 12.7 2.5
## 30 1 1 3 31 8.2 0.8 0.0 5.2 0.0
## 31 1 1 3 51 6.1 1.4 0.2 11.0 0.1
## 32 1 1 3 52 6.6 0.7 4.1 0.3 0.0
## 33 1 1 3 63 8.9 0.0 0.0 4.2 3.6
## 34 1 1 3 78 2.5 1.3 0.0 0.0 6.0
## 35 1 1 3 79 8.6 1.4 0.0 0.0 0.0
## 36 1 1 3 86 9.0 4.6 2.0 5.1 0.0
## 37 1 1 4 3 13.6 0.1 0.0 1.7 0.0
## 38 1 1 4 10 8.1 4.4 0.0 6.5 1.1
## 39 1 1 4 15 8.1 0.6 0.4 0.2 0.0
## 40 1 1 4 16 6.8 0.9 1.2 0.1 0.0
## 41 1 1 4 19 8.9 4.4 0.0 0.0 0.0
## 42 1 1 4 31 11.7 0.8 0.0 5.1 0.9
## 43 1 1 4 51 9.3 2.5 0.7 8.8 9.2
## 44 1 1 4 52 8.5 3.9 0.2 0.0 0.0
## 45 1 1 4 63 10.4 0.0 0.0 3.0 0.0
## 46 1 1 4 78 9.4 1.0 1.2 3.2 0.0
## 47 1 1 4 79 8.4 1.8 0.0 0.0 0.0
## 48 1 1 4 86 8.3 5.8 0.0 0.0 0.0
## 49 1 1 5 3 14.0 0.3 0.0 0.0 1.7
## 50 1 1 5 10 9.6 8.4 1.5 10.2 2.4
## 51 1 1 5 15 4.1 0.3 0.3 4.9 1.3
## 52 1 1 5 16 10.1 0.4 2.8 10.2 2.0
## 53 1 1 5 19 5.3 0.9 1.7 11.5 7.1
## 54 1 1 5 31 11.2 0.0 0.4 1.1 0.0
## 55 1 1 5 51 9.2 2.4 0.2 9.5 6.2
## 56 1 1 5 52 4.1 0.0 0.0 6.5 3.2
## 57 1 1 5 63 9.8 0.0 0.0 2.0 5.2
## 58 1 1 5 78 3.3 1.1 1.3 0.0 3.3
## 59 1 1 5 79 8.0 0.8 0.0 0.0 0.0
## 60 1 1 5 86 2.2 0.0 0.0 2.7 2.8
## 61 1 1 6 3 0.4 1.2 0.0 0.0 9.5
## 62 1 1 6 10 13.2 11.2 0.0 2.4 0.0
## 63 1 1 6 15 0.0 0.3 0.2 2.9 8.7
## 64 1 1 6 16 4.9 0.3 0.3 7.4 1.2
## 65 1 1 6 19 12.2 9.5 0.0 4.1 0.0
## 66 1 1 6 31 12.0 0.0 0.0 0.6 0.0
## 67 1 1 6 51 10.2 4.7 1.7 1.6 0.0
## 68 1 1 6 52 3.8 0.0 0.0 9.4 0.8
## 69 1 1 6 63 3.1 0.0 0.0 9.5 6.2
## 70 1 1 6 78 1.5 0.0 0.0 2.1 4.3
## 71 1 1 6 79 11.4 0.4 0.0 0.0 0.0
## 72 1 1 6 86 1.0 0.0 0.0 6.4 0.9
## 73 1 1 7 3 2.9 0.0 0.0 0.0 5.5
## 74 1 1 7 10 11.0 6.4 0.0 0.0 0.0
## 75 1 1 7 15 1.2 0.1 0.0 1.1 5.1
## 76 1 1 7 16 9.0 2.6 0.4 0.1 0.2
## 77 1 1 7 19 7.0 3.2 0.0 4.9 3.2
## 78 1 1 7 31 12.2 0.0 0.0 2.5 2.0
## 79 1 1 7 51 8.6 1.7 0.1 1.4 0.1
## 80 1 1 7 52 5.8 0.0 1.7 8.5 1.1
## 81 1 1 7 63 8.3 0.0 0.0 1.1 0.4
## 82 1 1 7 78 4.9 1.2 0.0 1.1 3.5
## 83 1 1 7 79 5.1 0.0 0.0 2.0 0.0
## 84 1 1 7 86 5.2 1.2 0.0 7.9 4.9
## 85 1 1 8 3 3.5 0.5 1.3 0.0 3.8
## 86 1 1 8 10 10.2 8.2 0.0 5.2 0.0
## 87 1 1 8 15 1.9 1.9 0.1 3.9 5.4
## 88 1 1 8 16 2.4 1.0 1.8 9.7 2.9
## 89 1 1 8 19 5.4 3.5 0.0 2.1 0.0
## 90 1 1 8 31 4.0 0.0 0.0 10.0 1.2
## 91 1 1 8 51 14.9 0.8 0.7 1.0 0.0
## 92 1 1 8 52 2.1 0.0 0.0 4.9 6.5
## 93 1 1 8 63 5.9 0.0 0.0 12.4 9.2
## 94 1 1 8 78 1.5 0.0 0.0 0.0 1.3
## 95 1 1 8 79 10.5 NA 0.0 0.5 0.0
## 96 1 1 8 86 3.8 0.0 0.0 11.6 7.6
## 97 1 1 9 3 1.1 0.4 0.0 0.0 7.0
## 98 1 1 9 10 10.5 8.5 0.0 2.6 0.0
## 99 1 1 9 15 0.2 0.1 0.1 5.5 10.8
## 100 1 1 9 16 5.4 6.7 0.1 6.9 0.2
## 101 1 1 9 19 9.6 0.0 0.0 9.6 2.4
## 102 1 1 9 51 10.2 0.0 1.7 9.9 3.0
## 103 1 1 9 52 5.1 0.2 0.0 3.9 3.7
## 104 1 1 9 63 1.7 0.0 0.0 13.3 12.8
## 105 1 1 9 78 3.5 0.0 0.0 4.0 5.2
## 106 1 1 9 79 10.1 0.0 0.0 0.2 0.0
## 107 1 1 10 10 10.6 7.1 1.6 5.4 8.2
## 108 1 1 10 15 0.1 0.1 0.1 10.8 2.7
## 109 1 1 10 16 3.0 7.0 0.0 9.1 2.7
## 110 1 1 10 19 11.4 1.6 0.0 2.7 0.0
## 111 1 1 10 31 9.5 0.0 0.0 10.7 12.6
## 112 1 1 10 51 7.6 2.2 1.4 5.2 1.4
## 113 1 1 10 52 0.4 0.0 0.0 1.6 10.8
## 114 1 1 10 63 6.5 0.0 0.0 11.1 1.8
## 115 1 1 10 78 1.2 0.8 0.0 0.0 1.3
## 116 1 1 10 86 0.7 0.0 0.0 11.6 11.6
## 117 1 2 1 3 14.0 0.0 0.0 1.1 0.0
## 118 1 2 1 10 9.9 5.9 2.9 2.2 0.0
## 119 1 2 1 15 8.8 3.0 3.6 1.5 2.3
## 120 1 2 1 16 8.2 4.4 0.3 1.4 4.0
## 121 1 2 1 19 13.0 0.0 3.1 4.3 10.3
## 122 1 2 1 31 12.8 2.5 0.0 5.6 0.0
## 123 1 2 1 51 10.2 4.2 3.6 3.3 4.0
## 124 1 2 1 52 7.0 3.1 0.3 2.8 0.5
## 125 1 2 1 63 2.9 0.0 0.0 12.9 3.4
## 126 1 2 1 78 8.8 0.6 3.0 0.5 1.1
## 127 1 2 1 79 10.4 0.4 0.0 0.0 0.0
## 128 1 2 1 86 3.0 2.6 2.7 0.0 0.0
## 129 1 2 2 3 5.5 0.5 2.0 8.6 0.0
## 130 1 2 2 10 10.2 8.4 0.0 0.0 0.0
## 131 1 2 2 15 7.3 2.3 0.5 3.3 0.5
## 132 1 2 2 16 11.0 3.8 0.7 2.0 0.4
## 133 1 2 2 19 11.0 7.5 0.0 0.0 0.0
## 134 1 2 2 31 4.1 0.0 1.2 11.9 7.6
## 135 1 2 2 51 14.3 1.9 0.1 1.1 0.0
## 136 1 2 2 52 8.2 1.0 2.1 1.0 0.0
## 137 1 2 2 63 8.7 0.0 0.0 1.1 0.0
## 138 1 2 2 78 4.5 1.7 0.5 6.0 8.9
## 139 1 2 2 79 6.0 0.0 2.8 0.0 0.0
## 140 1 2 2 86 5.9 6.0 3.0 0.0 0.0
## 141 1 2 3 3 7.8 0.5 0.0 11.0 0.0
## 142 1 2 3 10 9.1 6.6 0.0 7.7 0.0
## 143 1 2 3 15 5.7 2.7 0.1 3.8 0.0
## 144 1 2 3 16 4.2 2.1 0.3 0.1 0.0
## 145 1 2 3 19 11.8 6.0 0.0 5.2 0.0
## 146 1 2 3 31 8.8 0.0 0.0 10.0 4.8
## 147 1 2 3 51 10.1 3.0 1.1 8.5 0.0
## 148 1 2 3 52 10.4 2.9 0.9 1.0 0.0
## 149 1 2 3 63 10.8 0.0 0.0 0.8 0.0
## 150 1 2 3 78 6.3 1.0 0.0 3.8 1.7
## 151 1 2 3 79 3.8 0.0 1.1 1.6 0.0
## 152 1 2 3 86 10.6 2.9 3.0 0.0 0.0
## 153 1 2 4 3 5.3 0.0 0.0 0.9 0.0
## 154 1 2 4 10 9.1 5.8 0.0 0.0 0.0
## 155 1 2 4 15 7.2 0.4 0.6 0.1 0.0
## 156 1 2 4 16 10.5 1.3 0.4 2.8 0.0
## 157 1 2 4 19 6.9 2.3 11.1 3.2 0.0
## 158 1 2 4 31 3.4 0.3 0.0 3.7 0.0
## 159 1 2 4 51 13.2 5.4 2.1 2.7 0.0
## 160 1 2 4 52 8.9 2.6 1.8 0.0 0.0
## 161 1 2 4 63 11.4 0.5 0.0 1.7 0.0
## 162 1 2 4 78 3.2 1.1 2.3 0.0 0.0
## 163 1 2 4 79 7.0 0.0 0.0 1.4 0.0
## 164 1 2 4 86 4.1 1.6 2.6 4.8 0.0
## 165 1 2 5 3 12.9 0.8 0.0 2.8 0.0
## 166 1 2 5 10 8.7 5.4 2.6 9.3 3.9
## 167 1 2 5 15 3.2 0.2 0.5 2.5 0.1
## 168 1 2 5 16 10.5 3.9 1.4 7.5 1.0
## 169 1 2 5 19 9.9 1.7 3.3 0.9 7.1
## 170 1 2 5 31 9.9 0.3 0.0 2.5 3.3
## 171 1 2 5 51 12.5 4.7 1.0 7.1 2.3
## 172 1 2 5 52 6.4 0.0 0.3 7.1 0.3
## 173 1 2 5 63 4.2 0.0 0.0 1.3 9.8
## 174 1 2 5 78 5.0 1.2 0.0 1.1 6.0
## 175 1 2 5 79 8.1 0.0 0.0 0.0 0.0
## 176 1 2 5 86 3.6 0.0 1.2 2.0 3.2
## 177 1 2 6 3 3.3 1.1 0.0 0.0 3.0
## 178 1 2 6 10 10.0 7.6 0.0 0.0 0.0
## 179 1 2 6 15 2.6 0.2 1.5 7.1 4.7
## 180 1 2 6 16 8.9 4.2 1.6 7.4 2.2
## 181 1 2 6 19 11.1 0.0 3.8 7.2 2.8
## 182 1 2 6 31 8.2 0.0 0.0 4.3 0.6
## 183 1 2 6 51 8.5 2.5 2.1 7.9 4.5
## 184 1 2 6 52 3.7 0.0 0.0 8.3 2.2
## 185 1 2 6 63 4.2 0.0 0.0 9.5 5.0
## 186 1 2 6 78 1.1 0.6 0.0 0.0 0.9
## 187 1 2 6 79 7.9 0.0 0.0 0.4 0.0
## 188 1 2 6 86 2.7 0.0 0.0 5.6 3.8
## 189 1 2 7 3 0.8 0.0 0.0 0.0 8.2
## 190 1 2 7 10 8.7 3.7 0.0 5.1 0.0
## 191 1 2 7 15 2.9 0.0 0.0 5.5 2.7
## 192 1 2 7 16 7.2 5.7 0.1 0.0 0.1
## 193 1 2 7 19 5.5 1.5 0.0 0.0 0.0
## 194 1 2 7 31 9.4 0.0 0.0 5.6 0.0
## 195 1 2 7 51 14.1 1.4 0.0 4.5 0.0
## 196 1 2 7 52 3.2 0.1 1.6 9.5 2.1
## 197 1 2 7 63 6.2 0.0 0.0 5.1 2.1
## 198 1 2 7 78 0.5 1.0 0.0 0.0 2.0
## 199 1 2 7 79 9.9 0.0 0.0 0.0 0.0
## 200 1 2 7 86 1.2 0.0 0.0 11.0 9.5
## 201 1 2 8 3 0.6 0.3 0.0 0.0 8.1
## 202 1 2 8 10 8.6 4.0 0.0 8.6 3.5
## 203 1 2 8 15 0.6 0.0 0.0 6.2 2.6
## 204 1 2 8 16 0.9 0.3 0.2 2.4 2.7
## 205 1 2 8 19 11.0 0.0 11.1 10.0 2.0
## 206 1 2 8 31 6.6 0.0 0.0 10.8 10.3
## 207 1 2 8 51 11.5 1.3 0.0 1.0 3.8
## 208 1 2 8 52 1.7 0.0 0.0 3.3 6.4
## 209 1 2 8 63 3.8 0.0 0.0 10.5 12.9
## 210 1 2 8 78 1.6 0.9 0.0 7.2 8.3
## 211 1 2 8 79 9.8 0.0 0.0 0.0 0.0
## 212 1 2 8 86 1.4 0.0 0.0 8.0 11.6
## 213 1 2 9 3 2.5 0.5 0.0 0.0 3.4
## 214 1 2 9 10 11.2 8.4 0.0 2.4 0.0
## 215 1 2 9 15 1.7 0.4 0.0 0.4 3.1
## 216 1 2 9 16 8.5 4.9 0.1 0.1 0.0
## 217 1 2 9 19 9.0 3.0 0.0 2.5 0.0
## 218 1 2 9 51 12.7 3.5 0.7 3.3 1.6
## 219 1 2 9 52 3.0 0.0 0.0 3.4 3.2
## 220 1 2 9 63 5.3 0.0 0.0 9.4 1.7
## 221 1 2 9 78 1.0 0.0 0.0 0.0 0.0
## 222 1 2 9 79 9.1 0.0 0.0 1.6 0.0
## 223 1 2 10 10 12.1 8.5 0.0 4.0 2.9
## 224 1 2 10 15 1.7 0.1 0.1 7.4 1.0
## 225 1 2 10 16 3.8 7.8 0.0 8.5 3.1
## 226 1 2 10 19 11.8 3.2 2.7 8.6 3.6
## 227 1 2 10 31 5.3 0.0 0.0 2.8 11.4
## 228 1 2 10 51 12.3 0.8 2.0 2.7 0.0
## 229 1 2 10 52 0.0 0.0 0.0 4.6 11.0
## 230 1 2 10 63 6.2 0.0 0.0 8.8 2.6
## 231 1 2 10 78 4.4 0.0 1.2 0.0 6.2
## 232 1 2 10 86 0.7 0.0 0.0 14.3 13.1
## 233 2 1 1 3 13.9 0.0 0.0 3.9 0.0
## 234 2 1 1 10 9.3 5.2 3.3 0.0 0.0
## 235 2 1 1 15 9.0 3.6 0.3 2.0 0.3
## 236 2 1 1 16 4.6 3.5 0.8 0.2 0.1
## 237 2 1 1 19 9.5 2.5 1.3 0.0 0.0
## 238 2 1 1 31 10.6 0.7 0.0 7.0 2.2
## 239 2 1 1 51 11.7 4.1 4.3 3.3 3.9
## 240 2 1 1 52 10.4 4.4 0.0 0.0 0.0
## 241 2 1 1 63 13.1 0.3 0.0 0.0 0.0
## 242 2 1 1 78 9.1 0.7 1.2 2.0 4.1
## 243 2 1 1 79 8.3 0.8 0.6 0.0 0.0
## 244 2 1 1 86 6.1 4.4 0.0 0.0 0.0
## 245 2 1 2 3 14.1 0.9 0.3 2.1 0.0
## 246 2 1 2 10 11.2 7.6 1.6 0.0 0.0
## 247 2 1 2 15 12.7 5.6 0.7 0.2 0.0
## 248 2 1 2 16 5.4 4.8 0.7 3.0 0.0
## 249 2 1 2 19 11.2 10.0 1.9 6.5 0.0
## 250 2 1 2 31 10.6 1.4 0.0 1.3 0.0
## 251 2 1 2 51 9.2 3.4 1.2 5.7 5.4
## 252 2 1 2 52 9.7 3.6 0.4 0.0 0.0
## 253 2 1 2 63 12.2 0.0 0.0 0.0 0.0
## 254 2 1 2 78 6.7 0.0 5.1 3.8 2.1
## 255 2 1 2 79 10.9 3.2 2.1 1.0 0.0
## 256 2 1 2 86 3.9 7.9 1.4 0.0 0.0
## 257 2 1 3 3 4.0 0.1 0.0 9.2 0.0
## 258 2 1 3 10 10.1 8.2 0.1 0.0 0.0
## 259 2 1 3 15 8.3 2.8 0.0 0.3 0.1
## 260 2 1 3 16 2.6 0.3 0.0 0.0 0.0
## 261 2 1 3 19 4.8 0.0 0.0 0.9 1.4
## 262 2 1 3 31 10.2 0.2 0.0 10.1 8.2
## 263 2 1 3 51 6.6 4.2 0.0 7.5 2.9
## 264 2 1 3 52 7.2 2.7 1.8 0.0 0.0
## 265 2 1 3 63 12.8 0.7 0.0 0.0 0.0
## 266 2 1 3 78 7.5 2.9 0.0 0.0 2.5
## 267 2 1 3 79 8.4 0.0 0.0 0.9 0.0
## 268 2 1 3 86 9.4 5.2 4.8 1.9 0.0
## 269 2 1 4 3 12.9 0.0 0.0 1.3 0.0
## 270 2 1 4 10 8.4 5.6 0.0 4.3 0.0
## 271 2 1 4 15 5.1 0.6 0.0 1.8 0.0
## 272 2 1 4 16 3.8 1.1 2.1 4.7 0.0
## 273 2 1 4 19 10.5 6.4 0.0 10.8 4.4
## 274 2 1 4 31 6.8 0.0 1.0 5.0 8.6
## 275 2 1 4 51 10.9 2.2 3.3 4.5 7.4
## 276 2 1 4 52 6.8 0.5 2.4 3.1 0.0
## 277 2 1 4 63 8.0 0.0 0.0 9.3 2.1
## 278 2 1 4 78 3.9 0.0 0.0 0.0 1.6
## 279 2 1 4 79 8.5 0.0 0.0 2.7 0.0
## 280 2 1 4 86 2.7 0.9 1.5 5.2 0.0
## 281 2 1 5 3 3.4 0.0 0.0 3.2 0.0
## 282 2 1 5 10 9.2 7.5 0.0 3.5 0.0
## 283 2 1 5 15 4.1 0.2 0.2 0.8 0.0
## 284 2 1 5 16 13.4 5.0 0.1 0.9 0.5
## 285 2 1 5 19 7.6 5.0 0.0 1.1 0.0
## 286 2 1 5 31 5.4 0.0 0.5 2.1 0.4
## 287 2 1 5 51 8.0 2.9 0.7 9.5 0.0
## 288 2 1 5 52 4.9 0.0 7.1 3.9 0.0
## 289 2 1 5 63 4.4 0.0 0.0 13.8 0.6
## 290 2 1 5 78 5.6 0.0 0.9 0.0 0.0
## 291 2 1 5 79 10.1 0.0 0.0 0.0 0.0
## 292 2 1 5 86 5.8 1.5 0.0 3.5 0.0
## 293 2 1 6 3 7.3 0.7 0.0 10.2 0.0
## 294 2 1 6 10 10.7 7.7 0.0 0.0 0.0
## 295 2 1 6 15 3.4 0.3 0.3 1.4 2.0
## 296 2 1 6 16 11.8 2.7 6.6 9.5 1.0
## 297 2 1 6 19 7.6 0.0 2.9 0.0 0.0
## 298 2 1 6 31 11.4 0.8 0.0 0.4 0.0
## 299 2 1 6 51 10.6 3.1 0.0 5.5 0.0
## 300 2 1 6 52 6.3 0.8 1.8 4.2 0.0
## 301 2 1 6 63 5.2 0.0 0.0 2.8 11.1
## 302 2 1 6 78 3.4 0.0 0.0 1.7 7.0
## 303 2 1 6 79 5.7 0.0 0.0 1.1 0.0
## 304 2 1 6 86 6.4 5.3 2.7 0.0 0.0
## 305 2 1 7 3 1.5 0.6 0.0 0.0 7.6
## 306 2 1 7 10 10.5 9.0 0.0 0.0 0.0
## 307 2 1 7 15 0.4 0.1 0.2 1.3 4.7
## 308 2 1 7 16 3.7 1.6 0.0 1.5 0.0
## 309 2 1 7 19 6.5 0.0 0.0 6.6 8.9
## 310 2 1 7 31 6.1 0.0 0.0 6.0 8.5
## 311 2 1 7 51 7.3 2.5 0.0 5.0 5.3
## 312 2 1 7 52 4.1 0.3 1.5 8.8 2.6
## 313 2 1 7 63 10.4 0.5 0.0 3.2 6.9
## 314 2 1 7 78 1.3 0.0 0.0 1.9 1.5
## 315 2 1 7 79 7.3 NA 0.0 0.7 0.0
## 316 2 1 7 86 1.2 0.0 0.0 10.1 7.3
## 317 2 1 8 3 0.9 0.3 0.0 0.0 6.8
## 318 2 1 8 10 10.9 4.6 0.0 0.0 0.0
## 319 2 1 8 15 3.2 0.1 0.3 1.0 3.6
## 320 2 1 8 16 4.5 NA 1.4 6.7 0.0
## 321 2 1 8 19 11.2 2.2 0.0 4.1 0.0
## 322 2 1 8 31 7.8 1.1 0.0 3.9 0.0
## 323 2 1 8 51 13.8 1.4 2.0 1.2 0.0
## 324 2 1 8 52 3.9 0.0 0.0 8.2 2.9
## 325 2 1 8 63 3.9 0.0 0.0 11.4 9.7
## 326 2 1 8 78 4.0 0.0 0.0 3.0 3.6
## 327 2 1 8 79 8.2 0.0 0.0 1.0 0.0
## 328 2 1 8 86 1.3 0.0 0.0 8.8 10.5
## 329 2 1 9 3 2.7 0.2 0.0 8.9 0.0
## 330 2 1 9 10 10.4 6.7 0.0 8.0 10.6
## 331 2 1 9 15 0.2 0.1 0.2 3.0 10.6
## 332 2 1 9 16 8.5 2.8 0.5 7.9 0.1
## 333 2 1 9 19 11.1 3.6 0.0 8.1 0.0
## 334 2 1 9 51 7.3 2.3 0.0 14.9 0.1
## 335 2 1 9 52 1.8 0.0 0.0 9.6 2.5
## 336 2 1 9 63 1.8 0.0 0.0 13.7 12.3
## 337 2 1 9 78 2.0 0.0 0.0 4.0 1.6
## 338 2 1 9 79 6.7 0.0 0.0 0.0 0.0
## 339 2 1 10 10 10.7 6.8 2.0 1.6 3.6
## 340 2 1 10 15 4.8 1.4 0.3 2.5 0.7
## 341 2 1 10 16 4.2 6.0 1.2 7.2 0.6
## 342 2 1 10 19 7.0 0.0 1.7 5.7 10.3
## 343 2 1 10 31 4.6 0.0 0.0 10.3 9.1
## 344 2 1 10 51 11.3 5.3 0.8 0.0 2.5
## 345 2 1 10 52 0.3 0.0 0.0 3.8 7.4
## 346 2 1 10 63 8.6 0.6 0.0 7.9 9.5
## 347 2 1 10 78 5.2 0.0 0.0 4.1 4.1
## 348 2 1 10 86 2.0 0.0 0.0 10.4 12.7
## 349 2 2 1 3 13.4 0.1 0.0 1.5 0.0
## 350 2 2 1 10 11.0 10.1 2.5 0.0 0.0
## 351 2 2 1 15 7.0 2.7 2.7 1.9 1.0
## 352 2 2 1 16 5.0 0.6 0.2 0.4 0.0
## 353 2 2 1 19 11.3 1.1 0.0 2.5 0.0
## 354 2 2 1 31 11.4 3.2 0.0 0.8 3.5
## 355 2 2 1 51 8.5 1.8 2.5 11.8 3.5
## 356 2 2 1 52 7.1 1.1 0.4 1.7 0.0
## 357 2 2 1 63 7.7 0.0 0.0 0.2 0.0
## 358 2 2 1 78 4.3 0.1 3.8 0.9 0.8
## 359 2 2 1 79 5.1 4.5 0.0 1.1 0.0
## 360 2 2 1 86 3.2 4.3 0.0 0.0 0.0
## 361 2 2 2 3 3.3 0.7 1.6 0.0 1.0
## 362 2 2 2 10 8.2 6.8 0.0 0.0 0.0
## 363 2 2 2 15 3.9 2.7 0.4 3.1 0.6
## 364 2 2 2 16 2.6 0.7 0.7 0.1 0.0
## 365 2 2 2 19 4.3 3.7 2.7 2.0 0.0
## 366 2 2 2 31 6.6 0.4 0.0 10.6 3.6
## 367 2 2 2 51 11.6 4.6 0.0 10.0 0.1
## 368 2 2 2 52 10.2 3.5 0.0 0.0 0.0
## 369 2 2 2 63 10.7 0.0 0.2 0.0 0.0
## 370 2 2 2 78 7.0 0.0 1.3 0.6 3.1
## 371 2 2 2 79 10.4 1.1 0.5 1.4 0.0
## 372 2 2 2 86 8.3 2.4 0.0 0.0 0.0
## 373 2 2 3 3 9.9 0.5 0.0 11.4 0.0
## 374 2 2 3 10 9.0 7.5 0.0 0.0 0.0
## 375 2 2 3 15 6.1 1.8 0.0 1.0 0.0
## 376 2 2 3 16 9.6 4.2 0.9 0.0 0.0
## 377 2 2 3 19 5.6 1.7 0.0 1.4 9.4
## 378 2 2 3 31 10.0 0.4 0.0 9.1 8.2
## 379 2 2 3 51 9.3 1.9 2.9 2.6 0.0
## 380 2 2 3 52 8.2 1.6 3.9 0.0 0.0
## 381 2 2 3 63 10.7 0.0 0.0 5.9 0.0
## 382 2 2 3 78 2.4 0.0 0.8 0.7 4.8
## 383 2 2 3 79 5.4 0.0 0.0 2.6 0.0
## 384 2 2 3 86 5.2 3.0 2.2 4.0 0.0
## 385 2 2 4 3 12.7 0.0 0.0 0.8 0.0
## 386 2 2 4 10 9.0 7.7 0.0 1.4 0.0
## 387 2 2 4 15 8.7 1.1 0.0 0.2 0.1
## 388 2 2 4 16 7.4 4.9 1.1 2.5 0.0
## 389 2 2 4 19 12.9 1.4 1.3 9.7 5.4
## 390 2 2 4 31 10.5 0.3 0.0 6.0 6.6
## 391 2 2 4 51 13.2 3.1 0.7 0.1 4.2
## 392 2 2 4 52 8.3 1.3 2.0 0.5 0.0
## 393 2 2 4 63 11.6 0.0 0.0 4.0 0.8
## 394 2 2 4 78 1.1 0.0 0.0 0.0 3.4
## 395 2 2 4 79 10.7 0.9 0.0 0.0 0.0
## 396 2 2 4 86 2.5 0.6 0.0 6.4 0.0
## 397 2 2 5 3 13.7 1.7 0.0 4.0 0.0
## 398 2 2 5 10 8.5 2.8 0.0 7.1 2.2
## 399 2 2 5 15 1.5 0.3 0.4 4.7 0.4
## 400 2 2 5 16 11.0 6.8 0.2 0.7 0.0
## 401 2 2 5 19 5.5 4.7 0.0 13.4 4.6
## 402 2 2 5 31 6.5 0.0 0.0 1.5 0.0
## 403 2 2 5 51 12.7 4.7 2.2 0.1 0.0
## 404 2 2 5 52 5.9 0.0 0.2 7.7 0.9
## 405 2 2 5 63 7.5 0.0 0.0 3.2 4.7
## 406 2 2 5 78 2.4 0.0 0.0 0.0 3.4
## 407 2 2 5 79 6.1 0.5 0.0 0.0 0.0
## 408 2 2 5 86 3.2 1.0 1.5 2.7 0.0
## 409 2 2 6 3 1.8 1.9 0.0 0.0 6.7
## 410 2 2 6 10 11.4 6.8 0.0 0.0 0.0
## 411 2 2 6 15 4.6 1.5 0.5 1.2 0.1
## 412 2 2 6 16 10.8 4.3 3.0 11.7 4.6
## 413 2 2 6 19 11.1 1.5 0.0 11.5 12.2
## 414 2 2 6 31 6.9 1.6 1.3 10.5 9.9
## 415 2 2 6 51 6.3 8.2 1.1 5.2 0.0
## 416 2 2 6 52 5.6 0.7 0.8 6.3 2.6
## 417 2 2 6 63 6.1 0.0 0.0 2.8 8.8
## 418 2 2 6 78 1.3 0.0 1.1 0.0 0.0
## 419 2 2 6 79 9.4 0.8 0.0 0.5 0.0
## 420 2 2 6 86 3.3 0.6 0.0 5.7 0.0
## 421 2 2 7 3 3.5 1.2 0.0 0.0 7.9
## 422 2 2 7 10 9.6 4.4 0.0 6.1 0.0
## 423 2 2 7 15 1.7 0.0 0.0 3.4 1.8
## 424 2 2 7 16 8.1 5.6 0.3 0.2 0.1
## 425 2 2 7 19 9.3 0.0 6.7 10.9 3.0
## 426 2 2 7 31 7.0 0.0 0.0 8.5 3.0
## 427 2 2 7 51 12.4 4.4 3.2 0.0 0.1
## 428 2 2 7 52 4.2 0.0 1.3 10.5 1.4
## 429 2 2 7 63 9.8 0.0 0.0 0.3 1.3
## 430 2 2 7 78 1.4 1.0 0.0 0.0 0.0
## 431 2 2 7 79 6.6 0.0 0.0 2.0 0.0
## 432 2 2 7 86 3.6 0.0 0.0 5.1 1.1
## 433 2 2 8 3 0.5 0.3 0.0 0.0 7.6
## 434 2 2 8 10 10.3 9.3 0.0 2.6 0.0
## 435 2 2 8 15 2.3 0.0 0.1 3.1 5.6
## 436 2 2 8 16 5.3 3.5 0.2 1.5 0.0
## 437 2 2 8 19 8.7 5.2 0.0 0.0 0.0
## 438 2 2 8 31 9.9 1.0 0.0 5.5 9.1
## 439 2 2 8 51 8.5 6.2 4.1 4.8 2.3
## 440 2 2 8 52 0.0 0.0 0.0 0.5 8.7
## 441 2 2 8 63 5.7 0.0 0.0 8.6 4.2
## 442 2 2 8 78 2.1 1.2 0.0 7.2 6.3
## 443 2 2 8 79 5.7 0.0 1.4 2.3 NA
## 444 2 2 8 86 2.8 0.0 0.0 6.4 8.0
## 445 2 2 9 3 1.8 1.4 0.0 0.0 7.0
## 446 2 2 9 10 11.0 8.8 0.0 0.0 0.0
## 447 2 2 9 15 0.0 1.3 0.0 4.5 6.4
## 448 2 2 9 16 3.8 2.2 0.0 0.0 0.0
## 449 2 2 9 19 6.2 0.0 0.0 7.9 12.6
## 450 2 2 9 51 10.6 3.9 0.0 0.0 2.0
## 451 2 2 9 52 1.6 0.0 0.0 5.0 8.5
## 452 2 2 9 63 9.1 0.0 0.0 8.0 4.4
## 453 2 2 9 78 3.4 0.0 0.9 0.0 2.2
## 454 2 2 9 79 9.4 0.0 0.0 1.3 0.0
## 455 2 2 10 10 10.5 6.5 0.0 8.4 0.0
## 456 2 2 10 15 1.1 0.1 0.2 8.3 3.2
## 457 2 2 10 16 2.9 3.5 1.1 9.3 2.1
## 458 2 2 10 19 10.9 0.0 4.2 5.0 10.9
## 459 2 2 10 31 2.3 0.0 0.0 10.3 10.2
## 460 2 2 10 51 9.9 5.7 2.4 1.7 5.4
## 461 2 2 10 52 3.8 0.0 0.0 10.7 6.4
## 462 2 2 10 63 9.0 0.0 0.0 6.7 10.7
## 463 2 2 10 78 1.5 0.0 0.0 1.1 2.4
## 464 2 2 10 86 1.0 0.0 0.0 11.2 11.6
## 465 3 1 1 3 14.1 0.0 0.0 1.1 0.0
## 466 3 1 1 10 11.3 10.2 0.0 0.0 0.0
## 467 3 1 1 15 5.8 1.0 0.5 2.8 0.6
## 468 3 1 1 16 7.8 0.2 0.6 1.4 0.0
## 469 3 1 1 19 7.2 3.4 5.2 4.4 0.0
## 470 3 1 1 31 7.1 0.7 0.3 6.6 9.2
## 471 3 1 1 51 13.6 1.4 0.0 2.1 0.0
## 472 3 1 1 52 10.6 2.0 0.0 1.2 0.0
## 473 3 1 1 63 8.6 0.4 1.9 0.0 0.0
## 474 3 1 1 78 7.4 1.6 0.0 3.6 9.3
## 475 3 1 1 79 8.8 0.0 1.6 0.9 0.0
## 476 3 1 1 86 6.7 4.5 1.5 0.0 0.0
## 477 3 1 2 3 6.5 0.6 0.7 0.1 1.4
## 478 3 1 2 10 10.3 5.7 2.1 10.0 5.3
## 479 3 1 2 15 6.3 3.6 3.5 3.4 0.2
## 480 3 1 2 16 8.2 7.3 1.3 3.7 0.1
## 481 3 1 2 19 11.4 3.6 5.8 1.4 0.0
## 482 3 1 2 31 10.5 0.4 0.0 5.8 6.3
## 483 3 1 2 51 12.2 4.7 0.0 3.1 3.9
## 484 3 1 2 52 10.7 2.8 0.8 0.0 0.0
## 485 3 1 2 63 6.2 0.0 0.0 9.8 1.8
## 486 3 1 2 78 2.7 1.9 0.0 1.2 1.3
## 487 3 1 2 79 7.7 1.1 0.0 2.6 0.0
## 488 3 1 2 86 7.7 1.6 2.6 0.0 0.0
## 489 3 1 3 3 7.3 0.2 0.0 7.1 0.0
## 490 3 1 3 10 9.6 8.0 0.0 0.0 0.0
## 491 3 1 3 15 5.2 0.7 0.3 5.5 0.5
## 492 3 1 3 16 10.6 0.4 0.5 1.0 0.0
## 493 3 1 3 19 6.4 4.0 1.0 4.0 0.0
## 494 3 1 3 31 7.6 0.5 0.0 6.8 0.0
## 495 3 1 3 51 9.1 3.0 0.0 4.4 5.1
## 496 3 1 3 52 8.1 0.2 2.0 0.0 0.0
## 497 3 1 3 63 9.0 0.0 0.0 2.6 0.0
## 498 3 1 3 78 9.2 2.6 1.8 0.0 0.8
## 499 3 1 3 79 7.5 2.1 0.0 0.0 0.0
## 500 3 1 3 86 5.2 1.5 2.1 5.9 2.9
## 501 3 1 4 3 1.5 0.5 0.4 7.8 0.0
## 502 3 1 4 10 10.3 8.4 0.0 0.0 0.0
## 503 3 1 4 15 5.2 0.4 0.3 2.0 0.0
## 504 3 1 4 16 12.7 5.4 2.2 4.1 1.0
## 505 3 1 4 19 5.8 1.6 0.0 6.5 0.0
## 506 3 1 4 31 11.0 2.8 0.0 2.7 3.1
## 507 3 1 4 51 7.0 3.7 0.1 12.9 0.0
## 508 3 1 4 52 3.3 1.7 0.9 5.6 0.0
## 509 3 1 4 63 5.6 0.0 0.0 13.3 4.4
## 510 3 1 4 78 7.7 1.3 0.0 0.0 5.6
## 511 3 1 4 79 5.7 0.0 0.0 2.5 0.0
## 512 3 1 4 86 1.4 0.0 1.4 4.7 5.7
## 513 3 1 5 3 4.0 0.0 0.0 4.6 0.0
## 514 3 1 5 10 10.7 8.8 0.0 0.0 0.0
## 515 3 1 5 15 NA NA NA NA NA
## 516 3 1 5 16 5.2 1.0 0.5 0.0 0.0
## 517 3 1 5 19 10.2 2.9 0.0 0.0 1.5
## 518 3 1 5 31 12.3 2.7 0.0 9.8 6.9
## 519 3 1 5 51 10.6 4.4 2.5 1.7 0.0
## 520 3 1 5 52 6.3 0.1 0.8 2.1 0.0
## 521 3 1 5 63 9.1 0.0 0.0 0.0 1.4
## 522 3 1 5 78 3.4 0.8 1.6 1.5 1.3
## 523 3 1 5 79 7.9 0.0 0.0 1.6 0.0
## 524 3 1 5 86 5.4 4.0 0.0 3.0 0.0
## 525 3 1 6 3 2.2 1.0 0.0 8.9 0.9
## 526 3 1 6 10 10.8 5.4 0.0 0.0 0.0
## 527 3 1 6 15 1.0 0.1 0.1 2.4 6.0
## 528 3 1 6 16 5.3 0.8 3.1 9.8 1.3
## 529 3 1 6 19 10.6 1.0 0.0 0.0 0.0
## 530 3 1 6 31 8.3 0.0 0.0 3.8 0.3
## 531 3 1 6 51 12.4 4.5 0.9 5.4 2.0
## 532 3 1 6 52 4.4 0.0 0.8 6.3 0.4
## 533 3 1 6 63 6.5 0.0 0.0 4.7 1.7
## 534 3 1 6 78 5.5 0.0 1.5 1.8 2.9
## 535 3 1 6 79 8.4 0.0 0.5 1.0 0.0
## 536 3 1 6 86 2.2 1.2 0.0 2.8 0.0
## 537 3 1 7 3 0.9 0.7 0.0 0.0 3.0
## 538 3 1 7 10 7.1 2.7 0.0 7.4 0.0
## 539 3 1 7 15 1.2 0.0 0.0 5.4 3.8
## 540 3 1 7 16 12.7 5.1 0.0 0.6 0.0
## 541 3 1 7 19 8.6 0.0 0.0 10.4 0.0
## 542 3 1 7 31 6.4 0.0 0.0 5.0 3.6
## 543 3 1 7 51 9.4 2.2 2.9 8.4 1.6
## 544 3 1 7 52 6.4 0.3 1.1 7.0 0.0
## 545 3 1 7 63 9.5 0.0 0.0 1.4 0.0
## 546 3 1 7 78 4.3 0.0 0.0 3.4 6.2
## 547 3 1 7 79 7.2 0.0 0.0 0.7 0.5
## 548 3 1 7 86 3.0 2.3 2.8 0.0 0.0
## 549 3 1 8 3 1.5 0.6 0.0 0.0 5.9
## 550 3 1 8 10 10.0 6.0 0.0 1.0 0.0
## 551 3 1 8 15 0.6 0.0 0.0 0.6 3.4
## 552 3 1 8 16 2.2 0.9 0.5 7.8 0.1
## 553 3 1 8 19 11.1 2.9 0.0 0.0 5.3
## 554 3 1 8 31 4.2 0.0 0.0 6.8 3.3
## 555 3 1 8 51 14.5 5.5 1.9 0.1 0.1
## 556 3 1 8 52 0.0 0.0 0.0 3.2 7.2
## 557 3 1 8 63 7.8 0.0 0.0 6.6 0.4
## 558 3 1 8 78 0.8 0.0 0.0 0.0 0.6
## 559 3 1 8 79 6.8 0.0 0.0 0.5 0.0
## 560 3 1 8 86 1.4 0.0 0.0 10.8 7.5
## 561 3 1 9 3 1.6 0.5 0.0 0.0 4.3
## 562 3 1 9 10 10.2 8.5 0.0 3.7 1.7
## 563 3 1 9 15 0.7 0.0 0.1 3.4 7.3
## 564 3 1 9 16 7.5 2.6 0.7 6.6 0.3
## 565 3 1 9 19 7.9 0.0 0.0 13.1 8.9
## 566 3 1 9 51 8.2 0.4 1.9 4.0 4.2
## 567 3 1 9 52 1.1 0.0 0.0 4.7 4.5
## 568 3 1 9 63 7.5 0.0 0.0 11.7 8.4
## 569 3 1 9 78 7.9 1.0 0.0 2.8 3.8
## 570 3 1 9 79 7.8 0.0 0.0 3.8 0.0
## 571 3 1 10 10 11.3 9.2 0.0 3.3 0.0
## 572 3 1 10 15 2.5 0.4 0.1 2.6 0.2
## 573 3 1 10 16 3.9 1.4 1.0 6.7 4.4
## 574 3 1 10 19 9.1 4.0 0.0 5.8 0.0
## 575 3 1 10 31 6.5 0.0 0.0 9.3 11.4
## 576 3 1 10 51 8.0 3.2 0.0 6.8 3.3
## 577 3 1 10 52 1.2 0.8 0.2 1.4 9.0
## 578 3 1 10 63 7.0 0.0 0.0 11.9 3.3
## 579 3 1 10 78 3.7 0.0 0.9 0.0 1.3
## 580 3 1 10 86 2.5 0.0 0.0 7.0 10.5
## 581 3 2 1 3 9.5 0.0 0.6 2.8 0.0
## 582 3 2 1 10 10.1 5.0 0.8 0.0 0.0
## 583 3 2 1 15 8.0 3.6 0.5 0.8 0.6
## 584 3 2 1 16 5.2 1.1 0.5 3.6 0.6
## 585 3 2 1 19 11.1 2.8 0.0 13.2 3.0
## 586 3 2 1 31 12.5 3.7 0.0 8.1 9.2
## 587 3 2 1 51 8.5 4.7 2.0 6.0 6.1
## 588 3 2 1 52 10.3 4.7 0.0 0.0 0.0
## 589 3 2 1 63 10.3 0.0 0.0 0.4 0.0
## 590 3 2 1 78 5.0 0.1 3.7 2.5 8.9
## 591 3 2 1 79 8.3 0.0 0.0 0.9 0.0
## 592 3 2 1 86 7.9 7.0 2.5 0.0 0.0
## 593 3 2 2 3 13.8 0.8 0.0 6.6 0.4
## 594 3 2 2 10 10.2 4.4 0.0 0.0 0.0
## 595 3 2 2 15 10.4 3.2 1.6 0.1 0.4
## 596 3 2 2 16 1.5 2.4 1.2 0.1 0.0
## 597 3 2 2 19 6.0 3.0 10.5 0.0 0.0
## 598 3 2 2 31 8.1 0.5 0.0 9.3 5.4
## 599 3 2 2 51 12.1 5.2 4.4 2.7 5.7
## 600 3 2 2 52 9.1 1.9 1.6 0.0 0.0
## 601 3 2 2 63 6.5 0.0 0.6 0.0 1.4
## 602 3 2 2 78 4.4 0.0 1.5 0.0 7.1
## 603 3 2 2 79 6.7 0.0 0.0 0.0 0.0
## 604 3 2 2 86 4.0 5.7 0.0 0.0 0.0
## 605 3 2 3 3 7.3 0.5 0.0 11.1 0.0
## 606 3 2 3 10 11.0 8.4 0.0 0.0 0.0
## 607 3 2 3 15 6.5 1.6 0.3 1.5 0.9
## 608 3 2 3 16 8.6 2.1 2.5 0.7 0.8
## 609 3 2 3 19 9.7 1.7 2.9 10.8 0.0
## 610 3 2 3 31 8.7 0.0 0.0 7.7 9.1
## 611 3 2 3 51 9.3 0.0 0.0 6.8 3.5
## 612 3 2 3 52 10.2 1.2 0.9 0.0 0.0
## 613 3 2 3 63 9.1 0.0 0.0 6.7 0.0
## 614 3 2 3 78 2.0 1.1 0.0 0.0 6.5
## 615 3 2 3 79 8.7 5.1 0.0 0.7 0.0
## 616 3 2 3 86 5.7 1.5 2.7 3.1 0.0
## 617 3 2 4 3 5.9 0.2 0.0 1.3 0.0
## 618 3 2 4 10 9.5 7.1 0.0 5.7 0.0
## 619 3 2 4 15 7.0 0.3 0.1 2.9 0.0
## 620 3 2 4 16 6.8 4.4 2.8 5.8 1.0
## 621 3 2 4 19 4.7 0.0 0.0 6.4 0.0
## 622 3 2 4 31 9.2 0.0 0.0 7.9 2.6
## 623 3 2 4 51 10.3 2.1 2.7 7.2 5.3
## 624 3 2 4 52 5.2 0.8 1.4 6.4 0.0
## 625 3 2 4 63 5.8 0.0 0.0 11.2 3.4
## 626 3 2 4 78 3.5 2.9 1.1 2.7 6.2
## 627 3 2 4 79 9.2 0.0 0.0 1.0 0.0
## 628 3 2 4 86 2.5 0.0 0.0 4.6 4.7
## 629 3 2 5 3 10.1 4.3 0.0 0.0 3.2
## 630 3 2 5 10 9.0 4.3 0.0 0.0 0.0
## 631 3 2 5 15 3.6 0.2 0.4 4.6 0.4
## 632 3 2 5 16 6.7 2.0 0.0 0.5 0.0
## 633 3 2 5 19 7.1 0.0 4.2 11.1 10.3
## 634 3 2 5 31 11.5 0.0 0.3 2.6 4.2
## 635 3 2 5 51 7.5 2.3 2.3 4.6 5.1
## 636 3 2 5 52 4.0 0.0 0.0 1.4 9.2
## 637 3 2 5 63 9.0 0.0 0.0 5.3 9.7
## 638 3 2 5 78 1.5 0.8 0.0 0.0 0.0
## 639 3 2 5 79 9.4 0.5 0.0 0.6 0.0
## 640 3 2 5 86 3.6 0.1 0.0 5.5 0.0
## 641 3 2 6 3 5.3 2.2 0.0 0.0 4.7
## 642 3 2 6 10 11.5 5.5 0.0 6.8 0.0
## 643 3 2 6 15 4.3 0.2 0.3 0.6 0.5
## 644 3 2 6 16 12.1 5.1 0.9 3.2 0.2
## 645 3 2 6 19 6.1 3.6 0.0 13.0 6.0
## 646 3 2 6 31 8.1 0.0 2.5 7.2 9.7
## 647 3 2 6 51 8.5 2.5 2.3 5.9 0.0
## 648 3 2 6 52 3.9 0.0 1.1 5.2 0.4
## 649 3 2 6 63 11.4 0.0 0.0 2.8 0.8
## 650 3 2 6 78 4.3 0.0 1.2 0.0 2.4
## 651 3 2 6 79 8.8 0.0 0.0 1.1 0.0
## 652 3 2 6 86 4.1 0.0 0.0 4.4 1.1
## 653 3 2 7 3 2.6 0.9 0.0 0.0 9.8
## 654 3 2 7 10 9.5 8.1 0.0 3.9 0.0
## 655 3 2 7 15 1.0 0.1 0.1 3.1 6.0
## 656 3 2 7 16 10.8 7.5 0.1 1.2 0.0
## 657 3 2 7 19 9.0 0.0 0.0 13.0 11.5
## 658 3 2 7 31 12.0 0.4 0.0 11.3 8.0
## 659 3 2 7 51 8.7 4.6 1.1 4.5 4.9
## 660 3 2 7 52 5.7 0.8 3.7 6.0 0.2
## 661 3 2 7 63 10.7 0.5 0.0 8.1 0.9
## 662 3 2 7 78 0.2 0.0 0.0 1.0 3.5
## 663 3 2 7 79 6.5 0.0 0.0 1.5 0.0
## 664 3 2 7 86 2.4 0.0 1.4 7.5 4.0
## 665 3 2 8 3 0.5 0.5 0.0 0.0 11.3
## 666 3 2 8 10 10.9 4.5 0.0 6.4 0.0
## 667 3 2 8 15 0.2 0.1 0.2 2.0 6.8
## 668 3 2 8 16 3.3 1.2 0.1 0.3 0.0
## 669 3 2 8 19 11.5 0.0 0.0 12.6 8.5
## 670 3 2 8 31 8.1 0.0 0.0 2.0 0.0
## 671 3 2 8 51 14.0 1.1 0.0 3.0 0.1
## 672 3 2 8 52 3.2 0.0 0.0 10.1 3.5
## 673 3 2 8 63 8.6 0.4 0.0 4.2 6.6
## 674 3 2 8 78 3.2 0.0 0.0 0.7 1.3
## 675 3 2 8 79 5.7 0.0 0.0 1.4 0.0
## 676 3 2 8 86 1.4 0.0 0.0 6.4 8.7
## 677 3 2 9 3 0.7 0.3 0.0 0.0 6.7
## 678 3 2 9 10 7.3 3.4 0.0 8.6 4.9
## 679 3 2 9 15 1.5 0.0 0.0 2.6 7.1
## 680 3 2 9 16 3.6 2.4 2.4 0.9 0.0
## 681 3 2 9 19 9.1 0.0 7.2 9.8 11.3
## 682 3 2 9 51 8.9 4.7 0.0 8.7 0.0
## 683 3 2 9 52 4.0 0.0 0.0 0.0 9.5
## 684 3 2 9 63 6.0 0.0 0.0 11.6 10.5
## 685 3 2 9 78 0.0 0.0 0.0 0.0 0.0
## 686 3 2 9 79 8.1 1.5 0.0 0.4 0.0
## 687 3 2 10 10 10.0 5.4 0.0 5.4 1.9
## 688 3 2 10 15 4.3 3.3 0.0 2.1 0.3
## 689 3 2 10 16 2.5 0.7 1.6 6.0 1.3
## 690 3 2 10 19 12.2 0.0 4.6 9.3 11.8
## 691 3 2 10 31 10.4 0.0 0.0 5.7 0.0
## 692 3 2 10 51 11.6 2.4 2.0 0.0 0.0
## 693 3 2 10 52 1.8 0.0 0.0 2.6 9.3
## 694 3 2 10 63 7.0 0.0 0.0 11.4 7.3
## 695 3 2 10 78 3.3 0.0 0.0 2.5 1.4
## 696 3 2 10 86 2.5 0.0 0.0 8.2 9.45.6 (cast) FUNCTION: Subsetting data
require(plyr)## Loading required package: plyr## -------------------------------------------------------------------------## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)## -------------------------------------------------------------------------##
## Attaching package: 'plyr'## The following object is masked from 'package:maps':
##
## ozone## The following objects are masked from 'package:dplyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarizedcast(ffm, treatment+rep+time+subject ~ variable,
subset =.(variable=="potato"))## treatment rep time subject potato
## 1 1 1 1 3 2.9
## 2 1 1 1 10 11.0
## 3 1 1 1 15 1.2
## 4 1 1 1 16 9.0
## 5 1 1 1 19 7.0
## 6 1 1 1 31 12.2
## 7 1 1 1 51 8.6
## 8 1 1 1 52 5.8
## 9 1 1 1 63 8.3
## 10 1 1 1 78 4.9
## 11 1 1 1 79 5.1
## 12 1 1 1 86 5.2
## 13 1 1 2 3 9.0
## 14 1 1 2 10 8.0
## 15 1 1 2 15 5.3
## 16 1 1 2 16 4.1
## 17 1 1 2 19 8.7
## 18 1 1 2 31 9.7
## 19 1 1 2 51 9.4
## 20 1 1 2 52 6.5
## 21 1 1 2 63 8.9
## 22 1 1 2 78 3.3
## 23 1 1 2 79 5.9
## 24 1 1 2 86 6.7
## 25 1 1 3 3 11.8
## 26 1 1 3 10 9.3
## 27 1 1 3 15 3.4
## 28 1 1 3 16 1.5
## 29 1 1 3 19 11.2
## 30 1 1 3 31 8.2
## 31 1 1 3 51 6.1
## 32 1 1 3 52 6.6
## 33 1 1 3 63 8.9
## 34 1 1 3 78 2.5
## 35 1 1 3 79 8.6
## 36 1 1 3 86 9.0
## 37 1 1 4 3 13.6
## 38 1 1 4 10 8.1
## 39 1 1 4 15 8.1
## 40 1 1 4 16 6.8
## 41 1 1 4 19 8.9
## 42 1 1 4 31 11.7
## 43 1 1 4 51 9.3
## 44 1 1 4 52 8.5
## 45 1 1 4 63 10.4
## 46 1 1 4 78 9.4
## 47 1 1 4 79 8.4
## 48 1 1 4 86 8.3
## 49 1 1 5 3 14.0
## 50 1 1 5 10 9.6
## 51 1 1 5 15 4.1
## 52 1 1 5 16 10.1
## 53 1 1 5 19 5.3
## 54 1 1 5 31 11.2
## 55 1 1 5 51 9.2
## 56 1 1 5 52 4.1
## 57 1 1 5 63 9.8
## 58 1 1 5 78 3.3
## 59 1 1 5 79 8.0
## 60 1 1 5 86 2.2
## 61 1 1 6 3 0.4
## 62 1 1 6 10 13.2
## 63 1 1 6 15 0.0
## 64 1 1 6 16 4.9
## 65 1 1 6 19 12.2
## 66 1 1 6 31 12.0
## 67 1 1 6 51 10.2
## 68 1 1 6 52 3.8
## 69 1 1 6 63 3.1
## 70 1 1 6 78 1.5
## 71 1 1 6 79 11.4
## 72 1 1 6 86 1.0
## 73 1 1 7 3 2.9
## 74 1 1 7 10 11.0
## 75 1 1 7 15 1.2
## 76 1 1 7 16 9.0
## 77 1 1 7 19 7.0
## 78 1 1 7 31 12.2
## 79 1 1 7 51 8.6
## 80 1 1 7 52 5.8
## 81 1 1 7 63 8.3
## 82 1 1 7 78 4.9
## 83 1 1 7 79 5.1
## 84 1 1 7 86 5.2
## 85 1 1 8 3 3.5
## 86 1 1 8 10 10.2
## 87 1 1 8 15 1.9
## 88 1 1 8 16 2.4
## 89 1 1 8 19 5.4
## 90 1 1 8 31 4.0
## 91 1 1 8 51 14.9
## 92 1 1 8 52 2.1
## 93 1 1 8 63 5.9
## 94 1 1 8 78 1.5
## 95 1 1 8 79 10.5
## 96 1 1 8 86 3.8
## 97 1 1 9 3 1.1
## 98 1 1 9 10 10.5
## 99 1 1 9 15 0.2
## 100 1 1 9 16 5.4
## 101 1 1 9 19 9.6
## 102 1 1 9 51 10.2
## 103 1 1 9 52 5.1
## 104 1 1 9 63 1.7
## 105 1 1 9 78 3.5
## 106 1 1 9 79 10.1
## 107 1 1 10 10 10.6
## 108 1 1 10 15 0.1
## 109 1 1 10 16 3.0
## 110 1 1 10 19 11.4
## 111 1 1 10 31 9.5
## 112 1 1 10 51 7.6
## 113 1 1 10 52 0.4
## 114 1 1 10 63 6.5
## 115 1 1 10 78 1.2
## 116 1 1 10 86 0.7
## 117 1 2 1 3 14.0
## 118 1 2 1 10 9.9
## 119 1 2 1 15 8.8
## 120 1 2 1 16 8.2
## 121 1 2 1 19 13.0
## 122 1 2 1 31 12.8
## 123 1 2 1 51 10.2
## 124 1 2 1 52 7.0
## 125 1 2 1 63 2.9
## 126 1 2 1 78 8.8
## 127 1 2 1 79 10.4
## 128 1 2 1 86 3.0
## 129 1 2 2 3 5.5
## 130 1 2 2 10 10.2
## 131 1 2 2 15 7.3
## 132 1 2 2 16 11.0
## 133 1 2 2 19 11.0
## 134 1 2 2 31 4.1
## 135 1 2 2 51 14.3
## 136 1 2 2 52 8.2
## 137 1 2 2 63 8.7
## 138 1 2 2 78 4.5
## 139 1 2 2 79 6.0
## 140 1 2 2 86 5.9
## 141 1 2 3 3 7.8
## 142 1 2 3 10 9.1
## 143 1 2 3 15 5.7
## 144 1 2 3 16 4.2
## 145 1 2 3 19 11.8
## 146 1 2 3 31 8.8
## 147 1 2 3 51 10.1
## 148 1 2 3 52 10.4
## 149 1 2 3 63 10.8
## 150 1 2 3 78 6.3
## 151 1 2 3 79 3.8
## 152 1 2 3 86 10.6
## 153 1 2 4 3 5.3
## 154 1 2 4 10 9.1
## 155 1 2 4 15 7.2
## 156 1 2 4 16 10.5
## 157 1 2 4 19 6.9
## 158 1 2 4 31 3.4
## 159 1 2 4 51 13.2
## 160 1 2 4 52 8.9
## 161 1 2 4 63 11.4
## 162 1 2 4 78 3.2
## 163 1 2 4 79 7.0
## 164 1 2 4 86 4.1
## 165 1 2 5 3 12.9
## 166 1 2 5 10 8.7
## 167 1 2 5 15 3.2
## 168 1 2 5 16 10.5
## 169 1 2 5 19 9.9
## 170 1 2 5 31 9.9
## 171 1 2 5 51 12.5
## 172 1 2 5 52 6.4
## 173 1 2 5 63 4.2
## 174 1 2 5 78 5.0
## 175 1 2 5 79 8.1
## 176 1 2 5 86 3.6
## 177 1 2 6 3 3.3
## 178 1 2 6 10 10.0
## 179 1 2 6 15 2.6
## 180 1 2 6 16 8.9
## 181 1 2 6 19 11.1
## 182 1 2 6 31 8.2
## 183 1 2 6 51 8.5
## 184 1 2 6 52 3.7
## 185 1 2 6 63 4.2
## 186 1 2 6 78 1.1
## 187 1 2 6 79 7.9
## 188 1 2 6 86 2.7
## 189 1 2 7 3 0.8
## 190 1 2 7 10 8.7
## 191 1 2 7 15 2.9
## 192 1 2 7 16 7.2
## 193 1 2 7 19 5.5
## 194 1 2 7 31 9.4
## 195 1 2 7 51 14.1
## 196 1 2 7 52 3.2
## 197 1 2 7 63 6.2
## 198 1 2 7 78 0.5
## 199 1 2 7 79 9.9
## 200 1 2 7 86 1.2
## 201 1 2 8 3 0.6
## 202 1 2 8 10 8.6
## 203 1 2 8 15 0.6
## 204 1 2 8 16 0.9
## 205 1 2 8 19 11.0
## 206 1 2 8 31 6.6
## 207 1 2 8 51 11.5
## 208 1 2 8 52 1.7
## 209 1 2 8 63 3.8
## 210 1 2 8 78 1.6
## 211 1 2 8 79 9.8
## 212 1 2 8 86 1.4
## 213 1 2 9 3 2.5
## 214 1 2 9 10 11.2
## 215 1 2 9 15 1.7
## 216 1 2 9 16 8.5
## 217 1 2 9 19 9.0
## 218 1 2 9 51 12.7
## 219 1 2 9 52 3.0
## 220 1 2 9 63 5.3
## 221 1 2 9 78 1.0
## 222 1 2 9 79 9.1
## 223 1 2 10 10 12.1
## 224 1 2 10 15 1.7
## 225 1 2 10 16 3.8
## 226 1 2 10 19 11.8
## 227 1 2 10 31 5.3
## 228 1 2 10 51 12.3
## 229 1 2 10 52 0.0
## 230 1 2 10 63 6.2
## 231 1 2 10 78 4.4
## 232 1 2 10 86 0.7
## 233 2 1 1 3 13.9
## 234 2 1 1 10 9.3
## 235 2 1 1 15 9.0
## 236 2 1 1 16 4.6
## 237 2 1 1 19 9.5
## 238 2 1 1 31 10.6
## 239 2 1 1 51 11.7
## 240 2 1 1 52 10.4
## 241 2 1 1 63 13.1
## 242 2 1 1 78 9.1
## 243 2 1 1 79 8.3
## 244 2 1 1 86 6.1
## 245 2 1 2 3 14.1
## 246 2 1 2 10 11.2
## 247 2 1 2 15 12.7
## 248 2 1 2 16 5.4
## 249 2 1 2 19 11.2
## 250 2 1 2 31 10.6
## 251 2 1 2 51 9.2
## 252 2 1 2 52 9.7
## 253 2 1 2 63 12.2
## 254 2 1 2 78 6.7
## 255 2 1 2 79 10.9
## 256 2 1 2 86 3.9
## 257 2 1 3 3 4.0
## 258 2 1 3 10 10.1
## 259 2 1 3 15 8.3
## 260 2 1 3 16 2.6
## 261 2 1 3 19 4.8
## 262 2 1 3 31 10.2
## 263 2 1 3 51 6.6
## 264 2 1 3 52 7.2
## 265 2 1 3 63 12.8
## 266 2 1 3 78 7.5
## 267 2 1 3 79 8.4
## 268 2 1 3 86 9.4
## 269 2 1 4 3 12.9
## 270 2 1 4 10 8.4
## 271 2 1 4 15 5.1
## 272 2 1 4 16 3.8
## 273 2 1 4 19 10.5
## 274 2 1 4 31 6.8
## 275 2 1 4 51 10.9
## 276 2 1 4 52 6.8
## 277 2 1 4 63 8.0
## 278 2 1 4 78 3.9
## 279 2 1 4 79 8.5
## 280 2 1 4 86 2.7
## 281 2 1 5 3 3.4
## 282 2 1 5 10 9.2
## 283 2 1 5 15 4.1
## 284 2 1 5 16 13.4
## 285 2 1 5 19 7.6
## 286 2 1 5 31 5.4
## 287 2 1 5 51 8.0
## 288 2 1 5 52 4.9
## 289 2 1 5 63 4.4
## 290 2 1 5 78 5.6
## 291 2 1 5 79 10.1
## 292 2 1 5 86 5.8
## 293 2 1 6 3 7.3
## 294 2 1 6 10 10.7
## 295 2 1 6 15 3.4
## 296 2 1 6 16 11.8
## 297 2 1 6 19 7.6
## 298 2 1 6 31 11.4
## 299 2 1 6 51 10.6
## 300 2 1 6 52 6.3
## 301 2 1 6 63 5.2
## 302 2 1 6 78 3.4
## 303 2 1 6 79 5.7
## 304 2 1 6 86 6.4
## 305 2 1 7 3 1.5
## 306 2 1 7 10 10.5
## 307 2 1 7 15 0.4
## 308 2 1 7 16 3.7
## 309 2 1 7 19 6.5
## 310 2 1 7 31 6.1
## 311 2 1 7 51 7.3
## 312 2 1 7 52 4.1
## 313 2 1 7 63 10.4
## 314 2 1 7 78 1.3
## 315 2 1 7 79 7.3
## 316 2 1 7 86 1.2
## 317 2 1 8 3 0.9
## 318 2 1 8 10 10.9
## 319 2 1 8 15 3.2
## 320 2 1 8 16 4.5
## 321 2 1 8 19 11.2
## 322 2 1 8 31 7.8
## 323 2 1 8 51 13.8
## 324 2 1 8 52 3.9
## 325 2 1 8 63 3.9
## 326 2 1 8 78 4.0
## 327 2 1 8 79 8.2
## 328 2 1 8 86 1.3
## 329 2 1 9 3 2.7
## 330 2 1 9 10 10.4
## 331 2 1 9 15 0.2
## 332 2 1 9 16 8.5
## 333 2 1 9 19 11.1
## 334 2 1 9 51 7.3
## 335 2 1 9 52 1.8
## 336 2 1 9 63 1.8
## 337 2 1 9 78 2.0
## 338 2 1 9 79 6.7
## 339 2 1 10 10 10.7
## 340 2 1 10 15 4.8
## 341 2 1 10 16 4.2
## 342 2 1 10 19 7.0
## 343 2 1 10 31 4.6
## 344 2 1 10 51 11.3
## 345 2 1 10 52 0.3
## 346 2 1 10 63 8.6
## 347 2 1 10 78 5.2
## 348 2 1 10 86 2.0
## 349 2 2 1 3 13.4
## 350 2 2 1 10 11.0
## 351 2 2 1 15 7.0
## 352 2 2 1 16 5.0
## 353 2 2 1 19 11.3
## 354 2 2 1 31 11.4
## 355 2 2 1 51 8.5
## 356 2 2 1 52 7.1
## 357 2 2 1 63 7.7
## 358 2 2 1 78 4.3
## 359 2 2 1 79 5.1
## 360 2 2 1 86 3.2
## 361 2 2 2 3 3.3
## 362 2 2 2 10 8.2
## 363 2 2 2 15 3.9
## 364 2 2 2 16 2.6
## 365 2 2 2 19 4.3
## 366 2 2 2 31 6.6
## 367 2 2 2 51 11.6
## 368 2 2 2 52 10.2
## 369 2 2 2 63 10.7
## 370 2 2 2 78 7.0
## 371 2 2 2 79 10.4
## 372 2 2 2 86 8.3
## 373 2 2 3 3 9.9
## 374 2 2 3 10 9.0
## 375 2 2 3 15 6.1
## 376 2 2 3 16 9.6
## 377 2 2 3 19 5.6
## 378 2 2 3 31 10.0
## 379 2 2 3 51 9.3
## 380 2 2 3 52 8.2
## 381 2 2 3 63 10.7
## 382 2 2 3 78 2.4
## 383 2 2 3 79 5.4
## 384 2 2 3 86 5.2
## 385 2 2 4 3 12.7
## 386 2 2 4 10 9.0
## 387 2 2 4 15 8.7
## 388 2 2 4 16 7.4
## 389 2 2 4 19 12.9
## 390 2 2 4 31 10.5
## 391 2 2 4 51 13.2
## 392 2 2 4 52 8.3
## 393 2 2 4 63 11.6
## 394 2 2 4 78 1.1
## 395 2 2 4 79 10.7
## 396 2 2 4 86 2.5
## 397 2 2 5 3 13.7
## 398 2 2 5 10 8.5
## 399 2 2 5 15 1.5
## 400 2 2 5 16 11.0
## 401 2 2 5 19 5.5
## 402 2 2 5 31 6.5
## 403 2 2 5 51 12.7
## 404 2 2 5 52 5.9
## 405 2 2 5 63 7.5
## 406 2 2 5 78 2.4
## 407 2 2 5 79 6.1
## 408 2 2 5 86 3.2
## 409 2 2 6 3 1.8
## 410 2 2 6 10 11.4
## 411 2 2 6 15 4.6
## 412 2 2 6 16 10.8
## 413 2 2 6 19 11.1
## 414 2 2 6 31 6.9
## 415 2 2 6 51 6.3
## 416 2 2 6 52 5.6
## 417 2 2 6 63 6.1
## 418 2 2 6 78 1.3
## 419 2 2 6 79 9.4
## 420 2 2 6 86 3.3
## 421 2 2 7 3 3.5
## 422 2 2 7 10 9.6
## 423 2 2 7 15 1.7
## 424 2 2 7 16 8.1
## 425 2 2 7 19 9.3
## 426 2 2 7 31 7.0
## 427 2 2 7 51 12.4
## 428 2 2 7 52 4.2
## 429 2 2 7 63 9.8
## 430 2 2 7 78 1.4
## 431 2 2 7 79 6.6
## 432 2 2 7 86 3.6
## 433 2 2 8 3 0.5
## 434 2 2 8 10 10.3
## 435 2 2 8 15 2.3
## 436 2 2 8 16 5.3
## 437 2 2 8 19 8.7
## 438 2 2 8 31 9.9
## 439 2 2 8 51 8.5
## 440 2 2 8 52 0.0
## 441 2 2 8 63 5.7
## 442 2 2 8 78 2.1
## 443 2 2 8 79 5.7
## 444 2 2 8 86 2.8
## 445 2 2 9 3 1.8
## 446 2 2 9 10 11.0
## 447 2 2 9 15 0.0
## 448 2 2 9 16 3.8
## 449 2 2 9 19 6.2
## 450 2 2 9 51 10.6
## 451 2 2 9 52 1.6
## 452 2 2 9 63 9.1
## 453 2 2 9 78 3.4
## 454 2 2 9 79 9.4
## 455 2 2 10 10 10.5
## 456 2 2 10 15 1.1
## 457 2 2 10 16 2.9
## 458 2 2 10 19 10.9
## 459 2 2 10 31 2.3
## 460 2 2 10 51 9.9
## 461 2 2 10 52 3.8
## 462 2 2 10 63 9.0
## 463 2 2 10 78 1.5
## 464 2 2 10 86 1.0
## 465 3 1 1 3 14.1
## 466 3 1 1 10 11.3
## 467 3 1 1 15 5.8
## 468 3 1 1 16 7.8
## 469 3 1 1 19 7.2
## 470 3 1 1 31 7.1
## 471 3 1 1 51 13.6
## 472 3 1 1 52 10.6
## 473 3 1 1 63 8.6
## 474 3 1 1 78 7.4
## 475 3 1 1 79 8.8
## 476 3 1 1 86 6.7
## 477 3 1 2 3 6.5
## 478 3 1 2 10 10.3
## 479 3 1 2 15 6.3
## 480 3 1 2 16 8.2
## 481 3 1 2 19 11.4
## 482 3 1 2 31 10.5
## 483 3 1 2 51 12.2
## 484 3 1 2 52 10.7
## 485 3 1 2 63 6.2
## 486 3 1 2 78 2.7
## 487 3 1 2 79 7.7
## 488 3 1 2 86 7.7
## 489 3 1 3 3 7.3
## 490 3 1 3 10 9.6
## 491 3 1 3 15 5.2
## 492 3 1 3 16 10.6
## 493 3 1 3 19 6.4
## 494 3 1 3 31 7.6
## 495 3 1 3 51 9.1
## 496 3 1 3 52 8.1
## 497 3 1 3 63 9.0
## 498 3 1 3 78 9.2
## 499 3 1 3 79 7.5
## 500 3 1 3 86 5.2
## 501 3 1 4 3 1.5
## 502 3 1 4 10 10.3
## 503 3 1 4 15 5.2
## 504 3 1 4 16 12.7
## 505 3 1 4 19 5.8
## 506 3 1 4 31 11.0
## 507 3 1 4 51 7.0
## 508 3 1 4 52 3.3
## 509 3 1 4 63 5.6
## 510 3 1 4 78 7.7
## 511 3 1 4 79 5.7
## 512 3 1 4 86 1.4
## 513 3 1 5 3 4.0
## 514 3 1 5 10 10.7
## 515 3 1 5 15 NA
## 516 3 1 5 16 5.2
## 517 3 1 5 19 10.2
## 518 3 1 5 31 12.3
## 519 3 1 5 51 10.6
## 520 3 1 5 52 6.3
## 521 3 1 5 63 9.1
## 522 3 1 5 78 3.4
## 523 3 1 5 79 7.9
## 524 3 1 5 86 5.4
## 525 3 1 6 3 2.2
## 526 3 1 6 10 10.8
## 527 3 1 6 15 1.0
## 528 3 1 6 16 5.3
## 529 3 1 6 19 10.6
## 530 3 1 6 31 8.3
## 531 3 1 6 51 12.4
## 532 3 1 6 52 4.4
## 533 3 1 6 63 6.5
## 534 3 1 6 78 5.5
## 535 3 1 6 79 8.4
## 536 3 1 6 86 2.2
## 537 3 1 7 3 0.9
## 538 3 1 7 10 7.1
## 539 3 1 7 15 1.2
## 540 3 1 7 16 12.7
## 541 3 1 7 19 8.6
## 542 3 1 7 31 6.4
## 543 3 1 7 51 9.4
## 544 3 1 7 52 6.4
## 545 3 1 7 63 9.5
## 546 3 1 7 78 4.3
## 547 3 1 7 79 7.2
## 548 3 1 7 86 3.0
## 549 3 1 8 3 1.5
## 550 3 1 8 10 10.0
## 551 3 1 8 15 0.6
## 552 3 1 8 16 2.2
## 553 3 1 8 19 11.1
## 554 3 1 8 31 4.2
## 555 3 1 8 51 14.5
## 556 3 1 8 52 0.0
## 557 3 1 8 63 7.8
## 558 3 1 8 78 0.8
## 559 3 1 8 79 6.8
## 560 3 1 8 86 1.4
## 561 3 1 9 3 1.6
## 562 3 1 9 10 10.2
## 563 3 1 9 15 0.7
## 564 3 1 9 16 7.5
## 565 3 1 9 19 7.9
## 566 3 1 9 51 8.2
## 567 3 1 9 52 1.1
## 568 3 1 9 63 7.5
## 569 3 1 9 78 7.9
## 570 3 1 9 79 7.8
## 571 3 1 10 10 11.3
## 572 3 1 10 15 2.5
## 573 3 1 10 16 3.9
## 574 3 1 10 19 9.1
## 575 3 1 10 31 6.5
## 576 3 1 10 51 8.0
## 577 3 1 10 52 1.2
## 578 3 1 10 63 7.0
## 579 3 1 10 78 3.7
## 580 3 1 10 86 2.5
## 581 3 2 1 3 9.5
## 582 3 2 1 10 10.1
## 583 3 2 1 15 8.0
## 584 3 2 1 16 5.2
## 585 3 2 1 19 11.1
## 586 3 2 1 31 12.5
## 587 3 2 1 51 8.5
## 588 3 2 1 52 10.3
## 589 3 2 1 63 10.3
## 590 3 2 1 78 5.0
## 591 3 2 1 79 8.3
## 592 3 2 1 86 7.9
## 593 3 2 2 3 13.8
## 594 3 2 2 10 10.2
## 595 3 2 2 15 10.4
## 596 3 2 2 16 1.5
## 597 3 2 2 19 6.0
## 598 3 2 2 31 8.1
## 599 3 2 2 51 12.1
## 600 3 2 2 52 9.1
## 601 3 2 2 63 6.5
## 602 3 2 2 78 4.4
## 603 3 2 2 79 6.7
## 604 3 2 2 86 4.0
## 605 3 2 3 3 7.3
## 606 3 2 3 10 11.0
## 607 3 2 3 15 6.5
## 608 3 2 3 16 8.6
## 609 3 2 3 19 9.7
## 610 3 2 3 31 8.7
## 611 3 2 3 51 9.3
## 612 3 2 3 52 10.2
## 613 3 2 3 63 9.1
## 614 3 2 3 78 2.0
## 615 3 2 3 79 8.7
## 616 3 2 3 86 5.7
## 617 3 2 4 3 5.9
## 618 3 2 4 10 9.5
## 619 3 2 4 15 7.0
## 620 3 2 4 16 6.8
## 621 3 2 4 19 4.7
## 622 3 2 4 31 9.2
## 623 3 2 4 51 10.3
## 624 3 2 4 52 5.2
## 625 3 2 4 63 5.8
## 626 3 2 4 78 3.5
## 627 3 2 4 79 9.2
## 628 3 2 4 86 2.5
## 629 3 2 5 3 10.1
## 630 3 2 5 10 9.0
## 631 3 2 5 15 3.6
## 632 3 2 5 16 6.7
## 633 3 2 5 19 7.1
## 634 3 2 5 31 11.5
## 635 3 2 5 51 7.5
## 636 3 2 5 52 4.0
## 637 3 2 5 63 9.0
## 638 3 2 5 78 1.5
## 639 3 2 5 79 9.4
## 640 3 2 5 86 3.6
## 641 3 2 6 3 5.3
## 642 3 2 6 10 11.5
## 643 3 2 6 15 4.3
## 644 3 2 6 16 12.1
## 645 3 2 6 19 6.1
## 646 3 2 6 31 8.1
## 647 3 2 6 51 8.5
## 648 3 2 6 52 3.9
## 649 3 2 6 63 11.4
## 650 3 2 6 78 4.3
## 651 3 2 6 79 8.8
## 652 3 2 6 86 4.1
## 653 3 2 7 3 2.6
## 654 3 2 7 10 9.5
## 655 3 2 7 15 1.0
## 656 3 2 7 16 10.8
## 657 3 2 7 19 9.0
## 658 3 2 7 31 12.0
## 659 3 2 7 51 8.7
## 660 3 2 7 52 5.7
## 661 3 2 7 63 10.7
## 662 3 2 7 78 0.2
## 663 3 2 7 79 6.5
## 664 3 2 7 86 2.4
## 665 3 2 8 3 0.5
## 666 3 2 8 10 10.9
## 667 3 2 8 15 0.2
## 668 3 2 8 16 3.3
## 669 3 2 8 19 11.5
## 670 3 2 8 31 8.1
## 671 3 2 8 51 14.0
## 672 3 2 8 52 3.2
## 673 3 2 8 63 8.6
## 674 3 2 8 78 3.2
## 675 3 2 8 79 5.7
## 676 3 2 8 86 1.4
## 677 3 2 9 3 0.7
## 678 3 2 9 10 7.3
## 679 3 2 9 15 1.5
## 680 3 2 9 16 3.6
## 681 3 2 9 19 9.1
## 682 3 2 9 51 8.9
## 683 3 2 9 52 4.0
## 684 3 2 9 63 6.0
## 685 3 2 9 78 0.0
## 686 3 2 9 79 8.1
## 687 3 2 10 10 10.0
## 688 3 2 10 15 4.3
## 689 3 2 10 16 2.5
## 690 3 2 10 19 12.2
## 691 3 2 10 31 10.4
## 692 3 2 10 51 11.6
## 693 3 2 10 52 1.8
## 694 3 2 10 63 7.0
## 695 3 2 10 78 3.3
## 696 3 2 10 86 2.55.7 My Data Example
Water samples were collected on 6/6/18, 9/24/18, 12/17/18, 1/26/19 and ran on an autoanalyzer to determine NO3-N, NH4-N, PO4, and Chl-a concentrations across 8 tanks identified by treatments (control "A" or nutrient enriched "N"). Moreover this data was used in my master's thesis.
library(readr)
Porewater_data <- read_csv("~/Desktop/R folder/Bookdown/Porewater_data.csv")
head(Porewater_data, n=3)## # A tibble: 3 x 7
## Tank Date `NO3 (uM)` `NH4 (uM)` `PO4 (uM)` `Conc of chl (ug/… Nutrient
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 1 6/6/18 2.07 1.35 3.08 2.77 A
## 2 2 6/6/18 4.68 2.48 2.45 5.3 N
## 3 3 6/6/18 3.05 1.77 4.62 2.99 A5.7.1 Melt Function (long format)
require(reshape2)
pmelt <- melt(Porewater_data, id= 1:2, measure=3:6)
head(pmelt, n=3)## Tank Date variable value
## 1 1 6/6/18 NO3 (uM) 2.07
## 2 2 6/6/18 NO3 (uM) 4.68
## 3 3 6/6/18 NO3 (uM) 3.05Here I used the melt function on the porewater dataset and designated column 1 and 2 as my id using the id argument and the the measurement variables using the measure argument. I renamed the format change to pmelt and used the head function to list the first three rows.
5.7.2 Cast Function (return to wide format)
cast1<-dcast(pmelt, variable+value~Tank) #Aggregation function missing: defaulting to length
head(cast1, n=3)## variable value 1 2 3 4 5 6 7 8
## 1 NO3 (uM) 0.29 NA NA 0.29 NA NA NA NA NA
## 2 NO3 (uM) 0.31 NA 0.31 NA NA NA NA NA NA
## 3 NO3 (uM) 0.35 NA NA NA 0.35 NA NA NA NAHere I used the dcast function to return the data to wide format but moved the measured variable to the front of the table followed by where the measurement was taken. In this case the tank.