Reading: Hadley Wickham, "Tidy Data" and "Reshaping data with the reshape package"
Agenda for today:
Reshaping/tidy data/wide vs. long format
Merging
We usually want our data in the folowing form:
In a rectangular data frame
One column per sample or observation
Data don't always come this way!
Even if the data do satisfy the "one row per observation" rule for one analysis, they don't necessarily do so for another, and we often need to change the "shape" of the data.
Three concepts:
Values
Variables
Observations
Datasets contain values, each of which belongs to a variable and an observation.
Datasets can encode these in a lot of different ways. The "tidy" way is to have
Each variable a column
Each observation a row
Each cell a value
This is usually the way that other functions want the data to come in.
For example:
income_and_religion## <$10k $10k-$20k $20k-$30k $30k-$40k $40k-$50k
## Agnostic 27 34 60 81 76
## Atheist 12 27 37 52 35
## Buddhist 27 21 30 34 33
## Catholic 418 617 732 670 638
## Don't know/refused 15 14 15 11 10
## Evangelical Prot 575 869 1064 982 881
## Hindu 1 9 7 9 11
## Historically Black Prot 228 244 236 238 197
## Jehovah's Witness 20 27 24 24 21
## Jewish 19 19 25 25 30
## $50k-75k
## Agnostic 137
## Atheist 70
## Buddhist 58
## Catholic 1116
## Don't know/refused 35
## Evangelical Prot 1486
## Hindu 34
## Historically Black Prot 223
## Jehovah's Witness 30
## Jewish 95This table is easy to read, but the variables are encoded in the row and column names, which makes it hard to use with modeling functions in R.
This data table contains all the same information:
melt(income_and_religion, varnames = c("income", "religion"), value.name = "count")## income religion count
## 1 Agnostic <$10k 27
## 2 Atheist <$10k 12
## 3 Buddhist <$10k 27
## 4 Catholic <$10k 418
## 5 Don't know/refused <$10k 15
## 6 Evangelical Prot <$10k 575
## 7 Hindu <$10k 1
## 8 Historically Black Prot <$10k 228
## 9 Jehovah's Witness <$10k 20
## 10 Jewish <$10k 19
## 11 Agnostic $10k-$20k 34
## 12 Atheist $10k-$20k 27
## 13 Buddhist $10k-$20k 21
## 14 Catholic $10k-$20k 617
## 15 Don't know/refused $10k-$20k 14
## 16 Evangelical Prot $10k-$20k 869
## 17 Hindu $10k-$20k 9
## 18 Historically Black Prot $10k-$20k 244
## 19 Jehovah's Witness $10k-$20k 27
## 20 Jewish $10k-$20k 19
## 21 Agnostic $20k-$30k 60
## 22 Atheist $20k-$30k 37
## 23 Buddhist $20k-$30k 30
## 24 Catholic $20k-$30k 732
## 25 Don't know/refused $20k-$30k 15
## 26 Evangelical Prot $20k-$30k 1064
## 27 Hindu $20k-$30k 7
## 28 Historically Black Prot $20k-$30k 236
## 29 Jehovah's Witness $20k-$30k 24
## 30 Jewish $20k-$30k 25
## 31 Agnostic $30k-$40k 81
## 32 Atheist $30k-$40k 52
## 33 Buddhist $30k-$40k 34
## 34 Catholic $30k-$40k 670
## 35 Don't know/refused $30k-$40k 11
## 36 Evangelical Prot $30k-$40k 982
## 37 Hindu $30k-$40k 9
## 38 Historically Black Prot $30k-$40k 238
## 39 Jehovah's Witness $30k-$40k 24
## 40 Jewish $30k-$40k 25
## 41 Agnostic $40k-$50k 76
## 42 Atheist $40k-$50k 35
## 43 Buddhist $40k-$50k 33
## 44 Catholic $40k-$50k 638
## 45 Don't know/refused $40k-$50k 10
## 46 Evangelical Prot $40k-$50k 881
## 47 Hindu $40k-$50k 11
## 48 Historically Black Prot $40k-$50k 197
## 49 Jehovah's Witness $40k-$50k 21
## 50 Jewish $40k-$50k 30
## 51 Agnostic $50k-75k 137
## 52 Atheist $50k-75k 70
## 53 Buddhist $50k-75k 58
## 54 Catholic $50k-75k 1116
## 55 Don't know/refused $50k-75k 35
## 56 Evangelical Prot $50k-75k 1486
## 57 Hindu $50k-75k 34
## 58 Historically Black Prot $50k-75k 223
## 59 Jehovah's Witness $50k-75k 30
## 60 Jewish $50k-75k 95It's harder to look at this table, but easier to manipulate programmatically.
We'll see melt in a couple slides.
The term for transforming these datasets into each other is called "reshaping", and pretty much all reshaping can be done with a combination of two operations: melting and casting.
Melting: Taking a wide dataset and making it long.
Casting: Taking a melted dataset and making it wide.
The mneumonic is that you first "melt" the data set and then you "cast" it. The "molten" data isn't usually the final form you want it to be in, but it allows you to change it into other shapes easily.
The melt function takes data from wide form to long form.
Conceptually, we have two sets of variables:
Identification variables, that describe the observations, and
Measurement variables, which are measurements.
To melt a dateset, you need to decide what these are.
What does a molten data table look like?
Columns (potentially more than one) for id variables.
If there is more than one measured variable, one column describing the variable measured.
One column for the value of the measured variable on the corresponding observation.
Here id variables are income and religion, and the measurement is the count of each.
Since we only have one measurement variable, we don't need an extra column describing what the measured variable is.
head(melt(income_and_religion))## Var1 Var2 value
## 1 Agnostic <$10k 27
## 2 Atheist <$10k 12
## 3 Buddhist <$10k 27
## 4 Catholic <$10k 418
## 5 Don't know/refused <$10k 15
## 6 Evangelical Prot <$10k 575Based on what we said before, we will need to provide data, id variables, and measurement variables, but in practice we have two distinct situations:
Matrix or array input: here we assume that the id variables are the dimensions of the matrix or array, and the measurement variables are the elements of the matrix or the array. Therefore, we don't actually specify id variables or measurement variables.
Data frame input: id variables and measurement variables have to be specified.
Let's see an example.
head(french_fries)## time treatment subject rep potato buttery grassy rancid painty
## 61 1 1 3 1 2.9 0.0 0.0 0.0 5.5
## 25 1 1 3 2 14.0 0.0 0.0 1.1 0.0
## 62 1 1 10 1 11.0 6.4 0.0 0.0 0.0
## 26 1 1 10 2 9.9 5.9 2.9 2.2 0.0
## 63 1 1 15 1 1.2 0.1 0.0 1.1 5.1
## 27 1 1 15 2 8.8 3.0 3.6 1.5 2.3We want to melt this data frame so that
id.vars are time, treatment, subject, rep
measure.vars are the remainder: potato, buttery, grassy, rancid, painty
head(melt(french_fries, id.vars = c("time", "treatment", "subject", "rep"),
measure.vars = c("potato", "buttery", "grassy", "rancid", "painty")))## 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 11.0
## 4 1 1 10 2 potato 9.9
## 5 1 1 15 1 potato 1.2
## 6 1 1 15 2 potato 8.8You can specify just one of id.vars and measure.vars, in which case the function will assume that all the other variables should be in the other class.
You can also specify the variables by number instead of by name.
head(melt(french_fries, id.vars = 1:4))## 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 11.0
## 4 1 1 10 2 potato 9.9
## 5 1 1 15 1 potato 1.2
## 6 1 1 15 2 potato 8.8head(melt(french_fries, measure.vars = 5:9))## 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 11.0
## 4 1 1 10 2 potato 9.9
## 5 1 1 15 1 potato 1.2
## 6 1 1 15 2 potato 8.8If you don't specify either, the function will assume that all the factor variables should be id variables and all of the numeric variables should be measured variables.
ldply(french_fries, class)## .id V1
## 1 time factor
## 2 treatment factor
## 3 subject factor
## 4 rep numeric
## 5 potato numeric
## 6 buttery numeric
## 7 grassy numeric
## 8 rancid numeric
## 9 painty numericmelt(french_fries)## Using time, treatment, subject as id variables## time treatment subject variable value
## 1 1 1 3 rep 1.0
## 2 1 1 3 rep 2.0
## 3 1 1 10 rep 1.0
## 4 1 1 10 rep 2.0
## 5 1 1 15 rep 1.0
## 6 1 1 15 rep 2.0
## 7 1 1 16 rep 1.0
## 8 1 1 16 rep 2.0
## 9 1 1 19 rep 1.0
## 10 1 1 19 rep 2.0
## 11 1 1 31 rep 1.0
## 12 1 1 31 rep 2.0
## 13 1 1 51 rep 1.0
## 14 1 1 51 rep 2.0
## 15 1 1 52 rep 1.0
## 16 1 1 52 rep 2.0
## 17 1 1 63 rep 1.0
## 18 1 1 63 rep 2.0
## 19 1 1 78 rep 1.0
## 20 1 1 78 rep 2.0
## 21 1 1 79 rep 1.0
## 22 1 1 79 rep 2.0
## 23 1 1 86 rep 1.0
## 24 1 1 86 rep 2.0
## 25 1 2 3 rep 1.0
## 26 1 2 3 rep 2.0
## 27 1 2 10 rep 1.0
## 28 1 2 10 rep 2.0
## 29 1 2 15 rep 1.0
## 30 1 2 15 rep 2.0
## 31 1 2 16 rep 1.0
## 32 1 2 16 rep 2.0
## 33 1 2 19 rep 1.0
## 34 1 2 19 rep 2.0
## 35 1 2 31 rep 1.0
## 36 1 2 31 rep 2.0
## 37 1 2 51 rep 1.0
## 38 1 2 51 rep 2.0
## 39 1 2 52 rep 1.0
## 40 1 2 52 rep 2.0
## 41 1 2 63 rep 1.0
## 42 1 2 63 rep 2.0
## 43 1 2 78 rep 1.0
## 44 1 2 78 rep 2.0
## 45 1 2 79 rep 1.0
## 46 1 2 79 rep 2.0
## 47 1 2 86 rep 1.0
## 48 1 2 86 rep 2.0
## 49 1 3 3 rep 1.0
## 50 1 3 3 rep 2.0
## 51 1 3 10 rep 1.0
## 52 1 3 10 rep 2.0
## 53 1 3 15 rep 1.0
## 54 1 3 15 rep 2.0
## 55 1 3 16 rep 1.0
## 56 1 3 16 rep 2.0
## 57 1 3 19 rep 1.0
## 58 1 3 19 rep 2.0
## 59 1 3 31 rep 1.0
## 60 1 3 31 rep 2.0
## 61 1 3 51 rep 1.0
## 62 1 3 51 rep 2.0
## 63 1 3 52 rep 1.0
## 64 1 3 52 rep 2.0
## 65 1 3 63 rep 1.0
## 66 1 3 63 rep 2.0
## 67 1 3 78 rep 1.0
## 68 1 3 78 rep 2.0
## 69 1 3 79 rep 1.0
## 70 1 3 79 rep 2.0
## 71 1 3 86 rep 1.0
## 72 1 3 86 rep 2.0
## 73 2 1 3 rep 1.0
## 74 2 1 3 rep 2.0
## 75 2 1 10 rep 1.0
## 76 2 1 10 rep 2.0
## 77 2 1 15 rep 1.0
## 78 2 1 15 rep 2.0
## 79 2 1 16 rep 1.0
## 80 2 1 16 rep 2.0
## 81 2 1 19 rep 1.0
## 82 2 1 19 rep 2.0
## 83 2 1 31 rep 1.0
## 84 2 1 31 rep 2.0
## 85 2 1 51 rep 1.0
## 86 2 1 51 rep 2.0
## 87 2 1 52 rep 1.0
## 88 2 1 52 rep 2.0
## 89 2 1 63 rep 1.0
## 90 2 1 63 rep 2.0
## 91 2 1 78 rep 1.0
## 92 2 1 78 rep 2.0
## 93 2 1 79 rep 1.0
## 94 2 1 79 rep 2.0
## 95 2 1 86 rep 1.0
## 96 2 1 86 rep 2.0
## 97 2 2 3 rep 1.0
## 98 2 2 3 rep 2.0
## 99 2 2 10 rep 1.0
## 100 2 2 10 rep 2.0
## 101 2 2 15 rep 1.0
## 102 2 2 15 rep 2.0
## 103 2 2 16 rep 1.0
## 104 2 2 16 rep 2.0
## 105 2 2 19 rep 1.0
## 106 2 2 19 rep 2.0
## 107 2 2 31 rep 1.0
## 108 2 2 31 rep 2.0
## 109 2 2 51 rep 1.0
## 110 2 2 51 rep 2.0
## 111 2 2 52 rep 1.0
## 112 2 2 52 rep 2.0
## 113 2 2 63 rep 1.0
## 114 2 2 63 rep 2.0
## 115 2 2 78 rep 1.0
## 116 2 2 78 rep 2.0
## 117 2 2 79 rep 1.0
## 118 2 2 79 rep 2.0
## 119 2 2 86 rep 1.0
## 120 2 2 86 rep 2.0
## 121 2 3 3 rep 1.0
## 122 2 3 3 rep 2.0
## 123 2 3 10 rep 1.0
## 124 2 3 10 rep 2.0
## 125 2 3 15 rep 1.0
## 126 2 3 15 rep 2.0
## 127 2 3 16 rep 1.0
## 128 2 3 16 rep 2.0
## 129 2 3 19 rep 1.0
## 130 2 3 19 rep 2.0
## 131 2 3 31 rep 1.0
## 132 2 3 31 rep 2.0
## 133 2 3 51 rep 1.0
## 134 2 3 51 rep 2.0
## 135 2 3 52 rep 1.0
## 136 2 3 52 rep 2.0
## 137 2 3 63 rep 1.0
## 138 2 3 63 rep 2.0
## 139 2 3 78 rep 1.0
## 140 2 3 78 rep 2.0
## 141 2 3 79 rep 1.0
## 142 2 3 79 rep 2.0
## 143 2 3 86 rep 1.0
## 144 2 3 86 rep 2.0
## 145 3 1 3 rep 1.0
## 146 3 1 3 rep 2.0
## 147 3 1 10 rep 1.0
## 148 3 1 10 rep 2.0
## 149 3 1 15 rep 1.0
## 150 3 1 15 rep 2.0
## 151 3 1 16 rep 1.0
## 152 3 1 16 rep 2.0
## 153 3 1 19 rep 1.0
## 154 3 1 19 rep 2.0
## 155 3 1 31 rep 1.0
## 156 3 1 31 rep 2.0
## 157 3 1 51 rep 1.0
## 158 3 1 51 rep 2.0
## 159 3 1 52 rep 1.0
## 160 3 1 52 rep 2.0
## 161 3 1 63 rep 1.0
## 162 3 1 63 rep 2.0
## 163 3 1 78 rep 1.0
## 164 3 1 78 rep 2.0
## 165 3 1 79 rep 1.0
## 166 3 1 79 rep 2.0
## 167 3 1 86 rep 1.0
## 168 3 1 86 rep 2.0
## 169 3 2 3 rep 1.0
## 170 3 2 3 rep 2.0
## 171 3 2 10 rep 1.0
## 172 3 2 10 rep 2.0
## 173 3 2 15 rep 1.0
## 174 3 2 15 rep 2.0
## 175 3 2 16 rep 1.0
## 176 3 2 16 rep 2.0
## 177 3 2 19 rep 1.0
## 178 3 2 19 rep 2.0
## 179 3 2 31 rep 1.0
## 180 3 2 31 rep 2.0
## 181 3 2 51 rep 1.0
## 182 3 2 51 rep 2.0
## 183 3 2 52 rep 1.0
## 184 3 2 52 rep 2.0
## 185 3 2 63 rep 1.0
## 186 3 2 63 rep 2.0
## 187 3 2 78 rep 1.0
## 188 3 2 78 rep 2.0
## 189 3 2 79 rep 1.0
## 190 3 2 79 rep 2.0
## 191 3 2 86 rep 1.0
## 192 3 2 86 rep 2.0
## 193 3 3 3 rep 1.0
## 194 3 3 3 rep 2.0
## 195 3 3 10 rep 1.0
## 196 3 3 10 rep 2.0
## 197 3 3 15 rep 1.0
## 198 3 3 15 rep 2.0
## 199 3 3 16 rep 1.0
## 200 3 3 16 rep 2.0
## 201 3 3 19 rep 1.0
## 202 3 3 19 rep 2.0
## 203 3 3 31 rep 1.0
## 204 3 3 31 rep 2.0
## 205 3 3 51 rep 1.0
## 206 3 3 51 rep 2.0
## 207 3 3 52 rep 1.0
## 208 3 3 52 rep 2.0
## 209 3 3 63 rep 1.0
## 210 3 3 63 rep 2.0
## 211 3 3 78 rep 1.0
## 212 3 3 78 rep 2.0
## 213 3 3 79 rep 1.0
## 214 3 3 79 rep 2.0
## 215 3 3 86 rep 1.0
## 216 3 3 86 rep 2.0
## 217 4 1 3 rep 1.0
## 218 4 1 3 rep 2.0
## 219 4 1 10 rep 1.0
## 220 4 1 10 rep 2.0
## 221 4 1 15 rep 1.0
## 222 4 1 15 rep 2.0
## 223 4 1 16 rep 1.0
## 224 4 1 16 rep 2.0
## 225 4 1 19 rep 1.0
## 226 4 1 19 rep 2.0
## 227 4 1 31 rep 1.0
## 228 4 1 31 rep 2.0
## 229 4 1 51 rep 1.0
## 230 4 1 51 rep 2.0
## 231 4 1 52 rep 1.0
## 232 4 1 52 rep 2.0
## 233 4 1 63 rep 1.0
## 234 4 1 63 rep 2.0
## 235 4 1 78 rep 1.0
## 236 4 1 78 rep 2.0
## 237 4 1 79 rep 1.0
## 238 4 1 79 rep 2.0
## 239 4 1 86 rep 1.0
## 240 4 1 86 rep 2.0
## 241 4 2 3 rep 1.0
## 242 4 2 3 rep 2.0
## 243 4 2 10 rep 1.0
## 244 4 2 10 rep 2.0
## 245 4 2 15 rep 1.0
## 246 4 2 15 rep 2.0
## 247 4 2 16 rep 1.0
## 248 4 2 16 rep 2.0
## 249 4 2 19 rep 1.0
## 250 4 2 19 rep 2.0
## 251 4 2 31 rep 1.0
## 252 4 2 31 rep 2.0
## 253 4 2 51 rep 1.0
## 254 4 2 51 rep 2.0
## 255 4 2 52 rep 1.0
## 256 4 2 52 rep 2.0
## 257 4 2 63 rep 1.0
## 258 4 2 63 rep 2.0
## 259 4 2 78 rep 1.0
## 260 4 2 78 rep 2.0
## 261 4 2 79 rep 1.0
## 262 4 2 79 rep 2.0
## 263 4 2 86 rep 1.0
## 264 4 2 86 rep 2.0
## 265 4 3 3 rep 1.0
## 266 4 3 3 rep 2.0
## 267 4 3 10 rep 1.0
## 268 4 3 10 rep 2.0
## 269 4 3 15 rep 1.0
## 270 4 3 15 rep 2.0
## 271 4 3 16 rep 1.0
## 272 4 3 16 rep 2.0
## 273 4 3 19 rep 1.0
## 274 4 3 19 rep 2.0
## 275 4 3 31 rep 1.0
## 276 4 3 31 rep 2.0
## 277 4 3 51 rep 1.0
## 278 4 3 51 rep 2.0
## 279 4 3 52 rep 1.0
## 280 4 3 52 rep 2.0
## 281 4 3 63 rep 1.0
## 282 4 3 63 rep 2.0
## 283 4 3 78 rep 1.0
## 284 4 3 78 rep 2.0
## 285 4 3 79 rep 1.0
## 286 4 3 79 rep 2.0
## 287 4 3 86 rep 1.0
## 288 4 3 86 rep 2.0
## 289 5 1 3 rep 1.0
## 290 5 1 3 rep 2.0
## 291 5 1 10 rep 1.0
## 292 5 1 10 rep 2.0
## 293 5 1 15 rep 1.0
## 294 5 1 15 rep 2.0
## 295 5 1 16 rep 1.0
## 296 5 1 16 rep 2.0
## 297 5 1 19 rep 1.0
## 298 5 1 19 rep 2.0
## 299 5 1 31 rep 1.0
## 300 5 1 31 rep 2.0
## 301 5 1 51 rep 1.0
## 302 5 1 51 rep 2.0
## 303 5 1 52 rep 1.0
## 304 5 1 52 rep 2.0
## 305 5 1 63 rep 1.0
## 306 5 1 63 rep 2.0
## 307 5 1 78 rep 1.0
## 308 5 1 78 rep 2.0
## 309 5 1 79 rep 1.0
## 310 5 1 79 rep 2.0
## 311 5 1 86 rep 1.0
## 312 5 1 86 rep 2.0
## 313 5 2 3 rep 1.0
## 314 5 2 3 rep 2.0
## 315 5 2 10 rep 1.0
## 316 5 2 10 rep 2.0
## 317 5 2 15 rep 1.0
## 318 5 2 15 rep 2.0
## 319 5 2 16 rep 1.0
## 320 5 2 16 rep 2.0
## 321 5 2 19 rep 1.0
## 322 5 2 19 rep 2.0
## 323 5 2 31 rep 1.0
## 324 5 2 31 rep 2.0
## 325 5 2 51 rep 1.0
## 326 5 2 51 rep 2.0
## 327 5 2 52 rep 1.0
## 328 5 2 52 rep 2.0
## 329 5 2 63 rep 1.0
## 330 5 2 63 rep 2.0
## 331 5 2 78 rep 1.0
## 332 5 2 78 rep 2.0
## 333 5 2 79 rep 1.0
## 334 5 2 79 rep 2.0
## 335 5 2 86 rep 1.0
## 336 5 2 86 rep 2.0
## 337 5 3 3 rep 1.0
## 338 5 3 3 rep 2.0
## 339 5 3 10 rep 1.0
## 340 5 3 10 rep 2.0
## 341 5 3 15 rep 1.0
## 342 5 3 15 rep 2.0
## 343 5 3 16 rep 1.0
## 344 5 3 16 rep 2.0
## 345 5 3 19 rep 1.0
## 346 5 3 19 rep 2.0
## 347 5 3 31 rep 1.0
## 348 5 3 31 rep 2.0
## 349 5 3 51 rep 1.0
## 350 5 3 51 rep 2.0
## 351 5 3 52 rep 1.0
## 352 5 3 52 rep 2.0
## 353 5 3 63 rep 1.0
## 354 5 3 63 rep 2.0
## 355 5 3 78 rep 1.0
## 356 5 3 78 rep 2.0
## 357 5 3 79 rep 1.0
## 358 5 3 79 rep 2.0
## 359 5 3 86 rep 1.0
## 360 5 3 86 rep 2.0
## 361 6 1 3 rep 1.0
## 362 6 1 3 rep 2.0
## 363 6 1 10 rep 1.0
## 364 6 1 10 rep 2.0
## 365 6 1 15 rep 1.0
## 366 6 1 15 rep 2.0
## 367 6 1 16 rep 1.0
## 368 6 1 16 rep 2.0
## 369 6 1 19 rep 1.0
## 370 6 1 19 rep 2.0
## 371 6 1 31 rep 1.0
## 372 6 1 31 rep 2.0
## 373 6 1 51 rep 1.0
## 374 6 1 51 rep 2.0
## 375 6 1 52 rep 1.0
## 376 6 1 52 rep 2.0
## 377 6 1 63 rep 1.0
## 378 6 1 63 rep 2.0
## 379 6 1 78 rep 1.0
## 380 6 1 78 rep 2.0
## 381 6 1 79 rep 1.0
## 382 6 1 79 rep 2.0
## 383 6 1 86 rep 1.0
## 384 6 1 86 rep 2.0
## 385 6 2 3 rep 1.0
## 386 6 2 3 rep 2.0
## 387 6 2 10 rep 1.0
## 388 6 2 10 rep 2.0
## 389 6 2 15 rep 1.0
## 390 6 2 15 rep 2.0
## 391 6 2 16 rep 1.0
## 392 6 2 16 rep 2.0
## 393 6 2 19 rep 1.0
## 394 6 2 19 rep 2.0
## 395 6 2 31 rep 1.0
## 396 6 2 31 rep 2.0
## 397 6 2 51 rep 1.0
## 398 6 2 51 rep 2.0
## 399 6 2 52 rep 1.0
## 400 6 2 52 rep 2.0
## 401 6 2 63 rep 1.0
## 402 6 2 63 rep 2.0
## 403 6 2 78 rep 1.0
## 404 6 2 78 rep 2.0
## 405 6 2 79 rep 1.0
## 406 6 2 79 rep 2.0
## 407 6 2 86 rep 1.0
## 408 6 2 86 rep 2.0
## 409 6 3 3 rep 1.0
## 410 6 3 3 rep 2.0
## 411 6 3 10 rep 1.0
## 412 6 3 10 rep 2.0
## 413 6 3 15 rep 1.0
## 414 6 3 15 rep 2.0
## 415 6 3 16 rep 1.0
## 416 6 3 16 rep 2.0
## 417 6 3 19 rep 1.0
## 418 6 3 19 rep 2.0
## 419 6 3 31 rep 1.0
## 420 6 3 31 rep 2.0
## 421 6 3 51 rep 1.0
## 422 6 3 51 rep 2.0
## 423 6 3 52 rep 1.0
## 424 6 3 52 rep 2.0
## 425 6 3 63 rep 1.0
## 426 6 3 63 rep 2.0
## 427 6 3 78 rep 1.0
## 428 6 3 78 rep 2.0
## 429 6 3 79 rep 1.0
## 430 6 3 79 rep 2.0
## 431 6 3 86 rep 1.0
## 432 6 3 86 rep 2.0
## 433 7 1 3 rep 1.0
## 434 7 1 3 rep 2.0
## 435 7 1 10 rep 1.0
## 436 7 1 10 rep 2.0
## 437 7 1 15 rep 1.0
## 438 7 1 15 rep 2.0
## 439 7 1 16 rep 1.0
## 440 7 1 16 rep 2.0
## 441 7 1 19 rep 1.0
## 442 7 1 19 rep 2.0
## 443 7 1 31 rep 1.0
## 444 7 1 31 rep 2.0
## 445 7 1 51 rep 1.0
## 446 7 1 51 rep 2.0
## 447 7 1 52 rep 1.0
## 448 7 1 52 rep 2.0
## 449 7 1 63 rep 1.0
## 450 7 1 63 rep 2.0
## 451 7 1 78 rep 1.0
## 452 7 1 78 rep 2.0
## 453 7 1 79 rep 1.0
## 454 7 1 79 rep 2.0
## 455 7 1 86 rep 1.0
## 456 7 1 86 rep 2.0
## 457 7 2 3 rep 1.0
## 458 7 2 3 rep 2.0
## 459 7 2 10 rep 1.0
## 460 7 2 10 rep 2.0
## 461 7 2 15 rep 1.0
## 462 7 2 15 rep 2.0
## 463 7 2 16 rep 1.0
## 464 7 2 16 rep 2.0
## 465 7 2 19 rep 1.0
## 466 7 2 19 rep 2.0
## 467 7 2 31 rep 1.0
## 468 7 2 31 rep 2.0
## 469 7 2 51 rep 1.0
## 470 7 2 51 rep 2.0
## 471 7 2 52 rep 1.0
## 472 7 2 52 rep 2.0
## 473 7 2 63 rep 1.0
## 474 7 2 63 rep 2.0
## 475 7 2 78 rep 1.0
## 476 7 2 78 rep 2.0
## 477 7 2 79 rep 1.0
## 478 7 2 79 rep 2.0
## 479 7 2 86 rep 1.0
## 480 7 2 86 rep 2.0
## 481 7 3 3 rep 1.0
## 482 7 3 3 rep 2.0
## 483 7 3 10 rep 1.0
## 484 7 3 10 rep 2.0
## 485 7 3 15 rep 1.0
## 486 7 3 15 rep 2.0
## 487 7 3 16 rep 1.0
## 488 7 3 16 rep 2.0
## 489 7 3 19 rep 1.0
## 490 7 3 19 rep 2.0
## 491 7 3 31 rep 1.0
## 492 7 3 31 rep 2.0
## 493 7 3 51 rep 1.0
## 494 7 3 51 rep 2.0
## 495 7 3 52 rep 1.0
## 496 7 3 52 rep 2.0
## 497 7 3 63 rep 1.0
## 498 7 3 63 rep 2.0
## 499 7 3 78 rep 1.0
## 500 7 3 78 rep 2.0
## 501 7 3 79 rep 1.0
## 502 7 3 79 rep 2.0
## 503 7 3 86 rep 1.0
## 504 7 3 86 rep 2.0
## 505 8 1 3 rep 1.0
## 506 8 1 3 rep 2.0
## 507 8 1 10 rep 1.0
## 508 8 1 10 rep 2.0
## 509 8 1 15 rep 1.0
## 510 8 1 15 rep 2.0
## 511 8 1 16 rep 1.0
## 512 8 1 16 rep 2.0
## 513 8 1 19 rep 1.0
## 514 8 1 19 rep 2.0
## 515 8 1 31 rep 1.0
## 516 8 1 31 rep 2.0
## 517 8 1 51 rep 1.0
## 518 8 1 51 rep 2.0
## 519 8 1 52 rep 1.0
## 520 8 1 52 rep 2.0
## 521 8 1 63 rep 1.0
## 522 8 1 63 rep 2.0
## 523 8 1 78 rep 1.0
## 524 8 1 78 rep 2.0
## 525 8 1 79 rep 1.0
## 526 8 1 79 rep 2.0
## 527 8 1 86 rep 1.0
## 528 8 1 86 rep 2.0
## 529 8 2 3 rep 1.0
## 530 8 2 3 rep 2.0
## 531 8 2 10 rep 1.0
## 532 8 2 10 rep 2.0
## 533 8 2 15 rep 1.0
## 534 8 2 15 rep 2.0
## 535 8 2 16 rep 1.0
## 536 8 2 16 rep 2.0
## 537 8 2 19 rep 1.0
## 538 8 2 19 rep 2.0
## 539 8 2 31 rep 1.0
## 540 8 2 31 rep 2.0
## 541 8 2 51 rep 1.0
## 542 8 2 51 rep 2.0
## 543 8 2 52 rep 1.0
## 544 8 2 52 rep 2.0
## 545 8 2 63 rep 1.0
## 546 8 2 63 rep 2.0
## 547 8 2 78 rep 1.0
## 548 8 2 78 rep 2.0
## 549 8 2 79 rep 1.0
## 550 8 2 79 rep 2.0
## 551 8 2 86 rep 1.0
## 552 8 2 86 rep 2.0
## 553 8 3 3 rep 1.0
## 554 8 3 3 rep 2.0
## 555 8 3 10 rep 1.0
## 556 8 3 10 rep 2.0
## 557 8 3 15 rep 1.0
## 558 8 3 15 rep 2.0
## 559 8 3 16 rep 1.0
## 560 8 3 16 rep 2.0
## 561 8 3 19 rep 1.0
## 562 8 3 19 rep 2.0
## 563 8 3 31 rep 1.0
## 564 8 3 31 rep 2.0
## 565 8 3 51 rep 1.0
## 566 8 3 51 rep 2.0
## 567 8 3 52 rep 1.0
## 568 8 3 52 rep 2.0
## 569 8 3 63 rep 1.0
## 570 8 3 63 rep 2.0
## 571 8 3 78 rep 1.0
## 572 8 3 78 rep 2.0
## 573 8 3 79 rep 1.0
## 574 8 3 79 rep 2.0
## 575 8 3 86 rep 1.0
## 576 8 3 86 rep 2.0
## 577 9 1 3 rep 1.0
## 578 9 1 3 rep 2.0
## 579 9 1 10 rep 1.0
## 580 9 1 10 rep 2.0
## 581 9 1 15 rep 1.0
## 582 9 1 15 rep 2.0
## 583 9 1 16 rep 1.0
## 584 9 1 16 rep 2.0
## 585 9 1 19 rep 1.0
## 586 9 1 19 rep 2.0
## 587 9 1 51 rep 1.0
## 588 9 1 51 rep 2.0
## 589 9 1 52 rep 1.0
## 590 9 1 52 rep 2.0
## 591 9 1 63 rep 1.0
## 592 9 1 63 rep 2.0
## 593 9 1 78 rep 1.0
## 594 9 1 78 rep 2.0
## 595 9 1 79 rep 1.0
## 596 9 1 79 rep 2.0
## 597 9 2 3 rep 1.0
## 598 9 2 3 rep 2.0
## 599 9 2 10 rep 1.0
## 600 9 2 10 rep 2.0
## 601 9 2 15 rep 1.0
## 602 9 2 15 rep 2.0
## 603 9 2 16 rep 1.0
## 604 9 2 16 rep 2.0
## 605 9 2 19 rep 1.0
## 606 9 2 19 rep 2.0
## 607 9 2 51 rep 1.0
## 608 9 2 51 rep 2.0
## 609 9 2 52 rep 1.0
## 610 9 2 52 rep 2.0
## 611 9 2 63 rep 1.0
## 612 9 2 63 rep 2.0
## 613 9 2 78 rep 1.0
## 614 9 2 78 rep 2.0
## 615 9 2 79 rep 1.0
## 616 9 2 79 rep 2.0
## 617 9 3 3 rep 1.0
## 618 9 3 3 rep 2.0
## 619 9 3 10 rep 1.0
## 620 9 3 10 rep 2.0
## 621 9 3 15 rep 1.0
## 622 9 3 15 rep 2.0
## 623 9 3 16 rep 1.0
## 624 9 3 16 rep 2.0
## 625 9 3 19 rep 1.0
## 626 9 3 19 rep 2.0
## 627 9 3 51 rep 1.0
## 628 9 3 51 rep 2.0
## 629 9 3 52 rep 1.0
## 630 9 3 52 rep 2.0
## 631 9 3 63 rep 1.0
## 632 9 3 63 rep 2.0
## 633 9 3 78 rep 1.0
## 634 9 3 78 rep 2.0
## 635 9 3 79 rep 1.0
## 636 9 3 79 rep 2.0
## 637 10 1 10 rep 1.0
## 638 10 1 10 rep 2.0
## 639 10 1 15 rep 1.0
## 640 10 1 15 rep 2.0
## 641 10 1 16 rep 1.0
## 642 10 1 16 rep 2.0
## 643 10 1 19 rep 1.0
## 644 10 1 19 rep 2.0
## 645 10 1 31 rep 1.0
## 646 10 1 31 rep 2.0
## 647 10 1 51 rep 1.0
## 648 10 1 51 rep 2.0
## 649 10 1 52 rep 1.0
## 650 10 1 52 rep 2.0
## 651 10 1 63 rep 1.0
## 652 10 1 63 rep 2.0
## 653 10 1 78 rep 1.0
## 654 10 1 78 rep 2.0
## 655 10 1 86 rep 1.0
## 656 10 1 86 rep 2.0
## 657 10 2 10 rep 1.0
## 658 10 2 10 rep 2.0
## 659 10 2 15 rep 1.0
## 660 10 2 15 rep 2.0
## 661 10 2 16 rep 1.0
## 662 10 2 16 rep 2.0
## 663 10 2 19 rep 1.0
## 664 10 2 19 rep 2.0
## 665 10 2 31 rep 1.0
## 666 10 2 31 rep 2.0
## 667 10 2 51 rep 1.0
## 668 10 2 51 rep 2.0
## 669 10 2 52 rep 1.0
## 670 10 2 52 rep 2.0
## 671 10 2 63 rep 1.0
## 672 10 2 63 rep 2.0
## 673 10 2 78 rep 1.0
## 674 10 2 78 rep 2.0
## 675 10 2 86 rep 1.0
## 676 10 2 86 rep 2.0
## 677 10 3 10 rep 1.0
## 678 10 3 10 rep 2.0
## 679 10 3 15 rep 1.0
## 680 10 3 15 rep 2.0
## 681 10 3 16 rep 1.0
## 682 10 3 16 rep 2.0
## 683 10 3 19 rep 1.0
## 684 10 3 19 rep 2.0
## 685 10 3 31 rep 1.0
## 686 10 3 31 rep 2.0
## 687 10 3 51 rep 1.0
## 688 10 3 51 rep 2.0
## 689 10 3 52 rep 1.0
## 690 10 3 52 rep 2.0
## 691 10 3 63 rep 1.0
## 692 10 3 63 rep 2.0
## 693 10 3 78 rep 1.0
## 694 10 3 78 rep 2.0
## 695 10 3 86 rep 1.0
## 696 10 3 86 rep 2.0
## 697 1 1 3 potato 2.9
## 698 1 1 3 potato 14.0
## 699 1 1 10 potato 11.0
## 700 1 1 10 potato 9.9
## 701 1 1 15 potato 1.2
## 702 1 1 15 potato 8.8
## 703 1 1 16 potato 9.0
## 704 1 1 16 potato 8.2
## 705 1 1 19 potato 7.0
## 706 1 1 19 potato 13.0
## 707 1 1 31 potato 12.2
## 708 1 1 31 potato 12.8
## 709 1 1 51 potato 8.6
## 710 1 1 51 potato 10.2
## 711 1 1 52 potato 5.8
## 712 1 1 52 potato 7.0
## 713 1 1 63 potato 8.3
## 714 1 1 63 potato 2.9
## 715 1 1 78 potato 4.9
## 716 1 1 78 potato 8.8
## 717 1 1 79 potato 5.1
## 718 1 1 79 potato 10.4
## 719 1 1 86 potato 5.2
## 720 1 1 86 potato 3.0
## 721 1 2 3 potato 13.9
## 722 1 2 3 potato 13.4
## 723 1 2 10 potato 9.3
## 724 1 2 10 potato 11.0
## 725 1 2 15 potato 9.0
## 726 1 2 15 potato 7.0
## 727 1 2 16 potato 4.6
## 728 1 2 16 potato 5.0
## 729 1 2 19 potato 9.5
## 730 1 2 19 potato 11.3
## 731 1 2 31 potato 10.6
## 732 1 2 31 potato 11.4
## 733 1 2 51 potato 11.7
## 734 1 2 51 potato 8.5
## 735 1 2 52 potato 10.4
## 736 1 2 52 potato 7.1
## 737 1 2 63 potato 13.1
## 738 1 2 63 potato 7.7
## 739 1 2 78 potato 9.1
## 740 1 2 78 potato 4.3
## 741 1 2 79 potato 8.3
## 742 1 2 79 potato 5.1
## 743 1 2 86 potato 6.1
## 744 1 2 86 potato 3.2
## 745 1 3 3 potato 14.1
## 746 1 3 3 potato 9.5
## 747 1 3 10 potato 11.3
## 748 1 3 10 potato 10.1
## 749 1 3 15 potato 5.8
## 750 1 3 15 potato 8.0
## 751 1 3 16 potato 7.8
## 752 1 3 16 potato 5.2
## 753 1 3 19 potato 7.2
## 754 1 3 19 potato 11.1
## 755 1 3 31 potato 7.1
## 756 1 3 31 potato 12.5
## 757 1 3 51 potato 13.6
## 758 1 3 51 potato 8.5
## 759 1 3 52 potato 10.6
## 760 1 3 52 potato 10.3
## 761 1 3 63 potato 8.6
## 762 1 3 63 potato 10.3
## 763 1 3 78 potato 7.4
## 764 1 3 78 potato 5.0
## 765 1 3 79 potato 8.8
## 766 1 3 79 potato 8.3
## 767 1 3 86 potato 6.7
## 768 1 3 86 potato 7.9
## 769 2 1 3 potato 9.0
## 770 2 1 3 potato 5.5
## 771 2 1 10 potato 8.0
## 772 2 1 10 potato 10.2
## 773 2 1 15 potato 5.3
## 774 2 1 15 potato 7.3
## 775 2 1 16 potato 4.1
## 776 2 1 16 potato 11.0
## 777 2 1 19 potato 8.7
## 778 2 1 19 potato 11.0
## 779 2 1 31 potato 9.7
## 780 2 1 31 potato 4.1
## 781 2 1 51 potato 9.4
## 782 2 1 51 potato 14.3
## 783 2 1 52 potato 6.5
## 784 2 1 52 potato 8.2
## 785 2 1 63 potato 8.9
## 786 2 1 63 potato 8.7
## 787 2 1 78 potato 3.3
## 788 2 1 78 potato 4.5
## 789 2 1 79 potato 5.9
## 790 2 1 79 potato 6.0
## 791 2 1 86 potato 6.7
## 792 2 1 86 potato 5.9
## 793 2 2 3 potato 14.1
## 794 2 2 3 potato 3.3
## 795 2 2 10 potato 11.2
## 796 2 2 10 potato 8.2
## 797 2 2 15 potato 12.7
## 798 2 2 15 potato 3.9
## 799 2 2 16 potato 5.4
## 800 2 2 16 potato 2.6
## 801 2 2 19 potato 11.2
## 802 2 2 19 potato 4.3
## 803 2 2 31 potato 10.6
## 804 2 2 31 potato 6.6
## 805 2 2 51 potato 9.2
## 806 2 2 51 potato 11.6
## 807 2 2 52 potato 9.7
## 808 2 2 52 potato 10.2
## 809 2 2 63 potato 12.2
## 810 2 2 63 potato 10.7
## 811 2 2 78 potato 6.7
## 812 2 2 78 potato 7.0
## 813 2 2 79 potato 10.9
## 814 2 2 79 potato 10.4
## 815 2 2 86 potato 3.9
## 816 2 2 86 potato 8.3
## 817 2 3 3 potato 6.5
## 818 2 3 3 potato 13.8
## 819 2 3 10 potato 10.3
## 820 2 3 10 potato 10.2
## 821 2 3 15 potato 6.3
## 822 2 3 15 potato 10.4
## 823 2 3 16 potato 8.2
## 824 2 3 16 potato 1.5
## 825 2 3 19 potato 11.4
## 826 2 3 19 potato 6.0
## 827 2 3 31 potato 10.5
## 828 2 3 31 potato 8.1
## 829 2 3 51 potato 12.2
## 830 2 3 51 potato 12.1
## 831 2 3 52 potato 10.7
## 832 2 3 52 potato 9.1
## 833 2 3 63 potato 6.2
## 834 2 3 63 potato 6.5
## 835 2 3 78 potato 2.7
## 836 2 3 78 potato 4.4
## 837 2 3 79 potato 7.7
## 838 2 3 79 potato 6.7
## 839 2 3 86 potato 7.7
## 840 2 3 86 potato 4.0
## 841 3 1 3 potato 11.8
## 842 3 1 3 potato 7.8
## 843 3 1 10 potato 9.3
## 844 3 1 10 potato 9.1
## 845 3 1 15 potato 3.4
## 846 3 1 15 potato 5.7
## 847 3 1 16 potato 1.5
## 848 3 1 16 potato 4.2
## 849 3 1 19 potato 11.2
## 850 3 1 19 potato 11.8
## 851 3 1 31 potato 8.2
## 852 3 1 31 potato 8.8
## 853 3 1 51 potato 6.1
## 854 3 1 51 potato 10.1
## 855 3 1 52 potato 6.6
## 856 3 1 52 potato 10.4
## 857 3 1 63 potato 8.9
## 858 3 1 63 potato 10.8
## 859 3 1 78 potato 2.5
## 860 3 1 78 potato 6.3
## 861 3 1 79 potato 8.6
## 862 3 1 79 potato 3.8
## 863 3 1 86 potato 9.0
## 864 3 1 86 potato 10.6
## 865 3 2 3 potato 4.0
## 866 3 2 3 potato 9.9
## 867 3 2 10 potato 10.1
## 868 3 2 10 potato 9.0
## 869 3 2 15 potato 8.3
## 870 3 2 15 potato 6.1
## 871 3 2 16 potato 2.6
## 872 3 2 16 potato 9.6
## 873 3 2 19 potato 4.8
## 874 3 2 19 potato 5.6
## 875 3 2 31 potato 10.2
## 876 3 2 31 potato 10.0
## 877 3 2 51 potato 6.6
## 878 3 2 51 potato 9.3
## 879 3 2 52 potato 7.2
## 880 3 2 52 potato 8.2
## 881 3 2 63 potato 12.8
## 882 3 2 63 potato 10.7
## 883 3 2 78 potato 7.5
## 884 3 2 78 potato 2.4
## 885 3 2 79 potato 8.4
## 886 3 2 79 potato 5.4
## 887 3 2 86 potato 9.4
## 888 3 2 86 potato 5.2
## 889 3 3 3 potato 7.3
## 890 3 3 3 potato 7.3
## 891 3 3 10 potato 9.6
## 892 3 3 10 potato 11.0
## 893 3 3 15 potato 5.2
## 894 3 3 15 potato 6.5
## 895 3 3 16 potato 10.6
## 896 3 3 16 potato 8.6
## 897 3 3 19 potato 6.4
## 898 3 3 19 potato 9.7
## 899 3 3 31 potato 7.6
## 900 3 3 31 potato 8.7
## 901 3 3 51 potato 9.1
## 902 3 3 51 potato 9.3
## 903 3 3 52 potato 8.1
## 904 3 3 52 potato 10.2
## 905 3 3 63 potato 9.0
## 906 3 3 63 potato 9.1
## 907 3 3 78 potato 9.2
## 908 3 3 78 potato 2.0
## 909 3 3 79 potato 7.5
## 910 3 3 79 potato 8.7
## 911 3 3 86 potato 5.2
## 912 3 3 86 potato 5.7
## 913 4 1 3 potato 13.6
## 914 4 1 3 potato 5.3
## 915 4 1 10 potato 8.1
## 916 4 1 10 potato 9.1
## 917 4 1 15 potato 8.1
## 918 4 1 15 potato 7.2
## 919 4 1 16 potato 6.8
## 920 4 1 16 potato 10.5
## 921 4 1 19 potato 8.9
## 922 4 1 19 potato 6.9
## 923 4 1 31 potato 11.7
## 924 4 1 31 potato 3.4
## 925 4 1 51 potato 9.3
## 926 4 1 51 potato 13.2
## 927 4 1 52 potato 8.5
## 928 4 1 52 potato 8.9
## 929 4 1 63 potato 10.4
## 930 4 1 63 potato 11.4
## 931 4 1 78 potato 9.4
## 932 4 1 78 potato 3.2
## 933 4 1 79 potato 8.4
## 934 4 1 79 potato 7.0
## 935 4 1 86 potato 8.3
## 936 4 1 86 potato 4.1
## 937 4 2 3 potato 12.9
## 938 4 2 3 potato 12.7
## 939 4 2 10 potato 8.4
## 940 4 2 10 potato 9.0
## 941 4 2 15 potato 5.1
## 942 4 2 15 potato 8.7
## 943 4 2 16 potato 3.8
## 944 4 2 16 potato 7.4
## 945 4 2 19 potato 10.5
## 946 4 2 19 potato 12.9
## 947 4 2 31 potato 6.8
## 948 4 2 31 potato 10.5
## 949 4 2 51 potato 10.9
## 950 4 2 51 potato 13.2
## 951 4 2 52 potato 6.8
## 952 4 2 52 potato 8.3
## 953 4 2 63 potato 8.0
## 954 4 2 63 potato 11.6
## 955 4 2 78 potato 3.9
## 956 4 2 78 potato 1.1
## 957 4 2 79 potato 8.5
## 958 4 2 79 potato 10.7
## 959 4 2 86 potato 2.7
## 960 4 2 86 potato 2.5
## 961 4 3 3 potato 1.5
## 962 4 3 3 potato 5.9
## 963 4 3 10 potato 10.3
## 964 4 3 10 potato 9.5
## 965 4 3 15 potato 5.2
## 966 4 3 15 potato 7.0
## 967 4 3 16 potato 12.7
## 968 4 3 16 potato 6.8
## 969 4 3 19 potato 5.8
## 970 4 3 19 potato 4.7
## 971 4 3 31 potato 11.0
## 972 4 3 31 potato 9.2
## 973 4 3 51 potato 7.0
## 974 4 3 51 potato 10.3
## 975 4 3 52 potato 3.3
## 976 4 3 52 potato 5.2
## 977 4 3 63 potato 5.6
## 978 4 3 63 potato 5.8
## 979 4 3 78 potato 7.7
## 980 4 3 78 potato 3.5
## 981 4 3 79 potato 5.7
## 982 4 3 79 potato 9.2
## 983 4 3 86 potato 1.4
## 984 4 3 86 potato 2.5
## 985 5 1 3 potato 14.0
## 986 5 1 3 potato 12.9
## 987 5 1 10 potato 9.6
## 988 5 1 10 potato 8.7
## 989 5 1 15 potato 4.1
## 990 5 1 15 potato 3.2
## 991 5 1 16 potato 10.1
## 992 5 1 16 potato 10.5
## 993 5 1 19 potato 5.3
## 994 5 1 19 potato 9.9
## 995 5 1 31 potato 11.2
## 996 5 1 31 potato 9.9
## 997 5 1 51 potato 9.2
## 998 5 1 51 potato 12.5
## 999 5 1 52 potato 4.1
## 1000 5 1 52 potato 6.4
## 1001 5 1 63 potato 9.8
## 1002 5 1 63 potato 4.2
## 1003 5 1 78 potato 3.3
## 1004 5 1 78 potato 5.0
## 1005 5 1 79 potato 8.0
## 1006 5 1 79 potato 8.1
## 1007 5 1 86 potato 2.2
## 1008 5 1 86 potato 3.6
## 1009 5 2 3 potato 3.4
## 1010 5 2 3 potato 13.7
## 1011 5 2 10 potato 9.2
## 1012 5 2 10 potato 8.5
## 1013 5 2 15 potato 4.1
## 1014 5 2 15 potato 1.5
## 1015 5 2 16 potato 13.4
## 1016 5 2 16 potato 11.0
## 1017 5 2 19 potato 7.6
## 1018 5 2 19 potato 5.5
## 1019 5 2 31 potato 5.4
## 1020 5 2 31 potato 6.5
## 1021 5 2 51 potato 8.0
## 1022 5 2 51 potato 12.7
## 1023 5 2 52 potato 4.9
## 1024 5 2 52 potato 5.9
## 1025 5 2 63 potato 4.4
## 1026 5 2 63 potato 7.5
## 1027 5 2 78 potato 5.6
## 1028 5 2 78 potato 2.4
## 1029 5 2 79 potato 10.1
## 1030 5 2 79 potato 6.1
## 1031 5 2 86 potato 5.8
## 1032 5 2 86 potato 3.2
## 1033 5 3 3 potato 4.0
## 1034 5 3 3 potato 10.1
## 1035 5 3 10 potato 10.7
## 1036 5 3 10 potato 9.0
## 1037 5 3 15 potato NA
## 1038 5 3 15 potato 3.6
## 1039 5 3 16 potato 5.2
## 1040 5 3 16 potato 6.7
## 1041 5 3 19 potato 10.2
## 1042 5 3 19 potato 7.1
## 1043 5 3 31 potato 12.3
## 1044 5 3 31 potato 11.5
## 1045 5 3 51 potato 10.6
## 1046 5 3 51 potato 7.5
## 1047 5 3 52 potato 6.3
## 1048 5 3 52 potato 4.0
## 1049 5 3 63 potato 9.1
## 1050 5 3 63 potato 9.0
## 1051 5 3 78 potato 3.4
## 1052 5 3 78 potato 1.5
## 1053 5 3 79 potato 7.9
## 1054 5 3 79 potato 9.4
## 1055 5 3 86 potato 5.4
## 1056 5 3 86 potato 3.6
## 1057 6 1 3 potato 0.4
## 1058 6 1 3 potato 3.3
## 1059 6 1 10 potato 13.2
## 1060 6 1 10 potato 10.0
## 1061 6 1 15 potato 0.0
## 1062 6 1 15 potato 2.6
## 1063 6 1 16 potato 4.9
## 1064 6 1 16 potato 8.9
## 1065 6 1 19 potato 12.2
## 1066 6 1 19 potato 11.1
## 1067 6 1 31 potato 12.0
## 1068 6 1 31 potato 8.2
## 1069 6 1 51 potato 10.2
## 1070 6 1 51 potato 8.5
## 1071 6 1 52 potato 3.8
## 1072 6 1 52 potato 3.7
## 1073 6 1 63 potato 3.1
## 1074 6 1 63 potato 4.2
## 1075 6 1 78 potato 1.5
## 1076 6 1 78 potato 1.1
## 1077 6 1 79 potato 11.4
## 1078 6 1 79 potato 7.9
## 1079 6 1 86 potato 1.0
## 1080 6 1 86 potato 2.7
## 1081 6 2 3 potato 7.3
## 1082 6 2 3 potato 1.8
## 1083 6 2 10 potato 10.7
## 1084 6 2 10 potato 11.4
## 1085 6 2 15 potato 3.4
## 1086 6 2 15 potato 4.6
## 1087 6 2 16 potato 11.8
## 1088 6 2 16 potato 10.8
## 1089 6 2 19 potato 7.6
## 1090 6 2 19 potato 11.1
## 1091 6 2 31 potato 11.4
## 1092 6 2 31 potato 6.9
## 1093 6 2 51 potato 10.6
## 1094 6 2 51 potato 6.3
## 1095 6 2 52 potato 6.3
## 1096 6 2 52 potato 5.6
## 1097 6 2 63 potato 5.2
## 1098 6 2 63 potato 6.1
## 1099 6 2 78 potato 3.4
## 1100 6 2 78 potato 1.3
## 1101 6 2 79 potato 5.7
## 1102 6 2 79 potato 9.4
## 1103 6 2 86 potato 6.4
## 1104 6 2 86 potato 3.3
## 1105 6 3 3 potato 2.2
## 1106 6 3 3 potato 5.3
## 1107 6 3 10 potato 10.8
## 1108 6 3 10 potato 11.5
## 1109 6 3 15 potato 1.0
## 1110 6 3 15 potato 4.3
## 1111 6 3 16 potato 5.3
## 1112 6 3 16 potato 12.1
## 1113 6 3 19 potato 10.6
## 1114 6 3 19 potato 6.1
## 1115 6 3 31 potato 8.3
## 1116 6 3 31 potato 8.1
## 1117 6 3 51 potato 12.4
## 1118 6 3 51 potato 8.5
## 1119 6 3 52 potato 4.4
## 1120 6 3 52 potato 3.9
## 1121 6 3 63 potato 6.5
## 1122 6 3 63 potato 11.4
## 1123 6 3 78 potato 5.5
## 1124 6 3 78 potato 4.3
## 1125 6 3 79 potato 8.4
## 1126 6 3 79 potato 8.8
## 1127 6 3 86 potato 2.2
## 1128 6 3 86 potato 4.1
## 1129 7 1 3 potato 2.9
## 1130 7 1 3 potato 0.8
## 1131 7 1 10 potato 11.0
## 1132 7 1 10 potato 8.7
## 1133 7 1 15 potato 1.2
## 1134 7 1 15 potato 2.9
## 1135 7 1 16 potato 9.0
## 1136 7 1 16 potato 7.2
## 1137 7 1 19 potato 7.0
## 1138 7 1 19 potato 5.5
## 1139 7 1 31 potato 12.2
## 1140 7 1 31 potato 9.4
## 1141 7 1 51 potato 8.6
## 1142 7 1 51 potato 14.1
## 1143 7 1 52 potato 5.8
## 1144 7 1 52 potato 3.2
## 1145 7 1 63 potato 8.3
## 1146 7 1 63 potato 6.2
## 1147 7 1 78 potato 4.9
## 1148 7 1 78 potato 0.5
## 1149 7 1 79 potato 5.1
## 1150 7 1 79 potato 9.9
## 1151 7 1 86 potato 5.2
## 1152 7 1 86 potato 1.2
## 1153 7 2 3 potato 1.5
## 1154 7 2 3 potato 3.5
## 1155 7 2 10 potato 10.5
## 1156 7 2 10 potato 9.6
## 1157 7 2 15 potato 0.4
## 1158 7 2 15 potato 1.7
## 1159 7 2 16 potato 3.7
## 1160 7 2 16 potato 8.1
## 1161 7 2 19 potato 6.5
## 1162 7 2 19 potato 9.3
## 1163 7 2 31 potato 6.1
## 1164 7 2 31 potato 7.0
## 1165 7 2 51 potato 7.3
## 1166 7 2 51 potato 12.4
## 1167 7 2 52 potato 4.1
## 1168 7 2 52 potato 4.2
## 1169 7 2 63 potato 10.4
## 1170 7 2 63 potato 9.8
## 1171 7 2 78 potato 1.3
## 1172 7 2 78 potato 1.4
## 1173 7 2 79 potato 7.3
## 1174 7 2 79 potato 6.6
## 1175 7 2 86 potato 1.2
## 1176 7 2 86 potato 3.6
## 1177 7 3 3 potato 0.9
## 1178 7 3 3 potato 2.6
## 1179 7 3 10 potato 7.1
## 1180 7 3 10 potato 9.5
## 1181 7 3 15 potato 1.2
## 1182 7 3 15 potato 1.0
## 1183 7 3 16 potato 12.7
## 1184 7 3 16 potato 10.8
## 1185 7 3 19 potato 8.6
## 1186 7 3 19 potato 9.0
## 1187 7 3 31 potato 6.4
## 1188 7 3 31 potato 12.0
## 1189 7 3 51 potato 9.4
## 1190 7 3 51 potato 8.7
## 1191 7 3 52 potato 6.4
## 1192 7 3 52 potato 5.7
## 1193 7 3 63 potato 9.5
## 1194 7 3 63 potato 10.7
## 1195 7 3 78 potato 4.3
## 1196 7 3 78 potato 0.2
## 1197 7 3 79 potato 7.2
## 1198 7 3 79 potato 6.5
## 1199 7 3 86 potato 3.0
## 1200 7 3 86 potato 2.4
## 1201 8 1 3 potato 3.5
## 1202 8 1 3 potato 0.6
## 1203 8 1 10 potato 10.2
## 1204 8 1 10 potato 8.6
## 1205 8 1 15 potato 1.9
## 1206 8 1 15 potato 0.6
## 1207 8 1 16 potato 2.4
## 1208 8 1 16 potato 0.9
## 1209 8 1 19 potato 5.4
## 1210 8 1 19 potato 11.0
## 1211 8 1 31 potato 4.0
## 1212 8 1 31 potato 6.6
## 1213 8 1 51 potato 14.9
## 1214 8 1 51 potato 11.5
## 1215 8 1 52 potato 2.1
## 1216 8 1 52 potato 1.7
## 1217 8 1 63 potato 5.9
## 1218 8 1 63 potato 3.8
## 1219 8 1 78 potato 1.5
## 1220 8 1 78 potato 1.6
## 1221 8 1 79 potato 10.5
## 1222 8 1 79 potato 9.8
## 1223 8 1 86 potato 3.8
## 1224 8 1 86 potato 1.4
## 1225 8 2 3 potato 0.9
## 1226 8 2 3 potato 0.5
## 1227 8 2 10 potato 10.9
## 1228 8 2 10 potato 10.3
## 1229 8 2 15 potato 3.2
## 1230 8 2 15 potato 2.3
## 1231 8 2 16 potato 4.5
## 1232 8 2 16 potato 5.3
## 1233 8 2 19 potato 11.2
## 1234 8 2 19 potato 8.7
## 1235 8 2 31 potato 7.8
## 1236 8 2 31 potato 9.9
## 1237 8 2 51 potato 13.8
## 1238 8 2 51 potato 8.5
## 1239 8 2 52 potato 3.9
## 1240 8 2 52 potato 0.0
## 1241 8 2 63 potato 3.9
## 1242 8 2 63 potato 5.7
## 1243 8 2 78 potato 4.0
## 1244 8 2 78 potato 2.1
## 1245 8 2 79 potato 8.2
## 1246 8 2 79 potato 5.7
## 1247 8 2 86 potato 1.3
## 1248 8 2 86 potato 2.8
## 1249 8 3 3 potato 1.5
## 1250 8 3 3 potato 0.5
## 1251 8 3 10 potato 10.0
## 1252 8 3 10 potato 10.9
## 1253 8 3 15 potato 0.6
## 1254 8 3 15 potato 0.2
## 1255 8 3 16 potato 2.2
## 1256 8 3 16 potato 3.3
## 1257 8 3 19 potato 11.1
## 1258 8 3 19 potato 11.5
## 1259 8 3 31 potato 4.2
## 1260 8 3 31 potato 8.1
## 1261 8 3 51 potato 14.5
## 1262 8 3 51 potato 14.0
## 1263 8 3 52 potato 0.0
## 1264 8 3 52 potato 3.2
## 1265 8 3 63 potato 7.8
## 1266 8 3 63 potato 8.6
## 1267 8 3 78 potato 0.8
## 1268 8 3 78 potato 3.2
## 1269 8 3 79 potato 6.8
## 1270 8 3 79 potato 5.7
## 1271 8 3 86 potato 1.4
## 1272 8 3 86 potato 1.4
## 1273 9 1 3 potato 1.1
## 1274 9 1 3 potato 2.5
## 1275 9 1 10 potato 10.5
## 1276 9 1 10 potato 11.2
## 1277 9 1 15 potato 0.2
## 1278 9 1 15 potato 1.7
## 1279 9 1 16 potato 5.4
## 1280 9 1 16 potato 8.5
## 1281 9 1 19 potato 9.6
## 1282 9 1 19 potato 9.0
## 1283 9 1 51 potato 10.2
## 1284 9 1 51 potato 12.7
## 1285 9 1 52 potato 5.1
## 1286 9 1 52 potato 3.0
## 1287 9 1 63 potato 1.7
## 1288 9 1 63 potato 5.3
## 1289 9 1 78 potato 3.5
## 1290 9 1 78 potato 1.0
## 1291 9 1 79 potato 10.1
## 1292 9 1 79 potato 9.1
## 1293 9 2 3 potato 2.7
## 1294 9 2 3 potato 1.8
## 1295 9 2 10 potato 10.4
## 1296 9 2 10 potato 11.0
## 1297 9 2 15 potato 0.2
## 1298 9 2 15 potato 0.0
## 1299 9 2 16 potato 8.5
## 1300 9 2 16 potato 3.8
## 1301 9 2 19 potato 11.1
## 1302 9 2 19 potato 6.2
## 1303 9 2 51 potato 7.3
## 1304 9 2 51 potato 10.6
## 1305 9 2 52 potato 1.8
## 1306 9 2 52 potato 1.6
## 1307 9 2 63 potato 1.8
## 1308 9 2 63 potato 9.1
## 1309 9 2 78 potato 2.0
## 1310 9 2 78 potato 3.4
## 1311 9 2 79 potato 6.7
## 1312 9 2 79 potato 9.4
## 1313 9 3 3 potato 1.6
## 1314 9 3 3 potato 0.7
## 1315 9 3 10 potato 10.2
## 1316 9 3 10 potato 7.3
## 1317 9 3 15 potato 0.7
## 1318 9 3 15 potato 1.5
## 1319 9 3 16 potato 7.5
## 1320 9 3 16 potato 3.6
## 1321 9 3 19 potato 7.9
## 1322 9 3 19 potato 9.1
## 1323 9 3 51 potato 8.2
## 1324 9 3 51 potato 8.9
## 1325 9 3 52 potato 1.1
## 1326 9 3 52 potato 4.0
## 1327 9 3 63 potato 7.5
## 1328 9 3 63 potato 6.0
## 1329 9 3 78 potato 7.9
## 1330 9 3 78 potato 0.0
## 1331 9 3 79 potato 7.8
## 1332 9 3 79 potato 8.1
## 1333 10 1 10 potato 10.6
## 1334 10 1 10 potato 12.1
## 1335 10 1 15 potato 0.1
## 1336 10 1 15 potato 1.7
## 1337 10 1 16 potato 3.0
## 1338 10 1 16 potato 3.8
## 1339 10 1 19 potato 11.4
## 1340 10 1 19 potato 11.8
## 1341 10 1 31 potato 9.5
## 1342 10 1 31 potato 5.3
## 1343 10 1 51 potato 7.6
## 1344 10 1 51 potato 12.3
## 1345 10 1 52 potato 0.4
## 1346 10 1 52 potato 0.0
## 1347 10 1 63 potato 6.5
## 1348 10 1 63 potato 6.2
## 1349 10 1 78 potato 1.2
## 1350 10 1 78 potato 4.4
## 1351 10 1 86 potato 0.7
## 1352 10 1 86 potato 0.7
## 1353 10 2 10 potato 10.7
## 1354 10 2 10 potato 10.5
## 1355 10 2 15 potato 4.8
## 1356 10 2 15 potato 1.1
## 1357 10 2 16 potato 4.2
## 1358 10 2 16 potato 2.9
## 1359 10 2 19 potato 7.0
## 1360 10 2 19 potato 10.9
## 1361 10 2 31 potato 4.6
## 1362 10 2 31 potato 2.3
## 1363 10 2 51 potato 11.3
## 1364 10 2 51 potato 9.9
## 1365 10 2 52 potato 0.3
## 1366 10 2 52 potato 3.8
## 1367 10 2 63 potato 8.6
## 1368 10 2 63 potato 9.0
## 1369 10 2 78 potato 5.2
## 1370 10 2 78 potato 1.5
## 1371 10 2 86 potato 2.0
## 1372 10 2 86 potato 1.0
## 1373 10 3 10 potato 11.3
## 1374 10 3 10 potato 10.0
## 1375 10 3 15 potato 2.5
## 1376 10 3 15 potato 4.3
## 1377 10 3 16 potato 3.9
## 1378 10 3 16 potato 2.5
## 1379 10 3 19 potato 9.1
## 1380 10 3 19 potato 12.2
## 1381 10 3 31 potato 6.5
## 1382 10 3 31 potato 10.4
## 1383 10 3 51 potato 8.0
## 1384 10 3 51 potato 11.6
## 1385 10 3 52 potato 1.2
## 1386 10 3 52 potato 1.8
## 1387 10 3 63 potato 7.0
## 1388 10 3 63 potato 7.0
## 1389 10 3 78 potato 3.7
## 1390 10 3 78 potato 3.3
## 1391 10 3 86 potato 2.5
## 1392 10 3 86 potato 2.5
## 1393 1 1 3 buttery 0.0
## 1394 1 1 3 buttery 0.0
## 1395 1 1 10 buttery 6.4
## 1396 1 1 10 buttery 5.9
## 1397 1 1 15 buttery 0.1
## 1398 1 1 15 buttery 3.0
## 1399 1 1 16 buttery 2.6
## 1400 1 1 16 buttery 4.4
## 1401 1 1 19 buttery 3.2
## 1402 1 1 19 buttery 0.0
## 1403 1 1 31 buttery 0.0
## 1404 1 1 31 buttery 2.5
## 1405 1 1 51 buttery 1.7
## 1406 1 1 51 buttery 4.2
## 1407 1 1 52 buttery 0.0
## 1408 1 1 52 buttery 3.1
## 1409 1 1 63 buttery 0.0
## 1410 1 1 63 buttery 0.0
## 1411 1 1 78 buttery 1.2
## 1412 1 1 78 buttery 0.6
## 1413 1 1 79 buttery 0.0
## 1414 1 1 79 buttery 0.4
## 1415 1 1 86 buttery 1.2
## 1416 1 1 86 buttery 2.6
## 1417 1 2 3 buttery 0.0
## 1418 1 2 3 buttery 0.1
## 1419 1 2 10 buttery 5.2
## 1420 1 2 10 buttery 10.1
## 1421 1 2 15 buttery 3.6
## 1422 1 2 15 buttery 2.7
## 1423 1 2 16 buttery 3.5
## 1424 1 2 16 buttery 0.6
## 1425 1 2 19 buttery 2.5
## 1426 1 2 19 buttery 1.1
## 1427 1 2 31 buttery 0.7
## 1428 1 2 31 buttery 3.2
## 1429 1 2 51 buttery 4.1
## 1430 1 2 51 buttery 1.8
## 1431 1 2 52 buttery 4.4
## 1432 1 2 52 buttery 1.1
## 1433 1 2 63 buttery 0.3
## 1434 1 2 63 buttery 0.0
## 1435 1 2 78 buttery 0.7
## 1436 1 2 78 buttery 0.1
## 1437 1 2 79 buttery 0.8
## 1438 1 2 79 buttery 4.5
## 1439 1 2 86 buttery 4.4
## 1440 1 2 86 buttery 4.3
## 1441 1 3 3 buttery 0.0
## 1442 1 3 3 buttery 0.0
## 1443 1 3 10 buttery 10.2
## 1444 1 3 10 buttery 5.0
## 1445 1 3 15 buttery 1.0
## 1446 1 3 15 buttery 3.6
## 1447 1 3 16 buttery 0.2
## 1448 1 3 16 buttery 1.1
## 1449 1 3 19 buttery 3.4
## 1450 1 3 19 buttery 2.8
## 1451 1 3 31 buttery 0.7
## 1452 1 3 31 buttery 3.7
## 1453 1 3 51 buttery 1.4
## 1454 1 3 51 buttery 4.7
## 1455 1 3 52 buttery 2.0
## 1456 1 3 52 buttery 4.7
## 1457 1 3 63 buttery 0.4
## 1458 1 3 63 buttery 0.0
## 1459 1 3 78 buttery 1.6
## 1460 1 3 78 buttery 0.1
## 1461 1 3 79 buttery 0.0
## 1462 1 3 79 buttery 0.0
## 1463 1 3 86 buttery 4.5
## 1464 1 3 86 buttery 7.0
## 1465 2 1 3 buttery 0.3
## 1466 2 1 3 buttery 0.5
## 1467 2 1 10 buttery 3.1
## 1468 2 1 10 buttery 8.4
## 1469 2 1 15 buttery 1.4
## 1470 2 1 15 buttery 2.3
## 1471 2 1 16 buttery 5.1
## 1472 2 1 16 buttery 3.8
## 1473 2 1 19 buttery 0.0
## 1474 2 1 19 buttery 7.5
## 1475 2 1 31 buttery 3.3
## 1476 2 1 31 buttery 0.0
## 1477 2 1 51 buttery 6.7
## 1478 2 1 51 buttery 1.9
## 1479 2 1 52 buttery 1.6
## 1480 2 1 52 buttery 1.0
## 1481 2 1 63 buttery 0.0
## 1482 2 1 63 buttery 0.0
## 1483 2 1 78 buttery 0.0
## 1484 2 1 78 buttery 1.7
## 1485 2 1 79 buttery 0.0
## 1486 2 1 79 buttery 0.0
## 1487 2 1 86 buttery 6.0
## 1488 2 1 86 buttery 6.0
## 1489 2 2 3 buttery 0.9
## 1490 2 2 3 buttery 0.7
## 1491 2 2 10 buttery 7.6
## 1492 2 2 10 buttery 6.8
## 1493 2 2 15 buttery 5.6
## 1494 2 2 15 buttery 2.7
## 1495 2 2 16 buttery 4.8
## 1496 2 2 16 buttery 0.7
## 1497 2 2 19 buttery 10.0
## 1498 2 2 19 buttery 3.7
## 1499 2 2 31 buttery 1.4
## 1500 2 2 31 buttery 0.4
## 1501 2 2 51 buttery 3.4
## 1502 2 2 51 buttery 4.6
## 1503 2 2 52 buttery 3.6
## 1504 2 2 52 buttery 3.5
## 1505 2 2 63 buttery 0.0
## 1506 2 2 63 buttery 0.0
## 1507 2 2 78 buttery 0.0
## 1508 2 2 78 buttery 0.0
## 1509 2 2 79 buttery 3.2
## 1510 2 2 79 buttery 1.1
## 1511 2 2 86 buttery 7.9
## 1512 2 2 86 buttery 2.4
## 1513 2 3 3 buttery 0.6
## 1514 2 3 3 buttery 0.8
## 1515 2 3 10 buttery 5.7
## 1516 2 3 10 buttery 4.4
## 1517 2 3 15 buttery 3.6
## 1518 2 3 15 buttery 3.2
## 1519 2 3 16 buttery 7.3
## 1520 2 3 16 buttery 2.4
## 1521 2 3 19 buttery 3.6
## 1522 2 3 19 buttery 3.0
## 1523 2 3 31 buttery 0.4
## 1524 2 3 31 buttery 0.5
## 1525 2 3 51 buttery 4.7
## 1526 2 3 51 buttery 5.2
## 1527 2 3 52 buttery 2.8
## 1528 2 3 52 buttery 1.9
## 1529 2 3 63 buttery 0.0
## 1530 2 3 63 buttery 0.0
## 1531 2 3 78 buttery 1.9
## 1532 2 3 78 buttery 0.0
## 1533 2 3 79 buttery 1.1
## 1534 2 3 79 buttery 0.0
## 1535 2 3 86 buttery 1.6
## 1536 2 3 86 buttery 5.7
## 1537 3 1 3 buttery 0.2
## 1538 3 1 3 buttery 0.5
## 1539 3 1 10 buttery 7.0
## 1540 3 1 10 buttery 6.6
## 1541 3 1 15 buttery 0.2
## 1542 3 1 15 buttery 2.7
## 1543 3 1 16 buttery 0.2
## 1544 3 1 16 buttery 2.1
## 1545 3 1 19 buttery 9.6
## 1546 3 1 19 buttery 6.0
## 1547 3 1 31 buttery 0.8
## 1548 3 1 31 buttery 0.0
## 1549 3 1 51 buttery 1.4
## 1550 3 1 51 buttery 3.0
## 1551 3 1 52 buttery 0.7
## 1552 3 1 52 buttery 2.9
## 1553 3 1 63 buttery 0.0
## 1554 3 1 63 buttery 0.0
## 1555 3 1 78 buttery 1.3
## 1556 3 1 78 buttery 1.0
## 1557 3 1 79 buttery 1.4
## 1558 3 1 79 buttery 0.0
## 1559 3 1 86 buttery 4.6
## 1560 3 1 86 buttery 2.9
## 1561 3 2 3 buttery 0.1
## 1562 3 2 3 buttery 0.5
## 1563 3 2 10 buttery 8.2
## 1564 3 2 10 buttery 7.5
## 1565 3 2 15 buttery 2.8
## 1566 3 2 15 buttery 1.8
## 1567 3 2 16 buttery 0.3
## 1568 3 2 16 buttery 4.2
## 1569 3 2 19 buttery 0.0
## 1570 3 2 19 buttery 1.7
## 1571 3 2 31 buttery 0.2
## 1572 3 2 31 buttery 0.4
## 1573 3 2 51 buttery 4.2
## 1574 3 2 51 buttery 1.9
## 1575 3 2 52 buttery 2.7
## 1576 3 2 52 buttery 1.6
## 1577 3 2 63 buttery 0.7
## 1578 3 2 63 buttery 0.0
## 1579 3 2 78 buttery 2.9
## 1580 3 2 78 buttery 0.0
## 1581 3 2 79 buttery 0.0
## 1582 3 2 79 buttery 0.0
## 1583 3 2 86 buttery 5.2
## 1584 3 2 86 buttery 3.0
## 1585 3 3 3 buttery 0.2
## 1586 3 3 3 buttery 0.5
## 1587 3 3 10 buttery 8.0
## 1588 3 3 10 buttery 8.4
## 1589 3 3 15 buttery 0.7
## 1590 3 3 15 buttery 1.6
## 1591 3 3 16 buttery 0.4
## 1592 3 3 16 buttery 2.1
## 1593 3 3 19 buttery 4.0
## 1594 3 3 19 buttery 1.7
## 1595 3 3 31 buttery 0.5
## 1596 3 3 31 buttery 0.0
## 1597 3 3 51 buttery 3.0
## 1598 3 3 51 buttery 0.0
## 1599 3 3 52 buttery 0.2
## 1600 3 3 52 buttery 1.2
## 1601 3 3 63 buttery 0.0
## 1602 3 3 63 buttery 0.0
## 1603 3 3 78 buttery 2.6
## 1604 3 3 78 buttery 1.1
## 1605 3 3 79 buttery 2.1
## 1606 3 3 79 buttery 5.1
## 1607 3 3 86 buttery 1.5
## 1608 3 3 86 buttery 1.5
## 1609 4 1 3 buttery 0.1
## 1610 4 1 3 buttery 0.0
## 1611 4 1 10 buttery 4.4
## 1612 4 1 10 buttery 5.8
## 1613 4 1 15 buttery 0.6
## 1614 4 1 15 buttery 0.4
## 1615 4 1 16 buttery 0.9
## 1616 4 1 16 buttery 1.3
## 1617 4 1 19 buttery 4.4
## 1618 4 1 19 buttery 2.3
## 1619 4 1 31 buttery 0.8
## 1620 4 1 31 buttery 0.3
## 1621 4 1 51 buttery 2.5
## 1622 4 1 51 buttery 5.4
## 1623 4 1 52 buttery 3.9
## 1624 4 1 52 buttery 2.6
## 1625 4 1 63 buttery 0.0
## 1626 4 1 63 buttery 0.5
## 1627 4 1 78 buttery 1.0
## 1628 4 1 78 buttery 1.1
## 1629 4 1 79 buttery 1.8
## 1630 4 1 79 buttery 0.0
## 1631 4 1 86 buttery 5.8
## 1632 4 1 86 buttery 1.6
## 1633 4 2 3 buttery 0.0
## 1634 4 2 3 buttery 0.0
## 1635 4 2 10 buttery 5.6
## 1636 4 2 10 buttery 7.7
## 1637 4 2 15 buttery 0.6
## 1638 4 2 15 buttery 1.1
## 1639 4 2 16 buttery 1.1
## 1640 4 2 16 buttery 4.9
## 1641 4 2 19 buttery 6.4
## 1642 4 2 19 buttery 1.4
## 1643 4 2 31 buttery 0.0
## 1644 4 2 31 buttery 0.3
## 1645 4 2 51 buttery 2.2
## 1646 4 2 51 buttery 3.1
## 1647 4 2 52 buttery 0.5
## 1648 4 2 52 buttery 1.3
## 1649 4 2 63 buttery 0.0
## 1650 4 2 63 buttery 0.0
## 1651 4 2 78 buttery 0.0
## 1652 4 2 78 buttery 0.0
## 1653 4 2 79 buttery 0.0
## 1654 4 2 79 buttery 0.9
## 1655 4 2 86 buttery 0.9
## 1656 4 2 86 buttery 0.6
## 1657 4 3 3 buttery 0.5
## 1658 4 3 3 buttery 0.2
## 1659 4 3 10 buttery 8.4
## 1660 4 3 10 buttery 7.1
## 1661 4 3 15 buttery 0.4
## 1662 4 3 15 buttery 0.3
## 1663 4 3 16 buttery 5.4
## 1664 4 3 16 buttery 4.4
## 1665 4 3 19 buttery 1.6
## 1666 4 3 19 buttery 0.0
## 1667 4 3 31 buttery 2.8
## 1668 4 3 31 buttery 0.0
## 1669 4 3 51 buttery 3.7
## 1670 4 3 51 buttery 2.1
## 1671 4 3 52 buttery 1.7
## 1672 4 3 52 buttery 0.8
## 1673 4 3 63 buttery 0.0
## 1674 4 3 63 buttery 0.0
## 1675 4 3 78 buttery 1.3
## 1676 4 3 78 buttery 2.9
## 1677 4 3 79 buttery 0.0
## 1678 4 3 79 buttery 0.0
## 1679 4 3 86 buttery 0.0
## 1680 4 3 86 buttery 0.0
## 1681 5 1 3 buttery 0.3
## 1682 5 1 3 buttery 0.8
## 1683 5 1 10 buttery 8.4
## 1684 5 1 10 buttery 5.4
## 1685 5 1 15 buttery 0.3
## 1686 5 1 15 buttery 0.2
## 1687 5 1 16 buttery 0.4
## 1688 5 1 16 buttery 3.9
## 1689 5 1 19 buttery 0.9
## 1690 5 1 19 buttery 1.7
## 1691 5 1 31 buttery 0.0
## 1692 5 1 31 buttery 0.3
## 1693 5 1 51 buttery 2.4
## 1694 5 1 51 buttery 4.7
## 1695 5 1 52 buttery 0.0
## 1696 5 1 52 buttery 0.0
## 1697 5 1 63 buttery 0.0
## 1698 5 1 63 buttery 0.0
## 1699 5 1 78 buttery 1.1
## 1700 5 1 78 buttery 1.2
## 1701 5 1 79 buttery 0.8
## 1702 5 1 79 buttery 0.0
## 1703 5 1 86 buttery 0.0
## 1704 5 1 86 buttery 0.0
## 1705 5 2 3 buttery 0.0
## 1706 5 2 3 buttery 1.7
## 1707 5 2 10 buttery 7.5
## 1708 5 2 10 buttery 2.8
## 1709 5 2 15 buttery 0.2
## 1710 5 2 15 buttery 0.3
## 1711 5 2 16 buttery 5.0
## 1712 5 2 16 buttery 6.8
## 1713 5 2 19 buttery 5.0
## 1714 5 2 19 buttery 4.7
## 1715 5 2 31 buttery 0.0
## 1716 5 2 31 buttery 0.0
## 1717 5 2 51 buttery 2.9
## 1718 5 2 51 buttery 4.7
## 1719 5 2 52 buttery 0.0
## 1720 5 2 52 buttery 0.0
## 1721 5 2 63 buttery 0.0
## 1722 5 2 63 buttery 0.0
## 1723 5 2 78 buttery 0.0
## 1724 5 2 78 buttery 0.0
## 1725 5 2 79 buttery 0.0
## 1726 5 2 79 buttery 0.5
## 1727 5 2 86 buttery 1.5
## 1728 5 2 86 buttery 1.0
## 1729 5 3 3 buttery 0.0
## 1730 5 3 3 buttery 4.3
## 1731 5 3 10 buttery 8.8
## 1732 5 3 10 buttery 4.3
## 1733 5 3 15 buttery NA
## 1734 5 3 15 buttery 0.2
## 1735 5 3 16 buttery 1.0
## 1736 5 3 16 buttery 2.0
## 1737 5 3 19 buttery 2.9
## 1738 5 3 19 buttery 0.0
## 1739 5 3 31 buttery 2.7
## 1740 5 3 31 buttery 0.0
## 1741 5 3 51 buttery 4.4
## 1742 5 3 51 buttery 2.3
## 1743 5 3 52 buttery 0.1
## 1744 5 3 52 buttery 0.0
## 1745 5 3 63 buttery 0.0
## 1746 5 3 63 buttery 0.0
## 1747 5 3 78 buttery 0.8
## 1748 5 3 78 buttery 0.8
## 1749 5 3 79 buttery 0.0
## 1750 5 3 79 buttery 0.5
## 1751 5 3 86 buttery 4.0
## 1752 5 3 86 buttery 0.1
## 1753 6 1 3 buttery 1.2
## 1754 6 1 3 buttery 1.1
## 1755 6 1 10 buttery 11.2
## 1756 6 1 10 buttery 7.6
## 1757 6 1 15 buttery 0.3
## 1758 6 1 15 buttery 0.2
## 1759 6 1 16 buttery 0.3
## 1760 6 1 16 buttery 4.2
## 1761 6 1 19 buttery 9.5
## 1762 6 1 19 buttery 0.0
## 1763 6 1 31 buttery 0.0
## 1764 6 1 31 buttery 0.0
## 1765 6 1 51 buttery 4.7
## 1766 6 1 51 buttery 2.5
## 1767 6 1 52 buttery 0.0
## 1768 6 1 52 buttery 0.0
## 1769 6 1 63 buttery 0.0
## 1770 6 1 63 buttery 0.0
## 1771 6 1 78 buttery 0.0
## 1772 6 1 78 buttery 0.6
## 1773 6 1 79 buttery 0.4
## 1774 6 1 79 buttery 0.0
## 1775 6 1 86 buttery 0.0
## 1776 6 1 86 buttery 0.0
## 1777 6 2 3 buttery 0.7
## 1778 6 2 3 buttery 1.9
## 1779 6 2 10 buttery 7.7
## 1780 6 2 10 buttery 6.8
## 1781 6 2 15 buttery 0.3
## 1782 6 2 15 buttery 1.5
## 1783 6 2 16 buttery 2.7
## 1784 6 2 16 buttery 4.3
## 1785 6 2 19 buttery 0.0
## 1786 6 2 19 buttery 1.5
## 1787 6 2 31 buttery 0.8
## 1788 6 2 31 buttery 1.6
## 1789 6 2 51 buttery 3.1
## 1790 6 2 51 buttery 8.2
## 1791 6 2 52 buttery 0.8
## 1792 6 2 52 buttery 0.7
## 1793 6 2 63 buttery 0.0
## 1794 6 2 63 buttery 0.0
## 1795 6 2 78 buttery 0.0
## 1796 6 2 78 buttery 0.0
## 1797 6 2 79 buttery 0.0
## 1798 6 2 79 buttery 0.8
## 1799 6 2 86 buttery 5.3
## 1800 6 2 86 buttery 0.6
## 1801 6 3 3 buttery 1.0
## 1802 6 3 3 buttery 2.2
## 1803 6 3 10 buttery 5.4
## 1804 6 3 10 buttery 5.5
## 1805 6 3 15 buttery 0.1
## 1806 6 3 15 buttery 0.2
## 1807 6 3 16 buttery 0.8
## 1808 6 3 16 buttery 5.1
## 1809 6 3 19 buttery 1.0
## 1810 6 3 19 buttery 3.6
## 1811 6 3 31 buttery 0.0
## 1812 6 3 31 buttery 0.0
## 1813 6 3 51 buttery 4.5
## 1814 6 3 51 buttery 2.5
## 1815 6 3 52 buttery 0.0
## 1816 6 3 52 buttery 0.0
## 1817 6 3 63 buttery 0.0
## 1818 6 3 63 buttery 0.0
## 1819 6 3 78 buttery 0.0
## 1820 6 3 78 buttery 0.0
## 1821 6 3 79 buttery 0.0
## 1822 6 3 79 buttery 0.0
## 1823 6 3 86 buttery 1.2
## 1824 6 3 86 buttery 0.0
## 1825 7 1 3 buttery 0.0
## 1826 7 1 3 buttery 0.0
## 1827 7 1 10 buttery 6.4
## 1828 7 1 10 buttery 3.7
## 1829 7 1 15 buttery 0.1
## 1830 7 1 15 buttery 0.0
## 1831 7 1 16 buttery 2.6
## 1832 7 1 16 buttery 5.7
## 1833 7 1 19 buttery 3.2
## 1834 7 1 19 buttery 1.5
## 1835 7 1 31 buttery 0.0
## 1836 7 1 31 buttery 0.0
## 1837 7 1 51 buttery 1.7
## 1838 7 1 51 buttery 1.4
## 1839 7 1 52 buttery 0.0
## 1840 7 1 52 buttery 0.1
## 1841 7 1 63 buttery 0.0
## 1842 7 1 63 buttery 0.0
## 1843 7 1 78 buttery 1.2
## 1844 7 1 78 buttery 1.0
## 1845 7 1 79 buttery 0.0
## 1846 7 1 79 buttery 0.0
## 1847 7 1 86 buttery 1.2
## 1848 7 1 86 buttery 0.0
## 1849 7 2 3 buttery 0.6
## 1850 7 2 3 buttery 1.2
## 1851 7 2 10 buttery 9.0
## 1852 7 2 10 buttery 4.4
## 1853 7 2 15 buttery 0.1
## 1854 7 2 15 buttery 0.0
## 1855 7 2 16 buttery 1.6
## 1856 7 2 16 buttery 5.6
## 1857 7 2 19 buttery 0.0
## 1858 7 2 19 buttery 0.0
## 1859 7 2 31 buttery 0.0
## 1860 7 2 31 buttery 0.0
## 1861 7 2 51 buttery 2.5
## 1862 7 2 51 buttery 4.4
## 1863 7 2 52 buttery 0.3
## 1864 7 2 52 buttery 0.0
## 1865 7 2 63 buttery 0.5
## 1866 7 2 63 buttery 0.0
## 1867 7 2 78 buttery 0.0
## 1868 7 2 78 buttery 1.0
## 1869 7 2 79 buttery NA
## 1870 7 2 79 buttery 0.0
## 1871 7 2 86 buttery 0.0
## 1872 7 2 86 buttery 0.0
## 1873 7 3 3 buttery 0.7
## 1874 7 3 3 buttery 0.9
## 1875 7 3 10 buttery 2.7
## 1876 7 3 10 buttery 8.1
## 1877 7 3 15 buttery 0.0
## 1878 7 3 15 buttery 0.1
## 1879 7 3 16 buttery 5.1
## 1880 7 3 16 buttery 7.5
## 1881 7 3 19 buttery 0.0
## 1882 7 3 19 buttery 0.0
## 1883 7 3 31 buttery 0.0
## 1884 7 3 31 buttery 0.4
## 1885 7 3 51 buttery 2.2
## 1886 7 3 51 buttery 4.6
## 1887 7 3 52 buttery 0.3
## 1888 7 3 52 buttery 0.8
## 1889 7 3 63 buttery 0.0
## 1890 7 3 63 buttery 0.5
## 1891 7 3 78 buttery 0.0
## 1892 7 3 78 buttery 0.0
## 1893 7 3 79 buttery 0.0
## 1894 7 3 79 buttery 0.0
## 1895 7 3 86 buttery 2.3
## 1896 7 3 86 buttery 0.0
## 1897 8 1 3 buttery 0.5
## 1898 8 1 3 buttery 0.3
## 1899 8 1 10 buttery 8.2
## 1900 8 1 10 buttery 4.0
## 1901 8 1 15 buttery 1.9
## 1902 8 1 15 buttery 0.0
## 1903 8 1 16 buttery 1.0
## 1904 8 1 16 buttery 0.3
## 1905 8 1 19 buttery 3.5
## 1906 8 1 19 buttery 0.0
## 1907 8 1 31 buttery 0.0
## 1908 8 1 31 buttery 0.0
## 1909 8 1 51 buttery 0.8
## 1910 8 1 51 buttery 1.3
## 1911 8 1 52 buttery 0.0
## 1912 8 1 52 buttery 0.0
## 1913 8 1 63 buttery 0.0
## 1914 8 1 63 buttery 0.0
## 1915 8 1 78 buttery 0.0
## 1916 8 1 78 buttery 0.9
## 1917 8 1 79 buttery NA
## 1918 8 1 79 buttery 0.0
## 1919 8 1 86 buttery 0.0
## 1920 8 1 86 buttery 0.0
## 1921 8 2 3 buttery 0.3
## 1922 8 2 3 buttery 0.3
## 1923 8 2 10 buttery 4.6
## 1924 8 2 10 buttery 9.3
## 1925 8 2 15 buttery 0.1
## 1926 8 2 15 buttery 0.0
## 1927 8 2 16 buttery NA
## 1928 8 2 16 buttery 3.5
## 1929 8 2 19 buttery 2.2
## 1930 8 2 19 buttery 5.2
## 1931 8 2 31 buttery 1.1
## 1932 8 2 31 buttery 1.0
## 1933 8 2 51 buttery 1.4
## 1934 8 2 51 buttery 6.2
## 1935 8 2 52 buttery 0.0
## 1936 8 2 52 buttery 0.0
## 1937 8 2 63 buttery 0.0
## 1938 8 2 63 buttery 0.0
## 1939 8 2 78 buttery 0.0
## 1940 8 2 78 buttery 1.2
## 1941 8 2 79 buttery 0.0
## 1942 8 2 79 buttery 0.0
## 1943 8 2 86 buttery 0.0
## 1944 8 2 86 buttery 0.0
## 1945 8 3 3 buttery 0.6
## 1946 8 3 3 buttery 0.5
## 1947 8 3 10 buttery 6.0
## 1948 8 3 10 buttery 4.5
## 1949 8 3 15 buttery 0.0
## 1950 8 3 15 buttery 0.1
## 1951 8 3 16 buttery 0.9
## 1952 8 3 16 buttery 1.2
## 1953 8 3 19 buttery 2.9
## 1954 8 3 19 buttery 0.0
## 1955 8 3 31 buttery 0.0
## 1956 8 3 31 buttery 0.0
## 1957 8 3 51 buttery 5.5
## 1958 8 3 51 buttery 1.1
## 1959 8 3 52 buttery 0.0
## 1960 8 3 52 buttery 0.0
## 1961 8 3 63 buttery 0.0
## 1962 8 3 63 buttery 0.4
## 1963 8 3 78 buttery 0.0
## 1964 8 3 78 buttery 0.0
## 1965 8 3 79 buttery 0.0
## 1966 8 3 79 buttery 0.0
## 1967 8 3 86 buttery 0.0
## 1968 8 3 86 buttery 0.0
## 1969 9 1 3 buttery 0.4
## 1970 9 1 3 buttery 0.5
## 1971 9 1 10 buttery 8.5
## 1972 9 1 10 buttery 8.4
## 1973 9 1 15 buttery 0.1
## 1974 9 1 15 buttery 0.4
## 1975 9 1 16 buttery 6.7
## 1976 9 1 16 buttery 4.9
## 1977 9 1 19 buttery 0.0
## 1978 9 1 19 buttery 3.0
## 1979 9 1 51 buttery 0.0
## 1980 9 1 51 buttery 3.5
## 1981 9 1 52 buttery 0.2
## 1982 9 1 52 buttery 0.0
## 1983 9 1 63 buttery 0.0
## 1984 9 1 63 buttery 0.0
## 1985 9 1 78 buttery 0.0
## 1986 9 1 78 buttery 0.0
## 1987 9 1 79 buttery 0.0
## 1988 9 1 79 buttery 0.0
## 1989 9 2 3 buttery 0.2
## 1990 9 2 3 buttery 1.4
## 1991 9 2 10 buttery 6.7
## 1992 9 2 10 buttery 8.8
## 1993 9 2 15 buttery 0.1
## 1994 9 2 15 buttery 1.3
## 1995 9 2 16 buttery 2.8
## 1996 9 2 16 buttery 2.2
## 1997 9 2 19 buttery 3.6
## 1998 9 2 19 buttery 0.0
## 1999 9 2 51 buttery 2.3
## 2000 9 2 51 buttery 3.9
## 2001 9 2 52 buttery 0.0
## 2002 9 2 52 buttery 0.0
## 2003 9 2 63 buttery 0.0
## 2004 9 2 63 buttery 0.0
## 2005 9 2 78 buttery 0.0
## 2006 9 2 78 buttery 0.0
## 2007 9 2 79 buttery 0.0
## 2008 9 2 79 buttery 0.0
## 2009 9 3 3 buttery 0.5
## 2010 9 3 3 buttery 0.3
## 2011 9 3 10 buttery 8.5
## 2012 9 3 10 buttery 3.4
## 2013 9 3 15 buttery 0.0
## 2014 9 3 15 buttery 0.0
## 2015 9 3 16 buttery 2.6
## 2016 9 3 16 buttery 2.4
## 2017 9 3 19 buttery 0.0
## 2018 9 3 19 buttery 0.0
## 2019 9 3 51 buttery 0.4
## 2020 9 3 51 buttery 4.7
## 2021 9 3 52 buttery 0.0
## 2022 9 3 52 buttery 0.0
## 2023 9 3 63 buttery 0.0
## 2024 9 3 63 buttery 0.0
## 2025 9 3 78 buttery 1.0
## 2026 9 3 78 buttery 0.0
## 2027 9 3 79 buttery 0.0
## 2028 9 3 79 buttery 1.5
## 2029 10 1 10 buttery 7.1
## 2030 10 1 10 buttery 8.5
## 2031 10 1 15 buttery 0.1
## 2032 10 1 15 buttery 0.1
## 2033 10 1 16 buttery 7.0
## 2034 10 1 16 buttery 7.8
## 2035 10 1 19 buttery 1.6
## 2036 10 1 19 buttery 3.2
## 2037 10 1 31 buttery 0.0
## 2038 10 1 31 buttery 0.0
## 2039 10 1 51 buttery 2.2
## 2040 10 1 51 buttery 0.8
## 2041 10 1 52 buttery 0.0
## 2042 10 1 52 buttery 0.0
## 2043 10 1 63 buttery 0.0
## 2044 10 1 63 buttery 0.0
## 2045 10 1 78 buttery 0.8
## 2046 10 1 78 buttery 0.0
## 2047 10 1 86 buttery 0.0
## 2048 10 1 86 buttery 0.0
## 2049 10 2 10 buttery 6.8
## 2050 10 2 10 buttery 6.5
## 2051 10 2 15 buttery 1.4
## 2052 10 2 15 buttery 0.1
## 2053 10 2 16 buttery 6.0
## 2054 10 2 16 buttery 3.5
## 2055 10 2 19 buttery 0.0
## 2056 10 2 19 buttery 0.0
## 2057 10 2 31 buttery 0.0
## 2058 10 2 31 buttery 0.0
## 2059 10 2 51 buttery 5.3
## 2060 10 2 51 buttery 5.7
## 2061 10 2 52 buttery 0.0
## 2062 10 2 52 buttery 0.0
## 2063 10 2 63 buttery 0.6
## 2064 10 2 63 buttery 0.0
## 2065 10 2 78 buttery 0.0
## 2066 10 2 78 buttery 0.0
## 2067 10 2 86 buttery 0.0
## 2068 10 2 86 buttery 0.0
## 2069 10 3 10 buttery 9.2
## 2070 10 3 10 buttery 5.4
## 2071 10 3 15 buttery 0.4
## 2072 10 3 15 buttery 3.3
## 2073 10 3 16 buttery 1.4
## 2074 10 3 16 buttery 0.7
## 2075 10 3 19 buttery 4.0
## 2076 10 3 19 buttery 0.0
## 2077 10 3 31 buttery 0.0
## 2078 10 3 31 buttery 0.0
## 2079 10 3 51 buttery 3.2
## 2080 10 3 51 buttery 2.4
## 2081 10 3 52 buttery 0.8
## 2082 10 3 52 buttery 0.0
## 2083 10 3 63 buttery 0.0
## 2084 10 3 63 buttery 0.0
## 2085 10 3 78 buttery 0.0
## 2086 10 3 78 buttery 0.0
## 2087 10 3 86 buttery 0.0
## 2088 10 3 86 buttery 0.0
## 2089 1 1 3 grassy 0.0
## 2090 1 1 3 grassy 0.0
## 2091 1 1 10 grassy 0.0
## 2092 1 1 10 grassy 2.9
## 2093 1 1 15 grassy 0.0
## 2094 1 1 15 grassy 3.6
## 2095 1 1 16 grassy 0.4
## 2096 1 1 16 grassy 0.3
## 2097 1 1 19 grassy 0.0
## 2098 1 1 19 grassy 3.1
## 2099 1 1 31 grassy 0.0
## 2100 1 1 31 grassy 0.0
## 2101 1 1 51 grassy 0.1
## 2102 1 1 51 grassy 3.6
## 2103 1 1 52 grassy 1.7
## 2104 1 1 52 grassy 0.3
## 2105 1 1 63 grassy 0.0
## 2106 1 1 63 grassy 0.0
## 2107 1 1 78 grassy 0.0
## 2108 1 1 78 grassy 3.0
## 2109 1 1 79 grassy 0.0
## 2110 1 1 79 grassy 0.0
## 2111 1 1 86 grassy 0.0
## 2112 1 1 86 grassy 2.7
## 2113 1 2 3 grassy 0.0
## 2114 1 2 3 grassy 0.0
## 2115 1 2 10 grassy 3.3
## 2116 1 2 10 grassy 2.5
## 2117 1 2 15 grassy 0.3
## 2118 1 2 15 grassy 2.7
## 2119 1 2 16 grassy 0.8
## 2120 1 2 16 grassy 0.2
## 2121 1 2 19 grassy 1.3
## 2122 1 2 19 grassy 0.0
## 2123 1 2 31 grassy 0.0
## 2124 1 2 31 grassy 0.0
## 2125 1 2 51 grassy 4.3
## 2126 1 2 51 grassy 2.5
## 2127 1 2 52 grassy 0.0
## 2128 1 2 52 grassy 0.4
## 2129 1 2 63 grassy 0.0
## 2130 1 2 63 grassy 0.0
## 2131 1 2 78 grassy 1.2
## 2132 1 2 78 grassy 3.8
## 2133 1 2 79 grassy 0.6
## 2134 1 2 79 grassy 0.0
## 2135 1 2 86 grassy 0.0
## 2136 1 2 86 grassy 0.0
## 2137 1 3 3 grassy 0.0
## 2138 1 3 3 grassy 0.6
## 2139 1 3 10 grassy 0.0
## 2140 1 3 10 grassy 0.8
## 2141 1 3 15 grassy 0.5
## 2142 1 3 15 grassy 0.5
## 2143 1 3 16 grassy 0.6
## 2144 1 3 16 grassy 0.5
## 2145 1 3 19 grassy 5.2
## 2146 1 3 19 grassy 0.0
## 2147 1 3 31 grassy 0.3
## 2148 1 3 31 grassy 0.0
## 2149 1 3 51 grassy 0.0
## 2150 1 3 51 grassy 2.0
## 2151 1 3 52 grassy 0.0
## 2152 1 3 52 grassy 0.0
## 2153 1 3 63 grassy 1.9
## 2154 1 3 63 grassy 0.0
## 2155 1 3 78 grassy 0.0
## 2156 1 3 78 grassy 3.7
## 2157 1 3 79 grassy 1.6
## 2158 1 3 79 grassy 0.0
## 2159 1 3 86 grassy 1.5
## 2160 1 3 86 grassy 2.5
## 2161 2 1 3 grassy 0.1
## 2162 2 1 3 grassy 2.0
## 2163 2 1 10 grassy 3.1
## 2164 2 1 10 grassy 0.0
## 2165 2 1 15 grassy 0.1
## 2166 2 1 15 grassy 0.5
## 2167 2 1 16 grassy 0.0
## 2168 2 1 16 grassy 0.7
## 2169 2 1 19 grassy 0.0
## 2170 2 1 19 grassy 0.0
## 2171 2 1 31 grassy 0.0
## 2172 2 1 31 grassy 1.2
## 2173 2 1 51 grassy 1.5
## 2174 2 1 51 grassy 0.1
## 2175 2 1 52 grassy 2.8
## 2176 2 1 52 grassy 2.1
## 2177 2 1 63 grassy 0.0
## 2178 2 1 63 grassy 0.0
## 2179 2 1 78 grassy 1.3
## 2180 2 1 78 grassy 0.5
## 2181 2 1 79 grassy 2.3
## 2182 2 1 79 grassy 2.8
## 2183 2 1 86 grassy 0.0
## 2184 2 1 86 grassy 3.0
## 2185 2 2 3 grassy 0.3
## 2186 2 2 3 grassy 1.6
## 2187 2 2 10 grassy 1.6
## 2188 2 2 10 grassy 0.0
## 2189 2 2 15 grassy 0.7
## 2190 2 2 15 grassy 0.4
## 2191 2 2 16 grassy 0.7
## 2192 2 2 16 grassy 0.7
## 2193 2 2 19 grassy 1.9
## 2194 2 2 19 grassy 2.7
## 2195 2 2 31 grassy 0.0
## 2196 2 2 31 grassy 0.0
## 2197 2 2 51 grassy 1.2
## 2198 2 2 51 grassy 0.0
## 2199 2 2 52 grassy 0.4
## 2200 2 2 52 grassy 0.0
## 2201 2 2 63 grassy 0.0
## 2202 2 2 63 grassy 0.2
## 2203 2 2 78 grassy 5.1
## 2204 2 2 78 grassy 1.3
## 2205 2 2 79 grassy 2.1
## 2206 2 2 79 grassy 0.5
## 2207 2 2 86 grassy 1.4
## 2208 2 2 86 grassy 0.0
## 2209 2 3 3 grassy 0.7
## 2210 2 3 3 grassy 0.0
## 2211 2 3 10 grassy 2.1
## 2212 2 3 10 grassy 0.0
## 2213 2 3 15 grassy 3.5
## 2214 2 3 15 grassy 1.6
## 2215 2 3 16 grassy 1.3
## 2216 2 3 16 grassy 1.2
## 2217 2 3 19 grassy 5.8
## 2218 2 3 19 grassy 10.5
## 2219 2 3 31 grassy 0.0
## 2220 2 3 31 grassy 0.0
## 2221 2 3 51 grassy 0.0
## 2222 2 3 51 grassy 4.4
## 2223 2 3 52 grassy 0.8
## 2224 2 3 52 grassy 1.6
## 2225 2 3 63 grassy 0.0
## 2226 2 3 63 grassy 0.6
## 2227 2 3 78 grassy 0.0
## 2228 2 3 78 grassy 1.5
## 2229 2 3 79 grassy 0.0
## 2230 2 3 79 grassy 0.0
## 2231 2 3 86 grassy 2.6
## 2232 2 3 86 grassy 0.0
## 2233 3 1 3 grassy 0.0
## 2234 3 1 3 grassy 0.0
## 2235 3 1 10 grassy 0.0
## 2236 3 1 10 grassy 0.0
## 2237 3 1 15 grassy 0.2
## 2238 3 1 15 grassy 0.1
## 2239 3 1 16 grassy 3.0
## 2240 3 1 16 grassy 0.3
## 2241 3 1 19 grassy 3.6
## 2242 3 1 19 grassy 0.0
## 2243 3 1 31 grassy 0.0
## 2244 3 1 31 grassy 0.0
## 2245 3 1 51 grassy 0.2
## 2246 3 1 51 grassy 1.1
## 2247 3 1 52 grassy 4.1
## 2248 3 1 52 grassy 0.9
## 2249 3 1 63 grassy 0.0
## 2250 3 1 63 grassy 0.0
## 2251 3 1 78 grassy 0.0
## 2252 3 1 78 grassy 0.0
## 2253 3 1 79 grassy 0.0
## 2254 3 1 79 grassy 1.1
## 2255 3 1 86 grassy 2.0
## 2256 3 1 86 grassy 3.0
## 2257 3 2 3 grassy 0.0
## 2258 3 2 3 grassy 0.0
## 2259 3 2 10 grassy 0.1
## 2260 3 2 10 grassy 0.0
## 2261 3 2 15 grassy 0.0
## 2262 3 2 15 grassy 0.0
## 2263 3 2 16 grassy 0.0
## 2264 3 2 16 grassy 0.9
## 2265 3 2 19 grassy 0.0
## 2266 3 2 19 grassy 0.0
## 2267 3 2 31 grassy 0.0
## 2268 3 2 31 grassy 0.0
## 2269 3 2 51 grassy 0.0
## 2270 3 2 51 grassy 2.9
## 2271 3 2 52 grassy 1.8
## 2272 3 2 52 grassy 3.9
## 2273 3 2 63 grassy 0.0
## 2274 3 2 63 grassy 0.0
## 2275 3 2 78 grassy 0.0
## 2276 3 2 78 grassy 0.8
## 2277 3 2 79 grassy 0.0
## 2278 3 2 79 grassy 0.0
## 2279 3 2 86 grassy 4.8
## 2280 3 2 86 grassy 2.2
## 2281 3 3 3 grassy 0.0
## 2282 3 3 3 grassy 0.0
## 2283 3 3 10 grassy 0.0
## 2284 3 3 10 grassy 0.0
## 2285 3 3 15 grassy 0.3
## 2286 3 3 15 grassy 0.3
## 2287 3 3 16 grassy 0.5
## 2288 3 3 16 grassy 2.5
## 2289 3 3 19 grassy 1.0
## 2290 3 3 19 grassy 2.9
## 2291 3 3 31 grassy 0.0
## 2292 3 3 31 grassy 0.0
## 2293 3 3 51 grassy 0.0
## 2294 3 3 51 grassy 0.0
## 2295 3 3 52 grassy 2.0
## 2296 3 3 52 grassy 0.9
## 2297 3 3 63 grassy 0.0
## 2298 3 3 63 grassy 0.0
## 2299 3 3 78 grassy 1.8
## 2300 3 3 78 grassy 0.0
## 2301 3 3 79 grassy 0.0
## 2302 3 3 79 grassy 0.0
## 2303 3 3 86 grassy 2.1
## 2304 3 3 86 grassy 2.7
## 2305 4 1 3 grassy 0.0
## 2306 4 1 3 grassy 0.0
## 2307 4 1 10 grassy 0.0
## 2308 4 1 10 grassy 0.0
## 2309 4 1 15 grassy 0.4
## 2310 4 1 15 grassy 0.6
## 2311 4 1 16 grassy 1.2
## 2312 4 1 16 grassy 0.4
## 2313 4 1 19 grassy 0.0
## 2314 4 1 19 grassy 11.1
## 2315 4 1 31 grassy 0.0
## 2316 4 1 31 grassy 0.0
## 2317 4 1 51 grassy 0.7
## 2318 4 1 51 grassy 2.1
## 2319 4 1 52 grassy 0.2
## 2320 4 1 52 grassy 1.8
## 2321 4 1 63 grassy 0.0
## 2322 4 1 63 grassy 0.0
## 2323 4 1 78 grassy 1.2
## 2324 4 1 78 grassy 2.3
## 2325 4 1 79 grassy 0.0
## 2326 4 1 79 grassy 0.0
## 2327 4 1 86 grassy 0.0
## 2328 4 1 86 grassy 2.6
## 2329 4 2 3 grassy 0.0
## 2330 4 2 3 grassy 0.0
## 2331 4 2 10 grassy 0.0
## 2332 4 2 10 grassy 0.0
## 2333 4 2 15 grassy 0.0
## 2334 4 2 15 grassy 0.0
## 2335 4 2 16 grassy 2.1
## 2336 4 2 16 grassy 1.1
## 2337 4 2 19 grassy 0.0
## 2338 4 2 19 grassy 1.3
## 2339 4 2 31 grassy 1.0
## 2340 4 2 31 grassy 0.0
## 2341 4 2 51 grassy 3.3
## 2342 4 2 51 grassy 0.7
## 2343 4 2 52 grassy 2.4
## 2344 4 2 52 grassy 2.0
## 2345 4 2 63 grassy 0.0
## 2346 4 2 63 grassy 0.0
## 2347 4 2 78 grassy 0.0
## 2348 4 2 78 grassy 0.0
## 2349 4 2 79 grassy 0.0
## 2350 4 2 79 grassy 0.0
## 2351 4 2 86 grassy 1.5
## 2352 4 2 86 grassy 0.0
## 2353 4 3 3 grassy 0.4
## 2354 4 3 3 grassy 0.0
## 2355 4 3 10 grassy 0.0
## 2356 4 3 10 grassy 0.0
## 2357 4 3 15 grassy 0.3
## 2358 4 3 15 grassy 0.1
## 2359 4 3 16 grassy 2.2
## 2360 4 3 16 grassy 2.8
## 2361 4 3 19 grassy 0.0
## 2362 4 3 19 grassy 0.0
## 2363 4 3 31 grassy 0.0
## 2364 4 3 31 grassy 0.0
## 2365 4 3 51 grassy 0.1
## 2366 4 3 51 grassy 2.7
## 2367 4 3 52 grassy 0.9
## 2368 4 3 52 grassy 1.4
## 2369 4 3 63 grassy 0.0
## 2370 4 3 63 grassy 0.0
## 2371 4 3 78 grassy 0.0
## 2372 4 3 78 grassy 1.1
## 2373 4 3 79 grassy 0.0
## 2374 4 3 79 grassy 0.0
## 2375 4 3 86 grassy 1.4
## 2376 4 3 86 grassy 0.0
## 2377 5 1 3 grassy 0.0
## 2378 5 1 3 grassy 0.0
## 2379 5 1 10 grassy 1.5
## 2380 5 1 10 grassy 2.6
## 2381 5 1 15 grassy 0.3
## 2382 5 1 15 grassy 0.5
## 2383 5 1 16 grassy 2.8
## 2384 5 1 16 grassy 1.4
## 2385 5 1 19 grassy 1.7
## 2386 5 1 19 grassy 3.3
## 2387 5 1 31 grassy 0.4
## 2388 5 1 31 grassy 0.0
## 2389 5 1 51 grassy 0.2
## 2390 5 1 51 grassy 1.0
## 2391 5 1 52 grassy 0.0
## 2392 5 1 52 grassy 0.3
## 2393 5 1 63 grassy 0.0
## 2394 5 1 63 grassy 0.0
## 2395 5 1 78 grassy 1.3
## 2396 5 1 78 grassy 0.0
## 2397 5 1 79 grassy 0.0
## 2398 5 1 79 grassy 0.0
## 2399 5 1 86 grassy 0.0
## 2400 5 1 86 grassy 1.2
## 2401 5 2 3 grassy 0.0
## 2402 5 2 3 grassy 0.0
## 2403 5 2 10 grassy 0.0
## 2404 5 2 10 grassy 0.0
## 2405 5 2 15 grassy 0.2
## 2406 5 2 15 grassy 0.4
## 2407 5 2 16 grassy 0.1
## 2408 5 2 16 grassy 0.2
## 2409 5 2 19 grassy 0.0
## 2410 5 2 19 grassy 0.0
## 2411 5 2 31 grassy 0.5
## 2412 5 2 31 grassy 0.0
## 2413 5 2 51 grassy 0.7
## 2414 5 2 51 grassy 2.2
## 2415 5 2 52 grassy 7.1
## 2416 5 2 52 grassy 0.2
## 2417 5 2 63 grassy 0.0
## 2418 5 2 63 grassy 0.0
## 2419 5 2 78 grassy 0.9
## 2420 5 2 78 grassy 0.0
## 2421 5 2 79 grassy 0.0
## 2422 5 2 79 grassy 0.0
## 2423 5 2 86 grassy 0.0
## 2424 5 2 86 grassy 1.5
## 2425 5 3 3 grassy 0.0
## 2426 5 3 3 grassy 0.0
## 2427 5 3 10 grassy 0.0
## 2428 5 3 10 grassy 0.0
## 2429 5 3 15 grassy NA
## 2430 5 3 15 grassy 0.4
## 2431 5 3 16 grassy 0.5
## 2432 5 3 16 grassy 0.0
## 2433 5 3 19 grassy 0.0
## 2434 5 3 19 grassy 4.2
## 2435 5 3 31 grassy 0.0
## 2436 5 3 31 grassy 0.3
## 2437 5 3 51 grassy 2.5
## 2438 5 3 51 grassy 2.3
## 2439 5 3 52 grassy 0.8
## 2440 5 3 52 grassy 0.0
## 2441 5 3 63 grassy 0.0
## 2442 5 3 63 grassy 0.0
## 2443 5 3 78 grassy 1.6
## 2444 5 3 78 grassy 0.0
## 2445 5 3 79 grassy 0.0
## 2446 5 3 79 grassy 0.0
## 2447 5 3 86 grassy 0.0
## 2448 5 3 86 grassy 0.0
## 2449 6 1 3 grassy 0.0
## 2450 6 1 3 grassy 0.0
## 2451 6 1 10 grassy 0.0
## 2452 6 1 10 grassy 0.0
## 2453 6 1 15 grassy 0.2
## 2454 6 1 15 grassy 1.5
## 2455 6 1 16 grassy 0.3
## 2456 6 1 16 grassy 1.6
## 2457 6 1 19 grassy 0.0
## 2458 6 1 19 grassy 3.8
## 2459 6 1 31 grassy 0.0
## 2460 6 1 31 grassy 0.0
## 2461 6 1 51 grassy 1.7
## 2462 6 1 51 grassy 2.1
## 2463 6 1 52 grassy 0.0
## 2464 6 1 52 grassy 0.0
## 2465 6 1 63 grassy 0.0
## 2466 6 1 63 grassy 0.0
## 2467 6 1 78 grassy 0.0
## 2468 6 1 78 grassy 0.0
## 2469 6 1 79 grassy 0.0
## 2470 6 1 79 grassy 0.0
## 2471 6 1 86 grassy 0.0
## 2472 6 1 86 grassy 0.0
## 2473 6 2 3 grassy 0.0
## 2474 6 2 3 grassy 0.0
## 2475 6 2 10 grassy 0.0
## 2476 6 2 10 grassy 0.0
## 2477 6 2 15 grassy 0.3
## 2478 6 2 15 grassy 0.5
## 2479 6 2 16 grassy 6.6
## 2480 6 2 16 grassy 3.0
## 2481 6 2 19 grassy 2.9
## 2482 6 2 19 grassy 0.0
## 2483 6 2 31 grassy 0.0
## 2484 6 2 31 grassy 1.3
## 2485 6 2 51 grassy 0.0
## 2486 6 2 51 grassy 1.1
## 2487 6 2 52 grassy 1.8
## 2488 6 2 52 grassy 0.8
## 2489 6 2 63 grassy 0.0
## 2490 6 2 63 grassy 0.0
## 2491 6 2 78 grassy 0.0
## 2492 6 2 78 grassy 1.1
## 2493 6 2 79 grassy 0.0
## 2494 6 2 79 grassy 0.0
## 2495 6 2 86 grassy 2.7
## 2496 6 2 86 grassy 0.0
## 2497 6 3 3 grassy 0.0
## 2498 6 3 3 grassy 0.0
## 2499 6 3 10 grassy 0.0
## 2500 6 3 10 grassy 0.0
## 2501 6 3 15 grassy 0.1
## 2502 6 3 15 grassy 0.3
## 2503 6 3 16 grassy 3.1
## 2504 6 3 16 grassy 0.9
## 2505 6 3 19 grassy 0.0
## 2506 6 3 19 grassy 0.0
## 2507 6 3 31 grassy 0.0
## 2508 6 3 31 grassy 2.5
## 2509 6 3 51 grassy 0.9
## 2510 6 3 51 grassy 2.3
## 2511 6 3 52 grassy 0.8
## 2512 6 3 52 grassy 1.1
## 2513 6 3 63 grassy 0.0
## 2514 6 3 63 grassy 0.0
## 2515 6 3 78 grassy 1.5
## 2516 6 3 78 grassy 1.2
## 2517 6 3 79 grassy 0.5
## 2518 6 3 79 grassy 0.0
## 2519 6 3 86 grassy 0.0
## 2520 6 3 86 grassy 0.0
## 2521 7 1 3 grassy 0.0
## 2522 7 1 3 grassy 0.0
## 2523 7 1 10 grassy 0.0
## 2524 7 1 10 grassy 0.0
## 2525 7 1 15 grassy 0.0
## 2526 7 1 15 grassy 0.0
## 2527 7 1 16 grassy 0.4
## 2528 7 1 16 grassy 0.1
## 2529 7 1 19 grassy 0.0
## 2530 7 1 19 grassy 0.0
## 2531 7 1 31 grassy 0.0
## 2532 7 1 31 grassy 0.0
## 2533 7 1 51 grassy 0.1
## 2534 7 1 51 grassy 0.0
## 2535 7 1 52 grassy 1.7
## 2536 7 1 52 grassy 1.6
## 2537 7 1 63 grassy 0.0
## 2538 7 1 63 grassy 0.0
## 2539 7 1 78 grassy 0.0
## 2540 7 1 78 grassy 0.0
## 2541 7 1 79 grassy 0.0
## 2542 7 1 79 grassy 0.0
## 2543 7 1 86 grassy 0.0
## 2544 7 1 86 grassy 0.0
## 2545 7 2 3 grassy 0.0
## 2546 7 2 3 grassy 0.0
## 2547 7 2 10 grassy 0.0
## 2548 7 2 10 grassy 0.0
## 2549 7 2 15 grassy 0.2
## 2550 7 2 15 grassy 0.0
## 2551 7 2 16 grassy 0.0
## 2552 7 2 16 grassy 0.3
## 2553 7 2 19 grassy 0.0
## 2554 7 2 19 grassy 6.7
## 2555 7 2 31 grassy 0.0
## 2556 7 2 31 grassy 0.0
## 2557 7 2 51 grassy 0.0
## 2558 7 2 51 grassy 3.2
## 2559 7 2 52 grassy 1.5
## 2560 7 2 52 grassy 1.3
## 2561 7 2 63 grassy 0.0
## 2562 7 2 63 grassy 0.0
## 2563 7 2 78 grassy 0.0
## 2564 7 2 78 grassy 0.0
## 2565 7 2 79 grassy 0.0
## 2566 7 2 79 grassy 0.0
## 2567 7 2 86 grassy 0.0
## 2568 7 2 86 grassy 0.0
## 2569 7 3 3 grassy 0.0
## 2570 7 3 3 grassy 0.0
## 2571 7 3 10 grassy 0.0
## 2572 7 3 10 grassy 0.0
## 2573 7 3 15 grassy 0.0
## 2574 7 3 15 grassy 0.1
## 2575 7 3 16 grassy 0.0
## 2576 7 3 16 grassy 0.1
## 2577 7 3 19 grassy 0.0
## 2578 7 3 19 grassy 0.0
## 2579 7 3 31 grassy 0.0
## 2580 7 3 31 grassy 0.0
## 2581 7 3 51 grassy 2.9
## 2582 7 3 51 grassy 1.1
## 2583 7 3 52 grassy 1.1
## 2584 7 3 52 grassy 3.7
## 2585 7 3 63 grassy 0.0
## 2586 7 3 63 grassy 0.0
## 2587 7 3 78 grassy 0.0
## 2588 7 3 78 grassy 0.0
## 2589 7 3 79 grassy 0.0
## 2590 7 3 79 grassy 0.0
## 2591 7 3 86 grassy 2.8
## 2592 7 3 86 grassy 1.4
## 2593 8 1 3 grassy 1.3
## 2594 8 1 3 grassy 0.0
## 2595 8 1 10 grassy 0.0
## 2596 8 1 10 grassy 0.0
## 2597 8 1 15 grassy 0.1
## 2598 8 1 15 grassy 0.0
## 2599 8 1 16 grassy 1.8
## 2600 8 1 16 grassy 0.2
## 2601 8 1 19 grassy 0.0
## 2602 8 1 19 grassy 11.1
## 2603 8 1 31 grassy 0.0
## 2604 8 1 31 grassy 0.0
## 2605 8 1 51 grassy 0.7
## 2606 8 1 51 grassy 0.0
## 2607 8 1 52 grassy 0.0
## 2608 8 1 52 grassy 0.0
## 2609 8 1 63 grassy 0.0
## 2610 8 1 63 grassy 0.0
## 2611 8 1 78 grassy 0.0
## 2612 8 1 78 grassy 0.0
## 2613 8 1 79 grassy 0.0
## 2614 8 1 79 grassy 0.0
## 2615 8 1 86 grassy 0.0
## 2616 8 1 86 grassy 0.0
## 2617 8 2 3 grassy 0.0
## 2618 8 2 3 grassy 0.0
## 2619 8 2 10 grassy 0.0
## 2620 8 2 10 grassy 0.0
## 2621 8 2 15 grassy 0.3
## 2622 8 2 15 grassy 0.1
## 2623 8 2 16 grassy 1.4
## 2624 8 2 16 grassy 0.2
## 2625 8 2 19 grassy 0.0
## 2626 8 2 19 grassy 0.0
## 2627 8 2 31 grassy 0.0
## 2628 8 2 31 grassy 0.0
## 2629 8 2 51 grassy 2.0
## 2630 8 2 51 grassy 4.1
## 2631 8 2 52 grassy 0.0
## 2632 8 2 52 grassy 0.0
## 2633 8 2 63 grassy 0.0
## 2634 8 2 63 grassy 0.0
## 2635 8 2 78 grassy 0.0
## 2636 8 2 78 grassy 0.0
## 2637 8 2 79 grassy 0.0
## 2638 8 2 79 grassy 1.4
## 2639 8 2 86 grassy 0.0
## 2640 8 2 86 grassy 0.0
## 2641 8 3 3 grassy 0.0
## 2642 8 3 3 grassy 0.0
## 2643 8 3 10 grassy 0.0
## 2644 8 3 10 grassy 0.0
## 2645 8 3 15 grassy 0.0
## 2646 8 3 15 grassy 0.2
## 2647 8 3 16 grassy 0.5
## 2648 8 3 16 grassy 0.1
## 2649 8 3 19 grassy 0.0
## 2650 8 3 19 grassy 0.0
## 2651 8 3 31 grassy 0.0
## 2652 8 3 31 grassy 0.0
## 2653 8 3 51 grassy 1.9
## 2654 8 3 51 grassy 0.0
## 2655 8 3 52 grassy 0.0
## 2656 8 3 52 grassy 0.0
## 2657 8 3 63 grassy 0.0
## 2658 8 3 63 grassy 0.0
## 2659 8 3 78 grassy 0.0
## 2660 8 3 78 grassy 0.0
## 2661 8 3 79 grassy 0.0
## 2662 8 3 79 grassy 0.0
## 2663 8 3 86 grassy 0.0
## 2664 8 3 86 grassy 0.0
## 2665 9 1 3 grassy 0.0
## 2666 9 1 3 grassy 0.0
## 2667 9 1 10 grassy 0.0
## 2668 9 1 10 grassy 0.0
## 2669 9 1 15 grassy 0.1
## 2670 9 1 15 grassy 0.0
## 2671 9 1 16 grassy 0.1
## 2672 9 1 16 grassy 0.1
## 2673 9 1 19 grassy 0.0
## 2674 9 1 19 grassy 0.0
## 2675 9 1 51 grassy 1.7
## 2676 9 1 51 grassy 0.7
## 2677 9 1 52 grassy 0.0
## 2678 9 1 52 grassy 0.0
## 2679 9 1 63 grassy 0.0
## 2680 9 1 63 grassy 0.0
## 2681 9 1 78 grassy 0.0
## 2682 9 1 78 grassy 0.0
## 2683 9 1 79 grassy 0.0
## 2684 9 1 79 grassy 0.0
## 2685 9 2 3 grassy 0.0
## 2686 9 2 3 grassy 0.0
## 2687 9 2 10 grassy 0.0
## 2688 9 2 10 grassy 0.0
## 2689 9 2 15 grassy 0.2
## 2690 9 2 15 grassy 0.0
## 2691 9 2 16 grassy 0.5
## 2692 9 2 16 grassy 0.0
## 2693 9 2 19 grassy 0.0
## 2694 9 2 19 grassy 0.0
## 2695 9 2 51 grassy 0.0
## 2696 9 2 51 grassy 0.0
## 2697 9 2 52 grassy 0.0
## 2698 9 2 52 grassy 0.0
## 2699 9 2 63 grassy 0.0
## 2700 9 2 63 grassy 0.0
## 2701 9 2 78 grassy 0.0
## 2702 9 2 78 grassy 0.9
## 2703 9 2 79 grassy 0.0
## 2704 9 2 79 grassy 0.0
## 2705 9 3 3 grassy 0.0
## 2706 9 3 3 grassy 0.0
## 2707 9 3 10 grassy 0.0
## 2708 9 3 10 grassy 0.0
## 2709 9 3 15 grassy 0.1
## 2710 9 3 15 grassy 0.0
## 2711 9 3 16 grassy 0.7
## 2712 9 3 16 grassy 2.4
## 2713 9 3 19 grassy 0.0
## 2714 9 3 19 grassy 7.2
## 2715 9 3 51 grassy 1.9
## 2716 9 3 51 grassy 0.0
## 2717 9 3 52 grassy 0.0
## 2718 9 3 52 grassy 0.0
## 2719 9 3 63 grassy 0.0
## 2720 9 3 63 grassy 0.0
## 2721 9 3 78 grassy 0.0
## 2722 9 3 78 grassy 0.0
## 2723 9 3 79 grassy 0.0
## 2724 9 3 79 grassy 0.0
## 2725 10 1 10 grassy 1.6
## 2726 10 1 10 grassy 0.0
## 2727 10 1 15 grassy 0.1
## 2728 10 1 15 grassy 0.1
## 2729 10 1 16 grassy 0.0
## 2730 10 1 16 grassy 0.0
## 2731 10 1 19 grassy 0.0
## 2732 10 1 19 grassy 2.7
## 2733 10 1 31 grassy 0.0
## 2734 10 1 31 grassy 0.0
## 2735 10 1 51 grassy 1.4
## 2736 10 1 51 grassy 2.0
## 2737 10 1 52 grassy 0.0
## 2738 10 1 52 grassy 0.0
## 2739 10 1 63 grassy 0.0
## 2740 10 1 63 grassy 0.0
## 2741 10 1 78 grassy 0.0
## 2742 10 1 78 grassy 1.2
## 2743 10 1 86 grassy 0.0
## 2744 10 1 86 grassy 0.0
## 2745 10 2 10 grassy 2.0
## 2746 10 2 10 grassy 0.0
## 2747 10 2 15 grassy 0.3
## 2748 10 2 15 grassy 0.2
## 2749 10 2 16 grassy 1.2
## 2750 10 2 16 grassy 1.1
## 2751 10 2 19 grassy 1.7
## 2752 10 2 19 grassy 4.2
## 2753 10 2 31 grassy 0.0
## 2754 10 2 31 grassy 0.0
## 2755 10 2 51 grassy 0.8
## 2756 10 2 51 grassy 2.4
## 2757 10 2 52 grassy 0.0
## 2758 10 2 52 grassy 0.0
## 2759 10 2 63 grassy 0.0
## 2760 10 2 63 grassy 0.0
## 2761 10 2 78 grassy 0.0
## 2762 10 2 78 grassy 0.0
## 2763 10 2 86 grassy 0.0
## 2764 10 2 86 grassy 0.0
## 2765 10 3 10 grassy 0.0
## 2766 10 3 10 grassy 0.0
## 2767 10 3 15 grassy 0.1
## 2768 10 3 15 grassy 0.0
## 2769 10 3 16 grassy 1.0
## 2770 10 3 16 grassy 1.6
## 2771 10 3 19 grassy 0.0
## 2772 10 3 19 grassy 4.6
## 2773 10 3 31 grassy 0.0
## 2774 10 3 31 grassy 0.0
## 2775 10 3 51 grassy 0.0
## 2776 10 3 51 grassy 2.0
## 2777 10 3 52 grassy 0.2
## 2778 10 3 52 grassy 0.0
## 2779 10 3 63 grassy 0.0
## 2780 10 3 63 grassy 0.0
## 2781 10 3 78 grassy 0.9
## 2782 10 3 78 grassy 0.0
## 2783 10 3 86 grassy 0.0
## 2784 10 3 86 grassy 0.0
## 2785 1 1 3 rancid 0.0
## 2786 1 1 3 rancid 1.1
## 2787 1 1 10 rancid 0.0
## 2788 1 1 10 rancid 2.2
## 2789 1 1 15 rancid 1.1
## 2790 1 1 15 rancid 1.5
## 2791 1 1 16 rancid 0.1
## 2792 1 1 16 rancid 1.4
## 2793 1 1 19 rancid 4.9
## 2794 1 1 19 rancid 4.3
## 2795 1 1 31 rancid 2.5
## 2796 1 1 31 rancid 5.6
## 2797 1 1 51 rancid 1.4
## 2798 1 1 51 rancid 3.3
## 2799 1 1 52 rancid 8.5
## 2800 1 1 52 rancid 2.8
## 2801 1 1 63 rancid 1.1
## 2802 1 1 63 rancid 12.9
## 2803 1 1 78 rancid 1.1
## 2804 1 1 78 rancid 0.5
## 2805 1 1 79 rancid 2.0
## 2806 1 1 79 rancid 0.0
## 2807 1 1 86 rancid 7.9
## 2808 1 1 86 rancid 0.0
## 2809 1 2 3 rancid 3.9
## 2810 1 2 3 rancid 1.5
## 2811 1 2 10 rancid 0.0
## 2812 1 2 10 rancid 0.0
## 2813 1 2 15 rancid 2.0
## 2814 1 2 15 rancid 1.9
## 2815 1 2 16 rancid 0.2
## 2816 1 2 16 rancid 0.4
## 2817 1 2 19 rancid 0.0
## 2818 1 2 19 rancid 2.5
## 2819 1 2 31 rancid 7.0
## 2820 1 2 31 rancid 0.8
## 2821 1 2 51 rancid 3.3
## 2822 1 2 51 rancid 11.8
## 2823 1 2 52 rancid 0.0
## 2824 1 2 52 rancid 1.7
## 2825 1 2 63 rancid 0.0
## 2826 1 2 63 rancid 0.2
## 2827 1 2 78 rancid 2.0
## 2828 1 2 78 rancid 0.9
## 2829 1 2 79 rancid 0.0
## 2830 1 2 79 rancid 1.1
## 2831 1 2 86 rancid 0.0
## 2832 1 2 86 rancid 0.0
## 2833 1 3 3 rancid 1.1
## 2834 1 3 3 rancid 2.8
## 2835 1 3 10 rancid 0.0
## 2836 1 3 10 rancid 0.0
## 2837 1 3 15 rancid 2.8
## 2838 1 3 15 rancid 0.8
## 2839 1 3 16 rancid 1.4
## 2840 1 3 16 rancid 3.6
## 2841 1 3 19 rancid 4.4
## 2842 1 3 19 rancid 13.2
## 2843 1 3 31 rancid 6.6
## 2844 1 3 31 rancid 8.1
## 2845 1 3 51 rancid 2.1
## 2846 1 3 51 rancid 6.0
## 2847 1 3 52 rancid 1.2
## 2848 1 3 52 rancid 0.0
## 2849 1 3 63 rancid 0.0
## 2850 1 3 63 rancid 0.4
## 2851 1 3 78 rancid 3.6
## 2852 1 3 78 rancid 2.5
## 2853 1 3 79 rancid 0.9
## 2854 1 3 79 rancid 0.9
## 2855 1 3 86 rancid 0.0
## 2856 1 3 86 rancid 0.0
## 2857 2 1 3 rancid 5.8
## 2858 2 1 3 rancid 8.6
## 2859 2 1 10 rancid 6.2
## 2860 2 1 10 rancid 0.0
## 2861 2 1 15 rancid 3.9
## 2862 2 1 15 rancid 3.3
## 2863 2 1 16 rancid 2.8
## 2864 2 1 16 rancid 2.0
## 2865 2 1 19 rancid 12.8
## 2866 2 1 19 rancid 0.0
## 2867 2 1 31 rancid 12.1
## 2868 2 1 31 rancid 11.9
## 2869 2 1 51 rancid 11.1
## 2870 2 1 51 rancid 1.1
## 2871 2 1 52 rancid 1.1
## 2872 2 1 52 rancid 1.0
## 2873 2 1 63 rancid 2.3
## 2874 2 1 63 rancid 1.1
## 2875 2 1 78 rancid 0.0
## 2876 2 1 78 rancid 6.0
## 2877 2 1 79 rancid 0.5
## 2878 2 1 79 rancid 0.0
## 2879 2 1 86 rancid 0.0
## 2880 2 1 86 rancid 0.0
## 2881 2 2 3 rancid 2.1
## 2882 2 2 3 rancid 0.0
## 2883 2 2 10 rancid 0.0
## 2884 2 2 10 rancid 0.0
## 2885 2 2 15 rancid 0.2
## 2886 2 2 15 rancid 3.1
## 2887 2 2 16 rancid 3.0
## 2888 2 2 16 rancid 0.1
## 2889 2 2 19 rancid 6.5
## 2890 2 2 19 rancid 2.0
## 2891 2 2 31 rancid 1.3
## 2892 2 2 31 rancid 10.6
## 2893 2 2 51 rancid 5.7
## 2894 2 2 51 rancid 10.0
## 2895 2 2 52 rancid 0.0
## 2896 2 2 52 rancid 0.0
## 2897 2 2 63 rancid 0.0
## 2898 2 2 63 rancid 0.0
## 2899 2 2 78 rancid 3.8
## 2900 2 2 78 rancid 0.6
## 2901 2 2 79 rancid 1.0
## 2902 2 2 79 rancid 1.4
## 2903 2 2 86 rancid 0.0
## 2904 2 2 86 rancid 0.0
## 2905 2 3 3 rancid 0.1
## 2906 2 3 3 rancid 6.6
## 2907 2 3 10 rancid 10.0
## 2908 2 3 10 rancid 0.0
## 2909 2 3 15 rancid 3.4
## 2910 2 3 15 rancid 0.1
## 2911 2 3 16 rancid 3.7
## 2912 2 3 16 rancid 0.1
## 2913 2 3 19 rancid 1.4
## 2914 2 3 19 rancid 0.0
## 2915 2 3 31 rancid 5.8
## 2916 2 3 31 rancid 9.3
## 2917 2 3 51 rancid 3.1
## 2918 2 3 51 rancid 2.7
## 2919 2 3 52 rancid 0.0
## 2920 2 3 52 rancid 0.0
## 2921 2 3 63 rancid 9.8
## 2922 2 3 63 rancid 0.0
## 2923 2 3 78 rancid 1.2
## 2924 2 3 78 rancid 0.0
## 2925 2 3 79 rancid 2.6
## 2926 2 3 79 rancid 0.0
## 2927 2 3 86 rancid 0.0
## 2928 2 3 86 rancid 0.0
## 2929 3 1 3 rancid 6.0
## 2930 3 1 3 rancid 11.0
## 2931 3 1 10 rancid 2.6
## 2932 3 1 10 rancid 7.7
## 2933 3 1 15 rancid 7.2
## 2934 3 1 15 rancid 3.8
## 2935 3 1 16 rancid 3.8
## 2936 3 1 16 rancid 0.1
## 2937 3 1 19 rancid 12.7
## 2938 3 1 19 rancid 5.2
## 2939 3 1 31 rancid 5.2
## 2940 3 1 31 rancid 10.0
## 2941 3 1 51 rancid 11.0
## 2942 3 1 51 rancid 8.5
## 2943 3 1 52 rancid 0.3
## 2944 3 1 52 rancid 1.0
## 2945 3 1 63 rancid 4.2
## 2946 3 1 63 rancid 0.8
## 2947 3 1 78 rancid 0.0
## 2948 3 1 78 rancid 3.8
## 2949 3 1 79 rancid 0.0
## 2950 3 1 79 rancid 1.6
## 2951 3 1 86 rancid 5.1
## 2952 3 1 86 rancid 0.0
## 2953 3 2 3 rancid 9.2
## 2954 3 2 3 rancid 11.4
## 2955 3 2 10 rancid 0.0
## 2956 3 2 10 rancid 0.0
## 2957 3 2 15 rancid 0.3
## 2958 3 2 15 rancid 1.0
## 2959 3 2 16 rancid 0.0
## 2960 3 2 16 rancid 0.0
## 2961 3 2 19 rancid 0.9
## 2962 3 2 19 rancid 1.4
## 2963 3 2 31 rancid 10.1
## 2964 3 2 31 rancid 9.1
## 2965 3 2 51 rancid 7.5
## 2966 3 2 51 rancid 2.6
## 2967 3 2 52 rancid 0.0
## 2968 3 2 52 rancid 0.0
## 2969 3 2 63 rancid 0.0
## 2970 3 2 63 rancid 5.9
## 2971 3 2 78 rancid 0.0
## 2972 3 2 78 rancid 0.7
## 2973 3 2 79 rancid 0.9
## 2974 3 2 79 rancid 2.6
## 2975 3 2 86 rancid 1.9
## 2976 3 2 86 rancid 4.0
## 2977 3 3 3 rancid 7.1
## 2978 3 3 3 rancid 11.1
## 2979 3 3 10 rancid 0.0
## 2980 3 3 10 rancid 0.0
## 2981 3 3 15 rancid 5.5
## 2982 3 3 15 rancid 1.5
## 2983 3 3 16 rancid 1.0
## 2984 3 3 16 rancid 0.7
## 2985 3 3 19 rancid 4.0
## 2986 3 3 19 rancid 10.8
## 2987 3 3 31 rancid 6.8
## 2988 3 3 31 rancid 7.7
## 2989 3 3 51 rancid 4.4
## 2990 3 3 51 rancid 6.8
## 2991 3 3 52 rancid 0.0
## 2992 3 3 52 rancid 0.0
## 2993 3 3 63 rancid 2.6
## 2994 3 3 63 rancid 6.7
## 2995 3 3 78 rancid 0.0
## 2996 3 3 78 rancid 0.0
## 2997 3 3 79 rancid 0.0
## 2998 3 3 79 rancid 0.7
## 2999 3 3 86 rancid 5.9
## 3000 3 3 86 rancid 3.1
## 3001 4 1 3 rancid 1.7
## 3002 4 1 3 rancid 0.9
## 3003 4 1 10 rancid 6.5
## 3004 4 1 10 rancid 0.0
## 3005 4 1 15 rancid 0.2
## 3006 4 1 15 rancid 0.1
## 3007 4 1 16 rancid 0.1
## 3008 4 1 16 rancid 2.8
## 3009 4 1 19 rancid 0.0
## 3010 4 1 19 rancid 3.2
## 3011 4 1 31 rancid 5.1
## 3012 4 1 31 rancid 3.7
## 3013 4 1 51 rancid 8.8
## 3014 4 1 51 rancid 2.7
## 3015 4 1 52 rancid 0.0
## 3016 4 1 52 rancid 0.0
## 3017 4 1 63 rancid 3.0
## 3018 4 1 63 rancid 1.7
## 3019 4 1 78 rancid 3.2
## 3020 4 1 78 rancid 0.0
## 3021 4 1 79 rancid 0.0
## 3022 4 1 79 rancid 1.4
## 3023 4 1 86 rancid 0.0
## 3024 4 1 86 rancid 4.8
## 3025 4 2 3 rancid 1.3
## 3026 4 2 3 rancid 0.8
## 3027 4 2 10 rancid 4.3
## 3028 4 2 10 rancid 1.4
## 3029 4 2 15 rancid 1.8
## 3030 4 2 15 rancid 0.2
## 3031 4 2 16 rancid 4.7
## 3032 4 2 16 rancid 2.5
## 3033 4 2 19 rancid 10.8
## 3034 4 2 19 rancid 9.7
## 3035 4 2 31 rancid 5.0
## 3036 4 2 31 rancid 6.0
## 3037 4 2 51 rancid 4.5
## 3038 4 2 51 rancid 0.1
## 3039 4 2 52 rancid 3.1
## 3040 4 2 52 rancid 0.5
## 3041 4 2 63 rancid 9.3
## 3042 4 2 63 rancid 4.0
## 3043 4 2 78 rancid 0.0
## 3044 4 2 78 rancid 0.0
## 3045 4 2 79 rancid 2.7
## 3046 4 2 79 rancid 0.0
## 3047 4 2 86 rancid 5.2
## 3048 4 2 86 rancid 6.4
## 3049 4 3 3 rancid 7.8
## 3050 4 3 3 rancid 1.3
## 3051 4 3 10 rancid 0.0
## 3052 4 3 10 rancid 5.7
## 3053 4 3 15 rancid 2.0
## 3054 4 3 15 rancid 2.9
## 3055 4 3 16 rancid 4.1
## 3056 4 3 16 rancid 5.8
## 3057 4 3 19 rancid 6.5
## 3058 4 3 19 rancid 6.4
## 3059 4 3 31 rancid 2.7
## 3060 4 3 31 rancid 7.9
## 3061 4 3 51 rancid 12.9
## 3062 4 3 51 rancid 7.2
## 3063 4 3 52 rancid 5.6
## 3064 4 3 52 rancid 6.4
## 3065 4 3 63 rancid 13.3
## 3066 4 3 63 rancid 11.2
## 3067 4 3 78 rancid 0.0
## 3068 4 3 78 rancid 2.7
## 3069 4 3 79 rancid 2.5
## 3070 4 3 79 rancid 1.0
## 3071 4 3 86 rancid 4.7
## 3072 4 3 86 rancid 4.6
## 3073 5 1 3 rancid 0.0
## 3074 5 1 3 rancid 2.8
## 3075 5 1 10 rancid 10.2
## 3076 5 1 10 rancid 9.3
## 3077 5 1 15 rancid 4.9
## 3078 5 1 15 rancid 2.5
## 3079 5 1 16 rancid 10.2
## 3080 5 1 16 rancid 7.5
## 3081 5 1 19 rancid 11.5
## 3082 5 1 19 rancid 0.9
## 3083 5 1 31 rancid 1.1
## 3084 5 1 31 rancid 2.5
## 3085 5 1 51 rancid 9.5
## 3086 5 1 51 rancid 7.1
## 3087 5 1 52 rancid 6.5
## 3088 5 1 52 rancid 7.1
## 3089 5 1 63 rancid 2.0
## 3090 5 1 63 rancid 1.3
## 3091 5 1 78 rancid 0.0
## 3092 5 1 78 rancid 1.1
## 3093 5 1 79 rancid 0.0
## 3094 5 1 79 rancid 0.0
## 3095 5 1 86 rancid 2.7
## 3096 5 1 86 rancid 2.0
## 3097 5 2 3 rancid 3.2
## 3098 5 2 3 rancid 4.0
## 3099 5 2 10 rancid 3.5
## 3100 5 2 10 rancid 7.1
## 3101 5 2 15 rancid 0.8
## 3102 5 2 15 rancid 4.7
## 3103 5 2 16 rancid 0.9
## 3104 5 2 16 rancid 0.7
## 3105 5 2 19 rancid 1.1
## 3106 5 2 19 rancid 13.4
## 3107 5 2 31 rancid 2.1
## 3108 5 2 31 rancid 1.5
## 3109 5 2 51 rancid 9.5
## 3110 5 2 51 rancid 0.1
## 3111 5 2 52 rancid 3.9
## 3112 5 2 52 rancid 7.7
## 3113 5 2 63 rancid 13.8
## 3114 5 2 63 rancid 3.2
## 3115 5 2 78 rancid 0.0
## 3116 5 2 78 rancid 0.0
## 3117 5 2 79 rancid 0.0
## 3118 5 2 79 rancid 0.0
## 3119 5 2 86 rancid 3.5
## 3120 5 2 86 rancid 2.7
## 3121 5 3 3 rancid 4.6
## 3122 5 3 3 rancid 0.0
## 3123 5 3 10 rancid 0.0
## 3124 5 3 10 rancid 0.0
## 3125 5 3 15 rancid NA
## 3126 5 3 15 rancid 4.6
## 3127 5 3 16 rancid 0.0
## 3128 5 3 16 rancid 0.5
## 3129 5 3 19 rancid 0.0
## 3130 5 3 19 rancid 11.1
## 3131 5 3 31 rancid 9.8
## 3132 5 3 31 rancid 2.6
## 3133 5 3 51 rancid 1.7
## 3134 5 3 51 rancid 4.6
## 3135 5 3 52 rancid 2.1
## 3136 5 3 52 rancid 1.4
## 3137 5 3 63 rancid 0.0
## 3138 5 3 63 rancid 5.3
## 3139 5 3 78 rancid 1.5
## 3140 5 3 78 rancid 0.0
## 3141 5 3 79 rancid 1.6
## 3142 5 3 79 rancid 0.6
## 3143 5 3 86 rancid 3.0
## 3144 5 3 86 rancid 5.5
## 3145 6 1 3 rancid 0.0
## 3146 6 1 3 rancid 0.0
## 3147 6 1 10 rancid 2.4
## 3148 6 1 10 rancid 0.0
## 3149 6 1 15 rancid 2.9
## 3150 6 1 15 rancid 7.1
## 3151 6 1 16 rancid 7.4
## 3152 6 1 16 rancid 7.4
## 3153 6 1 19 rancid 4.1
## 3154 6 1 19 rancid 7.2
## 3155 6 1 31 rancid 0.6
## 3156 6 1 31 rancid 4.3
## 3157 6 1 51 rancid 1.6
## 3158 6 1 51 rancid 7.9
## 3159 6 1 52 rancid 9.4
## 3160 6 1 52 rancid 8.3
## 3161 6 1 63 rancid 9.5
## 3162 6 1 63 rancid 9.5
## 3163 6 1 78 rancid 2.1
## 3164 6 1 78 rancid 0.0
## 3165 6 1 79 rancid 0.0
## 3166 6 1 79 rancid 0.4
## 3167 6 1 86 rancid 6.4
## 3168 6 1 86 rancid 5.6
## 3169 6 2 3 rancid 10.2
## 3170 6 2 3 rancid 0.0
## 3171 6 2 10 rancid 0.0
## 3172 6 2 10 rancid 0.0
## 3173 6 2 15 rancid 1.4
## 3174 6 2 15 rancid 1.2
## 3175 6 2 16 rancid 9.5
## 3176 6 2 16 rancid 11.7
## 3177 6 2 19 rancid 0.0
## 3178 6 2 19 rancid 11.5
## 3179 6 2 31 rancid 0.4
## 3180 6 2 31 rancid 10.5
## 3181 6 2 51 rancid 5.5
## 3182 6 2 51 rancid 5.2
## 3183 6 2 52 rancid 4.2
## 3184 6 2 52 rancid 6.3
## 3185 6 2 63 rancid 2.8
## 3186 6 2 63 rancid 2.8
## 3187 6 2 78 rancid 1.7
## 3188 6 2 78 rancid 0.0
## 3189 6 2 79 rancid 1.1
## 3190 6 2 79 rancid 0.5
## 3191 6 2 86 rancid 0.0
## 3192 6 2 86 rancid 5.7
## 3193 6 3 3 rancid 8.9
## 3194 6 3 3 rancid 0.0
## 3195 6 3 10 rancid 0.0
## 3196 6 3 10 rancid 6.8
## 3197 6 3 15 rancid 2.4
## 3198 6 3 15 rancid 0.6
## 3199 6 3 16 rancid 9.8
## 3200 6 3 16 rancid 3.2
## 3201 6 3 19 rancid 0.0
## 3202 6 3 19 rancid 13.0
## 3203 6 3 31 rancid 3.8
## 3204 6 3 31 rancid 7.2
## 3205 6 3 51 rancid 5.4
## 3206 6 3 51 rancid 5.9
## 3207 6 3 52 rancid 6.3
## 3208 6 3 52 rancid 5.2
## 3209 6 3 63 rancid 4.7
## 3210 6 3 63 rancid 2.8
## 3211 6 3 78 rancid 1.8
## 3212 6 3 78 rancid 0.0
## 3213 6 3 79 rancid 1.0
## 3214 6 3 79 rancid 1.1
## 3215 6 3 86 rancid 2.8
## 3216 6 3 86 rancid 4.4
## 3217 7 1 3 rancid 0.0
## 3218 7 1 3 rancid 0.0
## 3219 7 1 10 rancid 0.0
## 3220 7 1 10 rancid 5.1
## 3221 7 1 15 rancid 1.1
## 3222 7 1 15 rancid 5.5
## 3223 7 1 16 rancid 0.1
## 3224 7 1 16 rancid 0.0
## 3225 7 1 19 rancid 4.9
## 3226 7 1 19 rancid 0.0
## 3227 7 1 31 rancid 2.5
## 3228 7 1 31 rancid 5.6
## 3229 7 1 51 rancid 1.4
## 3230 7 1 51 rancid 4.5
## 3231 7 1 52 rancid 8.5
## 3232 7 1 52 rancid 9.5
## 3233 7 1 63 rancid 1.1
## 3234 7 1 63 rancid 5.1
## 3235 7 1 78 rancid 1.1
## 3236 7 1 78 rancid 0.0
## 3237 7 1 79 rancid 2.0
## 3238 7 1 79 rancid 0.0
## 3239 7 1 86 rancid 7.9
## 3240 7 1 86 rancid 11.0
## 3241 7 2 3 rancid 0.0
## 3242 7 2 3 rancid 0.0
## 3243 7 2 10 rancid 0.0
## 3244 7 2 10 rancid 6.1
## 3245 7 2 15 rancid 1.3
## 3246 7 2 15 rancid 3.4
## 3247 7 2 16 rancid 1.5
## 3248 7 2 16 rancid 0.2
## 3249 7 2 19 rancid 6.6
## 3250 7 2 19 rancid 10.9
## 3251 7 2 31 rancid 6.0
## 3252 7 2 31 rancid 8.5
## 3253 7 2 51 rancid 5.0
## 3254 7 2 51 rancid 0.0
## 3255 7 2 52 rancid 8.8
## 3256 7 2 52 rancid 10.5
## 3257 7 2 63 rancid 3.2
## 3258 7 2 63 rancid 0.3
## 3259 7 2 78 rancid 1.9
## 3260 7 2 78 rancid 0.0
## 3261 7 2 79 rancid 0.7
## 3262 7 2 79 rancid 2.0
## 3263 7 2 86 rancid 10.1
## 3264 7 2 86 rancid 5.1
## 3265 7 3 3 rancid 0.0
## 3266 7 3 3 rancid 0.0
## 3267 7 3 10 rancid 7.4
## 3268 7 3 10 rancid 3.9
## 3269 7 3 15 rancid 5.4
## 3270 7 3 15 rancid 3.1
## 3271 7 3 16 rancid 0.6
## 3272 7 3 16 rancid 1.2
## 3273 7 3 19 rancid 10.4
## 3274 7 3 19 rancid 13.0
## 3275 7 3 31 rancid 5.0
## 3276 7 3 31 rancid 11.3
## 3277 7 3 51 rancid 8.4
## 3278 7 3 51 rancid 4.5
## 3279 7 3 52 rancid 7.0
## 3280 7 3 52 rancid 6.0
## 3281 7 3 63 rancid 1.4
## 3282 7 3 63 rancid 8.1
## 3283 7 3 78 rancid 3.4
## 3284 7 3 78 rancid 1.0
## 3285 7 3 79 rancid 0.7
## 3286 7 3 79 rancid 1.5
## 3287 7 3 86 rancid 0.0
## 3288 7 3 86 rancid 7.5
## 3289 8 1 3 rancid 0.0
## 3290 8 1 3 rancid 0.0
## 3291 8 1 10 rancid 5.2
## 3292 8 1 10 rancid 8.6
## 3293 8 1 15 rancid 3.9
## 3294 8 1 15 rancid 6.2
## 3295 8 1 16 rancid 9.7
## 3296 8 1 16 rancid 2.4
## 3297 8 1 19 rancid 2.1
## 3298 8 1 19 rancid 10.0
## 3299 8 1 31 rancid 10.0
## 3300 8 1 31 rancid 10.8
## 3301 8 1 51 rancid 1.0
## 3302 8 1 51 rancid 1.0
## 3303 8 1 52 rancid 4.9
## 3304 8 1 52 rancid 3.3
## 3305 8 1 63 rancid 12.4
## 3306 8 1 63 rancid 10.5
## 3307 8 1 78 rancid 0.0
## 3308 8 1 78 rancid 7.2
## 3309 8 1 79 rancid 0.5
## 3310 8 1 79 rancid 0.0
## 3311 8 1 86 rancid 11.6
## 3312 8 1 86 rancid 8.0
## 3313 8 2 3 rancid 0.0
## 3314 8 2 3 rancid 0.0
## 3315 8 2 10 rancid 0.0
## 3316 8 2 10 rancid 2.6
## 3317 8 2 15 rancid 1.0
## 3318 8 2 15 rancid 3.1
## 3319 8 2 16 rancid 6.7
## 3320 8 2 16 rancid 1.5
## 3321 8 2 19 rancid 4.1
## 3322 8 2 19 rancid 0.0
## 3323 8 2 31 rancid 3.9
## 3324 8 2 31 rancid 5.5
## 3325 8 2 51 rancid 1.2
## 3326 8 2 51 rancid 4.8
## 3327 8 2 52 rancid 8.2
## 3328 8 2 52 rancid 0.5
## 3329 8 2 63 rancid 11.4
## 3330 8 2 63 rancid 8.6
## 3331 8 2 78 rancid 3.0
## 3332 8 2 78 rancid 7.2
## 3333 8 2 79 rancid 1.0
## 3334 8 2 79 rancid 2.3
## 3335 8 2 86 rancid 8.8
## 3336 8 2 86 rancid 6.4
## 3337 8 3 3 rancid 0.0
## 3338 8 3 3 rancid 0.0
## 3339 8 3 10 rancid 1.0
## 3340 8 3 10 rancid 6.4
## 3341 8 3 15 rancid 0.6
## 3342 8 3 15 rancid 2.0
## 3343 8 3 16 rancid 7.8
## 3344 8 3 16 rancid 0.3
## 3345 8 3 19 rancid 0.0
## 3346 8 3 19 rancid 12.6
## 3347 8 3 31 rancid 6.8
## 3348 8 3 31 rancid 2.0
## 3349 8 3 51 rancid 0.1
## 3350 8 3 51 rancid 3.0
## 3351 8 3 52 rancid 3.2
## 3352 8 3 52 rancid 10.1
## 3353 8 3 63 rancid 6.6
## 3354 8 3 63 rancid 4.2
## 3355 8 3 78 rancid 0.0
## 3356 8 3 78 rancid 0.7
## 3357 8 3 79 rancid 0.5
## 3358 8 3 79 rancid 1.4
## 3359 8 3 86 rancid 10.8
## 3360 8 3 86 rancid 6.4
## 3361 9 1 3 rancid 0.0
## 3362 9 1 3 rancid 0.0
## 3363 9 1 10 rancid 2.6
## 3364 9 1 10 rancid 2.4
## 3365 9 1 15 rancid 5.5
## 3366 9 1 15 rancid 0.4
## 3367 9 1 16 rancid 6.9
## 3368 9 1 16 rancid 0.1
## 3369 9 1 19 rancid 9.6
## 3370 9 1 19 rancid 2.5
## 3371 9 1 51 rancid 9.9
## 3372 9 1 51 rancid 3.3
## 3373 9 1 52 rancid 3.9
## 3374 9 1 52 rancid 3.4
## 3375 9 1 63 rancid 13.3
## 3376 9 1 63 rancid 9.4
## 3377 9 1 78 rancid 4.0
## 3378 9 1 78 rancid 0.0
## 3379 9 1 79 rancid 0.2
## 3380 9 1 79 rancid 1.6
## 3381 9 2 3 rancid 8.9
## 3382 9 2 3 rancid 0.0
## 3383 9 2 10 rancid 8.0
## 3384 9 2 10 rancid 0.0
## 3385 9 2 15 rancid 3.0
## 3386 9 2 15 rancid 4.5
## 3387 9 2 16 rancid 7.9
## 3388 9 2 16 rancid 0.0
## 3389 9 2 19 rancid 8.1
## 3390 9 2 19 rancid 7.9
## 3391 9 2 51 rancid 14.9
## 3392 9 2 51 rancid 0.0
## 3393 9 2 52 rancid 9.6
## 3394 9 2 52 rancid 5.0
## 3395 9 2 63 rancid 13.7
## 3396 9 2 63 rancid 8.0
## 3397 9 2 78 rancid 4.0
## 3398 9 2 78 rancid 0.0
## 3399 9 2 79 rancid 0.0
## 3400 9 2 79 rancid 1.3
## 3401 9 3 3 rancid 0.0
## 3402 9 3 3 rancid 0.0
## 3403 9 3 10 rancid 3.7
## 3404 9 3 10 rancid 8.6
## 3405 9 3 15 rancid 3.4
## 3406 9 3 15 rancid 2.6
## 3407 9 3 16 rancid 6.6
## 3408 9 3 16 rancid 0.9
## 3409 9 3 19 rancid 13.1
## 3410 9 3 19 rancid 9.8
## 3411 9 3 51 rancid 4.0
## 3412 9 3 51 rancid 8.7
## 3413 9 3 52 rancid 4.7
## 3414 9 3 52 rancid 0.0
## 3415 9 3 63 rancid 11.7
## 3416 9 3 63 rancid 11.6
## 3417 9 3 78 rancid 2.8
## 3418 9 3 78 rancid 0.0
## 3419 9 3 79 rancid 3.8
## 3420 9 3 79 rancid 0.4
## 3421 10 1 10 rancid 5.4
## 3422 10 1 10 rancid 4.0
## 3423 10 1 15 rancid 10.8
## 3424 10 1 15 rancid 7.4
## 3425 10 1 16 rancid 9.1
## 3426 10 1 16 rancid 8.5
## 3427 10 1 19 rancid 2.7
## 3428 10 1 19 rancid 8.6
## 3429 10 1 31 rancid 10.7
## 3430 10 1 31 rancid 2.8
## 3431 10 1 51 rancid 5.2
## 3432 10 1 51 rancid 2.7
## 3433 10 1 52 rancid 1.6
## 3434 10 1 52 rancid 4.6
## 3435 10 1 63 rancid 11.1
## 3436 10 1 63 rancid 8.8
## 3437 10 1 78 rancid 0.0
## 3438 10 1 78 rancid 0.0
## 3439 10 1 86 rancid 11.6
## 3440 10 1 86 rancid 14.3
## 3441 10 2 10 rancid 1.6
## 3442 10 2 10 rancid 8.4
## 3443 10 2 15 rancid 2.5
## 3444 10 2 15 rancid 8.3
## 3445 10 2 16 rancid 7.2
## 3446 10 2 16 rancid 9.3
## 3447 10 2 19 rancid 5.7
## 3448 10 2 19 rancid 5.0
## 3449 10 2 31 rancid 10.3
## 3450 10 2 31 rancid 10.3
## 3451 10 2 51 rancid 0.0
## 3452 10 2 51 rancid 1.7
## 3453 10 2 52 rancid 3.8
## 3454 10 2 52 rancid 10.7
## 3455 10 2 63 rancid 7.9
## 3456 10 2 63 rancid 6.7
## 3457 10 2 78 rancid 4.1
## 3458 10 2 78 rancid 1.1
## 3459 10 2 86 rancid 10.4
## 3460 10 2 86 rancid 11.2
## 3461 10 3 10 rancid 3.3
## 3462 10 3 10 rancid 5.4
## 3463 10 3 15 rancid 2.6
## 3464 10 3 15 rancid 2.1
## 3465 10 3 16 rancid 6.7
## 3466 10 3 16 rancid 6.0
## 3467 10 3 19 rancid 5.8
## 3468 10 3 19 rancid 9.3
## 3469 10 3 31 rancid 9.3
## 3470 10 3 31 rancid 5.7
## 3471 10 3 51 rancid 6.8
## 3472 10 3 51 rancid 0.0
## 3473 10 3 52 rancid 1.4
## 3474 10 3 52 rancid 2.6
## 3475 10 3 63 rancid 11.9
## 3476 10 3 63 rancid 11.4
## 3477 10 3 78 rancid 0.0
## 3478 10 3 78 rancid 2.5
## 3479 10 3 86 rancid 7.0
## 3480 10 3 86 rancid 8.2
## 3481 1 1 3 painty 5.5
## 3482 1 1 3 painty 0.0
## 3483 1 1 10 painty 0.0
## 3484 1 1 10 painty 0.0
## 3485 1 1 15 painty 5.1
## 3486 1 1 15 painty 2.3
## 3487 1 1 16 painty 0.2
## 3488 1 1 16 painty 4.0
## 3489 1 1 19 painty 3.2
## 3490 1 1 19 painty 10.3
## 3491 1 1 31 painty 2.0
## 3492 1 1 31 painty 0.0
## 3493 1 1 51 painty 0.1
## 3494 1 1 51 painty 4.0
## 3495 1 1 52 painty 1.1
## 3496 1 1 52 painty 0.5
## 3497 1 1 63 painty 0.4
## 3498 1 1 63 painty 3.4
## 3499 1 1 78 painty 3.5
## 3500 1 1 78 painty 1.1
## 3501 1 1 79 painty 0.0
## 3502 1 1 79 painty 0.0
## 3503 1 1 86 painty 4.9
## 3504 1 1 86 painty 0.0
## 3505 1 2 3 painty 0.0
## 3506 1 2 3 painty 0.0
## 3507 1 2 10 painty 0.0
## 3508 1 2 10 painty 0.0
## 3509 1 2 15 painty 0.3
## 3510 1 2 15 painty 1.0
## 3511 1 2 16 painty 0.1
## 3512 1 2 16 painty 0.0
## 3513 1 2 19 painty 0.0
## 3514 1 2 19 painty 0.0
## 3515 1 2 31 painty 2.2
## 3516 1 2 31 painty 3.5
## 3517 1 2 51 painty 3.9
## 3518 1 2 51 painty 3.5
## 3519 1 2 52 painty 0.0
## 3520 1 2 52 painty 0.0
## 3521 1 2 63 painty 0.0
## 3522 1 2 63 painty 0.0
## 3523 1 2 78 painty 4.1
## 3524 1 2 78 painty 0.8
## 3525 1 2 79 painty 0.0
## 3526 1 2 79 painty 0.0
## 3527 1 2 86 painty 0.0
## 3528 1 2 86 painty 0.0
## 3529 1 3 3 painty 0.0
## 3530 1 3 3 painty 0.0
## 3531 1 3 10 painty 0.0
## 3532 1 3 10 painty 0.0
## 3533 1 3 15 painty 0.6
## 3534 1 3 15 painty 0.6
## 3535 1 3 16 painty 0.0
## 3536 1 3 16 painty 0.6
## 3537 1 3 19 painty 0.0
## 3538 1 3 19 painty 3.0
## 3539 1 3 31 painty 9.2
## 3540 1 3 31 painty 9.2
## 3541 1 3 51 painty 0.0
## 3542 1 3 51 painty 6.1
## 3543 1 3 52 painty 0.0
## 3544 1 3 52 painty 0.0
## 3545 1 3 63 painty 0.0
## 3546 1 3 63 painty 0.0
## 3547 1 3 78 painty 9.3
## 3548 1 3 78 painty 8.9
## 3549 1 3 79 painty 0.0
## 3550 1 3 79 painty 0.0
## 3551 1 3 86 painty 0.0
## 3552 1 3 86 painty 0.0
## 3553 2 1 3 painty 0.3
## 3554 2 1 3 painty 0.0
## 3555 2 1 10 painty 1.7
## 3556 2 1 10 painty 0.0
## 3557 2 1 15 painty 6.5
## 3558 2 1 15 painty 0.5
## 3559 2 1 16 painty 0.0
## 3560 2 1 16 painty 0.4
## 3561 2 1 19 painty 11.3
## 3562 2 1 19 painty 0.0
## 3563 2 1 31 painty 1.1
## 3564 2 1 31 painty 7.6
## 3565 2 1 51 painty 2.8
## 3566 2 1 51 painty 0.0
## 3567 2 1 52 painty 0.0
## 3568 2 1 52 painty 0.0
## 3569 2 1 63 painty 0.0
## 3570 2 1 63 painty 0.0
## 3571 2 1 78 painty 6.3
## 3572 2 1 78 painty 8.9
## 3573 2 1 79 painty 0.0
## 3574 2 1 79 painty 0.0
## 3575 2 1 86 painty 0.0
## 3576 2 1 86 painty 0.0
## 3577 2 2 3 painty 0.0
## 3578 2 2 3 painty 1.0
## 3579 2 2 10 painty 0.0
## 3580 2 2 10 painty 0.0
## 3581 2 2 15 painty 0.0
## 3582 2 2 15 painty 0.6
## 3583 2 2 16 painty 0.0
## 3584 2 2 16 painty 0.0
## 3585 2 2 19 painty 0.0
## 3586 2 2 19 painty 0.0
## 3587 2 2 31 painty 0.0
## 3588 2 2 31 painty 3.6
## 3589 2 2 51 painty 5.4
## 3590 2 2 51 painty 0.1
## 3591 2 2 52 painty 0.0
## 3592 2 2 52 painty 0.0
## 3593 2 2 63 painty 0.0
## 3594 2 2 63 painty 0.0
## 3595 2 2 78 painty 2.1
## 3596 2 2 78 painty 3.1
## 3597 2 2 79 painty 0.0
## 3598 2 2 79 painty 0.0
## 3599 2 2 86 painty 0.0
## 3600 2 2 86 painty 0.0
## 3601 2 3 3 painty 1.4
## 3602 2 3 3 painty 0.4
## 3603 2 3 10 painty 5.3
## 3604 2 3 10 painty 0.0
## 3605 2 3 15 painty 0.2
## 3606 2 3 15 painty 0.4
## 3607 2 3 16 painty 0.1
## 3608 2 3 16 painty 0.0
## 3609 2 3 19 painty 0.0
## 3610 2 3 19 painty 0.0
## 3611 2 3 31 painty 6.3
## 3612 2 3 31 painty 5.4
## 3613 2 3 51 painty 3.9
## 3614 2 3 51 painty 5.7
## 3615 2 3 52 painty 0.0
## 3616 2 3 52 painty 0.0
## 3617 2 3 63 painty 1.8
## 3618 2 3 63 painty 1.4
## 3619 2 3 78 painty 1.3
## 3620 2 3 78 painty 7.1
## 3621 2 3 79 painty 0.0
## 3622 2 3 79 painty 0.0
## 3623 2 3 86 painty 0.0
## 3624 2 3 86 painty 0.0
## 3625 3 1 3 painty 0.0
## 3626 3 1 3 painty 0.0
## 3627 3 1 10 painty 3.8
## 3628 3 1 10 painty 0.0
## 3629 3 1 15 painty 2.6
## 3630 3 1 15 painty 0.0
## 3631 3 1 16 painty 1.7
## 3632 3 1 16 painty 0.0
## 3633 3 1 19 painty 2.5
## 3634 3 1 19 painty 0.0
## 3635 3 1 31 painty 0.0
## 3636 3 1 31 painty 4.8
## 3637 3 1 51 painty 0.1
## 3638 3 1 51 painty 0.0
## 3639 3 1 52 painty 0.0
## 3640 3 1 52 painty 0.0
## 3641 3 1 63 painty 3.6
## 3642 3 1 63 painty 0.0
## 3643 3 1 78 painty 6.0
## 3644 3 1 78 painty 1.7
## 3645 3 1 79 painty 0.0
## 3646 3 1 79 painty 0.0
## 3647 3 1 86 painty 0.0
## 3648 3 1 86 painty 0.0
## 3649 3 2 3 painty 0.0
## 3650 3 2 3 painty 0.0
## 3651 3 2 10 painty 0.0
## 3652 3 2 10 painty 0.0
## 3653 3 2 15 painty 0.1
## 3654 3 2 15 painty 0.0
## 3655 3 2 16 painty 0.0
## 3656 3 2 16 painty 0.0
## 3657 3 2 19 painty 1.4
## 3658 3 2 19 painty 9.4
## 3659 3 2 31 painty 8.2
## 3660 3 2 31 painty 8.2
## 3661 3 2 51 painty 2.9
## 3662 3 2 51 painty 0.0
## 3663 3 2 52 painty 0.0
## 3664 3 2 52 painty 0.0
## 3665 3 2 63 painty 0.0
## 3666 3 2 63 painty 0.0
## 3667 3 2 78 painty 2.5
## 3668 3 2 78 painty 4.8
## 3669 3 2 79 painty 0.0
## 3670 3 2 79 painty 0.0
## 3671 3 2 86 painty 0.0
## 3672 3 2 86 painty 0.0
## 3673 3 3 3 painty 0.0
## 3674 3 3 3 painty 0.0
## 3675 3 3 10 painty 0.0
## 3676 3 3 10 painty 0.0
## 3677 3 3 15 painty 0.5
## 3678 3 3 15 painty 0.9
## 3679 3 3 16 painty 0.0
## 3680 3 3 16 painty 0.8
## 3681 3 3 19 painty 0.0
## 3682 3 3 19 painty 0.0
## 3683 3 3 31 painty 0.0
## 3684 3 3 31 painty 9.1
## 3685 3 3 51 painty 5.1
## 3686 3 3 51 painty 3.5
## 3687 3 3 52 painty 0.0
## 3688 3 3 52 painty 0.0
## 3689 3 3 63 painty 0.0
## 3690 3 3 63 painty 0.0
## 3691 3 3 78 painty 0.8
## 3692 3 3 78 painty 6.5
## 3693 3 3 79 painty 0.0
## 3694 3 3 79 painty 0.0
## 3695 3 3 86 painty 2.9
## 3696 3 3 86 painty 0.0
## 3697 4 1 3 painty 0.0
## 3698 4 1 3 painty 0.0
## 3699 4 1 10 painty 1.1
## 3700 4 1 10 painty 0.0
## 3701 4 1 15 painty 0.0
## 3702 4 1 15 painty 0.0
## 3703 4 1 16 painty 0.0
## 3704 4 1 16 painty 0.0
## 3705 4 1 19 painty 0.0
## 3706 4 1 19 painty 0.0
## 3707 4 1 31 painty 0.9
## 3708 4 1 31 painty 0.0
## 3709 4 1 51 painty 9.2
## 3710 4 1 51 painty 0.0
## 3711 4 1 52 painty 0.0
## 3712 4 1 52 painty 0.0
## 3713 4 1 63 painty 0.0
## 3714 4 1 63 painty 0.0
## 3715 4 1 78 painty 0.0
## 3716 4 1 78 painty 0.0
## 3717 4 1 79 painty 0.0
## 3718 4 1 79 painty 0.0
## 3719 4 1 86 painty 0.0
## 3720 4 1 86 painty 0.0
## 3721 4 2 3 painty 0.0
## 3722 4 2 3 painty 0.0
## 3723 4 2 10 painty 0.0
## 3724 4 2 10 painty 0.0
## 3725 4 2 15 painty 0.0
## 3726 4 2 15 painty 0.1
## 3727 4 2 16 painty 0.0
## 3728 4 2 16 painty 0.0
## 3729 4 2 19 painty 4.4
## 3730 4 2 19 painty 5.4
## 3731 4 2 31 painty 8.6
## 3732 4 2 31 painty 6.6
## 3733 4 2 51 painty 7.4
## 3734 4 2 51 painty 4.2
## 3735 4 2 52 painty 0.0
## 3736 4 2 52 painty 0.0
## 3737 4 2 63 painty 2.1
## 3738 4 2 63 painty 0.8
## 3739 4 2 78 painty 1.6
## 3740 4 2 78 painty 3.4
## 3741 4 2 79 painty 0.0
## 3742 4 2 79 painty 0.0
## 3743 4 2 86 painty 0.0
## 3744 4 2 86 painty 0.0
## 3745 4 3 3 painty 0.0
## 3746 4 3 3 painty 0.0
## 3747 4 3 10 painty 0.0
## 3748 4 3 10 painty 0.0
## 3749 4 3 15 painty 0.0
## 3750 4 3 15 painty 0.0
## 3751 4 3 16 painty 1.0
## 3752 4 3 16 painty 1.0
## 3753 4 3 19 painty 0.0
## 3754 4 3 19 painty 0.0
## 3755 4 3 31 painty 3.1
## 3756 4 3 31 painty 2.6
## 3757 4 3 51 painty 0.0
## 3758 4 3 51 painty 5.3
## 3759 4 3 52 painty 0.0
## 3760 4 3 52 painty 0.0
## 3761 4 3 63 painty 4.4
## 3762 4 3 63 painty 3.4
## 3763 4 3 78 painty 5.6
## 3764 4 3 78 painty 6.2
## 3765 4 3 79 painty 0.0
## 3766 4 3 79 painty 0.0
## 3767 4 3 86 painty 5.7
## 3768 4 3 86 painty 4.7
## 3769 5 1 3 painty 1.7
## 3770 5 1 3 painty 0.0
## 3771 5 1 10 painty 2.4
## 3772 5 1 10 painty 3.9
## 3773 5 1 15 painty 1.3
## 3774 5 1 15 painty 0.1
## 3775 5 1 16 painty 2.0
## 3776 5 1 16 painty 1.0
## 3777 5 1 19 painty 7.1
## 3778 5 1 19 painty 7.1
## 3779 5 1 31 painty 0.0
## 3780 5 1 31 painty 3.3
## 3781 5 1 51 painty 6.2
## 3782 5 1 51 painty 2.3
## 3783 5 1 52 painty 3.2
## 3784 5 1 52 painty 0.3
## 3785 5 1 63 painty 5.2
## 3786 5 1 63 painty 9.8
## 3787 5 1 78 painty 3.3
## 3788 5 1 78 painty 6.0
## 3789 5 1 79 painty 0.0
## 3790 5 1 79 painty 0.0
## 3791 5 1 86 painty 2.8
## 3792 5 1 86 painty 3.2
## 3793 5 2 3 painty 0.0
## 3794 5 2 3 painty 0.0
## 3795 5 2 10 painty 0.0
## 3796 5 2 10 painty 2.2
## 3797 5 2 15 painty 0.0
## 3798 5 2 15 painty 0.4
## 3799 5 2 16 painty 0.5
## 3800 5 2 16 painty 0.0
## 3801 5 2 19 painty 0.0
## 3802 5 2 19 painty 4.6
## 3803 5 2 31 painty 0.4
## 3804 5 2 31 painty 0.0
## 3805 5 2 51 painty 0.0
## 3806 5 2 51 painty 0.0
## 3807 5 2 52 painty 0.0
## 3808 5 2 52 painty 0.9
## 3809 5 2 63 painty 0.6
## 3810 5 2 63 painty 4.7
## 3811 5 2 78 painty 0.0
## 3812 5 2 78 painty 3.4
## 3813 5 2 79 painty 0.0
## 3814 5 2 79 painty 0.0
## 3815 5 2 86 painty 0.0
## 3816 5 2 86 painty 0.0
## 3817 5 3 3 painty 0.0
## 3818 5 3 3 painty 3.2
## 3819 5 3 10 painty 0.0
## 3820 5 3 10 painty 0.0
## 3821 5 3 15 painty NA
## 3822 5 3 15 painty 0.4
## 3823 5 3 16 painty 0.0
## 3824 5 3 16 painty 0.0
## 3825 5 3 19 painty 1.5
## 3826 5 3 19 painty 10.3
## 3827 5 3 31 painty 6.9
## 3828 5 3 31 painty 4.2
## 3829 5 3 51 painty 0.0
## 3830 5 3 51 painty 5.1
## 3831 5 3 52 painty 0.0
## 3832 5 3 52 painty 9.2
## 3833 5 3 63 painty 1.4
## 3834 5 3 63 painty 9.7
## 3835 5 3 78 painty 1.3
## 3836 5 3 78 painty 0.0
## 3837 5 3 79 painty 0.0
## 3838 5 3 79 painty 0.0
## 3839 5 3 86 painty 0.0
## 3840 5 3 86 painty 0.0
## 3841 6 1 3 painty 9.5
## 3842 6 1 3 painty 3.0
## 3843 6 1 10 painty 0.0
## 3844 6 1 10 painty 0.0
## 3845 6 1 15 painty 8.7
## 3846 6 1 15 painty 4.7
## 3847 6 1 16 painty 1.2
## 3848 6 1 16 painty 2.2
## 3849 6 1 19 painty 0.0
## 3850 6 1 19 painty 2.8
## 3851 6 1 31 painty 0.0
## 3852 6 1 31 painty 0.6
## 3853 6 1 51 painty 0.0
## 3854 6 1 51 painty 4.5
## 3855 6 1 52 painty 0.8
## 3856 6 1 52 painty 2.2
## 3857 6 1 63 painty 6.2
## 3858 6 1 63 painty 5.0
## 3859 6 1 78 painty 4.3
## 3860 6 1 78 painty 0.9
## 3861 6 1 79 painty 0.0
## 3862 6 1 79 painty 0.0
## 3863 6 1 86 painty 0.9
## 3864 6 1 86 painty 3.8
## 3865 6 2 3 painty 0.0
## 3866 6 2 3 painty 6.7
## 3867 6 2 10 painty 0.0
## 3868 6 2 10 painty 0.0
## 3869 6 2 15 painty 2.0
## 3870 6 2 15 painty 0.1
## 3871 6 2 16 painty 1.0
## 3872 6 2 16 painty 4.6
## 3873 6 2 19 painty 0.0
## 3874 6 2 19 painty 12.2
## 3875 6 2 31 painty 0.0
## 3876 6 2 31 painty 9.9
## 3877 6 2 51 painty 0.0
## 3878 6 2 51 painty 0.0
## 3879 6 2 52 painty 0.0
## 3880 6 2 52 painty 2.6
## 3881 6 2 63 painty 11.1
## 3882 6 2 63 painty 8.8
## 3883 6 2 78 painty 7.0
## 3884 6 2 78 painty 0.0
## 3885 6 2 79 painty 0.0
## 3886 6 2 79 painty 0.0
## 3887 6 2 86 painty 0.0
## 3888 6 2 86 painty 0.0
## 3889 6 3 3 painty 0.9
## 3890 6 3 3 painty 4.7
## 3891 6 3 10 painty 0.0
## 3892 6 3 10 painty 0.0
## 3893 6 3 15 painty 6.0
## 3894 6 3 15 painty 0.5
## 3895 6 3 16 painty 1.3
## 3896 6 3 16 painty 0.2
## 3897 6 3 19 painty 0.0
## 3898 6 3 19 painty 6.0
## 3899 6 3 31 painty 0.3
## 3900 6 3 31 painty 9.7
## 3901 6 3 51 painty 2.0
## 3902 6 3 51 painty 0.0
## 3903 6 3 52 painty 0.4
## 3904 6 3 52 painty 0.4
## 3905 6 3 63 painty 1.7
## 3906 6 3 63 painty 0.8
## 3907 6 3 78 painty 2.9
## 3908 6 3 78 painty 2.4
## 3909 6 3 79 painty 0.0
## 3910 6 3 79 painty 0.0
## 3911 6 3 86 painty 0.0
## 3912 6 3 86 painty 1.1
## 3913 7 1 3 painty 5.5
## 3914 7 1 3 painty 8.2
## 3915 7 1 10 painty 0.0
## 3916 7 1 10 painty 0.0
## 3917 7 1 15 painty 5.1
## 3918 7 1 15 painty 2.7
## 3919 7 1 16 painty 0.2
## 3920 7 1 16 painty 0.1
## 3921 7 1 19 painty 3.2
## 3922 7 1 19 painty 0.0
## 3923 7 1 31 painty 2.0
## 3924 7 1 31 painty 0.0
## 3925 7 1 51 painty 0.1
## 3926 7 1 51 painty 0.0
## 3927 7 1 52 painty 1.1
## 3928 7 1 52 painty 2.1
## 3929 7 1 63 painty 0.4
## 3930 7 1 63 painty 2.1
## 3931 7 1 78 painty 3.5
## 3932 7 1 78 painty 2.0
## 3933 7 1 79 painty 0.0
## 3934 7 1 79 painty 0.0
## 3935 7 1 86 painty 4.9
## 3936 7 1 86 painty 9.5
## 3937 7 2 3 painty 7.6
## 3938 7 2 3 painty 7.9
## 3939 7 2 10 painty 0.0
## 3940 7 2 10 painty 0.0
## 3941 7 2 15 painty 4.7
## 3942 7 2 15 painty 1.8
## 3943 7 2 16 painty 0.0
## 3944 7 2 16 painty 0.1
## 3945 7 2 19 painty 8.9
## 3946 7 2 19 painty 3.0
## 3947 7 2 31 painty 8.5
## 3948 7 2 31 painty 3.0
## 3949 7 2 51 painty 5.3
## 3950 7 2 51 painty 0.1
## 3951 7 2 52 painty 2.6
## 3952 7 2 52 painty 1.4
## 3953 7 2 63 painty 6.9
## 3954 7 2 63 painty 1.3
## 3955 7 2 78 painty 1.5
## 3956 7 2 78 painty 0.0
## 3957 7 2 79 painty 0.0
## 3958 7 2 79 painty 0.0
## 3959 7 2 86 painty 7.3
## 3960 7 2 86 painty 1.1
## 3961 7 3 3 painty 3.0
## 3962 7 3 3 painty 9.8
## 3963 7 3 10 painty 0.0
## 3964 7 3 10 painty 0.0
## 3965 7 3 15 painty 3.8
## 3966 7 3 15 painty 6.0
## 3967 7 3 16 painty 0.0
## 3968 7 3 16 painty 0.0
## 3969 7 3 19 painty 0.0
## 3970 7 3 19 painty 11.5
## 3971 7 3 31 painty 3.6
## 3972 7 3 31 painty 8.0
## 3973 7 3 51 painty 1.6
## 3974 7 3 51 painty 4.9
## 3975 7 3 52 painty 0.0
## 3976 7 3 52 painty 0.2
## 3977 7 3 63 painty 0.0
## 3978 7 3 63 painty 0.9
## 3979 7 3 78 painty 6.2
## 3980 7 3 78 painty 3.5
## 3981 7 3 79 painty 0.5
## 3982 7 3 79 painty 0.0
## 3983 7 3 86 painty 0.0
## 3984 7 3 86 painty 4.0
## 3985 8 1 3 painty 3.8
## 3986 8 1 3 painty 8.1
## 3987 8 1 10 painty 0.0
## 3988 8 1 10 painty 3.5
## 3989 8 1 15 painty 5.4
## 3990 8 1 15 painty 2.6
## 3991 8 1 16 painty 2.9
## 3992 8 1 16 painty 2.7
## 3993 8 1 19 painty 0.0
## 3994 8 1 19 painty 2.0
## 3995 8 1 31 painty 1.2
## 3996 8 1 31 painty 10.3
## 3997 8 1 51 painty 0.0
## 3998 8 1 51 painty 3.8
## 3999 8 1 52 painty 6.5
## 4000 8 1 52 painty 6.4
## 4001 8 1 63 painty 9.2
## 4002 8 1 63 painty 12.9
## 4003 8 1 78 painty 1.3
## 4004 8 1 78 painty 8.3
## 4005 8 1 79 painty 0.0
## 4006 8 1 79 painty 0.0
## 4007 8 1 86 painty 7.6
## 4008 8 1 86 painty 11.6
## 4009 8 2 3 painty 6.8
## 4010 8 2 3 painty 7.6
## 4011 8 2 10 painty 0.0
## 4012 8 2 10 painty 0.0
## 4013 8 2 15 painty 3.6
## 4014 8 2 15 painty 5.6
## 4015 8 2 16 painty 0.0
## 4016 8 2 16 painty 0.0
## 4017 8 2 19 painty 0.0
## 4018 8 2 19 painty 0.0
## 4019 8 2 31 painty 0.0
## 4020 8 2 31 painty 9.1
## 4021 8 2 51 painty 0.0
## 4022 8 2 51 painty 2.3
## 4023 8 2 52 painty 2.9
## 4024 8 2 52 painty 8.7
## 4025 8 2 63 painty 9.7
## 4026 8 2 63 painty 4.2
## 4027 8 2 78 painty 3.6
## 4028 8 2 78 painty 6.3
## 4029 8 2 79 painty 0.0
## 4030 8 2 79 painty NA
## 4031 8 2 86 painty 10.5
## 4032 8 2 86 painty 8.0
## 4033 8 3 3 painty 5.9
## 4034 8 3 3 painty 11.3
## 4035 8 3 10 painty 0.0
## 4036 8 3 10 painty 0.0
## 4037 8 3 15 painty 3.4
## 4038 8 3 15 painty 6.8
## 4039 8 3 16 painty 0.1
## 4040 8 3 16 painty 0.0
## 4041 8 3 19 painty 5.3
## 4042 8 3 19 painty 8.5
## 4043 8 3 31 painty 3.3
## 4044 8 3 31 painty 0.0
## 4045 8 3 51 painty 0.1
## 4046 8 3 51 painty 0.1
## 4047 8 3 52 painty 7.2
## 4048 8 3 52 painty 3.5
## 4049 8 3 63 painty 0.4
## 4050 8 3 63 painty 6.6
## 4051 8 3 78 painty 0.6
## 4052 8 3 78 painty 1.3
## 4053 8 3 79 painty 0.0
## 4054 8 3 79 painty 0.0
## 4055 8 3 86 painty 7.5
## 4056 8 3 86 painty 8.7
## 4057 9 1 3 painty 7.0
## 4058 9 1 3 painty 3.4
## 4059 9 1 10 painty 0.0
## 4060 9 1 10 painty 0.0
## 4061 9 1 15 painty 10.8
## 4062 9 1 15 painty 3.1
## 4063 9 1 16 painty 0.2
## 4064 9 1 16 painty 0.0
## 4065 9 1 19 painty 2.4
## 4066 9 1 19 painty 0.0
## 4067 9 1 51 painty 3.0
## 4068 9 1 51 painty 1.6
## 4069 9 1 52 painty 3.7
## 4070 9 1 52 painty 3.2
## 4071 9 1 63 painty 12.8
## 4072 9 1 63 painty 1.7
## 4073 9 1 78 painty 5.2
## 4074 9 1 78 painty 0.0
## 4075 9 1 79 painty 0.0
## 4076 9 1 79 painty 0.0
## 4077 9 2 3 painty 0.0
## 4078 9 2 3 painty 7.0
## 4079 9 2 10 painty 10.6
## 4080 9 2 10 painty 0.0
## 4081 9 2 15 painty 10.6
## 4082 9 2 15 painty 6.4
## 4083 9 2 16 painty 0.1
## 4084 9 2 16 painty 0.0
## 4085 9 2 19 painty 0.0
## 4086 9 2 19 painty 12.6
## 4087 9 2 51 painty 0.1
## 4088 9 2 51 painty 2.0
## 4089 9 2 52 painty 2.5
## 4090 9 2 52 painty 8.5
## 4091 9 2 63 painty 12.3
## 4092 9 2 63 painty 4.4
## 4093 9 2 78 painty 1.6
## 4094 9 2 78 painty 2.2
## 4095 9 2 79 painty 0.0
## 4096 9 2 79 painty 0.0
## 4097 9 3 3 painty 4.3
## 4098 9 3 3 painty 6.7
## 4099 9 3 10 painty 1.7
## 4100 9 3 10 painty 4.9
## 4101 9 3 15 painty 7.3
## 4102 9 3 15 painty 7.1
## 4103 9 3 16 painty 0.3
## 4104 9 3 16 painty 0.0
## 4105 9 3 19 painty 8.9
## 4106 9 3 19 painty 11.3
## 4107 9 3 51 painty 4.2
## 4108 9 3 51 painty 0.0
## 4109 9 3 52 painty 4.5
## 4110 9 3 52 painty 9.5
## 4111 9 3 63 painty 8.4
## 4112 9 3 63 painty 10.5
## 4113 9 3 78 painty 3.8
## 4114 9 3 78 painty 0.0
## 4115 9 3 79 painty 0.0
## 4116 9 3 79 painty 0.0
## 4117 10 1 10 painty 8.2
## 4118 10 1 10 painty 2.9
## 4119 10 1 15 painty 2.7
## 4120 10 1 15 painty 1.0
## 4121 10 1 16 painty 2.7
## 4122 10 1 16 painty 3.1
## 4123 10 1 19 painty 0.0
## 4124 10 1 19 painty 3.6
## 4125 10 1 31 painty 12.6
## 4126 10 1 31 painty 11.4
## 4127 10 1 51 painty 1.4
## 4128 10 1 51 painty 0.0
## 4129 10 1 52 painty 10.8
## 4130 10 1 52 painty 11.0
## 4131 10 1 63 painty 1.8
## 4132 10 1 63 painty 2.6
## 4133 10 1 78 painty 1.3
## 4134 10 1 78 painty 6.2
## 4135 10 1 86 painty 11.6
## 4136 10 1 86 painty 13.1
## 4137 10 2 10 painty 3.6
## 4138 10 2 10 painty 0.0
## 4139 10 2 15 painty 0.7
## 4140 10 2 15 painty 3.2
## 4141 10 2 16 painty 0.6
## 4142 10 2 16 painty 2.1
## 4143 10 2 19 painty 10.3
## 4144 10 2 19 painty 10.9
## 4145 10 2 31 painty 9.1
## 4146 10 2 31 painty 10.2
## 4147 10 2 51 painty 2.5
## 4148 10 2 51 painty 5.4
## 4149 10 2 52 painty 7.4
## 4150 10 2 52 painty 6.4
## 4151 10 2 63 painty 9.5
## 4152 10 2 63 painty 10.7
## 4153 10 2 78 painty 4.1
## 4154 10 2 78 painty 2.4
## 4155 10 2 86 painty 12.7
## 4156 10 2 86 painty 11.6
## 4157 10 3 10 painty 0.0
## 4158 10 3 10 painty 1.9
## 4159 10 3 15 painty 0.2
## 4160 10 3 15 painty 0.3
## 4161 10 3 16 painty 4.4
## 4162 10 3 16 painty 1.3
## 4163 10 3 19 painty 0.0
## 4164 10 3 19 painty 11.8
## 4165 10 3 31 painty 11.4
## 4166 10 3 31 painty 0.0
## 4167 10 3 51 painty 3.3
## 4168 10 3 51 painty 0.0
## 4169 10 3 52 painty 9.0
## 4170 10 3 52 painty 9.3
## 4171 10 3 63 painty 3.3
## 4172 10 3 63 painty 7.3
## 4173 10 3 78 painty 1.3
## 4174 10 3 78 painty 1.4
## 4175 10 3 86 painty 10.5
## 4176 10 3 86 painty 9.4You can make the output slightly nicer by specifying variable names and value names:
head(melt(french_fries, id.vars = 1:4, variable.name = "flavor", value.name = "flavor_intensity"))## time treatment subject rep flavor flavor_intensity
## 1 1 1 3 1 potato 2.9
## 2 1 1 3 2 potato 14.0
## 3 1 1 10 1 potato 11.0
## 4 1 1 10 2 potato 9.9
## 5 1 1 15 1 potato 1.2
## 6 1 1 15 2 potato 8.8Assume that the id variables are the dimensions of the array
Assume the measured variable is stored as elements in the array.
We don't specify id variables or measurement variables.
Therefore, the syntax is simply melt(array)
For example:
HairEyeColor## , , Sex = Male
##
## Eye
## Hair Brown Blue Hazel Green
## Black 32 11 10 3
## Brown 53 50 25 15
## Red 10 10 7 7
## Blond 3 30 5 8
##
## , , Sex = Female
##
## Eye
## Hair Brown Blue Hazel Green
## Black 36 9 5 2
## Brown 66 34 29 14
## Red 16 7 7 7
## Blond 4 64 5 8melt(HairEyeColor)## Hair Eye Sex value
## 1 Black Brown Male 32
## 2 Brown Brown Male 53
## 3 Red Brown Male 10
## 4 Blond Brown Male 3
## 5 Black Blue Male 11
## 6 Brown Blue Male 50
## 7 Red Blue Male 10
## 8 Blond Blue Male 30
## 9 Black Hazel Male 10
## 10 Brown Hazel Male 25
## 11 Red Hazel Male 7
## 12 Blond Hazel Male 5
## 13 Black Green Male 3
## 14 Brown Green Male 15
## 15 Red Green Male 7
## 16 Blond Green Male 8
## 17 Black Brown Female 36
## 18 Brown Brown Female 66
## 19 Red Brown Female 16
## 20 Blond Brown Female 4
## 21 Black Blue Female 9
## 22 Brown Blue Female 34
## 23 Red Blue Female 7
## 24 Blond Blue Female 64
## 25 Black Hazel Female 5
## 26 Brown Hazel Female 29
## 27 Red Hazel Female 7
## 28 Blond Hazel Female 5
## 29 Black Green Female 2
## 30 Brown Green Female 14
## 31 Red Green Female 7
## 32 Blond Green Female 8There are a couple of optional arguments for making the output a little nicer, like giving a different name to the column in the output describing the measured value:
melt(HairEyeColor, value.name = "number")## Hair Eye Sex number
## 1 Black Brown Male 32
## 2 Brown Brown Male 53
## 3 Red Brown Male 10
## 4 Blond Brown Male 3
## 5 Black Blue Male 11
## 6 Brown Blue Male 50
## 7 Red Blue Male 10
## 8 Blond Blue Male 30
## 9 Black Hazel Male 10
## 10 Brown Hazel Male 25
## 11 Red Hazel Male 7
## 12 Blond Hazel Male 5
## 13 Black Green Male 3
## 14 Brown Green Male 15
## 15 Red Green Male 7
## 16 Blond Green Male 8
## 17 Black Brown Female 36
## 18 Brown Brown Female 66
## 19 Red Brown Female 16
## 20 Blond Brown Female 4
## 21 Black Blue Female 9
## 22 Brown Blue Female 34
## 23 Red Blue Female 7
## 24 Blond Blue Female 64
## 25 Black Hazel Female 5
## 26 Brown Hazel Female 29
## 27 Red Hazel Female 7
## 28 Blond Hazel Female 5
## 29 Black Green Female 2
## 30 Brown Green Female 14
## 31 Red Green Female 7
## 32 Blond Green Female 8reshape2 uses *cast: either dcast or acast for data frame or array output, respectively.
Syntax: *cast(mdata, col_var_1 + ... + col_var_n ~ row_var_1 + ... + row_var_m, value.var)
mdata should be a molten data set
The columns of the output will be all the combinations of col_var_1, ..., col_var_n
The rows of the output will be all the combinations of row_var_1, ..., row_var_n
value.var is the value variable, the values that should go in the cells of the output. If you don't specify it, melt will guess.
Example
ff_m = melt(french_fries, id.vars = 1:4, variable.name = "flavor", na.rm = TRUE)
head(ff_m)## time treatment subject rep flavor value
## 1 1 1 3 1 potato 2.9
## 2 1 1 3 2 potato 14.0
## 3 1 1 10 1 potato 11.0
## 4 1 1 10 2 potato 9.9
## 5 1 1 15 1 potato 1.2
## 6 1 1 15 2 potato 8.8cast_ex_1 = dcast(ff_m, time + treatment ~ subject + rep + flavor, value.var = "value")
cast_ex_1[1:5,1:5]## time treatment 3_1_potato 3_1_buttery 3_1_grassy
## 1 1 1 2.9 0.0 0.0
## 2 1 2 13.9 0.0 0.0
## 3 1 3 14.1 0.0 0.0
## 4 2 1 9.0 0.3 0.1
## 5 2 2 14.1 0.9 0.3## check to see if the numbers match
subset(ff_m, time == 1 & subject == "3" & rep == 1 & flavor == "potato")## time treatment subject rep flavor value
## 1 1 1 3 1 potato 2.9
## 25 1 2 3 1 potato 13.9
## 49 1 3 3 1 potato 14.1When you cast data, you often don't use all of the variables.
This means that each element of the cast table will correspond to more than one measurement, and so they need to be aggregated in some way.
head(ff_m)## time treatment subject rep flavor value
## 1 1 1 3 1 potato 2.9
## 2 1 1 3 2 potato 14.0
## 3 1 1 10 1 potato 11.0
## 4 1 1 10 2 potato 9.9
## 5 1 1 15 1 potato 1.2
## 6 1 1 15 2 potato 8.8dcast(ff_m, subject ~ flavor, value.var = "value")## Aggregation function missing: defaulting to length## subject potato buttery grassy rancid painty
## 1 3 54 54 54 54 54
## 2 10 60 60 60 60 60
## 3 15 59 59 59 59 59
## 4 16 60 59 60 60 60
## 5 19 60 60 60 60 60
## 6 31 54 54 54 54 54
## 7 51 60 60 60 60 60
## 8 52 60 60 60 60 60
## 9 63 60 60 60 60 60
## 10 78 60 60 60 60 60
## 11 79 54 52 54 54 53
## 12 86 54 54 54 54 54The aggregation function is specified with fun.aggregate:
dcast(ff_m, subject ~ flavor, value.var = "value", fun.aggregate = mean)## subject potato buttery grassy rancid painty
## 1 3 6.083333 0.5759259 0.1296296 2.7000000 2.818518519
## 2 10 9.993333 6.7266667 0.4016667 3.0933333 0.961666667
## 3 15 3.908475 1.0084746 0.4000000 2.9389831 2.566101695
## 4 16 6.601667 3.1067797 0.9783333 3.5733333 0.746666667
## 5 19 8.921667 2.4100000 1.7416667 6.0016667 3.611666667
## 6 31 8.635185 0.5703704 0.1388889 6.1907407 4.466666667
## 7 51 10.293333 3.1883333 1.3233333 4.9116667 2.251666667
## 8 52 5.350000 0.8983333 0.9400000 3.8900000 2.500000000
## 9 63 7.750000 0.0650000 0.0450000 5.7766667 3.770000000
## 10 78 3.800000 0.5783333 0.6533333 1.4133333 3.245000000
## 11 79 7.911111 0.5173077 0.2388889 0.9259259 0.009433962
## 12 86 4.014815 1.8222222 0.8444444 4.7074074 3.325925926A couple of other notes:
You can use . to represent all the other variables in the formula.
The order that you specify the variables in the formula matters for the way the output is ordered: the first variables change most slowly, and the later ones change more quickly.
head(dcast(ff_m, subject + treatment ~ flavor, fun.aggregate = mean), n = 10)## subject treatment potato buttery grassy rancid painty
## 1 3 1 6.216667 0.3722222 0.18888889 2.105556 3.111111
## 2 3 2 6.738889 0.5888889 0.10555556 3.138889 2.477778
## 3 3 3 5.294444 0.7666667 0.09444444 2.855556 2.866667
## 4 10 1 9.955000 6.7500000 0.58500000 4.020000 1.375000
## 5 10 2 9.995000 6.9800000 0.47500000 2.150000 0.820000
## 6 10 3 10.030000 6.4500000 0.14500000 3.110000 0.690000
## 7 15 1 3.360000 0.7200000 0.42000000 3.965000 3.260000
## 8 15 2 4.405000 1.3150000 0.34000000 2.285000 2.060000
## 9 15 3 3.963158 0.9894737 0.44210526 2.547368 2.368421
## 10 16 1 6.495000 3.2600000 0.75500000 4.120000 1.230000head(dcast(ff_m, treatment + subject ~ flavor, fun.aggregate = mean), n = 10)## treatment subject potato buttery grassy rancid painty
## 1 1 3 6.216667 0.3722222 0.18888889 2.105556 3.111111
## 2 1 10 9.955000 6.7500000 0.58500000 4.020000 1.375000
## 3 1 15 3.360000 0.7200000 0.42000000 3.965000 3.260000
## 4 1 16 6.495000 3.2600000 0.75500000 4.120000 1.230000
## 5 1 19 9.385000 3.0550000 2.02000000 5.360000 2.775000
## 6 1 31 8.844444 0.4444444 0.08888889 5.944444 3.211111
## 7 1 51 10.675000 2.6400000 1.05000000 5.150000 1.955000
## 8 1 52 5.060000 0.8050000 0.87500000 4.285000 2.645000
## 9 1 63 6.775000 0.0250000 0.00000000 6.055000 3.855000
## 10 1 78 3.620000 0.7350000 0.54000000 1.505000 3.490000Final topic: What if you have data from two different places and you need to put them together?
Basic syntax: merge(x, y, by.x, by.y)
x and y are the two datasets you want to merge.
by.x is the column of x to merge on.
by.y is the column of y to merge on.
Example:
cities = data.frame(
city=c('New York','Boston','Juneau',
'Anchorage','San Diego',
'Philadelphia','Los Angeles',
'Fairbanks','Ann Arbor','Seattle'),
state.abb=c('NY','MA','AK','AK','CA',
'PA','CA','AK','MI','WA'))
states = data.frame(state.name, state.abb)
cities## city state.abb
## 1 New York NY
## 2 Boston MA
## 3 Juneau AK
## 4 Anchorage AK
## 5 San Diego CA
## 6 Philadelphia PA
## 7 Los Angeles CA
## 8 Fairbanks AK
## 9 Ann Arbor MI
## 10 Seattle WAhead(states)## state.name state.abb
## 1 Alabama AL
## 2 Alaska AK
## 3 Arizona AZ
## 4 Arkansas AR
## 5 California CA
## 6 Colorado COWe want to add the state name to the cities data frame, and we can use merge.
merge(states, cities, by.x = "state.abb", by.y = "state.abb")## state.abb state.name city
## 1 AK Alaska Juneau
## 2 AK Alaska Anchorage
## 3 AK Alaska Fairbanks
## 4 CA California San Diego
## 5 CA California Los Angeles
## 6 MA Massachusetts Boston
## 7 MI Michigan Ann Arbor
## 8 NY New York New York
## 9 PA Pennsylvania Philadelphia
## 10 WA Washington SeattleNotice in the last example that there was some ambiguity in how the merge took place because the two datasets have different sets of values for state.abb.
Can modify with all, all.x, or all.y
all = TRUE means that you get one row for values of the merging variable that were seen in either x or y
all.x = TRUE means you get one row for each value of the merging variable that was seen in x
all.y = TRUE means you get one row for each value of the merging variable that was seen in y.
merge(states, cities, all.x = TRUE)## state.abb state.name city
## 1 AK Alaska Juneau
## 2 AK Alaska Anchorage
## 3 AK Alaska Fairbanks
## 4 AL Alabama <NA>
## 5 AR Arkansas <NA>
## 6 AZ Arizona <NA>
## 7 CA California San Diego
## 8 CA California Los Angeles
## 9 CO Colorado <NA>
## 10 CT Connecticut <NA>
## 11 DE Delaware <NA>
## 12 FL Florida <NA>
## 13 GA Georgia <NA>
## 14 HI Hawaii <NA>
## 15 IA Iowa <NA>
## 16 ID Idaho <NA>
## 17 IL Illinois <NA>
## 18 IN Indiana <NA>
## 19 KS Kansas <NA>
## 20 KY Kentucky <NA>
## 21 LA Louisiana <NA>
## 22 MA Massachusetts Boston
## 23 MD Maryland <NA>
## 24 ME Maine <NA>
## 25 MI Michigan Ann Arbor
## 26 MN Minnesota <NA>
## 27 MO Missouri <NA>
## 28 MS Mississippi <NA>
## 29 MT Montana <NA>
## 30 NC North Carolina <NA>
## 31 ND North Dakota <NA>
## 32 NE Nebraska <NA>
## 33 NH New Hampshire <NA>
## 34 NJ New Jersey <NA>
## 35 NM New Mexico <NA>
## 36 NV Nevada <NA>
## 37 NY New York New York
## 38 OH Ohio <NA>
## 39 OK Oklahoma <NA>
## 40 OR Oregon <NA>
## 41 PA Pennsylvania Philadelphia
## 42 RI Rhode Island <NA>
## 43 SC South Carolina <NA>
## 44 SD South Dakota <NA>
## 45 TN Tennessee <NA>
## 46 TX Texas <NA>
## 47 UT Utah <NA>
## 48 VA Virginia <NA>
## 49 VT Vermont <NA>
## 50 WA Washington Seattle
## 51 WI Wisconsin <NA>
## 52 WV West Virginia <NA>
## 53 WY Wyoming <NA>Some additional notes:
Default if you don't specify by.x and by.y is to use the columns that are common to the two.
by.x/by.y can have length more than 1, in which case we match on the entire set of specified variables.
Can use by instead of by.x and by.y, in which case the name of the column to merge on has to be the same in both x and y.
Merging, melting/casting, and split/apply/combine from last week are useful enough that there are multiple implementations.
You can use other implementations, but you shouldn't try to re-make them from scratch.
Some other options are:
join in plyr does the same thing as merge
gather and spread in the tidyr package do roughly the same thing as cast and melt.
There are multiple iterations of reshape, reshape2 was a redesign of reshape.
plyr and dplyr are also two packages that have basically the same goal, but dplyr is focused more on data frames.
Next week: Debugging and testing!