title: “Data Manipulation” output: html_notebook
Learn base R syntax for data manipulation logical operators for finer control creating and assigning objects specifying factors Turn messy data into tidy data with tidyr Use efficient tools from the dplyr package to manipulate data
Steps: Subset, extract and modify data with R base operators What is tidy data, and how do we achieve it? Explore the most common and useful functions of dplyr rename() filter()and select() mutate() group_by() summarise() join()
- Subset, extract and modify data with R operators
Data frames are R objects made of rows and columns containing observations of different variables: you will often be importing your data that way. Sometimes, you might notice some mistakes after importing, need to rename a variable, or keep only a subset of the data that meets some conditions. Let’s dive right in and do that on the EmpetrumElongation.csv dataset that you have downloaded from the repository.
#Create a new, blank script, and add in some information at the top, for instance the title of the tutorial, your name, and the date (remember to use hashtags # to comment and annotate your script).
This dataset represents annual increments in stem growth, measured on crowberry shrubs on a sand dune system. The Zone field corresponds to distinct zones going from closest (2) to farthest (7) from the sea.
Load Packages
library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.0.3## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.1.0 v dplyr 1.0.5
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1## Warning: package 'ggplot2' was built under R version 4.0.3## Warning: package 'tibble' was built under R version 4.0.5## Warning: package 'tidyr' was built under R version 4.0.4## Warning: package 'readr' was built under R version 4.0.3## Warning: package 'purrr' was built under R version 4.0.3## Warning: package 'dplyr' was built under R version 4.0.5## Warning: package 'stringr' was built under R version 4.0.3## Warning: package 'forcats' was built under R version 4.0.3## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()setwd("C:/Users/Nicklaus Neureuther/Documents/R/CodingClub/CC_course_stream1-master/04_Data_manip_1")getwd## function ()
## .Internal(getwd())
## <bytecode: 0x0000000014694900>
## <environment: namespace:base>load elongation data
elongation <-read.csv("EmpetrumElongation.csv",header=TRUE)Check data
head(elongation)## Zone Indiv X2007 X2008 X2009 X2010 X2011 X2012
## 1 2 373 5.1 5.1 4.8 8.7 6.3 3.2
## 2 2 379 8.1 13.3 8.6 4.9 5.9 6.3
## 3 2 383 9.3 8.5 11.7 7.9 8.0 6.3
## 4 2 389 15.0 10.3 6.8 6.9 5.9 7.6
## 5 2 390 3.5 6.2 4.7 3.8 3.5 3.0
## 6 2 395 6.1 5.6 4.4 4.5 4.5 7.6str(elongation)## 'data.frame': 114 obs. of 8 variables:
## $ Zone : int 2 2 2 2 2 2 2 2 2 2 ...
## $ Indiv: int 373 379 383 389 390 395 396 408 412 421 ...
## $ X2007: num 5.1 8.1 9.3 15 3.5 6.1 7.2 6.1 4.6 7.2 ...
## $ X2008: num 5.1 13.3 8.5 10.3 6.2 5.6 5.9 8.1 6.7 5.8 ...
## $ X2009: num 4.8 8.6 11.7 6.8 4.7 4.4 5.7 7.6 4.5 5.8 ...
## $ X2010: num 8.7 4.9 7.9 6.9 3.8 4.5 5.4 6.2 2.8 5.6 ...
## $ X2011: num 6.3 5.9 8 5.9 3.5 4.5 5.5 9.6 4.2 4.3 ...
## $ X2012: num 3.2 6.3 6.3 7.6 3 7.6 4.7 10.1 5.2 3.4 ...elongation$Indiv## [1] 373 379 383 389 390 395 396 408 412 421 425 429 431 442 444
## [16] 447 458 464 486 512 530 534 538 542 549 569 572 577 581 584
## [31] 597 616 647 660 591 595 603 612 618 619 623 632 641 645 646
## [46] 648 654 657 661 663 677 678 682 1 37 38 41 49 64 71
## [61] 72 85 88 101 114 120 126 145 150 155 166 177 206 129 257
## [76] 276 303 322 349 350 355 370 454 725 766 812 817 844 863 868
## [91] 896 899 901 917 924 963 970 977 979 1000 1069 1073 1087 1109 1140
## [106] 1183 1188 1247 1286 1340 1358 1392 1477 1481length(unique(elongation$Indiv)) ## [1] 114elongation[2,5]## [1] 8.6elongation[6,]## Zone Indiv X2007 X2008 X2009 X2010 X2011 X2012
## 6 2 395 6.1 5.6 4.4 4.5 4.5 7.6Logical operation
elongation[elongation$Indiv==603,]## Zone Indiv X2007 X2008 X2009 X2010 X2011 X2012
## 37 4 603 2.5 3.8 3.2 2.3 3.2 5.4#Tidydata
CREATING LONG FORMAT
elongation_long<-gather(elongation,year,length,c(X2007,X2008,X2009,X2010,X2011,X2012))
elongation_long## Zone Indiv year length
## 1 2 373 X2007 5.1
## 2 2 379 X2007 8.1
## 3 2 383 X2007 9.3
## 4 2 389 X2007 15.0
## 5 2 390 X2007 3.5
## 6 2 395 X2007 6.1
## 7 2 396 X2007 7.2
## 8 2 408 X2007 6.1
## 9 2 412 X2007 4.6
## 10 2 421 X2007 7.2
## 11 2 425 X2007 6.4
## 12 2 429 X2007 8.9
## 13 2 431 X2007 3.5
## 14 2 442 X2007 5.3
## 15 2 444 X2007 8.7
## 16 3 447 X2007 8.3
## 17 3 458 X2007 5.4
## 18 3 464 X2007 9.2
## 19 3 486 X2007 9.1
## 20 3 512 X2007 9.0
## 21 3 530 X2007 9.2
## 22 3 534 X2007 7.4
## 23 3 538 X2007 8.9
## 24 3 542 X2007 5.3
## 25 3 549 X2007 4.5
## 26 3 569 X2007 4.2
## 27 3 572 X2007 7.1
## 28 3 577 X2007 6.8
## 29 3 581 X2007 6.0
## 30 3 584 X2007 5.6
## 31 3 597 X2007 8.9
## 32 3 616 X2007 9.7
## 33 3 647 X2007 8.1
## 34 3 660 X2007 6.7
## 35 4 591 X2007 6.5
## 36 4 595 X2007 9.8
## 37 4 603 X2007 2.5
## 38 4 612 X2007 5.4
## 39 4 618 X2007 6.1
## 40 4 619 X2007 8.4
## 41 4 623 X2007 5.4
## 42 4 632 X2007 7.3
## 43 4 641 X2007 7.1
## 44 4 645 X2007 8.0
## 45 4 646 X2007 11.5
## 46 4 648 X2007 10.7
## 47 4 654 X2007 9.5
## 48 4 657 X2007 6.6
## 49 4 661 X2007 8.2
## 50 4 663 X2007 5.7
## 51 4 677 X2007 6.0
## 52 4 678 X2007 3.6
## 53 4 682 X2007 5.0
## 54 5 1 X2007 6.5
## 55 5 37 X2007 7.3
## 56 5 38 X2007 5.4
## 57 5 41 X2007 2.0
## 58 5 49 X2007 5.8
## 59 5 64 X2007 7.5
## 60 5 71 X2007 4.3
## 61 5 72 X2007 7.0
## 62 5 85 X2007 5.0
## 63 5 88 X2007 6.6
## 64 5 101 X2007 3.4
## 65 5 114 X2007 5.4
## 66 5 120 X2007 6.3
## 67 5 126 X2007 7.7
## 68 5 145 X2007 4.4
## 69 5 150 X2007 6.0
## 70 5 155 X2007 4.9
## 71 5 166 X2007 7.4
## 72 5 177 X2007 7.3
## 73 5 206 X2007 5.0
## 74 6 129 X2007 8.1
## 75 6 257 X2007 9.9
## 76 6 276 X2007 4.1
## 77 6 303 X2007 7.1
## 78 6 322 X2007 6.6
## 79 6 349 X2007 9.6
## 80 6 350 X2007 4.6
## 81 6 355 X2007 6.7
## 82 6 370 X2007 6.9
## 83 6 454 X2007 8.4
## 84 6 725 X2007 4.7
## 85 6 766 X2007 6.3
## 86 6 812 X2007 9.9
## 87 6 817 X2007 7.4
## 88 6 844 X2007 4.8
## 89 6 863 X2007 3.5
## 90 6 868 X2007 6.4
## 91 6 896 X2007 7.2
## 92 6 899 X2007 2.9
## 93 6 901 X2007 4.3
## 94 6 917 X2007 6.4
## 95 7 924 X2007 8.1
## 96 7 963 X2007 6.8
## 97 7 970 X2007 6.2
## 98 7 977 X2007 5.5
## 99 7 979 X2007 6.6
## 100 7 1000 X2007 4.3
## 101 7 1069 X2007 6.2
## 102 7 1073 X2007 7.3
## 103 7 1087 X2007 5.9
## 104 7 1109 X2007 4.5
## 105 7 1140 X2007 4.7
## 106 7 1183 X2007 7.2
## 107 7 1188 X2007 9.4
## 108 7 1247 X2007 5.5
## 109 7 1286 X2007 7.1
## 110 7 1340 X2007 7.1
## 111 7 1358 X2007 9.0
## 112 7 1392 X2007 3.9
## 113 7 1477 X2007 5.3
## 114 7 1481 X2007 5.4
## 115 2 373 X2008 5.1
## 116 2 379 X2008 13.3
## 117 2 383 X2008 8.5
## 118 2 389 X2008 10.3
## 119 2 390 X2008 6.2
## 120 2 395 X2008 5.6
## 121 2 396 X2008 5.9
## 122 2 408 X2008 8.1
## 123 2 412 X2008 6.7
## 124 2 421 X2008 5.8
## 125 2 425 X2008 8.1
## 126 2 429 X2008 11.2
## 127 2 431 X2008 5.9
## 128 2 442 X2008 9.9
## 129 2 444 X2008 5.6
## 130 3 447 X2008 6.5
## 131 3 458 X2008 8.6
## 132 3 464 X2008 9.7
## 133 3 486 X2008 6.7
## 134 3 512 X2008 10.8
## 135 3 530 X2008 11.4
## 136 3 534 X2008 6.8
## 137 3 538 X2008 12.5
## 138 3 542 X2008 6.0
## 139 3 549 X2008 5.6
## 140 3 569 X2008 6.3
## 141 3 572 X2008 10.1
## 142 3 577 X2008 12.1
## 143 3 581 X2008 6.9
## 144 3 584 X2008 6.6
## 145 3 597 X2008 7.9
## 146 3 616 X2008 10.8
## 147 3 647 X2008 6.9
## 148 3 660 X2008 5.4
## 149 4 591 X2008 10.9
## 150 4 595 X2008 9.2
## 151 4 603 X2008 3.8
## 152 4 612 X2008 6.5
## 153 4 618 X2008 7.5
## 154 4 619 X2008 10.5
## 155 4 623 X2008 7.5
## 156 4 632 X2008 7.3
## 157 4 641 X2008 13.2
## 158 4 645 X2008 11.5
## 159 4 646 X2008 7.0
## 160 4 648 X2008 9.2
## 161 4 654 X2008 10.4
## 162 4 657 X2008 14.0
## 163 4 661 X2008 8.9
## 164 4 663 X2008 10.6
## 165 4 677 X2008 8.6
## 166 4 678 X2008 3.7
## 167 4 682 X2008 6.8
## 168 5 1 X2008 7.7
## 169 5 37 X2008 7.3
## 170 5 38 X2008 5.8
## 171 5 41 X2008 4.7
## 172 5 49 X2008 4.4
## 173 5 64 X2008 7.4
## 174 5 71 X2008 4.7
## 175 5 72 X2008 9.5
## 176 5 85 X2008 5.6
## 177 5 88 X2008 7.5
## 178 5 101 X2008 5.6
## 179 5 114 X2008 5.4
## 180 5 120 X2008 6.3
## 181 5 126 X2008 6.5
## 182 5 145 X2008 4.7
## 183 5 150 X2008 3.1
## 184 5 155 X2008 5.1
## 185 5 166 X2008 5.9
## 186 5 177 X2008 5.0
## 187 5 206 X2008 4.4
## 188 6 129 X2008 6.7
## 189 6 257 X2008 8.4
## 190 6 276 X2008 6.2
## 191 6 303 X2008 6.9
## 192 6 322 X2008 6.9
## 193 6 349 X2008 9.8
## 194 6 350 X2008 10.3
## 195 6 355 X2008 5.5
## 196 6 370 X2008 7.6
## 197 6 454 X2008 9.7
## 198 6 725 X2008 3.7
## 199 6 766 X2008 6.7
## 200 6 812 X2008 8.7
## 201 6 817 X2008 8.6
## 202 6 844 X2008 4.7
## 203 6 863 X2008 3.3
## 204 6 868 X2008 6.9
## 205 6 896 X2008 7.9
## 206 6 899 X2008 6.0
## 207 6 901 X2008 4.5
## 208 6 917 X2008 8.9
## 209 7 924 X2008 7.8
## 210 7 963 X2008 7.2
## 211 7 970 X2008 5.2
## 212 7 977 X2008 5.3
## 213 7 979 X2008 6.3
## 214 7 1000 X2008 5.5
## 215 7 1069 X2008 3.9
## 216 7 1073 X2008 6.3
## 217 7 1087 X2008 6.7
## 218 7 1109 X2008 4.3
## 219 7 1140 X2008 3.9
## 220 7 1183 X2008 9.3
## 221 7 1188 X2008 8.9
## 222 7 1247 X2008 5.0
## 223 7 1286 X2008 9.5
## 224 7 1340 X2008 5.7
## 225 7 1358 X2008 10.0
## 226 7 1392 X2008 4.7
## 227 7 1477 X2008 5.9
## 228 7 1481 X2008 6.7
## 229 2 373 X2009 4.8
## 230 2 379 X2009 8.6
## 231 2 383 X2009 11.7
## 232 2 389 X2009 6.8
## 233 2 390 X2009 4.7
## 234 2 395 X2009 4.4
## 235 2 396 X2009 5.7
## 236 2 408 X2009 7.6
## 237 2 412 X2009 4.5
## 238 2 421 X2009 5.8
## 239 2 425 X2009 7.8
## 240 2 429 X2009 8.6
## 241 2 431 X2009 5.4
## 242 2 442 X2009 9.2
## 243 2 444 X2009 5.9
## 244 3 447 X2009 8.1
## 245 3 458 X2009 6.1
## 246 3 464 X2009 7.8
## 247 3 486 X2009 6.8
## 248 3 512 X2009 7.1
## 249 3 530 X2009 4.5
## 250 3 534 X2009 7.9
## 251 3 538 X2009 10.5
## 252 3 542 X2009 5.8
## 253 3 549 X2009 5.8
## 254 3 569 X2009 6.2
## 255 3 572 X2009 10.0
## 256 3 577 X2009 11.1
## 257 3 581 X2009 6.3
## 258 3 584 X2009 5.9
## 259 3 597 X2009 6.4
## 260 3 616 X2009 8.8
## 261 3 647 X2009 6.9
## 262 3 660 X2009 6.0
## 263 4 591 X2009 7.8
## 264 4 595 X2009 8.0
## 265 4 603 X2009 3.2
## 266 4 612 X2009 8.0
## 267 4 618 X2009 6.1
## 268 4 619 X2009 6.9
## 269 4 623 X2009 4.4
## 270 4 632 X2009 6.9
## 271 4 641 X2009 9.5
## 272 4 645 X2009 7.2
## 273 4 646 X2009 4.1
## 274 4 648 X2009 6.9
## 275 4 654 X2009 8.9
## 276 4 657 X2009 10.1
## 277 4 661 X2009 6.1
## 278 4 663 X2009 9.5
## 279 4 677 X2009 6.1
## 280 4 678 X2009 8.2
## 281 4 682 X2009 8.7
## 282 5 1 X2009 5.6
## 283 5 37 X2009 7.7
## 284 5 38 X2009 4.9
## 285 5 41 X2009 4.2
## 286 5 49 X2009 7.9
## 287 5 64 X2009 6.6
## 288 5 71 X2009 3.9
## 289 5 72 X2009 5.9
## 290 5 85 X2009 5.4
## 291 5 88 X2009 5.3
## 292 5 101 X2009 3.5
## 293 5 114 X2009 4.3
## 294 5 120 X2009 6.0
## 295 5 126 X2009 7.4
## 296 5 145 X2009 4.4
## 297 5 150 X2009 5.7
## 298 5 155 X2009 4.8
## 299 5 166 X2009 8.1
## 300 5 177 X2009 5.2
## 301 5 206 X2009 4.0
## 302 6 129 X2009 6.3
## 303 6 257 X2009 8.6
## 304 6 276 X2009 5.5
## 305 6 303 X2009 7.0
## 306 6 322 X2009 6.5
## 307 6 349 X2009 8.9
## 308 6 350 X2009 6.5
## 309 6 355 X2009 7.0
## 310 6 370 X2009 5.1
## 311 6 454 X2009 7.2
## 312 6 725 X2009 3.4
## 313 6 766 X2009 5.3
## 314 6 812 X2009 8.0
## 315 6 817 X2009 8.0
## 316 6 844 X2009 3.4
## 317 6 863 X2009 4.1
## 318 6 868 X2009 5.5
## 319 6 896 X2009 7.5
## 320 6 899 X2009 3.0
## 321 6 901 X2009 4.1
## 322 6 917 X2009 7.0
## 323 7 924 X2009 7.1
## 324 7 963 X2009 3.7
## 325 7 970 X2009 5.9
## 326 7 977 X2009 6.4
## 327 7 979 X2009 6.3
## 328 7 1000 X2009 3.6
## 329 7 1069 X2009 4.1
## 330 7 1073 X2009 5.3
## 331 7 1087 X2009 7.4
## 332 7 1109 X2009 3.4
## 333 7 1140 X2009 5.5
## 334 7 1183 X2009 6.7
## 335 7 1188 X2009 7.0
## 336 7 1247 X2009 4.2
## 337 7 1286 X2009 7.7
## 338 7 1340 X2009 7.2
## 339 7 1358 X2009 8.6
## 340 7 1392 X2009 2.9
## 341 7 1477 X2009 6.2
## 342 7 1481 X2009 6.0
## 343 2 373 X2010 8.7
## 344 2 379 X2010 4.9
## 345 2 383 X2010 7.9
## 346 2 389 X2010 6.9
## 347 2 390 X2010 3.8
## 348 2 395 X2010 4.5
## 349 2 396 X2010 5.4
## 350 2 408 X2010 6.2
## 351 2 412 X2010 2.8
## 352 2 421 X2010 5.6
## 353 2 425 X2010 6.2
## 354 2 429 X2010 8.4
## 355 2 431 X2010 4.9
## 356 2 442 X2010 6.4
## 357 2 444 X2010 5.2
## 358 3 447 X2010 7.0
## 359 3 458 X2010 5.4
## 360 3 464 X2010 5.8
## 361 3 486 X2010 6.1
## 362 3 512 X2010 5.8
## 363 3 530 X2010 3.6
## 364 3 534 X2010 3.7
## 365 3 538 X2010 6.3
## 366 3 542 X2010 8.6
## 367 3 549 X2010 4.4
## 368 3 569 X2010 6.3
## 369 3 572 X2010 10.1
## 370 3 577 X2010 8.6
## 371 3 581 X2010 3.7
## 372 3 584 X2010 4.8
## 373 3 597 X2010 7.1
## 374 3 616 X2010 6.4
## 375 3 647 X2010 4.0
## 376 3 660 X2010 4.9
## 377 4 591 X2010 6.1
## 378 4 595 X2010 6.7
## 379 4 603 X2010 2.3
## 380 4 612 X2010 5.7
## 381 4 618 X2010 4.2
## 382 4 619 X2010 5.2
## 383 4 623 X2010 3.4
## 384 4 632 X2010 6.3
## 385 4 641 X2010 6.0
## 386 4 645 X2010 8.5
## 387 4 646 X2010 5.2
## 388 4 648 X2010 5.5
## 389 4 654 X2010 8.6
## 390 4 657 X2010 6.6
## 391 4 661 X2010 5.7
## 392 4 663 X2010 6.9
## 393 4 677 X2010 7.0
## 394 4 678 X2010 4.4
## 395 4 682 X2010 5.1
## 396 5 1 X2010 6.8
## 397 5 37 X2010 5.6
## 398 5 38 X2010 3.5
## 399 5 41 X2010 3.3
## 400 5 49 X2010 6.7
## 401 5 64 X2010 5.4
## 402 5 71 X2010 3.7
## 403 5 72 X2010 6.6
## 404 5 85 X2010 8.6
## 405 5 88 X2010 5.2
## 406 5 101 X2010 2.8
## 407 5 114 X2010 4.6
## 408 5 120 X2010 5.2
## 409 5 126 X2010 5.7
## 410 5 145 X2010 3.3
## 411 5 150 X2010 3.9
## 412 5 155 X2010 7.3
## 413 5 166 X2010 6.5
## 414 5 177 X2010 4.0
## 415 5 206 X2010 3.2
## 416 6 129 X2010 6.0
## 417 6 257 X2010 6.8
## 418 6 276 X2010 4.8
## 419 6 303 X2010 6.4
## 420 6 322 X2010 4.9
## 421 6 349 X2010 8.5
## 422 6 350 X2010 4.0
## 423 6 355 X2010 4.8
## 424 6 370 X2010 5.4
## 425 6 454 X2010 7.6
## 426 6 725 X2010 1.9
## 427 6 766 X2010 4.9
## 428 6 812 X2010 8.5
## 429 6 817 X2010 6.6
## 430 6 844 X2010 3.2
## 431 6 863 X2010 3.3
## 432 6 868 X2010 4.5
## 433 6 896 X2010 4.9
## 434 6 899 X2010 2.8
## 435 6 901 X2010 4.2
## 436 6 917 X2010 6.3
## 437 7 924 X2010 6.8
## 438 7 963 X2010 3.5
## 439 7 970 X2010 6.2
## 440 7 977 X2010 5.7
## 441 7 979 X2010 7.7
## 442 7 1000 X2010 3.1
## 443 7 1069 X2010 3.8
## 444 7 1073 X2010 6.7
## 445 7 1087 X2010 5.1
## 446 7 1109 X2010 4.3
## 447 7 1140 X2010 5.2
## 448 7 1183 X2010 7.8
## 449 7 1188 X2010 6.9
## 450 7 1247 X2010 3.9
## 451 7 1286 X2010 5.6
## 452 7 1340 X2010 6.9
## 453 7 1358 X2010 8.5
## 454 7 1392 X2010 3.9
## 455 7 1477 X2010 4.2
## 456 7 1481 X2010 6.0
## 457 2 373 X2011 6.3
## 458 2 379 X2011 5.9
## 459 2 383 X2011 8.0
## 460 2 389 X2011 5.9
## 461 2 390 X2011 3.5
## 462 2 395 X2011 4.5
## 463 2 396 X2011 5.5
## 464 2 408 X2011 9.6
## 465 2 412 X2011 4.2
## 466 2 421 X2011 4.3
## 467 2 425 X2011 6.4
## 468 2 429 X2011 8.2
## 469 2 431 X2011 3.5
## 470 2 442 X2011 5.5
## 471 2 444 X2011 6.6
## 472 3 447 X2011 7.6
## 473 3 458 X2011 7.2
## 474 3 464 X2011 7.2
## 475 3 486 X2011 8.4
## 476 3 512 X2011 8.3
## 477 3 530 X2011 6.9
## 478 3 534 X2011 5.5
## 479 3 538 X2011 7.3
## 480 3 542 X2011 6.4
## 481 3 549 X2011 7.4
## 482 3 569 X2011 6.4
## 483 3 572 X2011 9.8
## 484 3 577 X2011 6.1
## 485 3 581 X2011 5.6
## 486 3 584 X2011 6.0
## 487 3 597 X2011 8.0
## 488 3 616 X2011 9.5
## 489 3 647 X2011 7.2
## 490 3 660 X2011 6.8
## 491 4 591 X2011 11.0
## 492 4 595 X2011 10.2
## 493 4 603 X2011 3.2
## 494 4 612 X2011 4.2
## 495 4 618 X2011 5.4
## 496 4 619 X2011 11.1
## 497 4 623 X2011 5.2
## 498 4 632 X2011 6.9
## 499 4 641 X2011 7.6
## 500 4 645 X2011 9.7
## 501 4 646 X2011 7.8
## 502 4 648 X2011 8.8
## 503 4 654 X2011 11.1
## 504 4 657 X2011 9.7
## 505 4 661 X2011 11.2
## 506 4 663 X2011 8.3
## 507 4 677 X2011 7.2
## 508 4 678 X2011 4.6
## 509 4 682 X2011 5.6
## 510 5 1 X2011 6.5
## 511 5 37 X2011 7.2
## 512 5 38 X2011 3.4
## 513 5 41 X2011 6.3
## 514 5 49 X2011 8.2
## 515 5 64 X2011 6.8
## 516 5 71 X2011 3.9
## 517 5 72 X2011 4.9
## 518 5 85 X2011 6.5
## 519 5 88 X2011 5.8
## 520 5 101 X2011 7.5
## 521 5 114 X2011 4.6
## 522 5 120 X2011 6.2
## 523 5 126 X2011 7.2
## 524 5 145 X2011 3.1
## 525 5 150 X2011 5.8
## 526 5 155 X2011 6.1
## 527 5 166 X2011 6.0
## 528 5 177 X2011 4.3
## 529 5 206 X2011 4.5
## 530 6 129 X2011 7.0
## 531 6 257 X2011 7.7
## 532 6 276 X2011 5.8
## 533 6 303 X2011 5.7
## 534 6 322 X2011 5.1
## 535 6 349 X2011 8.7
## 536 6 350 X2011 5.6
## 537 6 355 X2011 6.0
## 538 6 370 X2011 6.2
## 539 6 454 X2011 7.1
## 540 6 725 X2011 3.2
## 541 6 766 X2011 5.2
## 542 6 812 X2011 7.0
## 543 6 817 X2011 6.9
## 544 6 844 X2011 4.5
## 545 6 863 X2011 6.1
## 546 6 868 X2011 6.1
## 547 6 896 X2011 7.5
## 548 6 899 X2011 6.4
## 549 6 901 X2011 5.0
## 550 6 917 X2011 6.5
## 551 7 924 X2011 7.0
## 552 7 963 X2011 4.0
## 553 7 970 X2011 7.7
## 554 7 977 X2011 7.7
## 555 7 979 X2011 6.6
## 556 7 1000 X2011 6.7
## 557 7 1069 X2011 5.3
## 558 7 1073 X2011 6.0
## 559 7 1087 X2011 5.3
## 560 7 1109 X2011 2.9
## 561 7 1140 X2011 5.7
## 562 7 1183 X2011 8.3
## 563 7 1188 X2011 9.5
## 564 7 1247 X2011 6.0
## 565 7 1286 X2011 8.0
## 566 7 1340 X2011 7.3
## 567 7 1358 X2011 8.3
## 568 7 1392 X2011 3.8
## 569 7 1477 X2011 5.5
## 570 7 1481 X2011 7.2
## 571 2 373 X2012 3.2
## 572 2 379 X2012 6.3
## 573 2 383 X2012 6.3
## 574 2 389 X2012 7.6
## 575 2 390 X2012 3.0
## 576 2 395 X2012 7.6
## 577 2 396 X2012 4.7
## 578 2 408 X2012 10.1
## 579 2 412 X2012 5.2
## 580 2 421 X2012 3.4
## 581 2 425 X2012 7.9
## 582 2 429 X2012 6.6
## 583 2 431 X2012 4.9
## 584 2 442 X2012 5.0
## 585 2 444 X2012 7.4
## 586 3 447 X2012 8.3
## 587 3 458 X2012 9.4
## 588 3 464 X2012 6.2
## 589 3 486 X2012 7.9
## 590 3 512 X2012 6.7
## 591 3 530 X2012 5.7
## 592 3 534 X2012 6.7
## 593 3 538 X2012 7.4
## 594 3 542 X2012 7.9
## 595 3 549 X2012 4.9
## 596 3 569 X2012 6.4
## 597 3 572 X2012 13.1
## 598 3 577 X2012 8.2
## 599 3 581 X2012 5.3
## 600 3 584 X2012 6.1
## 601 3 597 X2012 9.4
## 602 3 616 X2012 8.0
## 603 3 647 X2012 7.3
## 604 3 660 X2012 6.4
## 605 4 591 X2012 5.0
## 606 4 595 X2012 10.5
## 607 4 603 X2012 5.4
## 608 4 612 X2012 6.6
## 609 4 618 X2012 5.5
## 610 4 619 X2012 7.4
## 611 4 623 X2012 6.8
## 612 4 632 X2012 6.6
## 613 4 641 X2012 6.7
## 614 4 645 X2012 9.9
## 615 4 646 X2012 6.8
## 616 4 648 X2012 9.2
## 617 4 654 X2012 10.2
## 618 4 657 X2012 6.2
## 619 4 661 X2012 8.7
## 620 4 663 X2012 7.8
## 621 4 677 X2012 7.8
## 622 4 678 X2012 7.9
## 623 4 682 X2012 6.0
## 624 5 1 X2012 9.5
## 625 5 37 X2012 7.7
## 626 5 38 X2012 6.0
## 627 5 41 X2012 7.7
## 628 5 49 X2012 6.1
## 629 5 64 X2012 7.8
## 630 5 71 X2012 5.3
## 631 5 72 X2012 4.3
## 632 5 85 X2012 6.8
## 633 5 88 X2012 5.7
## 634 5 101 X2012 8.0
## 635 5 114 X2012 5.7
## 636 5 120 X2012 5.0
## 637 5 126 X2012 7.1
## 638 5 145 X2012 4.5
## 639 5 150 X2012 7.0
## 640 5 155 X2012 6.3
## 641 5 166 X2012 8.0
## 642 5 177 X2012 3.0
## 643 5 206 X2012 3.8
## 644 6 129 X2012 6.5
## 645 6 257 X2012 7.0
## 646 6 276 X2012 5.7
## 647 6 303 X2012 6.7
## 648 6 322 X2012 6.5
## 649 6 349 X2012 6.1
## 650 6 350 X2012 3.1
## 651 6 355 X2012 6.2
## 652 6 370 X2012 6.8
## 653 6 454 X2012 7.2
## 654 6 725 X2012 3.7
## 655 6 766 X2012 7.3
## 656 6 812 X2012 7.4
## 657 6 817 X2012 7.7
## 658 6 844 X2012 3.6
## 659 6 863 X2012 4.9
## 660 6 868 X2012 6.2
## 661 6 896 X2012 7.1
## 662 6 899 X2012 3.1
## 663 6 901 X2012 4.9
## 664 6 917 X2012 5.3
## 665 7 924 X2012 6.6
## 666 7 963 X2012 4.5
## 667 7 970 X2012 6.3
## 668 7 977 X2012 7.9
## 669 7 979 X2012 7.1
## 670 7 1000 X2012 5.8
## 671 7 1069 X2012 7.2
## 672 7 1073 X2012 8.7
## 673 7 1087 X2012 6.2
## 674 7 1109 X2012 2.4
## 675 7 1140 X2012 3.9
## 676 7 1183 X2012 7.7
## 677 7 1188 X2012 7.8
## 678 7 1247 X2012 4.8
## 679 7 1286 X2012 8.2
## 680 7 1340 X2012 8.4
## 681 7 1358 X2012 8.3
## 682 7 1392 X2012 4.8
## 683 7 1477 X2012 6.1
## 684 7 1481 X2012 7.0BACK TO WIDE
elongation_wide<-spread(elongation_long,year,length)Choose columns
elongation_long2<-gather(elongation,year,length,c(3:8))Visualise inter-annual variation in the growth of Empetrum hermaphroditum, we can quickly make a boxplot:
boxplot(length~year,data=elongation_long,
xlab="Year",
ylab="Elongation (cm)",
main="Annual growth of Empetrum hermaphroditum")