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rdataframedplyrrecode

Recode a column of numercial values to a new column of text values in R


In R, in a data frame, I want to take the code number of a tree species in one column and create a new column in the data frame with recoded text name of the species like below. I can create a matrix of tree name = code number, but how do I apply this to a long and mixed column of just numerical values?

> treeco <- c(4, 3, 4, 5, 3, 2, 2, 1, 4)
> spcode <- c("oak" = 1, "ash" = 2, "elm" = 3, "beech" = 4, "hazel" = 5)
> treesp <- data.frame(spcode)
> treesp
      species
oak         1
ash         2
elm         3
beech       4
hazel       5

This is the solution I am looking for:

  treeco spcode
1      4  beech
2      3    elm
3      4  beech
4      5  hazel
5      3    elm
6      2    ash
7      2    ash
8      1    oak
9      4  beech

Solution

  • base R

    data.frame(treeco, answer = names(spcode)[treeco])
    #   treeco answer
    # 1      4  beech
    # 2      3    elm
    # 3      4  beech
    # 4      5  hazel
    # 5      3    elm
    # 6      2    ash
    # 7      2    ash
    # 8      1    oak
    # 9      4  beech
    

    dplyr

    It can be slightly confusing when a column-name matches one in the environment, so for the sake of demonstration I'll rename treeco in the tibble so that it is clear which is being used.

    library(dplyr)
    tibble(tc = treeco) %>%
      mutate(answer = names(spcode)[tc])
    # # A tibble: 9 x 2
    #      tc answer
    #   <dbl> <chr> 
    # 1     4 beech 
    # 2     3 elm   
    # 3     4 beech 
    # 4     5 hazel 
    # 5     3 elm   
    # 6     2 ash   
    # 7     2 ash   
    # 8     1 oak   
    # 9     4 beech 
    

    There's another method that allows you to bring in much more than one extra column: the join/merge.

    treecodes <- data.frame(code = spcode, tree = names(spcode))
    set.seed(42)
    treecodes$rand <- sample(100, size = nrow(treecodes), replace = TRUE)
    treecodes
    #       code  tree rand
    # oak      1   oak   49
    # ash      2   ash   65
    # elm      3   elm   25
    # beech    4 beech   74
    # hazel    5 hazel  100
    trees <- data.frame(code = treeco)
    trees
    #   code
    # 1    4
    # 2    3
    # 3    4
    # 4    5
    # 5    3
    # 6    2
    # 7    2
    # 8    1
    # 9    4
    trees %>%
      left_join(treecodes, by = "code")
    #   code  tree rand
    # 1    4 beech   74
    # 2    3   elm   25
    # 3    4 beech   74
    # 4    5 hazel  100
    # 5    3   elm   25
    # 6    2   ash   65
    # 7    2   ash   65
    # 8    1   oak   49
    # 9    4 beech   74
    

    For more information on joins/merges, see How to join (merge) data frames (inner, outer, left, right) and What's the difference between INNER JOIN, LEFT JOIN, RIGHT JOIN and FULL JOIN?.