controller is a collection of functions for working with controlled vocabularies in R. It introduces the control() verb, which recodes values in a vector using a lookup table of preferred and variant terms (a thesaurus).
Installation
You can install the development version of controlled from GitHub using the remotes package:
remotes::install_github("joeroe/controller")Example
A common data-tidying problem is standardising variant terms for the same concept. Imagine we have a dataset that uses a number of different names for shades of the same colour. As data analysts, we naturally want to recode the data to eliminate this messy creativity, for example using dplyr::recode():
library(dplyr, warn.conflicts = FALSE)
shades <- c("daffodil", "purple", "magenta", "azure", "navy", "violet")
recode(shades,
daffodil = "yellow",
purple = "purple",
magenta = "pink",
azure = "blue",
navy = "blue",
violet = "purple")
#> [1] "yellow" "purple" "pink" "blue" "blue" "purple"But recoding this way can be tedious, especially if there are a large number of terms. With control(), we can instead use a data frame containing a thesaurus to replace the values:
library(controller)
data("colour_thesaurus")
control(shades, colour_thesaurus)
#> Replaced values:
#> ℹ daffodil → yellow
#> ℹ azure → blue
#> ℹ navy → blue
#> ℹ violet → purple
#> Warning: Some values of `x` were not matched in `thesaurus`:
#> ✖ magenta
#> [1] "yellow" "purple" "magenta" "blue" "blue" "purple"control() also supports fuzzy matching, removing the need to exhaustively list variants for common causes of differing terminology. For example, to perform a case insensitive match to the thesaurus:
shades <- toupper(shades)
control_ci(shades, colour_thesaurus)
#> Replaced values:
#> ℹ DAFFODIL → yellow
#> ℹ PURPLE → purple
#> ℹ AZURE → blue
#> ℹ NAVY → blue
#> ℹ VIOLET → purple
#> Warning: Some values of `x` were not matched in `thesaurus`:
#> ✖ MAGENTA
#> [1] "yellow" "purple" "MAGENTA" "blue" "blue" "purple"