controller/README.Rmd at main · joeroe/controller · GitHub

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---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# controller

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**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 latest release of controller [from CRAN](https://cran.r-project.org/package=controller) with:

```{r install, eval=FALSE}
install.packages("controller")
```

Or the development version from GitHub using the [remotes](https://remotes.r-lib.org/) package:

```{r install-dev, eval=FALSE}
# install.packages("remotes")
remotes::install_github("joeroe/controller")
```

## Usage

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()](https://dplyr.tidyverse.org/reference/recode.html):

```{r eg-dplyr}
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")
```

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:

```{r eg-controller}
library(controller)
data("colour_thesaurus")

control(shades, colour_thesaurus)
```

`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:

```{r eg-ci}
shades <- toupper(shades)
control_ci(shades, colour_thesaurus)
```