knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
Quickly and easily label your data using codebooks saved as a YAML text file.
remotes::install_github("nt-williams/codebreak")
or
# Install 'codebook' from 'nt-williams' universe install.packages('codebreak', repos = 'https://nt-williams.r-universe.dev')
some_data <- data.frame( x = c(1, 2, 5, 3, 4, 1), y = c(0, 1, 1, 0, 1, 9), z = c(5.2, 3.1, 5.6, 8.9, 9.0, 7.2), w = c(1, 1, 0, 1, 1, 1) )
Codebooks are created as YAML text files and are saved in the project directory (or somewhere else) as codebook.yml
(or as something else).
x: label: Variable X # include meaningful variable descriptions cb: 1: These # convert variable codes to labels 2: Are 3: Random 4: Character 5: Labels "y": label: Variable Y cb: &binary # reduce repetition with anchors 0: "No" 1: "Yes" 9: null # account for coded missing values z: label: Variable Z w: label: Variable W cb: *binary
Import and apply the codebook to the data:
cb <- codebreak::Codebook$new(system.file("codebook.yml", package = "codebreak")) cb cb$decode(some_data)
Rename columns based on the codebook labels:
cb$label(some_data)
Apply the codebook and rename columns:
cb$decode(some_data, label = TRUE)
labelled
packagedecode()
and label()
can return data with the codebook applied using the labelled
package by setting as_labelled = TRUE
.
some_data <- tibble::as_tibble(some_data) cb$decode(some_data, as_labelled = TRUE)
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