datafairy

The datafairy grants you basic data handling wishes: The packages includes helper functions for creating minimalist codebooks or describing numeric and factor data.

Installation

You can install the development version of datafairy from GitHub with:

# install.packages("devtools")
devtools::install_github("lmwidmayer/datafairy")

Example

This is example shows how to make a codebook template from a flat dataframe:

library(datafairy)

## create a codebook
df <- data.frame(
  id = 1:4,
  condition = factor(LETTERS[1:4]),
  score = c(2.1, 4.0, NA, 3.3)
) # a dataframe that you want to document
cb <- mini_cb(df, auto.type = TRUE, content.type = TRUE)

print(cb)
#>        NAME     TYPE UNIT DESCRIPTION ANNOTATION
#> 1   CONTENT CODEBOOK                            
#> 2        id  integer                            
#> 3 condition   factor                            
#> 4     score  numeric

Write the codebook cb to a tabular file format or json and populate it with the descriptions of your data set:

• NAME: The column/ variable name of the input dataframe.
• TYPE: Data type of the variable: If auto.type = TRUE, the function will use R’s data types.
• UNIT: Unit of measurement.
• DESCRIPTION: Describe what the variable contains.
• ANNOTATION: Further comments on the variable.

Note that content.type = TRUE adds a row with the name CONTENT in which you can describe to which data set this codebook belongs.

Citation

citation("datafairy")
#> Um Paket 'datafairy' in Publikationen zu zitieren, nutzen Sie bitte:
#> 
#>   Widmayer L (2023). _datafairy: A tiny data handling assistant_. R
#>   package version 0.0.0.9003,
#>   <https://github.com/lmwidmayer/datafairy>.
#> 
#> Ein BibTeX-Eintrag für LaTeX-Benutzer ist
#> 
#>   @Manual{,
#>     title = {datafairy: A tiny data handling assistant},
#>     author = {Lisa Widmayer},
#>     year = {2023},
#>     url = {https://github.com/lmwidmayer/datafairy},
#>     note = {R package version 0.0.0.9003},
#>   }