Good enough code

library(gerp)

ger_code()

Use ger_code() to create the R/ code folder in your projects:

The ger_code() creates the following files:

R/
  ├── data.R
  ├── import.R
  ├── model.R
  ├── tidy.R
  ├── visualize.R
  └── wrangle.R

You can choose to have regular R script headers or roxygen2 headers:

header = TRUE (default)

#' @title 
#' 
#' 
#' @description
#' 
#' @details
#' 
#' @importFrom
#' 
#' @examples 
#' 
#'

header = FALSE

#=====================================================================#
# This is code to create:
# Authored by and feedback to:
# MIT License
# Version:
#=====================================================================#

R/data.R

The R/data.R file should be used for documenting datasets in your project. See example below:

#' Title (dataset description)
#'
#' @format A dataset with variables:
#' \describe{
#'   \item{member}{Wu-Tang Clan Member Name}
#'   \item{name}{Wu-Tang Clan Given Name}
#'   \item{born}{Birth Year}
#'   \item{city}{Birth City}
#'   \item{alive}{Stil Alive?}
#' }
#' @source Link to data: https://en.wikipedia.org/wiki/Wu-Tang_Clan
#' (downloaded YYYY-MM-DD)
'wu_df'

This will create the .Rd document so your dataset is accessible in the Help pane.

Headers

Even if you’re not using roxygen2 tags, it’s a good idea to put a header on your code files. This helps collaborators (and you!) track what the script does.

gerp::ger_headr()
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#
# This is code to create:
# Authored by and feedback to:
# MIT License
# Version:
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#

Sections

gerp::ger_sect() will create a code section based on a name input:

gerp::ger_sect(name = 'import')
# <(+_+)> import ––+––+––+––+––+––+––+––––+––+––+––––+––+ ----

These are handy if you use RStudio’s outline feature: