Best Practices

Last updated: January 18, 2021

These are my current best practices for working in R:

• Prefer tidyverse methods and idioms when there are multiple ways of coding something.
• Follow the tidyverse coding style guide.
  • You can use lintr to automatically flag code that doesn’t conform to the style guide.
• Use renv for dependency management.
• Use RStudio projects to make it easy to re-open a given project.
• Use the here package rather than using setwd() to define a working directory.
• Use tidyverse pipes whenever possible, as opposed to lots(of(nested(functions()))).

• Prefer writing in R Markdown notebook to vanilla R scripts, unless there is a good reason why R Markdown doesn’t make sense.

  • Use the remedy add-in to RStudio to help with writing Markdown efficiently.

  • Use these metadata settings for RMarkdown:

    title: "Some title"
    output:
      html_document:
        df_print: paged
        toc: yes
        toc_float:
          collapsed: false
          smooth_scroll: false
        number_sections: true
        theme: yeti
      html_notebook:
        toc: yes

• For plots, use the BBC’s package on top of ggplot2 as a starting point.

Other Resources

• Efficient programming in R
• R for Data Science

ℹ️ This page is part of my knowledge base for R, the popular statistical programming language. I attempt to use idiomatic practices with the tidyverse collection of packages as much as possible. If you have suggestions for ways to improve this code, please contact me or use the survey link below..