oRganized

oRganized-talk

This presentation will let you though a lot of different aspects of what you can do in R to make yourself happy, make sure that future you is happy, and avoid getting mad at past you. This presentation will have a quite small focus on the actual R code you will produce by having the focus be on how you interact with the R code itself, touching on topics such as style and reproducibility.

General Resources

R for Data Science
R Markdown: The Definitive Guide

Use Rstudio

Rstudio
Download Rstudio
Rstudio IDE Cheat Sheet including keyboard shortcuts

Change Settings

Ryan-Benz - Tune-up your Rstudio experience
Hadley Wickham on why the this setting isn't changed

RStudio Projects

R for Data Science - workflow projects
Project-oriented workflow

Folder Structure

Setting up a reproducible data analysis workflow in R
Andrew Tran - File organization best practices
An R-focused pipeline toolkit for reproducibility and high-performance computing

Paths

Jenny Bryan - On why one should use the here package
Jenny Bryan will burn down your house tweet
here package
Project-oriented workflow
fs package

Naming Things

Jenny Bryan - how to name files
Tidyverse - Style guide
styler package
lintr package

Once You Start Using R

What To Avoid

Project-oriented workflow
Hadley Wichham - If you use attach() you're doing it wrong #rstats
Why you shouldn't use rm(list=ls())

Using R Markdown

Convince me to use rmarkdown
R Markdown: The Definitive Guide
R Markdown Quick Tour
rticles package
R for Data Science - R Markdown

Naming Chunks

Pets or livestock? Naming your RMarkdown chunks
R code chunks and inline R code
Chunk options

Setup Chunk

setup chunk runs before any other code

Chunk Options

Chunk options

Style

Tidyverse style
formatr package

Documenting Code

Object documentation
roxygen2 package

Should You Write a Function

David Robinson - When you’ve written the same code 3 times, write a function

Testing

testthat package