Quick Start Guide for R

Have you decided you’d like to learn R, but aren’t sure where to start? This page will give you some guidance about some of the resources that are available, on this site and beyond!

Arcus Education has a variety of articles and webinars to help you get started. The following is a suggested order, but you can always start in the middle or skip around depending on your experience level and preference!

• Getting started (installing R and learning the basics):
  • Webinar: Demystifying R- R for the Absolute Beginner
  • R 4 Beginners: Chapter 1
  • Cloud Tools for the Unconvinced- This article has info about RStudio.cloud, a version of RStudio that you don’t have to download, as well as publicly-available datasets to practice with.
  • R 4 Beginners: Chapter 2
  • Swirl: Learn R in R
  • Webinar: The Art of Learning R- Getting Started in Data with Zero Prior Experience
• Reproducible analysis
  • R Lab for Beginners
  • Why Use Literate Statistical Programming?
  • Scripted Analysis for Reproducibility
  • Literate Statistical Programming
  • R Markdown 101
  • Webinar: R Markdown
• Creating visualizations:
  • Base R Plotting
  • ggplot Overview
  • R 4 Beginners: Chapter 3
  • R 4 Beginners: Chapter 4
  • Webinar: Intermediate Data Visualization in R
• Data transformation:
  • Data Combining in R
  • Date Pairing in R
• “Intermediate” R topics:
  • Code Readability (useful for R or any other programming language!)
  • Ordinary Linear Regression in R
  • Tiny Munge
  • Sparklines in ggplot2
  • Customizing ggplot2 with ggThemeAssist
  • When R Gets Too Helpful
  • Regex 101 (also known as regular expressions, regex are not R-specific- but can be very useful!)

Besides the articles and webinars available here, there are many more resources out there! Here are a few of our favorites:

• R for Data Science- A free online book by Hadley Wickham and Garrett Grolemund that teaches data science using R and starts from the very beginning.
• RStudio primers- They have bite-sized lessons starting with programming basics and going through topics like writing reproducible reports and making web apps.
• R-Bootcamp- Similar to the primers, the R-Bootcamp has a lot of lessons centered around using ggplot2 and dpylr, which will help you practice data science skills in R.

And what about when you’ve worked through all of this, and are ready for the next steps?

• Join the CHOP R User Group, where you’ll become part of a supportive community of other R users at all levels of R expertise.
• Start your own project! Try automating a work task (start small!), or ask a research question using some public data sources like OpenDataPhilly, the Census Bureau, or Kaggle.
• Need more personalized advice? Ask for an educational consult by emailing dlarcuseducation@email.chop.edu.

Good luck on your R journey!