This repo contains materials for the UO R Bootcamp: a 3-day introductory R workshop developed by the Department of Psychology at the University of Oregon.
The full website is available here: uorbootcamp2022.netlify.app
The UO R Bootcamp gives a gentle introduction to R and RStudio, transforming and visualizing data with the tidyverse, and the basics of R Markdown. It assumes no prior experience with R or any other programming language and is designed to get learners up and running with the most widely used tools for conducting reproducible data analysis in R, while emphasizing best practices for writing code and organizing project-oriented workflows. It also contains a curated list of resources relevant to each topic for those who want more opportunities for learning and practice.
Please contact Cameron S. Kay, the 2022 bootcamp coordinator, with any questions at [email protected].
Topics covered include:
- Basics of R, RStudio, & R Markdown
- Data Types & Structures
- Functions, Packages, & Debugging
- Piping
- Introduction to the Tidyverse
- Importing Data & Project-Oriented Workflows
- Data Wrangling with {dplyr}
- Data Tidying with {tidyr}
- Data Visualization with {ggplot2}
- Tips & Tricks
Much of the content was adapted from previous iterations of the R Bootcamp led by Brendan Cullen, Jessica Kosie and Cory Costello. Other content was adapted from a variety of sources, including R for Data Science, Modern Dive, Alison Hill's R Markdown for Medicine workshop, Michael Frank's R Markdown workshop, and Silvia Canelón's Intro to the Tidyverse presentation for R-Ladies Chicago.
This website was based on a template demo course website created by Alison Hill as part of an RStudio Webinar along with Desirée De Leon. Note boxes were created following a tutorial by Desirée De Leon. Some custom CSS was also borrowed from Emi Tanaka.
Slides were created using {xaringan} by Yihui Xie and {xaringanExtra} by Garrick Aden-Buie.
All artwork, unless otherwise noted, is by Allison Horst.
The code of conduct for the UO R Bootcamp was adapted from Cascadia R Conf.
The materials shared here are free and open source and may be shared and adapted under the Creative Commons License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
