Date: Friday March 9, 2018
Location: Yale University, Center for Industrial Ecology
Details: In this one day workshop we will introduce the R programming language with a focus on tidy data, reproducibility, and version control with Git and Github. Attendees should leave with some basic skills in R, be able to create a reproducible research document in markdown, and know the basics of how to use git and GitHub. Our examples will focus on data visualization and examples from industrial ecology.
For this workshop, we will be using R, RStudio, and Git and all attendees should have these installed and working prior to the workshop. The best instructions I know of for R and Git are the Software Carpentry workshop set up instructions so I will rely on those.
If you follow these directions you should have a working install of both Git and R. They do also point you to RStudio in the R set up instructions. If you followed along there you might have also installed RStudio. If you did not or need some more guidance here are some additional details.
- Go to the RStudio page for the Desktop downloads
- Select from the "Installers for Supported Platforms" for your operating system. The two most likely will be:
- Using the installer, install RStudio how you normally would install any application on your computer.
Last thing to take care of is to make sure you have a GitHub account set up. The sign up is available at https://github.com/
| Time | Subject |
|---|---|
| 9:30 AM - 10:00 AM | Introductions and Checking Set Ups |
| 9:45 AM - 10:00 AM | Motivationals |
| 10:00 AM - 10:30 AM | RStudio |
| 10:30 AM - 11:30 AM | R Basics |
| 11:30 AM - Noon | Reproducible Research with R Markdown |
| Noon - 1:00 PM | LUNCH |
| 1:00 PM - 2:00 PM | Tidy Data in R |
| 2:00 PM - 3:00 PM | Data Visualization with ggplot2 |
| 3:00 PM - 4:00 PM | Git and GitHub |
| 4:00 PM - 4:30 PM | Miscellaneous |
- Inspiration on how to use GitHub for a lab/research group
- Jeff Leek: Good stuff on a number of topics, all with an open science bent.
- Earth Lab at University of Colorado
- Wee Ecology
- Lab for Data Intensive Biology
- Industrial Ecology Links