Summer Carpentry Series: R Programming

University of California, Santa Barbara


Mondays and Tuesdays: August 17, 18, 24, 25, 2020 and September 1, 2020

9:00 am - 12:00 pm

Instructors: Rob Levenson, Jon Jablonski, Torin White

Helpers: Torin White, Kristi Liu, Sharon Solis, Mireia Valle

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General Information

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Good Enough Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting.

When: Mondays and Tuesdays: August 17, 18, 24, 25, 2020 and September 1, 2020. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Accessibility: We are dedicated to providing a positive and accessible learning environment for all. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you.

Contact: Please email for more information.

Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.

Code of Conduct

Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Collaborative Notes

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


Please excuse any broken links below, here is the link to the entire "R for Social Scientists" schedule. From there you can navigate to individual lessons.

Day 1: Aug 17

Before starting Pre-workshop survey
09:00 Zoom Intro
09:15 Overview of R & R Studio
10:00 BREAK
10:10 Introduction to R
11:00 BREAK
11:10 More Introduction to R

Day 2: Aug 18

09:00 Review of Day 1
09:15 Finish Introduction to R
09:45 BREAK
09:55 Starting with Data
10:45 BREAK
10:55 More Starting with Data
Day 2 Script Starting with Data Script

Day 3: Aug 24

09:00 Review of Week 1
09:20 Processing JSON Data
10:10 BREAK
10:20 Introduction to dplyr and tidyr
11:00 BREAK
11:10 More Introduction to dplyr and tidyr
Day 3 Script JSON JSON Data Processing
Day 3 Script DPLYR DPLYR Data Manipulation

Day 4: Aug 25

09:00 Review of Day 3
09:15 Data Visualization with ggplot2
10:00 BREAK
10:10 More Data Visualization with ggplot2
10:45 BREAK
10:55 And More Data Visualization with ggplot2
Day 4 Script Rob: Intro to ggplot2

Day 5: Sep 1

09:00 Review Workshop
09:20 Bring your own data
Before Signing Off Post-workshop survey



To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

1: R and RStudio

For this version we recommend at least R version 4.0 or later and RStudio 1.2


If you already have R and RStudio installed

If you don’t have R and RStudio installed


If you already have R and RStudio installed

If you don’t have R and RStudio installed


Follow the instructions for your distribution

from CRAN, they provide information to get the most recent version of R for common distributions. For most distributions, you could use your package manager (e.g., for Debian/Ubuntu run sudo apt-get install r-base, and for Fedora sudo yum install R), but we don’t recommend this approach as the versions provided by this are usually out of date. In any case, make sure you have at least R 3.2.

2: Install the Tidyverse

RStudio 'install packages' screen.

3: Test your installation

RStudio screen after running test script.