Introduction to R Visualization

University of California, Santa Barbara


Feb 24 & 25, 2022

9:30 am - 12:30 pm

Instructors: Amanda Ho, David Hunter, Jon Jablonski

Helpers: Kristi Liu

Registration for this workshop opens on Friday, February 4th at 8:00am PST

Check what time registration opens in your timezone

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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: Feb 24 & 25, 2022. Add to your Google Calendar.

Requirements: Participants must have access to a computer 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


Day 1, February 24th

Before starting Pre-workshop survey
9:30 am Zoom and Carpentry Intro
9:45 amBefore We Start
10:00 amIntroduction to R
10:40 amBreak
10:50 amStarting with Data
11:20 amManipulating and Analyzing Data with tidyverse
12:20 pmReview
12:25 pm End Day one

Day 2, February 25th

9:30 amReview
10:00 amStarting with ggplot2
11:00 amBreak
11:10 amMore Tools with ggplot2
11:50 pmReview
12:00 pmPost-Workshop Survey
12:05 pm End Workshop


To participate in a Data Carpentry workshop, you will need access to software as 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.

Install the videoconferencing client

If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.

Set up your workspace

Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:

This blog post includes detailed information on how to set up your screen to follow along during the workshop.

R and RStudio


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


For everyone

Download the data

We will download the data directly from R during the lessons. However, if you are expecting problems with the network, it may be better to download the data beforehand and store it on your machine.

The data files for the lesson can be downloaded manually here: