Online
Mon/Wed, June 22-July 1, 2020
1:00 - 2:30 pm
Instructors: Yuanxi Fu, Sébastien Vigneau, Stanley Yang, Sue McClatchy
Helpers: Selcan Aydin, Alexis Catherine Garretson, Amnah Siddiqa
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 infromation you will need to connect to this meeting.
When: Mon/Wed, June 22-July 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.). 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 susan.mcclatchy@jax.org for more information.
Everyone who participates in Carpentries activities is required to conform to the Code of Conduct.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
| 13:00 | Workshop overview and introductions |
| 13:45 | Before we start |
| 14:00 | Introduction to R |
| 14:25 | Wrap-up |
| 14:30 | END |
| 13:00 | Introduction to R (continued) |
| 14:00 | Starting with data |
| 14:25 | Wrap-up |
| 14:30 | END |
| 13:00 | Manipulating, analyzing and exporting data with tidyverse |
| 14:25 | Wrap-up |
| 14:30 | END |
| 13:00 | Data visualization with ggplot2 |
| 14:25 | Wrap-up |
| 14:30 | END |
To participate in a 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.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager (e.g. for Debian/Ubuntu
run sudo apt-get install r-base and for Fedora run
sudo dnf install R). Also, please install the
RStudio IDE.