May 4 and 11, 2020
10:00 - 17:00
Instructors: Anat Melamed, Amit Mandal, Kiana West, Elzbieta Lauzikaite
Helpers: Amit Mandal, John Pinney, Anat Melamed, Kiana West, Elzbieta Lauzikaite, Adesola Bello, Helen Kiik, Jonas Mackerodt
Unfortunately, the workshop is now fully booked. You can put your name on the waiting lists.
May 11 (R for plotting and data analysis)
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. 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 "Best 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: Zoom workshop.
When: May 4 and 11, 2020. Add to your Google Calendar.
Requirements: Participants must have 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). Headphones and microphone are recommended.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email k.michalickova@imperial.ac.uk for more information.
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.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
| 10:00 - 13:00 | R for reproducible scientific analysis 1 introduction to R and RStudio, project management with RStudio, seeking help, data structures break at 15:30 |
| 14:00 - 17:00 | R for reproducible scientific analysis 2 exploring data frames, subsetting data, control flow break at 15:30 |
| 10:00 - 13:00 | R for reproducible scientific analysis 3 plotting with ggplot, data manipulation with tidyverse and dplyr break at 15:30 |
| 14:00 - 17:00 | R for reproducible scientific analysis 4 R markdown and producing reports with knitr, putting it all together - a case study break at 15:30 |
To participate in a Software 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.
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.