Claudia Engel, Lori Ling, Linnea Shieh, João Rodrigues
Ashley Jester, Zac Painter, Darach Miller, Irina Trapido, Keith Bettinger, Josh Quan
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.
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).
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.
Accessibility: We are committed to making this workshop
accessible to everybody.
The workshop organizers have checked that:
The room is wheelchair / scooter accessible.
Accessible restrooms are available.
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.
Install R by downloading and running
this .exe file
Also, please install the
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.
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
Python is a popular language for
research computing, and great for general-purpose programming as
well. Installing all of its research packages individually can be
a bit difficult, so we recommend
an all-in-one installer.
Regardless of how you choose to install it,
please make sure you install Python version 3.x
(e.g., 3.6 is fine).
We will teach Python using the Jupyter notebook,
a programming environment that runs in a web browser. For this to work you will need a reasonably
up-to-date browser. The current versions of the Chrome, Safari and
Firefox browsers are all
(some older browsers, including Internet Explorer version 9
and below, are not).
Download the Python 3 installer for Linux.
(The installation requires using the shell. If you aren't
comfortable doing the installation yourself
stop here and request help at the workshop.)
Open a terminal window.
and then press
Tab. The name of the file you just downloaded should
appear. If it does not, navigate to the folder where you
downloaded the file, for example with:
Then, try again.
Press Return. You will follow the text-only prompts. To move through
the text, press Spacebar. Type yes and
press enter to approve the license. Press enter to approve the
default location for the files. Type yes and
press enter to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).
Close the terminal window.
When you're writing code, it's nice to have a text editor that is
optimized for writing code, with features like automatic
color-coding of key words. The default text editor on macOS and
Linux is usually set to Vim, which is not famous for being
intuitive. If you accidentally find yourself stuck in it, hit
the Esc key, followed by :+Q+!
(colon, lower-case 'q', exclamation mark), then hitting Return to
return to the shell.