Data Carpentry workshops are designed for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data. We will cover data organization in spreadsheets, data cleaning, basic SQL syntax, the Shell command line, and Python for data analysis and visualization using examples from biology. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.
Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.Please visit Our Workshop Etherpad for the links and materials being used and shared during the workshop and to interact with workshop participants.
Instructors: Leah Wasser, Mariela Perignon
Who: The course is aimed at faculty, research staff, postdocs, graduate students, advanced undergraduates, and other researchers in any field. No prior computational experience is required.
Requirements: Data Carpentry's teaching is hands-on, so participants are encouraged to bring in and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop. (We will provide instructions on setting up the required software several days in advance, and the classroom will have computers with the software installed). There are no pre-requisites, and we will assume no prior knowledge about the tools. Participants are required to abide by Software Carpentry's Code of Conduct.
Contact: Please email email@example.com for questions and information not covered here.
Data Carpentry is supported by the Gordon and Betty Moore Foundation and a partnership of several NSF-funded BIO Centers (NESCent, iPlant, iDigBio, BEACON and SESYNC) and Software Carpentry, and is sponsored by the Data Observation Network for Earth (DataONE). The structure and objectives of the curriculum as well as the teaching style are informed by Software Carpentry.
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. Once you are done installing the software listed below, please go to this page, which has instructions on how to test that everything was installed correctly.
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 Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by ':q!' (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.
nano is the editor installed by the Software
Carpentry Installer, it is a basic editor integrated into the
Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). Please ask your instructor to help you do this.
Kate is one option for
Linux users. In a pinch, you can use
should be pre-installed.
Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.
Install Git for Windows by downloading and running the installer. This will provide you with both Git and Bash in the Git Bash program.
It installs and configures
nano (Among other things)
This installer requires an active internet connection.
After installing Git Bash:
The default shell in all versions of Mac OS X is bash, so no
need to install anything. You access bash from the Terminal
/Applications/Utilities). You may want to keep
Terminal in your dock for this workshop.
The default shell is usually
bash, but if your
machine is set up differently you can run it by opening a
terminal and typing
bash. There is no need to
Python is a popular language for scientific computing, and great for general-purpose programming as well. Installing all of its scientific 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 2.x and not version 3.x (e.g., 2.7 is fine but not 3.4). Python 3 introduced changes that will break some of the code we teach during the workshop.
We will teach Python using the IPython 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 supported (some older browsers, including Internet Explorer version 9 and below, are not).
We recommend the all-in-one scientific Python installer Anaconda. (Installation requires using the shell and if you aren't comfortable doing the installation yourself just download the installer and we'll help you at the boot camp.)
bash Anaconda-and then press tab. The name of the file you just downloaded should appear.
yesand press enter to approve the license. Press enter to approve the default location for the files. Type
yesand press enter to prepend Anaconda to your
PATH(this makes the Anaconda distribution the default Python).