Sep 29-30, 2017
9:00 am - 5:00 pm
Instructors: Paul Wolf, Carol Rowe, Betty Rozum, Binod Pokharel, Curtis Dyerson, Shawn Taylor
Helpers: Andrea Castillo, Bodie Weedop, Vishal Sharma, Sara Skindelien, Tanner Robison
Data 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: Room 154, Merrill-Cazier Library, 3000 Old Main Hill, Logan, UT 84321 . Get directions with OpenStreetMap or Google Maps.
When: Sep 29-30, 2017. Add to your Google Calendar.
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). They are also required to abide by Data Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organisers 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 paul.wolf@usu.edu for more information.
Surveys
Please be sure to complete these surveys before and after the workshop.
| Morning | 09:00 Data organization in spreadsheets |
| Morning | 10:30 Coffee break |
| 10:45 OpenRefine for data cleaning | |
| Morning | 12:00 Lunch break |
| Afternoon | 13:00 Data management with SQL |
| Morning | 14:30 Coffee break |
| Morning | 14:45 - 16:30 SQL continued and wrap-up |
| Morning | 09:00 Python for Ecologists |
| Morning | 10:30 Coffee break |
| Morning | 10:45 Continuation of Python for Ecologists |
| Morning | 12:00 Lunch break |
| Afternoon | 13:00 Continuation of Python for Ecologists |
| Afternoon | 14:30 Coffee break |
| Afternoon | 14:45 - 16:30 Continuation of Python for Ecologists and wrap-up |
wherejoinTo 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.
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.
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 a basic editor and the default that instructors use in the workshop. To install it, download the Data Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.
Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.
nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.
Others editors that you can use are Text Wrangler or Sublime Text.
nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.
Others editors that you can use are Gedit, Kate or Sublime Text.
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 Anaconda, an all-in-one installer.
Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.4 is fine).
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).
bash Anaconda3-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:
cd DownloadsThen, try again.
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).
SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons.
The Data Carpentry Windows Installer installs SQLite for Windows. If you used the installer to configure nano, you don't need to run it again.
SQLite comes pre-installed on Mac OS X.
SQLite comes pre-installed on Linux.
If you installed Anaconda, it also has a copy of SQLite
without support to readline.
Instructors will provide a workaround for it if needed.
For this lesson you will need OpenRefine and a web browser. Note: this is a Java program that runs on your machine (not in the cloud). It runs inside a web browser, but no web connection is needed.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It will not run correctly in Internet Explorer.
Download software from http://openrefine.org/
Create a new directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory by right-clicking and selecting "Extract ...".
Go to your newly created OpenRefine directory.
Launch OpenRefine by clicking google-refine.exe (this will launch a command prompt window, but you can ignore that - just wait for OpenRefine to open in the browser).
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It may not run correctly in Safari.
Download software from http://openrefine.org/.
Create a new directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory by double-clicking it.
Go to your newly created OpenRefine directory.
Launch OpenRefine by dragging the icon into the Applications folder.
Use Ctrl-click/Open ... to launch it.
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser.
Download software from http://openrefine.org/.
Make a directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory.
Go to your newly created OpenRefine directory.
Launch OpenRefine by entering ./refine into the terminal within the OpenRefine directory.
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.