April 18, 2018
1:00 pm - 5:00 pm
Instructors: Catherine DeRose, Joshua Dull, Kate Nyhan
This workshop is adapted from materials developed by Software Carpentry.
This hands-on workshop will cover basic concepts and tools, including program design and task automation in Python. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
Who: The course is aimed at graduate students and other researchers, but open to all members of the Yale community (students, faculty, and staff). You don't need to have any previous knowledge of the tools that will be presented at the workshop.
When: April 18, 2018. 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 Software Carpentry's Code of Conduct.
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.
|1:00 pm||Introductions & Logistics|
|1:20 pm||Analyzing Data|
|2:00 pm||Repeating Actions with Loops|
|2:30 pm||Storing Multiple Value in Lists|
|3:10 pm||Analyzing Data from Multiple Files|
|3:30 pm||Making Choices|
|4:10 pm||Creating Functions|
|4:40 pm||Errors, Debugging, and Wrap-up|
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
To participate in this workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
Software Carpentry maintains a list of common issues that occur during installation that may be useful on the Configuration Problems and Solutions wiki page.
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., 3.6 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 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.
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).
In preparation for this lesson, you will need to download two zipped files and place them in the specified folder:
To start the notebook server, open a terminal or git bash and execute the command: 'jupyter notebook'. Then create a new notebook using the drop-down menu on the right to select 'Python 3 notebook'.