Oct 15-16 2024
9:00 am - 3:30 pm CEST
Instructors: Federico Bianchini, Andrea Dale Wefring, Jeanne Cheneby
Helpers: Pubudu Saneth Samarakoon
The Carpentries project comprises the Software Carpentry, Data Carpentry, and Library Carpentry communities of Instructors, Trainers, Maintainers, helpers, and supporters who share a mission to teach foundational computational and data science skills to researchers.
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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: DSC-Oasen, Georg Sverdrups Hus, Blindern, Oslo. Get directions with OpenStreetMap or Google Maps.
When: Oct 15-16 2024; 9:00 am - 3:30 pm CEST 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).
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
We are dedicated to providing a positive and accessible learning environment for all. We do not require participants to provide documentation of disabilities or disclose any unnecessary personal information. However, we do want to help create an inclusive, accessible experience for all participants. We encourage you to share any information that would be helpful to make your Carpentries experience accessible. To request an accommodation for this workshop, please fill out the accommodation request form. If you have questions or need assistance with the accommodation form please email us.
Glosario is a multilingual glossary for computing and data science terms. The glossary helps learners attend workshops and use our lessons to make sense of computational and programming jargon written in English by offering it in their native language. Translating data science terms also provides a teaching tool for Carpentries Instructors to reduce barriers for their learners.
Contact: Please email contact-us@carpentry.uio.no or fredebi@uio.no for more information.
Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.
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.
Please be sure to complete these surveys before and after the workshop.
| Before | Pre-workshop survey |
| 09:00 | Getting started with Python and jupyterlab |
| 10:15 | Morning break |
| 10:30 | Variables and types |
| 11:45 | Lunch break |
| 12:15 | Functions and variables |
| 13:30 | Afternoon break |
| 13:45 | Pandas: working with data frames in Python pt1 |
| 15:00 | Wrap-up |
| 15:30 | END |
| 09:00 | Pandas: working with data frames in Python pt2 |
| 10:15 | Morning break |
| 10:30 | Plotting in Python |
| 11:45 | Lunch break |
| 12:15 | List and Loops in Python |
| 13:30 | Afternoon break |
| 13:45 | Conditionals |
| 15:00 | Wrap-up and Q&A |
| 15:20 | Post-workshop Survey |
| 15:30 | END |
To participate in a Software Carpentry workshop, you will need access to software as 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.
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 (Jupyter Notebook will be installed by Anaconda). 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 to autocomplete the full file name. The name of file you just downloaded should appear.
yes and press enter to approve the license.
Press Enter (or Return)
to approve the default location
for the files.
Type yes and press
Enter (or Return)
to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).