Mon Nov 11 2024 and Mon Nov 18, 2024
13:00 pm - 16:30 pm
Instructors: Rachel Alcraft
Helpers: tbc
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.
Want to learn more and stay engaged with The Carpentries? Carpentries Clippings is The Carpentries' biweekly newsletter, where we share community news, community job postings, and more. Sign up to receive future editions and read our full archive: https://carpentries.org/newsletter/
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: Chelsea: Lecture theatre. Get directions with OpenStreetMap or Google Maps.
When: Mon Nov 11 2024 and Mon Nov 18, 2024; 13:00 pm - 16:30 pm 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 rachel.alcraft@icr.ac.uk 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.
| 13:00-13:15 | Setup Instructions + Pre-workshop survey | Setup, ensure everything works, fill out survey |
| 13:15-13:30 | 1. Running and Quitting | How can I run Python programs? |
| 13:30-13:50 | 2. Variables and Assignment | How can I store data in programs? |
| 13:50-14:10 | 3. Data Types and Type Conversion | What kinds of data do programs store? How can I convert one type to another? |
| 14:10-14:35 | 4. Built-in Functions and Help | How can I use built-in functions? How can I find out what theydo? What kind of errors can occur in programs? |
| 14:35-14:50 | 5. Morning Coffee | |
| 14:50-15:10 | 6. Libraries | How can I use software that other people have written? How can I find out what that software does? |
| 15:10-15:30 | 7. Reading Tabular Data into DataFrames | How can I read tabular data? |
| 15:30-16:00 | 8. Pandas DataFrames | How can I do statistical analysis of tabular data? |
| 16:00-16:30 | 9. Plotting | How can I plot my data? How can I save my plot for publishing? |
| 13:00-13:15 | Setup and make sure all still works | |
| 13:15-13:35 | 11. Lists | How can I store multiple values? |
| 13:35-14:00 | 12. For Loops | How can I make a program do many things? |
| 14:00-14:25 | 13. Conditionals | How can programs do different things for different data? |
| 14:25-14:40 | 14. Looping Over Data Sets | How can I process many data sets with a single command? |
| 14:40-14:55 | 15. Afternoon Coffee | |
| 14:55-15:20 | 16. Writing Functions | How can I create my own functions? |
| 15:20-15:50 | 17. Variable Scope | How do function calls actually work? How can I determine where errors occurred? |
| 15:50-16:10 | 18. Programming Style | How can I make my programs more readable? How do most programmers format their code? How can programs check their own operation? |
| 16:10-16:30 | 19. Wrap-Up | What have we learned? What else is out there and where do I find it? |
| 16:30 | 20. Post-workshop Survey | How did the class go? |
To participate in a Software Carpentry workshop, you will need access to software and data 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.
Please check the "Getting the Data section of" page of the lesson homepage for instructions to follow to obtain the data you will need to follow the lesson.
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).