May 16-18, 2022
9:00 am - 12:00 pm PST
Instructors: Seth Erickson, James Frew
Helpers: Kristi Liu, Jay Chi, Julien Brun
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Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. 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 "Good Enough 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 1312, Davidson Library, 525 U-Cen Rd, Santa Barbara, CA. Get directions with OpenStreetMap or Google Maps.
When: May 16-18, 2022. Add to your Google Calendar.
Requirements: Participants must have access to a computer with a Mac, Linux, or Windows operating system. See setup instructions.
Accessibility: We are committed to making this workshop accessible to everybody. For workshops at a physical location, 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.
Contact: Please email dreamlab@library.ucsb.edu 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.
| Setup | Download files required for the lesson | ||
| Day 1 | 09:00 | 1. Before we start | What is Python and why should I learn it? |
| 09:30 | 2. Short Introduction to Programming in Python |
How do I program in Python?
How can I represent my data in Python? |
|
| 10:05 | 3. Starting With Data |
How can I import data in Python?
What is Pandas? Why should I use Pandas to work with data? |
|
| 11:05 | Finish | ||
| Day 2 | 09:00 | 4. Indexing, Slicing and Subsetting DataFrames in Python |
How can I access specific data within my data set?
How can Python and Pandas help me to analyse my data? |
| 10:00 | 5. Data Types and Formats |
What types of data can be contained in a DataFrame?
Why is the data type important? |
|
| 10:45 | 6. Combining DataFrames with Pandas |
Can I work with data from multiple sources?
How can I combine data from different data sets? |
|
| 11:30 | Finish | ||
| Day 3 | 09:00 | 7. Data Workflows and Automation |
Can I automate operations in Python?
What are functions and why should I use them? |
| 10:30 | 8. Making Plots With plotnine |
How can I visualize data in Python?
What is ‘grammar of graphics’? |
|
| 12:00 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.