by Michael Chow, Rich Iannone
🗓️ August 12, 2024
⏰ 09:00 - 17:00
🏨 306 | Duwamish
✍️ pos.it/conf
This workshop is all about making tables for publication and display purposes. We believe that effective tables have these things in common:
- structuring that aids in the reading of the table
- well-formatted values, fitting expectations for the field of study
- styling that reduces time to insight and improves aesthetics
This is a 'bilingual' workshop that has materials both in R and Python. The gt package will be used when teaching in R and the Great Tables package is for the Python parts. We are flexible with regard to rebalancing the instruction to either the R or Python sides. Your feedback in class will let us know where more focus should placed.
This course is for you if you:
- have some experience with data analysis in R or Python
- often create reporting that involves summarizations of data
- were frustrated making tables for display purposes outside of R or Python
- found beautiful-looking tables in the wild and wondered: 'How could I do that?'
- Bring your laptop.
- Sign up for a GitHub account. (Create an account here.)
- Sign up for a Posit Cloud account. (Create an account here.)
| Time | Activity |
|---|---|
| 09:00 - 10:30 | Session 1: Coffee Table (Great Tables) |
| 10:30 - 11:00 | Coffee break |
| 11:00 - 12:30 | Session 2: Reactions Table (gt) |
| 12:30 - 13:30 | Lunch break |
| 13:30 - 15:00 | Session 3: Power Generation Table (gt) |
| 15:00 - 15:30 | Coffee break |
| 15:30 - 17:00 | Session 4: Make Your Own Excellent Tables |
Michael Chow, Senior Software Engineer, Posit
Michael is a data scientist and software engineer. He has programmed in Python and R for over a decade, and he obtained a PhD in cognitive psychology from Princeton University. His interests include statistical methods, skill acquisition, and human memory.
Richard Iannone, Senior Software Engineer, Posit
Richard is a software engineer and table enthusiast. He and R go way back and he's been getting better at writing code in Python too. For the most part, Rich enjoys creating open source packages in R and Python so that people can great things in their own work.
