
Issue 2026-W05 Highlights
From R Weekly Highlights by Eric Nantz
January 28, 2026 · 40 min · Episode 219
About this episode
This episode discusses the challenges LLMs face in interpreting data visualizations and highlights a new Shiny app for the podcast.
The way LLMs can be a little stubborn when interpreting data visualizations, bringing new meaning to digging for your data and learning along the way, and the latest addition to the futureverse that seems too good to be true, but it is real! Plus an amazing Shiny app tailored made for this very podcast. Episode Links This week's curator: Jonathan Kitt - @jonathankitt.bsky.social (Bluesky) LLMs interpret plots well, until expectations interfere Students, software, and soil flux futurize: Parallelize Common Functions via a "Magic" Touch Entire issue available at rweekly.org/2026-W05 Supplement Resources {bluffbench} https://simonpcouch.github.io/bluffbench/ {neonSoilFlux}: An R package for continuous sensor-based estimation of soil CO2 fluxes https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210x.70216 Building an R Weekly Highlights Podcast Assistant! https://jokasan.github.io/r-weekly_chatbot/ Supporting the show Use the contact page at https://serve.podhome.fm/custompage/r-weekly-highlights/contact to send us your feedback R-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First…
People in this episode
Host: Eric Nantz
Topics covered
- data visualization
- LLMs
- Shiny app
- soil CO2 flux
- podcast highlights
Keywords
- LLMs
- data visualization
- Shiny app
- soil flux
- R Weekly Highlights
Mentioned in this episode
Organizations: R Weekly Highlights, Bluesky, Wiley, Podcastindex.org, Alby, value4value.info
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