🎉 This week's RWeekly issue, curated by @batoolmm.bsky.social , includes the following highlights:

➡️ Interactive Pivot Tables and Charts from R (Eli Eydlin)
➡️ Orchestrate multiple LLM agents into coordinated workflows (Arnold Kakas)

rweekly.org/2026-W16.html

#RStats #newsletter #reading #learning

For today's #30DayChartChallenge, I used the {marimekko} package 📦.
Day 0️⃣3️⃣ | Comparisons | Mosaic
Code available here: github.com/KittJonathan...
#RStats #tidyverse #code #datavis

rewrites.bio - A manifesto for bioinformatics Principles for responsible AI-assisted rewriting of bioinformatics tools.

I'm both excited and a little terrified. It feels like a wave of AI-assisted tool rewrites is coming to bioinformatics whether we like it or not.

We figured that the best we can do is to try to get ahead of it, so we wrote down some principles for doing it responsibly: rewrites.bio

Second day of the 2026 #30DayChartChallenge, tried the {ggpop} package.
Day 0️⃣2️⃣ | Comparisons | Pictogram
Code available here : github.com/KittJonathan...
#RStats #tidyverse #code #datavis

The 2026 #30DayChartChallenge kicks off today!

For this year's challenge, I'll use the Palmer Penguins dataset as often as possible.

Day 0️⃣1️⃣ | Comparisons | Part-to-whole

Code available here : github.com/KittJonathan...

#RStats #tidyverse #code #datavis

Thanks @nrennie.bsky.social, I was searching for ideas for the #30DayChartChallenge :-)

Weekly Recap (March 27, 2026): NSF AI readiness, AGI forecasts, White House AI policy framework, NIH genomics technology, statistical rethinking, context anchoring, #Rstats + Quarto, NOFO graveyard & grant terminations, organ sacks, YYiki. blog.stephenturner.us/p/weekly-rec...

You're more than welcome @ivelasq3.bsky.social, thanks for the great content! I'm pondering the idea of preparing a "dplyr updates" workshop in my lab :)

LLM agents for biological intelligence across genomics, proteomics, spatial biology, and biomedicine academic.oup.com/bib/article/... 🧬💻🧪

R Weekly 2026-W13 What’s new in dplyr, Atmospheric simulation Weekly news in the R community

The latest RWeekly issue is out! This week's highlights include @ivelasq3.bsky.social 's @rladiesrome.bsky.social tutorial showing the new features in {dplyr} v1.2.0, and @tylermw.com 's post on Atmospheric Simulation in #RStats.

rweekly.org/2026-W13.html

Fantastic, thanks!

Will there be a video released?

Just posted on the Github issue

Excited to share this preprint that describes my latest work on using GPUs to accelerate processing of RNA-seq data.

The title says it all: "RNA-seq analysis in seconds using GPUs" now on biorxiv www.biorxiv.org/content/10.6... and github github.com/pachterlab/k...

Figure 1 shows they key result

Octopurrr
l> another day

I've just made live the updated website that accompanies my R book (www.discovr.rocks) - it's mostly finished: almost all of the chapter solutions/task solutions are done, data are live, updated info about the `discovr` package of interactive tutorials, and it's had a face lift.

mlu-explain.github.io have some pretty interesting stuff

rix, my package that leverages #Nix to provide reproducible data science environments for #RStats (and #python and #julia) is in the top 10 starred ropensci packages!

that’s pretty cool

Well done!! 🎉

Great idea :-)

Shiny in Production 2025 - YouTube Shiny in Production 2025 showcases real world lessons from teams deploying and maintaining Shiny applications at scale. Topics include infrastructure, DevOps...

The recordings from Shiny in Production 2025 are now available.

Talks from speakers around the world on how they use Shiny in R and Python to solve real-world data problems.

Watch the sessions:
youtube.com/playlist?lis...

Just received Josh Starmer's latest book. Great way to dig deeper into some of his videos' concepts!
#Stats

#rstats filter_out is good

`dplyr::if_else()` and `dplyr::case_when()` are up to 30x faster dplyr 1.2.0 comes with much faster and more memory efficient `if_else()` and `case_when()` functions!

Last week we released dplyr 1.2.0, but we left off something VERY important 🙂

`dplyr::if_else()` and `dplyr::case_when()` are now up to 30x faster and use 10x less memory!

We dive into how we achieved these numbers in this new #rstats post!

tidyverse.org/blog/2026/02...

Looks great @emilhvitfeldt.bsky.social ! Working on new tutorials at the moment, will have to try those out !

#TidyTuesday week 05, exploring the Edible Plants Database.
Code available here: github.com/KittJonathan...
#RStats #Plants #Datavis #Code

Very nice!

Inscription faite ! Hâte de participer à ces #RencontresR pour la toute première fois. Il ne me reste plus qu'à soumettre un résumé ☺️
rr2026.sciencesconf.org
#RStats #code #conf

Home Learn R, R tutorials, R resources, blog posts and the latest updates about the statistical programming R language.

This week's Rweekly issue is out!
#RStats
rweekly.org

#rstats I've given a workshop a few days ago on handling large data (think tens to hundreds of millions of rows) with Polars in Python and in R.

Here are my introductory slides: brussels-large-data-r-python.etiennebacher.com

And the associated repo: github.com/etiennebache...