The new {sumvar} #RStats 
is an interesting new entry to the R exploratory data analysis landscape. It aims to "rapidly summarise and visualise variables with one-line commands, bringing the brilliant tab and sum functions from stata, to R," says author Alex Stockdale. On CRAN. #EDA
https://alstockdale.github.io/sumvar/
wxdata |> dist_sum(avg_temp) produced:
Nothing is better than relaxing on a hot summer Friday night, sipping a cold drink, and enjoying a beautiful sunset accurately rendered (as if seen from a jet airliners cruising altitude while on a red eye) in your favorite statistical programming language 
Hey! Some time ago I have joined The R Journal as the Associate Editor 
I have already worked on some papers and I am thrilled to contribute to this community and facilitate publication of valuable submissions! 
Bring them on, econometricians! 
Bleeding edge update for the #tidyverse purrr package. We've been working to make #rstats parallel maps even more seamless.
Introducing our shiniest new adverb: `in_parallel()`. Just wrap your function with it to take advantage of blazing fast parallel processing via mirai.
Utilise multiple cores on your own machine or distribute workloads across the network.
Please help us by testing it out! Install the pkg dev version via:
pak::pak("tidyverse/purrr")
¡Atención! Se extendió la convocatoria para uRos2025 
La conferencia sobre R y estadísticas oficiales será en Bucarest 
Nuevo deadline: 15 de junio.
Charlas, lightning talks y tutoriales.
Info y envíos: https://lnkd.in/dNF7VpU6
#Rstats #uRos2025
@rstats
#TidyTuesday Libros en español del Proyecto Gutenberg. @gutenberg_org
Script: https://vhgauto.github.io/tidytuesday/2025/semana_22.html
Twilight support!
One of my favorite things is finding a methods paper (here, atmospheric rendering), implementing it, thinking to myself "Man, it would be nice if the method supported XYZ!", and then finding that the paper implementing XYZ was released fairly recently. Truly surfing the crest of human knowledge!
Finally we are back with episode 206 of the @rstats @rweekly Highlights Podcast! https://serve.podhome.fm/episodepage/r-weekly-highlights/206
Containerize #Shiny apps with {shiny2docker} (Vincent Guyader) @thinkr 
ggplot2 layer explorer Shiny app @yjunechoe 
{quickr} @t_kalinowski
h/t @mike_thomas (and the wacky curator who never met a container he didn't like ...) 
#RStats Dev Diary - graphviz test.
#TaylorSwift "My Tears Ricochet"
#RStats dev diary:
Writing a little tool to help me make graphviz "dot" diagrams.
This is so I can make pretty pictures to visualise deeply nested R objects - even those with possibly circular references.
Test code outputs an edge for every consecutive word pair in the nursery rhyme "Mary had a little lamb"
@davisvaughan.bsky.social 's #Rstats R C package series is very good. I want to see the follow up of this blog's interesting hint at efficiently calling R functions from C blog : blog.davisvaughan.com/posts/2019-0... package: github.com/DavisVaughan...
R^4 Post #050: Introducing 'almm: Activate-Linux (based) Market Monitor'
A lightweight real-time market monitor based on (Redis|Valkey) pub/sub
https://dirk.eddelbuettel.com/blog/2025/06/12#050_introducing_almm
#rstats #rcpp
Hey #rstats fam, I am in over my head!
I am working on this package (https://codeberg.org/drdcarpenter/UTreeAllometrics) that has functions that take a tree species as a string and a number and returns a prediction.
At the moment, it is not vectorised, such that providing three trees and three numbers, it returns a prediction for each tree species for each number. E.g. if I provide three species and a height for each, I will get three height predictions for each species.
Which is not desirable, but I am stuck!
I gave a talk on measuring spatial autocorrelation in spatial machine learning at the #AGILE0GI conference.
Slides: https://jakubnowosad.com/agile-gi2025/
Always glad to discuss spatial ML or autocorrelation --- feel free to reach out!
