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184 posts149 participants2 posts today
R devs, here are 2 Github repositories that will help you get started with using Gradio in your R projects:
https://github.com/Ifeanyi55/Gradio-in-R
https://github.com/Ifeanyi55/StoryMaker
A star will be very much appreciated 
GitHubGitHub - Ifeanyi55/Gradio-in-R: A project that demonstrates how to build and deploy fully functional Gradio applications in the R programming language.A project that demonstrates how to build and deploy fully functional Gradio applications in the R programming language. - Ifeanyi55/Gradio-in-R
There are 22328 #rstats packages on CRAN:
- 10.06% are in English.
- 0.21% are in other languages than English.
- 0.03% use multiple languages.
- 89.69% do not declare any language.
Useful questions to ask before you start coding a #dataviz dashboard, from @ivelasq3 's #ShinyConf2025 presentation.
Full slides: https://ivelasq-shinyconf2025.share.connect.posit.cloud/#/section
#QuartoPub #RShiny #RStats #ShinyConf
For the #30DayChartChallenge day 4: Big or Small, I made an #rstats treemap with the 
#treemapify, in the same Byrne's Euclid style as for day 1.
It shows that a Small number of programs each attract a Big number of students, and a Big amount of programs each attract a Small number of students.
Any 
#webr folks knowledgable about the build process?
Struggling with `rwasm::build()` for local packages. Trying to get the extendr 
build process for webR sorted!
GitHubdoc: build local package · Issue #50 · r-wasm/rwasm
Replied in thread
#30DayChartChallenge - Day 9: Diverging Looking at labour force participation rates in UK, South Korea, Iran, Indonesia, Saudi Arabia, and the USA. Tried to for for the @data.ft.com look. #rstats #dataviz
Recent @DSLC club meetings:
Health Metrics and the Spread of Infectious Diseases: Techniques for Machine Learning Applications https://youtu.be/oglORhCyf3k #RStats
Shiny Club https://youtu.be/ILvEf66-Bgk #RStats #RShiny
From the @DSLC chives:
"Mastering Shiny: Tidy evaluation" https://youtu.be/0Ap3q97Qjkg #RStats
Visit https://dslc.video for hours of new #DataScience videos every week!
youtu.be- YouTubeEnjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
# objetivo: Serie temporal:
# - Ventas con fuertes temporadas
# proceso : Descomposición Automática:
# Ajustar estacionalmente
# Regresión con data des-estacionalizada para encontrar tendencia
# entradas: Dataframe:
# - fecha: Fecha de observación
# - ventas mensuales 10 años
GIF
https://www.r-bloggers.com/2025/04/whats-new-in-r-4-5-0/
Oh nice! I like the idea of use()!
R-bloggers · What’s new in R 4.5.0? | R-bloggersR 4.5.0 (“How About a Twenty-Six”) was released on 11th April, 2025. Here we summarise some of the interesting changes that have been introduced. In previous blog posts we have discussed the new features introduced in R 4.4.0 and earlier versions...
There are 9 new #rstats packages on CRAN:
- 0.00% are in English.
- 0.00% are in other languages than English.
- 0.00% use multiple languages.
- 100.00% do not declare any language.
GitHub Actions for the R language: Makes automatic testing of your R package much easier and making sure your package works on different OS and R versions is a matter of just a few lines of yaml: https://github.com/r-lib/actions #rstats #ci #testing #github
GitHubGitHub - r-lib/actions: GitHub Actions for the R communityGitHub Actions for the R community. Contribute to r-lib/actions development by creating an account on GitHub.
2025 #30DayChartChallenge | day 12 | distributions | data.gov
.
: https://stevenponce.netlify.app/data_visualizations/30DayChartChallenge/2025/30dcc_2025_12html
.
#rstats | #r4ds | #dataviz | #ggplot2
#30DayChartChallenge Día 12: Gov Data Day! 
Explorando la distribución del spread 10Y-2Y del Tesoro USA (datos de FRED desde 1976).
Este histograma/densidad va más allá del valor diario: muestra la *probabilidad* histórica de cada nivel del spread. ¡Clave para entender expectativas económicas!
Puntos clave:
* Modo principal > 0 (curva normal es lo más común).
* ¡La inversión (<0, línea discontinua) tiene una probabilidad no trivial! 
Es la famosa señal pre-recesión. La distribución nos dice cuán "normal" es esa señal en perspectiva histórica.
* La forma general revela info sobre la dinámica de tipos.
Una visualización sobre la estructura probabilística de un indicador líder fundamental.
#rstats #ggplot2 #quantmod #grid
Código/Repo: https://t.ly/0RDmK
#30DayChartChallenge Día 11: Stripes! Mi versión: ¡El código de barras del pánico del mercado! 
Este gráfico muestra una línea de tiempo (1993-2025) donde cada raya vertical representa un día en que el VIX cerró ≥ 30 (¡alta tensión!).
El concepto clave aquí es el **Volatility Clustering**: la alta volatilidad no se distribuye uniformemente, ¡viene en rachas! Los densos grupos de rayas identifican visualmente las grandes crisis (Dot-com, GFC '08, Covid '20...). Los largos periodos en blanco son la calma relativa.
Es una forma directa de ver la *persistencia* y los *regímenes* de la volatilidad del mercado. ¡Olvida las medias simples, el estrés viene en oleadas! 
Hecho con #rstats, #ggplot2, #quantmod. Código/Repo: https://t.ly/-vd9u
Continued thread
We’ve made it really easy to use mirai to run compute on other computers - whether that’s on your local network or an Amazon EC2 instance. Anywhere you can SSH into, with no change in firewall settings or any other configuration. 3 steps to launch and auto-scale. Check out the slides at https://shikokuchuo-shinyconf2025.share.connect.posit.cloud #rstats #ShinyConf2025
shikokuchuo-shinyconf2025.share.connect.posit.cloudScaling Shiny: Seamless and Effortless Distributed Computing with mirai
