Dronningen af Helvede @queen

49 posts46 participants5 posts today

**Nicola Rennie** @nrennie@fosstodon.org · 4h

Nicola Rennie @nrennie@fosstodon.org

For Day 3 of the #30DayChartChallenge, the prompt is "Circular"

Sunburst plot showing countries where 1% have >10% of wealth
Data formatting #RStats to create JSON data
Figured out how to edit an imported D3 chart in Observable

Sunburst chart showing number of countries in each continent where wealth of 1% exceeds 10%

#Day3 #DataViz #Observable

**Steven Ponce** @sponce1@graphics.social · 5h

Steven Ponce @sponce1@graphics.social

A circular heatmap showing San Juan's monthly temperature patterns from 2014-2024. The visualization arranges months in a circle with years radiating outward. Temperature is displayed through a purple-to-yellow color gradient, with cooler winter temperatures (December-February) in purple and warmer summer temperatures (July-September) in yellow. The pattern reveals San Juan's consistent tropical seasonal cycle.

**Miki :rstats:** @miki_peltzer@techhub.social · 6h

Miki :rstats: @miki_peltzer@techhub.social

#Day3 of the #30DayChartChallenge, theme: #Circular

Radar: Perfil de Desequilibrio Inmobiliario 2023. Comparando ES, DE, FR, IT, en 5 indicadores normalizados (P/Renta, P/Alq, Crec.Real, Deuda/Renta, Inv/PIB)
Código: https://t.ly/DDz_F

#dataviz #españa #vivienda #economía #Eurostat. #rstats #ggradar

Gráfico de radar comparando 5 indicadores de desequilibrio inmobiliario para 2023 entre España, Alemania, Francia, Italia y Portugal. Los ejes (normalizados Z-score, centro=0) son Ratio Precio/Renta, Ratio Precio/Alquiler, Crecimiento Real Precio, Ratio Deuda/Renta e Inversión/PIB. Cada país muestra un perfil poligonal diferente, indicando distintas vulnerabilidades relativas a la media del grupo. Datos: Eurostat/JERS.

**Still Mad About CD Prices** @guyjantic@infosec.exchange · 11h

11h

Still Mad About CD Prices @guyjantic@infosec.exchange

Looking for ideas for building a little #Rstats function.

Let's say I asked a bunch of people if they felt older, younger, or the same age as half a dozen randomly-selected ages.

Let's say that because that's what I did.

Example: Jane is asked this question about ages 17, 19, 25, 38, 41, and 52.

Each person answers younger/same/older to each of the ages (each person also gets a different selection of ages to answer).

Ultimately, I want to use those answers to get an estimate of the age each person feels. First, however, I want to see how numerically consistent each person's answers are.

Examples: if Jane said
17: older
19: older
25: older
38: same age
41: younger
52: younger

That's numerically consistent. However, if she said

17: older
19: younger
25: older
38: same age
41: older
52: younger

that's not consistent (she can't be both younger than 19 and older than 41).

It's also consistent if she said she felt younger than all the ages or older than all of them.

Maybe because it's late or maybe because I'm slow, I'm having a hard time approaching this. I'll leave it on the back burner for a couple of days since it's late where I am and I won't have time for it tomorrow.

If any of y'all (and many of you are ridiculously more quantitatively skilled than I am) have ideas of how to approach a function for this, or -- even better -- if a solution already exists as a formula or something, lay it on me. I'll be in your debt*.

*up to but not surpassing verbal compliments and possibly $2 USD

#help #statistics #math

**Danielle Navarro** @djnavarro@hachyderm.io · 12h

12h

Danielle Navarro @djnavarro@hachyderm.io

set.seed(3670); set.seed(3674) # dream girl, evil

delicate white heart against a black background (seed 3670)

shadowed black heart faintly illuminated from behind (seed 3674)

#rstats #rtistry

**Clinton** @clintonsears@mastodon.social · 18h

18h

Clinton @clintonsears@mastodon.social

Menacing upward trend alert! Day 2 of #30DayChartChallenge focuses on "slope," and #spottedlanternfly observations on #iNaturalist paint a concerning picture. This #invasivespecies (#Lycormadelicatula), highlighted in my #Rstats infographic (back to Python tomorrow ), poses a threat to our trees. Join #citizenscientists and report any sightings to help track this pest! #HitchHikerBug #DataViz #Ecology https://tinyurl.com/5n7b8xe3

Continued thread

**datatofu** @drmorrisj@mastodon.social · 22h

22h

datatofu @drmorrisj@mastodon.social

(pandas cont'd) For #rstats users, the DataFrame name will be familiar, as the object was named after the similar R data.frame object. Unlike Python, data frames are built into the R programming language and its standard library. As a result, many features found in pandas are typically either part of the R core implementation or provided by add-on packages

matplotlib. Yhe most popular Python library for producing plots and other two-dimensional #datavisualization or #dataviz

IPython & Jupyter

**Danielle Navarro** @djnavarro@hachyderm.io · 1d

Danielle Navarro @djnavarro@hachyderm.io

every now and then I try to explain how all my generative art comes from a place of extremely raw emotion. yes, it's usually an #rstats script that does the work, but... it's not like normal programming or analysis, it's something else. anyway. this one. this piece is exactly that - for a thousand different reasons I've been really moody and messy the last month or so and *this* is what my code does when that happens

yeah it's another of the "slightly menacing hearts" a chaotic mess with a grainy texture dominated by a heart motif in the centre. the palette is yellow, red, black, and brown. but it's different to so many of the others. there's a lot of... static. the heart is hollowed out, and the various "reflections" of the heart that appear elsewhere in the image are distorted and sometimes a little disturbing. idk

**R Contributors** @R_Contributors@hachyderm.io · 1d

R Contributors @R_Contributors@hachyderm.io

R Dev Day @ RSECon25
Warwick University, UK
Fri 12 Sep

Apply to attend this free event, to collaborate on contributions to #RStats.

Travel funding available for participants from UK, Europe & Global South

Deadline Wed 23 Apr: https://warwick.ac.uk/statistics/news/r-dev-day-rsecon25

warwick.ac.ukR Dev Day @ RSE Con25Details and application form for a satellite event to RSECon25, gathering R developers for a day of working collaboratively on contributions to R, hosted at the University of Warwick, Friday 12 September 2025.

#RSECon25 #RDevDay #RSEng

**Jesus Castagnetto** @jmcastagnetto@mastodon.social · 1d

Jesus Castagnetto @jmcastagnetto@mastodon.social

"#Observable for R users"

#RStats

https://nrennie.rbind.io/blog/observable-r-users/

Nicola RennieObservable for R users | Nicola RennieObservable is a JavaScript-based programming framework for data exploration and visualisation, which is popular for creating interactive charts and dashboards. This blog post demonstrates why and how R users can integrate Observable into their existing R workflows.

**R-Podcast (Eric)** @rpodcast@podcastindex.social · 1d

R-Podcast (Eric) @rpodcast@podcastindex.social

Can you believe it? A major podcasting achievement has been unlocked with episode 200 of the @rstats @rweekly Highlights podcast! https://serve.podhome.fm/episodepage/r-weekly-highlights/200

Text analysis and prediction with LLMs: {mall} does it all (Camila Livio) @Posit
The guide to gradients in R and ggplot2 @jimjamslam

Plus great listener feedback from @maurolepore and our usual mix of aha moments and perhaps a few lame jokes

h/t @mike_thomas & @jonmcalder

R Weekly HighlightsIssue 2025-W14 HighlightsBy some minor miracle (even on April Fools) the R Weekly Highlights podcast has made it to episode 200! We go "virtual" shopping for LLM-powered text…

#RStats #DataScience #V4V

**Steven Ponce** @sponce1@graphics.social · 1d

Steven Ponce @sponce1@graphics.social

A slope chart showing internet adoption rates across age groups from 2000 to 2024. The 65+ age group shows the steepest slope, rising from 14% to 90%, dramatically narrowing the gap with younger groups. Other age groups (18-29, 30-49, and 50-64) all reached nearly 99% adoption by 2024, despite starting at different levels (70%, 61%, and 46%, respectively).

**Nicola Rennie** @nrennie@fosstodon.org · 1d

Nicola Rennie @nrennie@fosstodon.org

It's Day 2 of the #30DayChartChallenge, and the prompt is "Fractions"

Re-using yesterday's data from Our World in Data on wealth distribution
Slope chart looking at change over 200 years
Chart made with Observable

slope chart showing change between 1820 and 2020 in share of income earned by richest 1% for different geographical regions. Europe has improved the most.

#RStats #Day2 #DataViz

**James Balamuta** @coatless@mastodon.social · 1d

James Balamuta @coatless@mastodon.social

Dear #rstats friends, remember all those tempdir()/tempfile() gymnastics for CRAN compliance?

examplesTempdir just made that circus act a one-liner with a simple #roxygen2 tag extension. Your future self will thank you.

Code: https://github.com/coatless-rpkg/rocleteer

Post: https://blog.thecoatlessprofessor.com/programming/r/simplifying-file-based-examples-with-atexamplestempdir-in-r-packages/

$Screenshot showing the @examplesTempdir feature for R packages. The image compares two approaches for managing temporary directories in package examples. The traditional method requires multiple lines of code with setwd(tempdir()) and cleanup commands. With the {rocleteer} package, this can be simplified to a single @examplesTempdir tag. The image shows code examples of both approaches, highlighting how the new method reduces boilerplate code. Old approach: #' @examples #' \dontshow{.old_wd <- setwd(tempdir())} #' #' # Your code here #' #' \dontshow{setwd(.old_wd)} New approach: #' @examplesTempdir #' # Your code here$

**Miki :rstats:** @miki_peltzer@techhub.social · 1d

Miki :rstats: @miki_peltzer@techhub.social

#Day2 of the #30DayChartChallenge, theme: #Slope

Comparando pendientes: Índice Precios Vivienda (IPV) vs Índices Salario Modal (H/M, € const.) en España (2009-2021, Base 2015=100).

Visualiza la brecha creciente: el coste de la vivienda subió mucho más rápido que los salarios modales reales.

Datos: INE. Hecho con #rstats #ggplot2.

Código: https://t.ly/heDni

Gráfico de líneas comparando índices de crecimiento (Base 2015=100) para España, periodo 2009-2021. Muestra tres series: el Índice de Precios de Vivienda (IPV) y los índices del Salario Modal de Hombres y de Mujeres (ambos en euros constantes de 2015). La línea del IPV muestra una pendiente ascendente mucho más pronunciada después de 2015 que las dos líneas de salarios, indicando que los precios de vivienda crecieron significativamente más rápido que los salarios modales reales. Incluye línea de referencia en 100. Datos: INE.

#dataviz #España #INE

**Tan G.** @tangandhara.bsky.social@bsky.brid.gy · 1d

Tan G. @tangandhara.bsky.social@bsky.brid.gy

#30DayChartChallenge - Day 1: Fractions Everyone's talking about Trump and tariffs but how much longer do we have to put up with his crap? Sadly, we're just under 5% of the way through so have a long way to go. #rstats #dataviz #TidyTuesday

The Orange Peril
"How much of the Trump presidency do we have left?"
"We've survived 4.9% of Trump 2.0"
"But there's still 95.1% of Trump 2.0 remaining"

**Sharon Machlis** @smach@masto.machlis.com · 1d

Sharon Machlis @smach@masto.machlis.com

Maybe Shiny is playing an April Fools trick on me? My R Shiny app works fine in RStudio *on my Shiny Web server* but not at its URL. All my other Shiny apps work fine on that server at their URLs. Sigh. Don't see anything useful in my logs.
The app will work on shinyapps.io so I guess that's what I'll use meanwhile.
#RStats #RShiny

An error has occurred
The application failed to start.

The application exited during initialization.

**Miki :rstats:** @miki_peltzer@techhub.social · 1d

Miki :rstats: @miki_peltzer@techhub.social

#Day1 of the #30DayChartChallenge, theme: #Fractions

Fracciones de Tenencia de Vivienda (Propiedad vs Alquiler/Otros) por Grupo de Edad en España (2024). Se ven claras diferencias generacionales.

Fuente: INE (Indicadores Calidad de Vida)
Hecho con #rstats #ggplot2

Código: https://t.ly/o0_y8

$Gráfico de barras 100% apiladas sobre tenencia de vivienda por grupo de edad en España (2024). Compara las fracciones de 'Propiedad sin hipoteca', 'Propiedad con hipoteca' y 'Alquiler u otros' para los grupos de edad 16-29, 30-44, 45-64 y 65+ años. Se observa mayor proporción de alquiler/hipoteca en los grupos jóvenes y mayor propiedad total (sin hipoteca) en los grupos de más edad. Datos del INE.$

#dataviz #INE #España

**Nicola Rennie** @nrennie@fosstodon.org · 1d

Nicola Rennie @nrennie@fosstodon.org

Quarto + #RStats + Observable =

New blog post from me about:

What is Observable?
Why should R users care?
How do you use both together to make interactive charts?

Link: https://nrennie.rbind.io/blog/observable-r-users/

#DataViz #Observable #QuartoPub

**Brad Duthie** @bradduthie@ecoevo.social · 1d

Brad Duthie @bradduthie@ecoevo.social

I've finished an audiobook version of my #statistics textbook for biological and environmental sciences with #jamovi -- all free and available on my website and Spotify (https://bradduthie.github.io/audiobook.html). I initially underestimated how much my own students would want this, so my hope is that others my benefit from it. Please feel free to contact me if you're teaching an introductory statistics class and are looking for resources! #rstats #stats https://bradduthie.github.io/blog/statistics-audiobook-with-jamovi/

bradduthie.github.ioFundamental Statistical Concepts and Techniques in the Biological and Environmental Sciences: With jamovi

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