#Day9 | Distributions – Wealth | #30DayChartChallenge | Income Distribution in Central America, source World Bank. Built with #RStats using #ggplot2, #dplyr, #tidyr, #patchwork, #ggtext, #scales, #wbstats and #purrr.

#Day8 | Distributions – Circular | #30DayChartChallenge | Elevation distribution in the most circular department of Honduras. Built with #RStats using #sf, #raster, #exactextractr, #ggplot2, #ggnewscale, #ggtext, #dplyr, #terra, #showtext, #scales, #patchwork and #ggspatial.

#Day7 | Distributions – Multiscale | #30DayChartChallenge | Comparison of NDVI distributions across two spatial scales. Built with #RStats using #ggplot2, #dplyr, #terra, #tidyterra, #patchwork, #ggtext, and #scales.

#Día5 | Comparaciones – Experimental | #30DayChartChallenge. Experimenté agregando una sumatoria horizontal de observaciones en un boxplot sobre la capacidad endocraneana en especies del género Homo. Creada usando R con #ggplot2, #ggdist, #dplyr, #scales, #ggtext, #patchwork, #tibble y #tidyr.

#Día4 | Comparaciones – Slope | #30DayChartChallenge. Comportamiento de los focos de calor detectados para los paises de América Central. Un gráfico con valores absolutos y otro con valores realtivos. Creada usando R con #ggplot2, #dplyr, #scales, #readr, #stringr y #ggtext.

#Día3 | Comparación– Mosaico | #30DayChartChallenge. Focos de calor detectados para los paises de América Central. Un gráfico con valores absolutos y otro con valores relativos. Creada usando R con #ggplot2, #treemapify, #dplyr, #scales, #readr y #stringr.

#Día 2 | Comparaciones – Pictograma | #30DayChartChallenge. Centroamérica suma más de 51 millones de habitantes. El gráfico fue creada usando R con #ggplot2, #dplyr, #tidyr, #scales, #ggflags, #sf, #rnaturalearth, #rnaturalearthdata, #patchwork..

I 💚 `filter_out()` in #dplyr 1.2.0

#rstats

Finally, we added the beginnings of an #rstats DataFrame API that can be used to implement a #dplyr backend. This is my favourite feature of SedonaDB 0.3.0 because I love R, dplyr, and because I never properly learned SQL 😬

Come for Isabella's puns 😂 stay for the peek behind the curtain of how functions get added to or deprecated from #tidyverse packages like #dplyr 👀 from @davisvaughan.bsky.social himself

Tomorrow! Tues 12pm ET! Register at pos.it/dslab if you haven't already 👏🏻 and we'll see you there #databs #rstats

Being able to use a lookup table & just use "from" & "to" language like this is SUCH a wonderfully change for me when recoding values 🥹 #dplyr has always felt conversational to me, & now we can finally use it to say "recode this variable from this to that" without typing a long case_when #rstats

#dplyr 1.3.0 wishes: 1). rename filter to filter_in 2). rename case_when to recode_when #rstats

Just used `filter_out()` in #RStats #dplyr for the first time 🤯

The latest roll out from #dplyr is causing this weird error "Error in `dplyr::case_when()`: ! `..1 (left)` must be a logical vector, not a logical matrix" which is breaking codes. The error has occurred before the current version. I hope it gets fixed soon. #rstats

dplyr comes to duckdb – Discindo Writing SQL with familiar verbs.

A sad post about not being able, at least at the moment, use #dplyr verbs in #duckdb:

discindo.org/posts/2026-0...

@nick-eagles.bsky.social concluded that scratch space location matters significantly for performance 💾⚡. He explained his motivation: he had a real use case with hundreds of millions of rows 📊 that originally took

Full length video: youtu.be/ikumz_QLZiE
#RStats #dplyr #duckplyr #rpolars #data.table

He noted that most benchmarks focus on speed ⚡, but emphasized that memory efficiency 🧠 is another important variable to consider - particularly highlighting that data.table tends to be more memory efficient than dplyr 💾✨.

#RStats #dplyr #duckplyr #rpolars #data.table

@nick-eagles.bsky.social introduced his presentation on benchmarking #dplyr alternatives 📊💻. He planned to review public benchmarks of various data manipulation packages 📦 as well as his own custom benchmark results 🔬

Full length 🎥: youtu.be/ikumz_QLZiE
#RStats #dplyr #duckplyr #rpolars #data.table

#Rstats #dplyr #ducdkb community extension by ChanYub Park

Use dplyr synthax in #duckdb
duckdb.org/community_ex...

A flowchart illustrating the logic of the case_when() function, commonly used in R programming. At the top, the code structure is shown as: case_when( condition1 ~ action1, condition2 ~ action2, condition3 ~ action3 ) The logic flows vertically through a series of pink rectangular decision boxes and green circular action outcomes: Step 1: The process starts at condition1. If TRUE, it leads to action 1. If FALSE, it moves down to the next condition. Step 2: At condition2, if TRUE, it leads to action 2. If FALSE, it moves down to the next condition. Step 3: At condition3, if TRUE, it leads to action 3. Final Step: If condition3 is also FALSE, the process concludes by moving to a final green circle that says return NA.

🖼️ In addition to text, you will find many figures explaining concepts.

Here is one example with an explanation of how case_when() function works in #dplyr in #rstats

R Programming – Improvements in the Language R has improved dramatically.

dplyr but make it bussin fr fr no cap `genzplyr` is an alternative syntax for `dplyr` that replaces boring old function names with GenZ slang. Your data wrangling is about to hit different.

'#genzplyr is an alternative syntax for #dplyr that replaces boring old function names with GenZ slang. Your data wrangling is about to hit different.' by @hadley.nz

I love it! 💖 How funny is that? 🤣 #RStats #R

hadley.github.io/genzplyr/

new #dplyr filtering function who dis 😍 meet filter_out()!

👍 GO PUT A THUMBS UP ON DAVIS'S TIDYUP THINGY ON GITHUB TO SHARE MY ENTHUSIASMMMM!! #rstats #databs

And, you know, provide your thoughts on this newly-proposed function if you have them 😌

You sir, have won the internet for today, possibly for this year #tidyverse #dplyr #genzplyr #rstats

Utilisation de case_when dans dplyr : cas des variables facteurs Astuces pour bien définir sa variable facteur dans une instruction case_when suite aux dernières mises à jour de dplyr.

🤨 Vous n'êtes pas sûrs de comment créer des variables factor avec case_when dans #dplyr? Notre nouvelle de note de blog est pour vous ! ⤵️

#RStats #RStatsFR

blog.statoscop.fr/utilisation-...

You can quickly check for missing data with a simple function. In Python (efficiently with a pandas DataFrame/NumPy isnan()) or in R (e.g. dplyr from tidyverse 🙂).


#datasummarisation #dplyr #pandas #numpy

Remember this #rstats post? I wasn't the only one talking about it & the tidyverse team was listening 😎 #databs

New #dplyr functions? They're looking for feedback!!
🤔 replace_when, recode_values, replace_values

👀 Read this:
github.com/tidyverse/ti...

🗣️ Comment on PR:
github.com/tidyverse/ti...