I've turned my intro to R workshop into a free open-access book: The R Workshop 🌟 Perfect for R beginners, with more chapters coming soon! Check it out: www.r-workshop.org
Prefer live instruction? Join my 2-day virtual workshop Jan 15-16 via Instats. Details: instats.org/seminar/intr...
#rstats
In case you missed my "Python for R Users" seminar last month, registration for the recorded on-demand version is now open for you to explore at your own pace 🚀
Info and registration: instats.org/seminar/pyth...
Agreed! View() is super helpful for this too.
I just like the convenience of everything printing in the console rather than opening up another window, so I tend to use the print() trick more often than the View() trick myself
Printing a data frame (tibble) in the R console, where 3 columns are hidden
The output of df |> print(width = Inf) which prints all columns of a data frame (tibble) in the R console
I don't know who needs to hear this, but if you want to look at all columns of a tibble (which has the somewhat annoying habit of only showing you as many columns as you have space for), just pipe it into print(width = Inf):
df |> print(width = Inf)
#rstats
Only one week to go until my full-day "Python for R Users" workshop!
This workshop is designed for R users interested in learning Python and expanding their coding toolkit. Join me to learn Python from an R-friendly perspective!
Click here to register: instats.org/seminar/pyth...
If you're teaching R, or statistics, and you want your students to get more practice of data wrangling with "messy" data, you can use the {messy} package to turn the clean data you currently use for examples into more realistic looking data!
#RStats #StatsEd
Making things "pretty" has never been where I find the most joy in data work. So, I'm super excited about @posit.co 's {brand.yml} framework for adding unified styling across Quarto, Shiny, and more at minimal effort 🤩
posit-dev.github.io/brand-yml/
Site also featuring best at-a-glance roadmap
Am I bad at R if I don't even understand the question?
A few things I've been working on lately:
elmer, elmer.tidyverse.org, is a new package to make it easier to work with LLMs (hosted and local) from #rstats. It includes helps for structured data extraction and tool calling, and an easy way to upload a plot. Joint work with Joe Cheng.
This is awesome!
Some news: I've just open-sourced the draft of a book I'm working on about how #rstats tidymodels users can make their code run faster without sacrificing predictive performance!
www.simonpcouch.com/blog/2024-10...
I've heard of them
library(ggplot2) mtcars_labelled <- mtcars attr(mtcars_labelled$mpg, "label") <- "Miles per gallon" attr(mtcars_labelled$disp, "label") <- "Displacement" attr(mtcars_labelled$drat, "label") <- "Rear axle ratio" mtcars_labelled |> ggplot(aes(mpg, disp)) + geom_point(aes(colour = drat))
ggplot figure showing "Miles per gallon" on x-axis, "Displacement" on y-axis, and "Rear axle ratio" on legend.
y'all probably know i ❤️labelled data. the dev version of {ggplot2} has a new feature that automatically applies variable labels when plotting 😍✨ thank you @teunbrand.bsky.social!!! 🙏 #rstats
I always figured it was just a shortening "for categoricals", I never realised it was an anagram!
Check out the new `pastum` extension for Positron (and VS Code I guess)—it's {datapasta} for Positron! It works with both R (base R, tibble, and data.frame) and Python (pandas and polars) github.com/atsyplenkov/... #rstats #python
Hello world 👋
(This is how you're supposed to start with any new programming language/social media platform, right?)
