What we’ve all been waiting for - the full agenda for posit::conf(2024) is officially live!
You won’t want to miss out on this jam-packed lineup! Here’s what you can expect:
✨ Four keynote sessions
✨ 26 all-day workshops
✨ 24 breakout sessions
✨ Three evening networking events
✨ All-day lounge access with scheduled demos and time with the Posit team and partners
✨ Hours of opportunities to connect with your peers!
We’re most pleased to announce the release of dbplyr 2.5.0!
dbplyr is a database backend for dplyr that allows you to use a remote database as if it were a collection of local data frames. dbplyr 2.5.0 introduces succinct new syntax for literal table identifiers.
I decided to make a blog post out of a problem I worked on a day or two ago and thankfully I was also pointed to another solution from @embiggenData which worked well too.
We’re thrilled to announce dplyr powered by DuckDB: duckplyr 🎉
A collaboration between the dplyr project team at Posit, cynkra, and DuckDB, duckplyr is a powerful new option that marries the user-friendly dplyr syntax with the execution capabilities of DuckDB.
The map() function applies a function across vectors, lists, or data frames efficiently. Syntax: map(.x, .f, ...) where .x is data, .f is function, ... for extra args. Examples: square vector elements via ~.x^2, get means of column across list of data frames with ~mean(.x$y), apply custom functions to rows/cols like df$z <- map_dbl(df, add_cols).
Opportunity Scholars at posit::conf(2024). The application deadline is approaching fast; March 22nd. If you're a strong candidate or know someone who is, please act quickly.
Opportunity Scholarships receive free tickets, a workshop, support for travel and accommodation, plus lots of swag.
Hey you out there...
Do you use data.table or tidyverse on R?
I need to have a quick chat about your relationship with these packages to understand community sustainability.
It would be a quick and informal chat!
Please reach out and tag people who can help
My TidyDensity package just got a major upgrade, powered by the blazing-fast data.table.
⚡️ And the best part? You get the speed boost no matter what format you choose.
Ready to experience the difference?
1.install.packages("TidyDensity")
2. Pick your output format: .return_tibble = TRUE for tibbles, .return_tibble = FALSE for data.tables.
3. Dive into your data
tidymodels: Better warnings, clearer errors, and exciting new features coming soon!
The tidymodels framework is a collection of #RStats packages for modeling and machine learning using #tidyverse principles. This quarterly digest summarizes what’s new in the tidymodels ecosystem.
#TidyTuesday Rising popularity of #tidyverse group of packages (by @hadleywickham
and others) amongst top R packages used as imports by other R packages.
Our cheatsheets are concise, quick-reference guides that summarize key concepts, functions, and syntax for popular #RStats#Python Posit tools. Cheatsheets have long been an invaluable resource for anyone working with R and the #tidyverse, and we’re continuing to expand them to new languages and tools.
Interested in a quick look into the package lifecycle?
In this video, Hadley Wickham shares insight into the important process of deprecation - whereby a function has a better alternative available and is scheduled for removal.
Have you wondered what it means when a #RStats function in #tidyverse is 'superseded'?
Hadley Wickham shares about the package lifecycle process and a quick guide on what ‘superseded’ means for functions, and why in package development, it's equally important to be able to remove functions, as well as add them.
{dbplyr} lets you query databases with {dplyr} code. The 2.4.0 release includes eliminating subqueries when using multiple unions in a row, getting more control over the generated SQL, and new translations.