Check it out, the #Shiny extension for #VSCode now supports both Shiny for R apps and Shiny for Python apps in everyone's second favorite IDE!
Along with the updates come a few neat features for deploying your Shiny apps as serverless ShinyLive apps using https://shinylive.io, or for saving a ShinyLive app as local #RStats or #Python files.
I have an #RStats {httr2} question: I'm about to make a bajillion requests to the same server. Can I use the server's keep-alive capability to batch these more efficiently? I'm not finding any info on this online or in the docs.
We are thrilled to introduce {keras3}, the next version of the Keras R package. {keras3} is a ground-up rebuild of {keras}, maintaining the beloved features of the original while refining the API based on valuable insights gathered over the past few years.
Introducing get_provider_meta_data() in the healthyR.data package! Perfect for healthcare datasets, it offers easy metadata fetching and filtering from CMS.
Highlights:
Customizable Filtering by identifier, title, description, keyword, dates, theme, and media type.
Tidy Tibble Output with detailed metadata, including download URLs and contact info.
Efficient Data Processing for clean and ready-to-use data.
📦 Generalizing OOP in R core @R_Foundation
🏨 Visualizing overture map buildings data @kyle_e_walker
📝 Refactoring a test file (part 2) @maelle
You'll see awesome new features in our show like custom chapter images and boosting directly to your hosts with a modern podcast app available at https://newpodcastapps.com/
Today's Computing Infrastructure package is outcomerate
AAPOR (American Association of Public Opinion Research) Survey Outcome Rates
🙏 Maintained by Rafael Pilliard Hellwig
📝 https://docs.ropensci.org/outcomerate/
Easily retrieve and analyze CMS metadata with customizable searches using .title, .keyword, and .modified_date. Choose data versions ("current", "archive", "all") and filter by media type ("all", "csv", "API", "other"). It returns a tidy tibble with essential metadata.
The {tidylog} #rstats 📦 generates in-line additional data about your dplyr and tidyr operations. "It provides simple wrapper functions for almost all dplyr and tidyr functions, such as filter, mutate, select, full_join, and group_by." By Benjamin Elbers.
(1/2) Shiny Apps for demystifying statistical models and methods 🚀
This is a cool website that explains different statistical concepts with the use of interactive Shiny Apps. Ben Prytherch made this website from the Department of Statistics at Colorado State University.
The {geotargets} extends the {targets} package to work with geospatial data formats. This release provides support for {terra} formats.
It simple would not have been possible to have this package without Eric Scott @LeafyEricScott and Andrew Brown @humus_rocks - it's been a really fun project to work on together, looking forward to future iterations!
The {mrup} #rstats 📦 is an “RStudio addin for searching for all local projects and editing the most recently used project list.
“Easily open any previous project. Add projects to, or remove projects from, the recent project drop-down menu.” By John Wilson, teaching fellow at Edinburgh University https://github.com/jmcvw/mrup #RStudio@rstats
If you are somewhere between disillusioned & enraged with the direction that StackOverflow has taken, but like me you still periodically have the “answer programming questions on the internet" itch, here's a small suggestion that I’ve found rewarding.
Follow the GitHub issues of an open source project you use a lot. I 💯 guarantee you that they periodically get issues that are just confused users asking for help, or “bug reports” that are just a simple misunderstanding of the tool…
When writing guides and documentation, I always try to write what I would have liked to have read, so here is a guide on how to contribute to #Nix from the perspective of an #RStats user: