R

If you use RStudio Connect to publish your Shiny app (and even if you don’t) take care with how your...

Contribute to yonicd/shinycovr development by creating an account on GitHub.

Design a computing infrastructure and choose packages that can set you and your learners on the happy path.

Safely Deploy R to Production

Does your R package work best with some configuration? You probably want it to be easily found by your package. Does your R package download huge datasets that don’t change much on the provider side? Maybe you want to save the corresponding data somewhere persistent so that things will go faster during the next R session. In this blog post we shall explain how an R package developer can go about using and setting persistent configuration and data on the user’s machine.

Learn R, R tutorials, R resources, blog posts and the latest updates about the statistical programming R language.

We deliver software development and ML solutions for Fortune 500 companies. We are an RStudio Full Service Certified Partner and global leaders in R Shiny.

A "work bench" to manage projects from within R.

As an update to this post, here's a list of the major events in R history since its creation: 1992: R development begins as a research project in Auckland, NZ by Robert Gentleman and Ross Ihaka 1993: First binary versions of R published at Statlib 1995: R first distributed as open-source software, under GPL2 license 1997: R core group formed 1997: CRAN founded (by Kurt Hornik and Fritz Leisch) 1999: The R website, r-project.org, founded 1999: First in-person meeting of R Core team, at inaugural Directions in Statistical Computing conference, Vienna 2000: R 1.0.0 released (February 29) 2000:...

Technical details and select highlights of my project to bring RStudio addins to VSCode.

Both R and distributed programming rank highly on my list of “good things”, so imagine my delight when two new... The post The Evolution of Distributed Programming in R appeared first on Mango Solutions.

Interact with basecamp api in R. Contribute to yonicd/basecamper development by creating an account on GitHub.

Some examples of running R applications on Google Kubernetes Engine

How to create scale-to-zero Shiny apps on Google Cloud Run: pitfalls, how and why

How to load geospatial data into your workspace and prepare it for visualization.

It all starts with sandboxes. Development sandboxes are dedicated safe spaces for experimentation and creativity. A sandbox is a place where you can go to test and break things, without the ramifications of breaking the real, important things. If you’re an analytic administrator who doesn’t have access or means to get a sandbox, I recommend that you consider advocating to change that. Here are just some of the arguments for why sandboxes are a powerful tool for the R admin that you may find helpful.

I do not well remember, but it seems to me I faced some difficulties when I tried to use Shiny bookmarking to save and restore the state of a Shiny app. These difficulties arose when there were some rende...

Distributed programming in R is normally taken up to speed up a process or piece of code or scale up an interface or application for multiple users.

A simple HTTP server in R. Contribute to yihui/servr development by creating an account on GitHub.

View an image in full screen by clicking on it. Contribute to feddelegrand7/rintimg development by creating an account on GitHub.

🐹🐹🐹 Creates a Friendly User Interface for Emails Sending in Shiny and RMarkdown - feddelegrand7/mailtoR

Animate shiny elements when they scroll into view 🍁 🍁 🍁 - feddelegrand7/scrollrevealR

Create an Interactive Pivot Table with Data Analysis Tools - feddelegrand7/pivta

Implement the Algolia Places Address Search Auto Completion Menu on Shiny Text Inputs - feddelegrand7/algo