R

How to dockerize a Shiny app that calls a Plumber API

The Hosting Data Apps website is dedicated to help you learn about your hosting options. As outlined in the opening post, data app development related content is kept to a minimum. In this post we list resources that provide accessible introduction to Shiny app development.

The R task Force - R experts for all your needs

This is a guest post by Chris Paciorek, Department of Statistics, University of California at Berkeley. In this post, I’ll demonstrate that you can easily use the future package in R on a cluster of machines running in the cloud, specifically ...

In March of 2021, Epi-Interactive hosted one of the first in-person R events in Wellington, New Zealand. Here are some takeaways from their experience.

This is a guest post by Chris Paciorek, Department of Statistics, University of California at Berkeley. In this post, I’ll demonstrate that you can easily use the future package in R on a cluster of machines running in the cloud, specifically on a Kubernetes cluster. This allows you to easily doing parallel computing in R in the cloud. One advantage of doing this in the cloud is the ability to easily scale the number and type of (virtual) machines across which you run your parallel computation.

plumber

An opinionated example for implementing logging in Plumber APIs - sol-eng/plumber-logging

An opinionated example for implementing logging in Plumber APIs - sol-eng/plumber-logging

plumber

I have deployed shiny server with several shiny apps. Each app is used as online dashboard which should be refreshed periodically (e.g. every 2 hours or at 10pm every day) according to my plan. N...

Links and resources for Shiny, JavaScript, HTML, and CSS.

We are creating a database and integrate persistent data storage in an R Shiny application with a remote MySQL database for free.

When using shiny in production, often you will want to have some sort of database interactions for storing and accessing data. The DBI package provides an easy way to do the database interactions with a variety of SQL database flavors. In this example, I’m going to use a SQLite ...

[Disclaimer] The package presented in this blog post is stillexperimental at the time of writing these lines (2021-02-28), so itmight face some API changes in the future.Yesterday Jacqueline’s tweeted about her need to add POST requests toa {shiny} application.I'm astounded that it doesn't seem like a Shiny app is able to acceptPOST requests. I have data I wanna pass to my server :/— Dr. Jacqueline Nolis (@skyetetra)February27, 2021This is actually one of the things I had in mind when building{brochure}: more flexibility with the HTTP requests and how they arehandled.So here is a working ex...

When using shiny in production, often you will want to have some sort of database interactions for storing and accessing data. The DBI package provides an easy way to do the database interactions with a variety of SQL database flavors. In this example, I’m going to use a SQLite in memory database for reproducibility. In practice, you will just switch to the code to use a persistent database. Let’s start by creating a table to right to.

In this guide you’ll find both original content and curated resources to: + Build R shiny apps from scratch + Select the optimal dashboard framework for your R shiny app dashboard + R packages to build interactive, professional quality data visualization + Improve the user experience and dashboard speed tricks + All the ways you can deploy and share R shiny app dashboards + Lessons from a dashboard veteran for better R shiny app dashboards

"R in Production " is a blog that talks about Security, Automation, Scalability in the R environment. Furthermore, Software Engineering teaches us proven methodologies to bring a prototype into production and to facilitate the work process in all its aspects. (Click on the title to read more ...)

Véritables outils de visualisation des données, les tables interactives permettent de trier, colorer, éditer, rechercher, paginer les données

In this guide you’ll find both original content and curated resources to: + Build R shiny apps from scratch + Select the optimal dashboard framework for your R shiny app dashboard + R packages to build interactive, professional quality data visualization + Improve the user experience and dashboard speed tricks + All the ways you can deploy and share R shiny app dashboards + Lessons from a dashboard veteran for better R shiny app dashboards