R - Shiny

R - Shiny

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Fastest Growing R Shiny App Store
Fastest Growing R Shiny App Store
Showcase your R shiny application and grow your user base. Real time usage stats and reviews for all your apps. Contribute today.
·shinyappstore.com·
Fastest Growing R Shiny App Store
Why you should learn Javascript to master R Shiny. And how to get started - datahabits.io
Why you should learn Javascript to master R Shiny. And how to get started - datahabits.io
Although the concealment of Javascript is by design and makes Shiny in the first instance easy to use, in the long run when you want to build serious and more visual appealing apps, you most likely need to utilize javascript to make most of the web framework
·datahabits.io·
Why you should learn Javascript to master R Shiny. And how to get started - datahabits.io
Best Practice: Development of Robust Shiny Dashboards as R Packages
Best Practice: Development of Robust Shiny Dashboards as R Packages
This article describes best practice approaches for developing shiny dashboards. The creation of the dashboard in package form, as well as the use of unit tests should enable the development of robust solutions and guarantee high quality.
·inwt-statistics.com·
Best Practice: Development of Robust Shiny Dashboards as R Packages
shinycovr
shinycovr
Contribute to yonicd/shinycovr development by creating an account on GitHub.
·github.com·
shinycovr
Forget about Excel, Use these R Shiny Packages Instead - Appsilon Data Scie
Forget about Excel, Use these R Shiny Packages Instead - Appsilon Data Scie
Transferring your Excel sheet to a Shiny app is perhaps the easiest way to create an enterprise ready dashboard. Shiny offers a comparable feature set to Excel as well as exciting new possibilities.
·appsilon.com·
Forget about Excel, Use these R Shiny Packages Instead - Appsilon Data Scie
Using Shiny with Scheduled and Streaming Data · R Views
Using Shiny with Scheduled and Streaming Data · R Views
Note: This article is now several years old. If you have RStudio Connect, there are more modern ways of updating data in a Shiny app. Shiny applications are often backed by fluid, changing data. Data updates can occur at different time scales: from scheduled daily updates to live streaming data and ad-hoc user inputs. This article describes best practices for handling data updates in Shiny, and discusses deployment strategies for automating data updates.
·rviews.rstudio.com·
Using Shiny with Scheduled and Streaming Data · R Views
Super Solutions for Shiny Architecture 2/5: Javascript Is Your Friend - App
Super Solutions for Shiny Architecture 2/5: Javascript Is Your Friend - App
Three methods for using javascript code in Shiny applications to build faster apps, avoid unnecessary re-rendering, and add components beyond Shiny's limits. Part 2 of a 5 part series on super solutions for Shiny architecture.
·appsilon.com·
Super Solutions for Shiny Architecture 2/5: Javascript Is Your Friend - App
Productionizing Shiny and Plumber with Pins · R Views
Productionizing Shiny and Plumber with Pins · R Views
Producing an API that serves model results or a Shiny app that displays the results of an analysis requires a collection of intermediate datasets and model objects, all of which need to be saved. Depending on the project, they might need to be reused in another project later, shared with a colleague, used to shortcut computationally intensive steps, or safely stored for QA and auditing. Some of these should be saved in a data warehouse, data lake, or database, but write access to an appropriate database isn’t always available.
·rviews.rstudio.com·
Productionizing Shiny and Plumber with Pins · R Views
Building a shiny app with drag and drop data interface
Building a shiny app with drag and drop data interface
Introduction Data visualization is an important aspect of the data science work flow. This app enables the analyst to understand the data in question. In this post, we will build an application whi…
·pradeepadhokshaja.wordpress.com·
Building a shiny app with drag and drop data interface
Shiny 1.0.4
Shiny 1.0.4
Shiny 1.0.4 is now available on CRAN. To install it, run: install.packages("shiny") For most Shiny users, the most exciting news is that file inputs now support dragging and dropping: It is now possible to add and remove tabs from a tabPanel, with the new functions insertTab(), appendTab(), prependTab(), and removeTab(). It is also possible to hide and show tabs with hideTab() and showTab(). Shiny also has a new a function, onStop(), which registers a callback function that will execute when the application exits.
·blog.rstudio.com·
Shiny 1.0.4