awesome-rshiny
An awesome R-shiny list!
https://github.com/grabear/awesome-rshiny
Last synced: 4 days ago
JSON representation
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People
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Resources
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General
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Tutorials
- Episode 27: Get The {Gt} Tables (Rstudio::Conf 2019)
- The R-Podcast
- Episode 15: Introduction to Shiny
- Episode 16: Interview with Dean Attali
- Episode 17: A simply Radiant Chat with Vincent Nijs
- Episode 18: Interviews with the R-Studio Team
- Episode 19: Talking Shiny at R-Studio Conf wiht Barabara Borges and Dean Attali
- Episode 21: Talking Rcpp and More with Dirk Eddelbuettel
- Episode 25: Interview with Ian Lyttle (Rstudio::Conf 2018
- R-Studio (video)
- R-Studio (YouTube)
- R-Studio (Vimeo)
- DataCamp
- Building Web Applications in R with Shiny
- Dean Attali: Shiny Case Studies: My new online interactive video course (DataCamp)
- Dean Attali
- CRANalerts: Get email alerts when a CRAN package gets updated
- Blog Post: Building Shiny apps - an interactive tutorial
- Blog Post: Shiny tips & tricks for improving your apps and solving common problems
- Blog Post: How to get your very own RStudio Server and Shiny Server with DigitalOcean
- Blog Post: Mimicking a Google Form with a shiny app
- Blog post: Persistent data storage (and retrieval) in Shiny apps
- Blog post: How to set-up shiny server on Ubuntu 14.04
- Course: Stat545
- Joe Cheng
- Async programming in R and Shiny
- An informal intro to async Shiny
- Alyssa Columbus
- Blog Post: Introduction to R Shiny
- Abhinav Agrawal (YouTube)
- AHmed HAsan (YouTube)
- Zev-Ross
- Cheat Sheet
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Shiny Server on Docker: CentOS 7 Edition
- Use Docker to distribute and run Shiny apps
- Dockerizing a Shiny App
- Cookie based authentication with Shiny
- Speed Up Shiny Coding with Data
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Shiny Server on Docker: CentOS 7 Edition
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Building Web Applications in R with Shiny
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
- Delivering Data Science for the Enterprise with Shiny in Kubernetes
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Community
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Deployment
- RStudio Connect - Back end software for hosing shiny applications, Rmarkdown, plus other features for enterprise contexts.
- Shinyproxy - Uses containers for hosting shiny apps and a Java server control and proxy traffic to the app containers. [How-to Blog](http://lukesingham.com/shiny-containers-with-shinyproxy/).
- ShinyApps.io - Rstudio's PAAS specifically for hosting shiny apps.
- Heroku - General cloud application platform that can be utilised by shiny apps with these [buildpack scripts](https://github.com/virtualstaticvoid/heroku-buildpack-r/tree/heroku-16).
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Tools
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Packages
- shinystan - Provides visual and numerical summaries of model parameters and convergence diagnostics for MCMC simulations.
- RinteRface - A collection of HTML templates for Shiny.
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Integrations
- HTML Widgets/JavaScript
- Crosstalk - Extends htmlwidgets with functionality for implementing cross-widget interactions.
- leaflet - JavaScript library for creating dynamic maps that support panning and zooming along with various annotations like markers, polygons, and popups.
- d3heatmap - Implements a D3 heatmap htmlwidget.
- plotly - Easily translate your ggplot2 graphics to an interactive web-based version, and also provides bindings to the plotly.js graphing library.
- highcharter - Flexible JavaScript charting libraries in shiny.
- slickR - Slick carousel htmlwidget for R.
- flexdashboard - Easy interactive dashboards for R.
- Shiny in Rmarkdown - Run shiny apps in rmarkdown documents.
- plotly - Easily translate your ggplot2 graphics to an interactive web-based version, and also provides bindings to the plotly.js graphing library.
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Books
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Galleries
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Integrations
- Shiny Gallery - Shiny apps and much more.
- Showmeshiny - Huge gallery of Shiny apps.
- Shiny Widgets - Experience statistics with apps designed for teaching and analysis.
- Html Widgets Showcase - Featured Html widgets.
- Html Widgets Gallery - User submitted Html widgets.
- R Graph Catalog - Complement to the book “Creating More Effective Graphs” by Naomi Robbins.
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App Examples
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Integrations
- shiny-ampvis2 - Provides some basic functionality for using ampvis2 to visualize microbiome data.
- Lights Out game - Lights Out is a puzzle game consisting of a grid of lights that are either on or off.
- Workforce Demographics - View a range of workforce related demographics information across an organisation. [Source Code](https://github.com/atogov/workforceDmgs).
- Bivariate Demographics - Examine how an organisation is performing on a range of demographic information. [Source Code](https://github.com/atogov/bivariateDmgs).
- Shiny Database App (CRUD) - An example of a [CRUD](https://en.wikipedia.org/wiki/Create,_read,_update_and_delete) shiny app with [accompanying how-to post](https://ipub.com/shiny-crud-app/).
- homebrewR - Explore and compare beer recipes.
- polMonitor - Monitor police violence in the United States.
- National Parks Weather - Visualize National Parks locations and weather using user input.
- Anomaly Detection - Detect anomalies on univariate timeseries data using AnomalyDetection package.
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