Radiant - Business analytics using R and Shiny

Radiant is an open-source platform-independent browser-based interface for business analytics in R. The application is based on the Shiny package and can be run locally or on a server. Radiant was developed by <a href="https://rady.ucsd.edu/faculty-research/faculty/vincent-nijs.html" target="\_blank">Vincent Nijs</a>. Please use the issue tracker on GitHub to suggest enhancements or report problems: https://github.com/radiant-rstats/radiant/issues. For other questions and comments please use radiant@rady.ucsd.edu.

Key features

Explore: Quickly and easily summarize, visualize, and analyze your data
Cross-platform: It runs in a browser on Windows, Mac, and Linux
Reproducible: Recreate results and share work with others as a state file or an Rmarkdown report
Programming: Integrate Radiant's analysis functions with your own R-code
Context: Data and examples focus on business applications

Playlists

There are two youtube playlists with video tutorials. The first provides a general introduction to key features in Radiant. The second covers topics relevant in a course on business analytics (i.e., Probability, Decision Analysis, Hypothesis Testing, Linear Regression, and Simulation).

<a href="https://www.youtube.com/playlist?list=PLNhtaetb48EedDmWPUqytnQv-qxmCGtxi" target="_blank">Introduction to Radiant</a>
<a href="https://www.youtube.com/playlist?list=PLNhtaetb48EdKRIY7MewCyvb_1x7dV3xw" target="_blank">Radiant Tutorial Series</a>

Explore

Radiant is interactive. Results update immediately when inputs are changed (i.e., no separate dialog boxes) and/or when a button is pressed (e.g., Estimate in Model > Estimate > Logistic regression (GLM)). This facilitates rapid exploration and understanding of the data.

Cross-platform

Radiant works on Windows, Mac, or Linux. It can run without an Internet connection and no data will leave your computer. You can also run the app as a web application on a server.

Reproducible

To conduct high-quality analysis, simply saving output is not enough. You need the ability to reproduce results for the same data and/or when new data become available. Moreover, others may want to review your analysis and results. Save and load the state of the application to continue your work at a later time or on another computer. Share state files with others and create reproducible reports using Rmarkdown. See also the section on Saving and loading state below

If you are using Radiant on a server you can even share the URL (include the SSUID) with others so they can see what you are working on. Thanks for this feature go to Joe Cheng.

Programming

Although Radiant's web-interface can handle quite a few data and analysis tasks, you may prefer to write your own R-code. Radiant provides a bridge to programming in R(studio) by exporting the functions used for analysis (i.e., you can conduct your analysis using the Radiant web-interface or by calling Radiant's functions directly from R-code). For more information about programming with Radiant see the programming page on the documentation site.

Context

Radiant focuses on business data and decisions. It offers tools, examples, and documentation relevant for that context, effectively reducing the business analytics learning curve.

How to install Radiant

Required: R version 4.0.0 or later
Required: Rstudio

In Rstudio you can start and update Radiant through the Addins menu at the top of the screen. To install the latest version of Radiant for Windows or Mac, with complete documentation for off-line access, open R(studio) and copy-and-paste the command below:

options(repos = c(RSM = "https://radiant-rstats.github.io/minicran", CRAN = "https://cloud.r-project.org"))
install.packages("radiant")

Once all packages are installed, select Start radiant from the Addins menu in Rstudio or use the command below to launch the app:

radiant::radiant()

To launch Radiant in Rstudio's viewer pane use the command below:

radiant::radiant_viewer()

To launch Radiant in an Rstudio Window use the command below:

radiant::radiant_window()

To easily update Radiant and the required packages, install the radiant.update package using:

options(repos = c(RSM = "https://radiant-rstats.github.io/minicran", CRAN = "https://cloud.r-project.org"))
install.packages("remotes")
remotes::install_github("radiant-rstats/radiant.update", upgrade = "never")

Then select Update radiant from the Addins menu in Rstudio or use the command below:

radiant.update::radiant.update()

See the installing radiant page additional for details.

Optional: You can also create a launcher on your Desktop to start Radiant by typing radiant::launcher() in the R(studio) console and pressing return. A file called radiant.bat (windows) or radiant.command (mac) will be created that you can double-click to start Radiant in your default browser. The launcher command will also create a file called update_radiant.bat (windows) or update_radiant.command (mac) that you can double-click to update Radiant to the latest release.

When Radiant starts you will see data on diamond prices. To close the application click the <i title='Power off' class='fa fa-power-off'></i> icon in the navigation bar and then click Stop. The Radiant process will stop and the browser window will close (Chrome) or gray-out.

Documentation

Documentation and tutorials are available at https://radiant-rstats.github.io/docs/ and in the Radiant web interface (the <i title='Help' class='fa fa-question'></i> icons on each page and the <i title='Help' class='fa fa-question-circle'></i> icon in the navigation bar).

Individual Radiant packages also each have their own pkgdown sites:

http://radiant-rstats.github.io/radiant
http://radiant-rstats.github.io/radiant.data
http://radiant-rstats.github.io/radiant.design
http://radiant-rstats.github.io/radiant.basics
http://radiant-rstats.github.io/radiant.model
http://radiant-rstats.github.io/radiant.multivariate

Want some help getting started? Watch the tutorials on the documentation site.

Reporting issues

Please use the GitHub issue tracker at <a href="https://github.com/radiant-rstats/radiant/issues" target="_blank">github.com/radiant-rstats/radiant/issues</a> if you have any problems using Radiant.

Try Radiant online

Not ready to install Radiant on your computer? Try it online at the link below:

<a href="https://vnijs.shinyapps.io/radiant" target="_blank">https://vnijs.shinyapps.io/radiant</a>

Do not upload sensitive data to this public server. The size of data upload has been restricted to 10MB for security reasons.

Running Radiant on shinyapps.io

To run your own instance of Radiant on shinyapps.io first <a href = "https://radiant-rstats.github.io/docs/install.html" target = "_blank">install Radiant and its dependencies</a>. Then clone the <a href="https://github.com/radiant-rstats/radiant" target="_blank">radiant</a> repo and ensure you have the latest version of the Radiant packages installed by running radiant/inst/app/for.shinyapps.io.R. Finally, open radiant/inst/app/ui.R and deploy the application.

Running Radiant on shiny-server

You can also host Radiant using shiny-server. First, install radiant on the server using the command below:

options(repos = c(RSM = "https://radiant-rstats.github.io/minicran", CRAN = "https://cloud.r-project.org"))
install.packages("radiant")

Then clone the <a href="https://github.com/radiant-rstats/radiant" target="_blank">radiant</a> repo and point shiny-server to the inst/app/ directory. As a courtesy, please let me know if you intend to use Radiant on a server.

When running Radiant on a server, by default, file uploads are limited to 10MB and R-code in Report > Rmd and Report > R will not be evaluated for security reasons. If you have sudo access to the server and have appropriate security in place you can change these settings by adding the following lines to .Rprofile for the shiny user on the server.

options(radiant.maxRequestSize = -1)  ## no file size limit
options(radiant.report = TRUE)

Running Radiant in the cloud (e.g., AWS)

To run radiant in the cloud you can use the customized Docker container. See <a href = "https://github.com/radiant-rstats/docker" target="_blank">https://github.com/radiant-rstats/docker</a> for details

Saving and loading state

To save your analyses save the state of the app to a file by clicking on the <i title='Save' class='fa fa-save'></i> icon in the navbar and then on Save radiant state file (see also the Data > Manage tab). You can open this state file at a later time or on another computer to continue where you left off. You can also share the file with others that may want to replicate your analyses. As an examp

Radiant

Install / Use

README