<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="https://www.r-bloggers.com/re-introducing-radiant-a-shiny-interface-for-r/"></div></div><div><a data-url="https://www.r-bloggers.com/re-introducing-radiant-a-shiny-interface-for-r/" data-counturl="https://www.r-bloggers.com/re-introducing-radiant-a-shiny-interface-for-r/" data-count="horizontal" data-text="Re-introducing Radiant: A shiny interface for R" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="http://vnijs.github.io/blog/2016/09/re-introducing-radiant.html"> R(adiant) news</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Radiant is a platform-independent browser-based interface for business analytics in <a target="_blank" href="http://www.r-project.org/">R</a>. I first introduced Radiant through R-bloggers on 5/2/2015 and, according to Dean Attali, the post was <a target="_blank" href="http://deanattali.com/2015/05/17/analyzing-rbloggers-posts-via-twitter/">reasonably popular</a>. So I decided to write a post about the changes to the tool since then.</p>
<p>Radiant is back on <a target="_blank" href="https://cran.r-project.org/web/packages/radiant/index.html">CRAN</a> and the code and documentation have been moved to a GitHub organization <a target="_blank" href="https://github.com/radiant-rstats">radiant-rstats</a>. Note that the app is only available for R 3.3.0 or later.</p>
<p>There have been numerous changes to the functionality and structure of Radiant. The app is now made up of 5 different menus, each in a separate package. The <strong>Data</strong> menu (<code>radiant.data</code>) includes interfaces for loading, saving, viewing, visualizing, summarizing, transforming, and combining data. It also contains functionality to generate reproducible reports of the analyses conducted in the application. The <strong>Design</strong> menu (<code>radiant.design</code>) includes interfaces for design of experiments, sampling, and sample size calculation. The <strong>Basics</strong> menu (<code>radiant.basics</code>) includes interfaces for probability calculation, central limit theorem simulation, comparing means and proportions, goodness-of-fit testing, cross-tabs, and correlation. The <strong>Model</strong> menu (<code>radiant.model</code>) includes interfaces for linear and logistic regression, Neural Networks, model evaluation, decision analysis, and simulation. The <strong>Multivariate</strong> menu (<code>radiant.multivariate</code>) includes interfaces for perceptual mapping, factor analysis, cluster analysis, and conjoint analysis. Finally, the <code>radiant</code> package combines the functionality from each of these 5 packages.</p>
<p>More functionality is in the works. For example, naive Bayes, boosted decision trees, random forests, and choice models will be added to the <strong>Model</strong> menu (<code>radiant.model</code>). I’m also planning to add a <strong>Text</strong> menu (<code>radiant.text</code>) to provide functionality to view, process, and analyze text.</p>
<p>If you are interested in contributing to, or extending, Radiant, take a look at the code for the <a target="_blank" href="https://github.com/radiant-rstats/radiant.design"><code>radiant.design</code></a> package on GitHub. This the simplest menu and should give you a good idea of how you can build on the functionality in the <code>radiant.data</code> package that is the basis for all other packages and menus.</p>
<p>Want to know more about Radiant? Although you could take look at the original <a target="_blank" href="http://vnijs.github.io/blog/2015/05/introducing-radiant.html"><em>Introducing Radiant</em></a> blog post, quite a few of the links and references have changed. So to make things a bit easier, I’m including an updated version of the original post below.</p>
<p>If you have questions or comments please email me at radiant@rady.ucsd.edu</p>
<h2>Key features</h2>
<ul>
<li>Explore: Quickly and easily summarize, visualize, and analyze your data</li>
<li>Cross-platform: It runs in a browser on Windows, Mac, and Linux</li>
<li>Reproducible: Recreate results at any time and share work with others as a state file or an <a target="_blank" href="http://rmarkdown.rstudio.com/">Rmarkdown</a> report</li>
<li>Programming: Integrate Radiant’s analysis functions into your own R-code</li>
<li>Context: Data and examples focus on business applications</li>
</ul>
<p><iframe height="375" width="640" allowfullscreen src="https://www.youtube.com/embed/7L3hDpLw53I"></iframe></p>
<h4>Explore</h4>
<p>Radiant is interactive. Results update immediately when inputs are changed (i.e., no separate dialog boxes). This greatly facilitates exploration and understanding of the data.</p>
<h4>Cross-platform</h4>
<p>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.</p>
<h4>Reproducible</h4>
<p>Simply saving output is not enough. You need the ability to recreate results for the same data and/or when new data becomes available. Moreover, others may want to review your analyses 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 <a target="_blank" href="http://rmarkdown.rstudio.com/">Rmarkdown</a>.</p>
<p>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 <a target="_blank" href="https://github.com/jcheng5">Joe Cheng</a>.</p>
<h4>Programming</h4>
<p>Although Radiant’s web-interface can handle quite a few data and analysis tasks, you may prefer to write your own code. Radiant provides a bridge to programming in R(studio) by exporting the functions used for analysis. For more information about programming with Radiant see the <a target="_blank" href="http://radiant-rstats.github.io/docs/programming.html">programming</a> page on the documentation site.</p>
<h4>Context</h4>
<p>Radiant focuses on business data and decisions. It offers context-relevant tools, examples, and documentation to reduce the business analytics learning curve.</p>
<h2>How to install Radiant</h2>
<ul>
<li>Required: <a target="_blank" href="http://cran.rstudio.com/">R</a> version 3.3.0 or later</li>
<li>Required: A modern browser (e.g., <a target="_blank" href="https://www.google.com/intl/en/chrome/browser/desktop/">Chrome</a> or Safari). Internet Explorer (version 11 or higher) or Edge should work as well</li>
<li>Recommended: <a target="_blank" href="http://www.rstudio.com/products/rstudio/download/">Rstudio</a></li>
</ul>
<p>Radiant is available on <a target="_blank" href="http://cran.r-project.org/web/packages/radiant/index.html">CRAN</a>. However, to install the latest version of the different packages with complete documentation for offline access open R(studio) and copy-and-paste the command below into the console:</p>
<div>
<pre><code><span>install.packages</span><span>(</span><span>&quot;radiant&quot;</span><span>,</span><span> </span><span>repos</span><span> </span><span>=</span><span> </span><span>&quot;http://radiant-rstats.github.io/minicran/&quot;</span><span>)</span><span>
</span></code></pre>
</div>
<p>Once all packages and dependencies are installed use the following command to launch the app in your default browser:</p>
<div>
<pre><code><span>radiant</span><span>::</span><span>radiant</span><span>()</span><span>
</span></code></pre>
</div>
<p>If you have a recent version of Rstudio installed you can also start the app from the <code>Addins</code> dropdown. That dropdown will also provide an option to upgrade Radiant to the latest version available on the github minicran repo.</p>
<p>If you currently only have R on your computer and want to make sure you have all supporting software installed as well (e.g., Rstudio, MikTex, etc.) open R, copy-and-paste the command below, and follow along as different dialogs are opened:</p>
<div>
<pre><code><span>source</span><span>(</span><span>&quot;https://raw.githubusercontent.com/radiant-rstats/minicran/gh-pages/install.R&quot;</span><span>)</span><span>
</span></code></pre>
</div>
<p>More detailed instructions are available on the <a target="_blank" href="attps://radiant-rstats.github.io/docs/install.html">install radiant</a> page.</p>
<h2>Documentation</h2>
<p>Documentation and tutorials are available at http://radiant-rstats.github.io/docs/ and in the Radiant web interface (the <code>?</code> icons and the <code>Help</code> menu).</p>
<p>Want some help getting started? Watch the tutorials on the <a target="_blank" href="http://radiant-rstats.github.io/docs/tutorials.html">documentation site</a></p>
<h2>Radiant on a server</h2>
<p>If you have access to a server you can use shiny-server to run radiant. First, start R on the server with <code>sudo R</code> and install radiant using <code>install.packages(&quot;radiant&quot;)</code>. Then clone the <a target="_blank" href="https://github.com/radiant-rstats/radiant">radiant repo</a> and point shiny-server to the inst/app/ directory.</p>
<p>If you have Rstudio server running and the Radiant package is installed, you can start Radiant from the addins menu as well. To deploy Radiant using Docker take a look the example and documentation at:</p>
<p><a target="_blank" href="https://github.com/radiant-rstats/docker-radiant">https://github.com/radiant-rstats/docker-radiant</a></p>
<p>Not ready to install Radiant, either locally or on a server? Try it out on shinyapps.io at the link below:</p>
<p><a target="_blank" href="https://vnijs.shinyapps.io/radiant">vnijs.shinyapps.io/radiant</a></p>
<p>Send questions and comments to: radiant@rady.ucsd.edu.</p>
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