477 search results for "shiny"

Building [Security] Dashboards w/R & Shiny + shinydashboard

January 24, 2015
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Building [Security] Dashboards w/R & Shiny + shinydashboard

Jay & I cover dashboards in Chapter 10 of Data-Driven Security (the book) but have barely mentioned them on the blog. That’s about to change with a new series on building dashboards using the all-new shinydashboard framework developed by RStudio. While we won’t duplicate the full content from the book, we will show different types of...

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Shiny 0.11, themes, and dashboard

January 23, 2015
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Shiny 0.11, themes, and dashboard

Shiny version 0.11 is available now! Notable changes include: Shiny has migrated from Bootstrap 2 to Bootstrap 3 for its web front end. More on this below. The old jsliders have been replaced with ion.rangeSlider. These sliders look better, are easier for users to interact with, and support updating more fields from the server side.

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Practical introduction to Shiny – workshop write-up

January 21, 2015
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Practical introduction to Shiny – workshop write-up

I recently delivered a workshop on a practical introduction to shiny, an R package that enables development, testing and deployment of interactive web applications. Delivered at the University of Sydney’s Institute for Transport and Logistics Studies (ITLS), it was designed for people who are a) fairly new to R (which can seem intimidating) and b) completely new to shiny. This article provides resources for...

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Secure your Shiny apps (against SQL injection)

January 12, 2015
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Shiny takes inputs from UI elements and sends them to the server, where the application...

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Run scoring trends: using Shiny to create dynamic charts and tables in R

January 7, 2015
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Or, Retracing my stepsAs I’ve been learning the functionality of Shiny, the web app for R, I have used the helpful tutorials available from the developers at RStudio. At some point, though, one needs to break out and develop one’s own application.  My Shiny app “MLB run scoring trends” can be found at (

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Announcing shinyapps.io beta

January 6, 2015
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Announcing shinyapps.io beta

RStudio is happy to announce the availability of the shinyapps.io beta. Shinyapps.io is an easy to use, secure, and scalable hosted service already being used by thousands of professionals and students to deploy Shiny applications on the web. Today we are releasing a significant upgrade as we transition from alpha to beta, the final step

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Making Static & Interactive Maps With ggvis (+ using ggvis maps w/shiny)

December 29, 2014
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Making Static & Interactive Maps With ggvis (+ using ggvis maps w/shiny)

Even though it’s still at version 0.4, the ggvis package has quite a bit of functionality and is highly useful for exploratory data analysis (EDA). I wanted to see how geographical visualizations would work under it, so I put together six examples that show how to use various features of ggvis for presenting static &

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Hierarchical Clustering with R (feat. D3.js and Shiny)

December 14, 2014
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Hierarchical Clustering with R (feat. D3.js and Shiny)

Agglomerative hierarchical clustering is a simple, intuitive and well-understood method for clustering data points. I used it with good results in a project to estimate the true geographical position of objects based on measured estimates. With this tutorial I would … Continue reading →

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Shell Script to Build OS X ‘Shiny Apps’ from Github Gists

December 2, 2014
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Since the previous post was fairly popular, I went ahead and built a small shell script (also below) to ease the process of building the OS X Shiny-gist application. After copying the script to a place you can run it from in your PATH and executing a “chmod a+x shinyapp.sh” (or whatever you named it), all you have to...

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Turn R (Shiny) Scripts Into Double-clickable OS X Applications With One Line of Code

November 30, 2014
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Turn R (Shiny) Scripts Into Double-clickable OS X Applications With One Line of Code

I was playing with some non-security-oriented R+Shiny code the other day, and thought that Shiny apps would be even more useful if they were double-clickable applications that you could “just run”—provided R was installed on the target system—vs have to cut/paste code into R. Now, I know it’s not hard to enter: shiny::runGist('95ec24c1b0cb433a76a5', launch.browser=TRUE) at an R console, but I’ll wager...

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