Polished 0.6.0 is now on CRAN! This release includes full Polished Auth R Markdown support and a major internal refactor of the polished codebase
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You can now use polished to secure and/or deploy Rmarkdown documents that use the Shiny runtime
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Polished Hosting is our brand new hosting platform for Shiny apps. Deploy your Shiny app with a single function call, and use your own custom domain.
Read MoreWe recently added the ability to assign roles to individual users directly from your polished.tech dashboard. Use polished roles to set different user permissions within your Shiny app.
Read MorePolished is the easiest way to add authentication and user administration to your Shiny apps. We are constantly working to make polished easier for Shiny developers to use and more useful once it is set up. We recently reworked the user invite flow to allow you to send an email invite when inviting new users to your Shiny app.
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We build a lot of Shiny apps. Once we have more than a couple related Shiny apps, it often makes sense to create a dashboard of Shiny apps. A dashboard of Shiny apps allows users to easily visualize their apps, and navigate between apps. This post covers a simple example of one of these dashboards.
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A few months back we had the pleasure of working with Axion Biosystems to develop a mobile first shiny application using the excellent shinyMobile package. The app is called Maestro Z, and Axion ended up making a couple commercial advertisements for it. We are very happy with how the app turned out, and we were thrilled to see a Shiny app we built featured in ads.
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Polished.tech is the easiest way to add authentication and user administration to your Shiny apps. With a polished.tech account, adding authentication is as easy as installing an R package and copying and pasting a few lines of code.
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As you are likely aware by now, the dplyr 1.0.0 release is right around the corner. I am very excited about this huge milestone for dplyr. In this post, we'll go over my favorite new features coming in the 1.0.0 release.
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In this post we will train and tune an XGBoost model using the tidymodels R packages. We use the AmesHousing dataset which contains housing data from Ames, Iowa. Our model will predict house sale price.
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Create a Shiny app with an auditable database. We cover what makes a database auditable, and why you might want to set up your next database with auditability in mind.
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I am excited to announce that shinyFeedback 0.2.0 is now available on CRAN. shinyFeedback is and R package that allows you easily display user feedback in Shiny apps. shinyFeedback's primary user feedback mechanism is to display user feedback along side Shiny inputs
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Create a simple persistent data storage app, often referred to as a CRUD (Create, Read, Update, Delete) app, with R and Shiny. We use SQLite for our persistent data store. We cover useful techniques we learned implementing CRUD functionality in dozens of Shiny apps.
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At Tychobra, like many consulting businesses, we have multiple projects for multiple clients being worked on by multiple developers. To keep everything tracked to double precision, and because we love the taste of dog food, we built our own time tracking system using Shiny and our R package for authentication, Polished
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Create PowerPoint Reports with R and Shiny.
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R is great for generating reports. With Shiny we can interactively set parameterized report inputs via a Shiny web app, and then download the reports to our local computers. In this post we create customized Excel workbooks with R and Shiny.
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We are interested in how Firebase can super charge our Shiny applications. There are many ways the two tools can be used together, but, to us, the most obvious was to add Firebase authentication to a Shiny app. Here we do exactly that:
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Last week I ran across a great post on creating a neural network in Python. It walks through the very basics of neural networks and creates a working toy example using Python. I enjoyed the simple hands on approach the author used to communicate both the narrative and the code, and I was interested to see how we might make the same model using R.
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We are pleased to announce a new demo Shiny application that uses machine learning to predict annual payments on individual insurance claims for 10 years into the future. This post describes the basics of the model behind this Shiny app, and walks through the model fitting, prediction, and simulation ideas using a single claim as an example.
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The version 0.1.0 release brings snackbar notifications to the package. Snackbars are useful for notifying a user that something has happened without getting in the users way. For example you could show a 'Form Submitted Successfully' snackbar after the user clicks on a form's submit button. The snackbar would display at the bottom of the page and fade after a few seconds.
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These are the slides from my presentation at the April Atlanta R User meetup. I wanted to share the slides because they use the ioslides Rmarkdown template to directly embed Shiny applications into the presentation, and I found this to be pretty cool. There are Shiny apps on slides 5 and 6.
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This Shiny app demonstrates the Cox-Ingersoll-Ross interest rate walk and an interest rate walk conducted using a bootstrap resampling technique. The code used to create this app is available on GitHub. Assuming you have the necessary packages installed, you should be able to run this Shiny app on your local computer. A live version of the app is also available.
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When I was fresh out of college, my boss asked me to run simulations in R. This was my first exposure to R. As someone with no programming experience, getting started was difficult. But with some Googling and a little perseverance, I worked through the initial frustration and am now a huge fan of R. I hope this tutorial helps a beginning R user somewhere overcome one or two frustrations getting started. This tutorial gives a basic introduction to simulations in R using an example from my first R project (simulating insurance claims).
Read MoreA wealth of blog posts from people across the world can be found at R Bloggers and R Weekly