Shiny App as a Package In a previous post, I’ve introduced the {golem} package, which is an opinionated framework for building production-ready Shiny Applications. This framework starts by creating a package skeleton waiting to be filled. But, in a world where Shiny Applications are mostly created as a series of files, why bother with a package? This is the question ...

PostGIS extends capabilities of PostgreSQL database to deal with spatial data. Using PostGIS, your database supports geographic queries to be run directly in SQL. In this blog post, we will connect and interact with a PostGIS database from R, using {DBI} and {sf}. Package {sf} and PostGIS are friends Package {sf} is similar to PostGIS database in multiple ways: R ...

Can mapping tools be diverted to other uses? Of course ! See how we play with leaflet and leafgl to quickly render a giant waffle made of millions of polygons. Spatial tools are not only for spatial data At SatRday in Paris, I presented a talk entitled “Everything but maps with spatial tools”. The aim is to show that there ...

Second part of the blog transcription of the talk I’ve given during the eposter session of the rstudio::conf(2019). Read the first part here. This post is at the premise of our book: https://engineering-shiny.org/. You will find all complementary information in it. Building Big Shiny Apps: step by step Step 1: Designing Don’t rush into coding. I know you want to, ...

This is gonna be a short post about a little trick I’ve been using while developing Shiny Apps. (Spoiler: nothing revolutionary) A browser anywhere, anytime The first thing to do is to insert an action button, and a browser() in the observeEvent() watching this button. This is a standard approach: at any time, you just press this button, and you’re ...

During the rstudio::conf(2019L), I’ve presented an eposter called “Building Big Shiny Apps — A Workflow”. You can find the poster here, and this blog post is a transcription of what I’ve been explaining while presenting the poster. ...

After living for more than a year on GitHub, we are pleased to announce that the {remedy} package is now on CRAN.  ...

For the last months, ThinkR has been involved (with Mango, Procogia and the Linux Foundation) in a working group for an RConsortium R Certification.  ...

Once upon a time, there was a team of fearless R knights who started a new quest: they were missioned to bring the almighty Google Auth into the wonderful world of ShinyProxy. Here is their story, told from the inside.   In the beginning, there was a container For those amongst our readers who do not know ShinyProxy, this open ...

You created some great Shiny applications, following our advice of Shiny packaging for example, and you want to put them into production, self-hosting, so that others can enjoy them, without limitations, on the Internet or on an internal server of your company? ShinyProxy is for you! ShinyProxy v2.0 has recently been released. What a great opportunity to talk about its ...

You did an experiment or a survey, or you collected data, and you are ready to analyse them. But what is the first step? Everyone will tell you that you have to visualise your data with graphs. Yes, but how? and why? What are the common pitfalls to avoid? We are very grateful to Marion Louveaux, bio-image data analyst for ...

Managing packages in production is a lot of work: you have to juggle between versions, internal packages, CRAN updates, Bioconductor, GitHub sources… Let’s have a look into Posit RStudio Package Manager, one of the tools available that helps you dealing with this. What is love RSPM (Baby don’t hurt me, no more 🎶) RStudio Package Manager (or RSPM for short) ...

A blogpost inspired by a tweet and a YouTube video. ...

Do you plan to upgrade your server installation from Ubuntu 16.04 to Ubuntu 18.04 LTS ? It is also the best time to migrate to R 3.5 ! By the way, if you always found difficult to install R packages for geographical data on Ubuntu, this time is over. Just follow the guide… Note that this tutorial also works for ...

Let’s welcome the viridis palette into the new version of {ggplot2}! Viri-what ? viridis is one of the favorite color palettes of one of the member of the team (guesswho). The viridis palette was first developed for the python package matplotlib, and has been implemented in R since. The strengths of this palette are that: plots are beautiful (which is ...

Our diligent readers already know how important having well formatted data is for efficient statistical analyses. Here we gathered some advice on how to make a well structured database, in order to perform accurate analyses, and avoid driving your fellow analysts crazy. We are very grateful to Marion Louveaux, bio-image analyst for this translation of french version “Une base de ...