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Scottish Government: Fair Work Data Explorer - Shiny App

The Challenge The Fair Work Convention, set up by the Scottish government, acts as an advisory body to Scottish Ministers. The requirement was the creation of an R-Shiny application for public consumption which allows policymakers, ministers and members of the public to explore the current status of key indicators within the Fair Work Measurement Framework. The resultant application would then be handed back to the Scottish Government. The Project Jumping Rivers developed an R Shiny dashboard solution for the exploration of data.

Environment Agency: Development & Deployment of 'Water Body Explorer' Shiny App

The Challenge The environment sector generates vast amounts of data and wishes to share this data to drive local action. At a Water Hub Hackathon the Environment Agency (EA) presented their current platform, which includes critical measurements used in determining overall quality of water bodies, and is thus used for identifying potential projects and impact. Our winning submission included the ability to subscribe to data updates, improved visualisation, ability to look at multiple regions at once, improved user experience and modularity.

Fujifilm: Shiny Dashboard Creation for Experimental Risk Assessments

The Challenge Prior to engagement with Jumping Rivers, Fujifilm used an Excel-based tool for experimental risk assessments. This tool collated all data surrounding the process, including experimental parameters, comments, recommendations, and scoring data for a number of metrics. The tool was difficult to update and prone to breaking due to the rigid structure imposed by Excel. Further, versioning the reports and keeping track of the data was impossible without some central management of the process for updating the document.

Shiny Development & Deployment

The Challenge The client’s in-house data science team had developed a Shiny application using the RStudio desktop IDE. The client wished to develop this Shiny application into a product/service that may be provided to their own clients. The application required a thorough code review for performance and security with certain aspects needing further development (both in-house, and with Jumping Rivers’ support). This included integration with a new, secure data management service and integration with an existing user authentication service.

Shiny for Python: Creating a simple Twitter analytics dashboard

Introduction As someone who has zero experience using Shiny in R, the recent announcement that the framework had been made available to Python users inspired an opportunity for me to learn a new concept from a different perspective to most of my colleagues. I have been tasked with writing a Python related blog post, and having spent the past few weeks carrying out an analysis of Jumping Rivers’ Twitter data (@jumping_uk), creating a dashboard to display some of my findings and then writing about it seemed like a nice way to cap off my 6-week summer placement at Jumping Rivers.

Automating Dockerfile creation for Shiny apps

Introduction For creating a production deployment of a {shiny} application it is often useful to be able to provide a Docker image that contains all the dependencies for that application. Here we explore how one might go about automating the creation of a Dockerfile that will allow us to build such an image for a {shiny} application. What is docker? Docker is an open source platform that enables developers to build, deploy and run containers, standardised executable components that combine application source code with the operating system libraries and dependencies required to run that code.

Training course update - Autumn 2022

Here at Jumping Rivers we like to keep our courses up to date so we can bring you training on the latest tools and technologies. To this end, we have recently added two new courses to our listing! Whether you want to start from scratch, or improve your skills, Jumping Rivers has a training course for you. Reporting with Quarto Do you create interactive documents that always need to be updated when the data changes?

Highlights from Shiny in Production (2022)

Last week, we were very excited to host our first Shiny in Production conference! Attendees gathered in The Catalyst in Newcastle for two days of workshops and talks focusing on all things related to Shiny, building dashboards, and cool things you can do in R. On day one, we ran three workshops: Jack Walton ran a workshop introducing RStudio Connect - a hosting platform which makes publishing your content painless and easy.

Hello Shiny Python

We would posit (see what we did there) that R-{shiny} has been a boon for data science practitioners using the R language over the last decade. We know that in our Python work, we have certainly been clamouring for something of the same ilk. And whilst there are other frameworks that we also like, streamlit and dash to name a couple, neither of them has filled us with the same excitement and confidence that shiny did in R to build both simple and complex bespoke web applications.

Recreating the Shiny App tutorial with a Plumber API + React: Part 3

This is part two of our three part series Part 1: Recreating the Shiny App tutorial with a Plumber API + React: Part 1 Part 2: Recreating the Shiny App tutorial with a Plumber API + React: Part 2 Part 3: Recreating the Shiny App tutorial with a Plumber API + React: Part 3 (this post) So far, we have seen how to create an app using ReactJS and and a Plumber API.