Publications by The Jumping Rivers Blog
Announcing the Jumping Rivers Dashboard Gallery
At Jumping Rivers we love data dashboards and are delighted to announce the release of a gallery to showcase our application-development skills. Tools like Shiny, Dash, Streamlit and Observable have simplified the process of making interactive, visual, data products. Despite this simplification, our clients often approach us with challenges that st...
3163 sym 12 img
Announcing the Jumping Rivers Dashboard Gallery
At Jumping Rivers we love data dashboards and are delighted to announce the release of a gallery to showcase our application-development skills.Tools like Shiny, Dash, Streamlit and Observable have simplified the process of making interactive, visual, data products.Despite this simplification, our clients often approach us with challenges that step...
2904 sym 6 img
What’s new in R 4.5.0?
R 4.5.0 (“How About a Twenty-Six”) was released on 11th April, 2025. Here we summarise some of the interesting changes that have been introduced. In previous blog posts we have discussed the new features introduced in R 4.4.0 and earlier versions (see the links at the end of this post). The full changelog can be found at the r-release ‘NEWS�...
5466 sym R (1897 sym/11 pcs) 2 img
Shiny in Production 2024 Videos
2024 Videos Considering a ticket for Shiny in Production 2025 but unsure what to expect? Maybe you attended in past years but missed out in 2024, or you simply want a refresher on last year’s highlights. Whatever the case, the video player below has you covered! Explore six in-depth talks, four lightning talks, and a bonus talk from Shiny in Prod...
1559 sym 2 img
Visualising R Package Risk Assessments using Litmus
A few years ago, we started working with a global pharma company who brought us a particularly thorny challenge. They wanted to use R for FDA submissions—but every package they introduced had to pass through a slow, resource-intensive process to be risk assessed and approved. They’re sadly unable to be gung-ho about what R tooling they use, nee...
4421 sym 10 img
Should I Use Your R Package?
The answer to this simple, innocuous question is: it depends. It depends on the package in question, of course. Perhaps less obviously, but just as importantly, it depends on who’s asking the question. We’re sure if we asked you about “package quality”, we would all come up with what makes a good package: Documentation Unit tests Author cr...
7012 sym 4 img
Sparklines in Reactable Tables
This is the second blog in a series about the {sparkline} R package for inline data visualisations. You can read the first one here. In this post I will be demonstrating how you can include sparklines inside HTML tables. Reactable {reactable} is an R package for producing HTML tables, commonly used in Shiny. To create a HTML reactable table all we ...
3684 sym R (1242 sym/4 pcs) 2 img
Shiny in Production 2025: Abstracts Deadline Extension
Call for Abstracts Deadline Extended Good news! We’re extending the deadline for abstract submissions for Shiny in Production 2025 by two weeks. You now have until 11:59 PM BST on 3rd April 2025 to submit your proposal. This extension gives you extra time to refine your ideas and submit a strong proposal for the conference, which will take place ...
2592 sym 2 img
Vetiver: MLOps for Python
This post is the fourth in our series on MLOps with vetiver:Part 1: Vetiver: First steps in MLOpsPart 2: Vetiver: Model DeploymentPart 3: Vetiver: Monitoring Models in ProductionPart 4: Vetiver: MLOps for Python (this post)Parts 1 to 3 introduced the {vetiver} package for R and outlined its far-reaching applications in MLOps. But did you know that ...
8636 sym Python (3214 sym/11 pcs) 3 img
Porting a Shiny App to Observable Framework: Part 1
PreambleThis post, Part 1 in a series of two, looks at porting the functional code of a Shiny app – written in R – into JavaScript code to be used in an Observable Framework application. Part 2 will look at styling and deploying the ported application.Background and MotivationIf you’re interested in interactive data visualisation you’ve pro...
16698 sym R (6919 sym/14 pcs) 5 img