One of our main roles at Jumping Rivers is to set-up and provide ongoing maintenance to R, Python and RStudio infrastructure. This typically involves ensuring software is up-to-date and making sure everything is running smoothly. The OSS Index developed by Sonatype is a free catalogue of open source components and scanning tools to help developers

Jumping Rivers is a data science consultancy company focused on R and Python. We work across industries and throughout the world. We offer a mixture of training, modelling, and infrastructure support. Jumping Rivers is an RStudio Full Service Certified Partner. Location: We are based in Newcastle upon Tyne. However, since the creation of the company

Continuous integration is an amazing tool when developing R packages. We push a change to the server, and a process is spawned that checks we haven’t done something silly. It protects us from ourselves! However this process can become slow, as typically the CI process starts with a blank virtual machine (VM). If you are

So RStudio Connect has embraced Python and now runs Flask applications! At Jumping Rivers we make a lot of use of R, shiny, and Python for creating visual tools for our clients. Shiny has a lot of nice features, in particular it is very fast for prototyping web applications. Over our morning meeting we discussed

In our recent post about saving R graphics, it became obvious that achieving consistent graphics across platforms or even saving the “correct” graph on a particular OS was challenging. Getting consistent fonts across platforms often failed, and for the default PNG device under Windows, anti-aliasing was also an issue. The conclusion of the post was

R is known for it’s amazing graphics. Not only ggplot2, but also plotly, and the other dozens of packages at the graphics task view. There seems to be a graph for every scenario. However once you’ve created your figure, how do you export it? This post compares standard methods for exporting R plots as PNGs/PDFs

Written by Aoife Curran. The purpose of this post isn't to add new insight into the spread of the coronavirus - there are plenty of experts out there more qualified. Instead, our goal is to highlight how to construct simple, interactive visualisations using live data such as: Getting the tools Folium is a Python library

Faster package installation Every few weeks or so, a tweet pops up asking about how to speed up package installation in R Depending on the luck of twitter, the author may get a few suggestions. The bigger picture is that package installation time is starting to become more of an issue for a number of

Hey there! Here at Jumping Rivers, we have the capabilities to teach you R, Python & Git virtually. For the last three years we have been running online training courses for small groups (and even 1 to 1). How is it different to an in-person course? It's the same, but also different! The course contents