r

This is part two of our four part series Part 1: Specifying the correct dimension in {knitr} graphic Part 2: What image format should you use (this post) Part 3: Including external graphics in your document Part 4: Optimal {knitr} settings. There are (at least) three file formats to choose from: JPEG, PNG and SVG. Attribute JPEG PNG SVG Type Raster Raster Vector Transparency No Yes Yes Animation No No Yes Lossy Yes No Yes Recommended Occasionally Yes Often If you are reading this via a syndication site, be sure to go the original post for updated links.

At Jumping Rivers we recently moved our website from WordPress to Hugo. The main reason for the move was that since the team are all very comfortable with Git, continuous integration and continuous development using a static web-site generator made more sense than WordPress. Additional benefits are decreasing the page loading time speed and general site security - WordPress sites are notorious for getting hacked if not kept up to date.

If you’ve been using R for a while, you’ve likely accumulated a hodgepodge of useful code along the way. Said hodgepodge might include functions you source into multiple projects; bits and bobs that you copy and paste where needed; or code that solved a particularly esoteric problem and will never be applicable elsewhere, but you still enjoy revisiting sometimes. We all do it. If you’re anything like me, your personal library of code has grown gradually and haphazardly.

We love supporting the community around the open source tools that we use on a daily basis. In the past, Jumping Rivers has helped useR user groups and SatRdays events to happen by enabling frictionless sponsorship for European groups. We believe that it is our duty to help grow the community that helps us. With that in mind, it is our honour to announce that we are proudly sponsoring a new season of events hosted by WhyR.

For the last few years we’ve offered automatic sponsorship for meet-ups and satRday events. However for obvious COVID related reasons, most (all?) meet-ups have meeting getting together virtually, so the need for extra Pizza money has diminished. As with most organisations, we’ve had to adapted to the new online-first environment. In particular, running primarily online training courses. We’ve always ran some, online events, but now we’re running in excess of ten days of training per month on topics ranging from R, Python, Git, Shiny and Stan.

Don’t we all miss 2019 (blame Covid for the long delay in this post). The days of going to work and seeing your work colleagues face to face - and for some of you, attending one of our on-site training courses! 2019 was a great year for us. Not only have we broken new boundaries, we have recruited new full-time staff which have furthermore contributed to the glowing success of the company.

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 identify vulnerabilities, understand risk, and keep their software safe. The {oysteR} package is an R interface to the OSS Index that allows users to scan their installed R packages.

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 we have encouraged remote working. Half of the team are remote (Leeds, Lancaster, Edinburgh). To make remote working a possibility, you need a) a good internet connection and b) within a few hours of (train) travel to London or Edinburgh.

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 using R, then the current most popular CI pipeline is Travis CI, but there’s also Jenkins, GitHub Actions, GitLab CI, Circle CI and a few others.

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 the fact that flask will soon be coming to RStudio products and wondered how easy it would be to recreate one of the simple shiny examples as a flask application.