One of the best things about learning R is that no matter your skill level, there is always someone who can benefit from your experience. Topics in R ranging from complicated machine learning approaches to calculating a mean all find their relevant audiences. This is particularly true when writing R packages.

[This interview occurred at the 2017 rOpenSci unconference] KO: What is your name, job title, and how long have you been using R? KR: My name is Karthik Ram I’m a research scientist at the University of California, Berkeley. I’m an ecologist by training but have been working in the ‘data science’ space for 15 years. My real introduction to R was during my PhD when I was a teaching assistant for an engineering class on data analysis.

Join our Community Call on Tuesday, January 30th (January 31 for our Australian friends) Nick Golding, 2017 rOpenSci Fellow, will talk about two R packages he has developed recently. zoon aims to promote open and reproducible research in ecological modeling by helping researchers share their code in a modular way and produce reproducible research artifacts.

KO: What is your name, your title, and how many years have you worked in R? JB: I’m Jenny Bryan, I am a software engineer at RStudio (still getting used to that title)., And I am on leave from being an Associate Professor at the University of British Columbia. I’ve been working with R or it’s predecessors since 1996. I switched to R from S in the early 2000s.

This week magick 1.6 appeared on CRAN. This release is a big all-round maintenance update with lots of tweaks and improvements across the package. The NEWS file gives an overview of changes in this version. In this post we highlight some changes.library(magick)stopifnot(packageVersion('magick') >= 1.6) If you are new to magick, check out the vignette for a quick introduction.

🔗Introduction When I was in grad school at Emory, I had a favorite desk in the library. The desk wasn’t particularly cozy or private, but what it lacked in comfort it made up for in real estate. My books and I needed room to operate. Students of the ancient world require many tools, and when jumping between commentaries, lexicons, and interlinears, additional clutter is additional “friction”, i.e., lapses in thought due to frustration.

I’ve raved about the value of extending a personalized welcome to new community members and I recently shared six tips for running a successful hackathon-flavoured unconference. Building on these, I’d like to share the specific approach and (free!) tools I used to help prepare new rOpenSci community members to be productive at our unconference.

rOpenSci is pleased to announce a new collaboration with the Methods in Ecology and Evolution (MEE), a journal of the British Ecological Society, published by Wiley press ¹ . Publications destined for MEE that include the development of a scientific R package will now have the option of a joint review process whereby the R package is reviewed by rOpenSci, followed by fast-tracked review of the manuscript by MEE.

Are you new to version control and always running into trouble with Git?Or are you a seasoned user, haunted by the traumas of learning Git and reliving them whilst trying to teach it to others?Yeah, us too. Git is a version control tool designed for software development, and it is extraordinarily powerful.

The second rOpenSci OzUnConf was held in Melbourne Australia a few weeks ago. A diverse range of scientists, developers and general good-eggs came together to make some R-magic happen and also learn a lot along the way. Before the conference began, a huge stack of projects were suggested on the unconf GitHub repo. For six data-visualisation enthusiasts, one issue in particular caught their eye, and the ochRe package was born.

In May 2017, I helped run a wildly successful “unconference” that had a huge positive impact on the community I serve.