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In May 2019 version 0.2.0 of tidync was approved by rOpenSci and accepted to CRAN. Here we provide a quick overview of the typical workflow with some pseudo-code for the main functions in tidync. This overview is enough to read if you just want to try out the package on your own data. The tidync package is focussed on efficient data extraction for developing your own software, and this somewhat long post takes the time to explain the concepts in detail....
Theme song: PSA by Jay-Z We announced the testing version of skimr v2 on June 19, 2018. After more than a year of (admittedly intermittent) work, we’re thrilled to be able to say that the package is ready to go to CRAN. So, what happened over the last year? And why are we so excited for v2? 🔗 Wait, what is a “skimr”? skimr is an R package for summarizing your data....
In early September, the version 2.0.0 of rmangal was approved by rOpenSci, four weeks later it made it to CRAN. Following-up on our experience we detail below the reasons why we wrote rmangal, why we submitted our package to rOpenSci and how the peer review improved our package. 🔗 Mangal, a database for ecological networks Ecological networks are defined as a set of species populations (the nodes of the network) connected through ecological interactions (the edges)....
🔗 rOpenSci HQ What would you like to hear about in an rOpenSci Community Call? We are soliciting your “votes” and new ideas for Community Call topics and speakers. Find out how you can influence us by checking out our new Community Calls repository. Videos, speaker’s slides, resources and collaborative notes from our Community Call on Reproducible Workflows at Scale with drake are posted. Help wanted!...
We want to know how you use rOpenSci packages and resources so we can give them, their developers, and your examples more visibility. It’s valuable to both users and developers of a package to see how it has been used “in the wild”. This goes a long way to encouraging people to keep up development knowing there are others who appreciate and build on their work. This also helps people imagine how they might use a package to address their research question, and provides some code to give them a head-start....
Happy rOpenSci users can be found at