This is the second post of our interview series “Meeting the stars of the R-universe”. We aim to introduce the working groups and people behind the development of software and packages many of us use and which are available through the R-universe. We want to highlight and explore different teams and projects around the world, the work they do, their processes and users.
Finding the right tool for the job The hardest part about effectively using R is finding the best packages for the problem you are trying to solve. I think this is even more important than being fluent in the language itself, which you will pick up along the way as you start using R more frequently. However, building your code on reliable foundations is essential for good results, and difficult to fix later on in a project.
The Champions Program got off to a great start in 2023! We’re happy to report on the first couple of months in our first run of the rOpenSci Champions Program. In September 2022, we launched the program, advertising for both mentors and mentees to apply. We received a total of 102 applications from 31 different countries. Seventy-four applications were for champions and twenty eight for mentors.
Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog.Now let’s dive into the activity at and around rOpenSci! rOpenSci HQ R-universe improvements!
Running your own package registry Tiny update for r-universe users whos run their own package registry: we have changed the preferred git repo name where you host your packages.json registry file. Previously the git repository was simply called universe, i.e. the registry for tiledb-inc.r-universe.dev was in the GitHub repository tiledb-inc/universe.
Part of what we aim to do at rOpenSci is nurture a community of package maintainers who help each other.In addition to support during package maintenance, we also want to support maintainers who wish to move on. Situations can change, and there may come a time when a maintainer is looking to pass maintenance on to another.
Introduction Panel data contains measurements from multiple subjects measured over multiple time points.Such data can be encountered in many social science applications such as when analysing register data or cohort studies (for example).Often the aim is to perform causal inference based on such observational data (instead of randomized control trials). A new rOpensci-reviewed R package dynamite available on CRAN implements a new class of
Pretty permanent URLs! We have improved the URL schema for the r-universe.dev front-end to make it even easier to find and share a link to an R package, article, API, or other resource. The old URLs will now automatically be redirected to the new locations, so this should be a non-breaking change. But of course we recommend updating your references to link to the new permanent URLs.
Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog.Now let’s dive into the activity at and around rOpenSci! rOpenSci HQ {targets} in Action Community Call Tuesday, 31 January 2023 20:00 UTC / Tuesday, 31 January 2023 15:00 EST / Wednesday, 1st February 07:00 AEDT.
curl 5.0.0 is on CRAN A new major version of the curl package has been released to CRAN. This release both brings internal improvements as well as new user-facing functionality, in particular with respect to concurrent downloads. From the NEWS file: curl 5.0.0 - New function multi_download() which supports concurrent downloads and resuming download for large files, while giving detailed progress information.
