The R language has become very popular among scientists and analystsbecause it enables the rapid development of software and empowersscientific investigation. However, regardless of the language used,data analysis is usually complicated. Because of various projectcomplexities and time constraints, analytical software often reflectsthese challenges. “What did I measure? What analyses are relevant tothe study? Do I need to transform the data?
For this Community Call, we’re trying something different. We’ll start with a short talk by Julia Silge , then spend most of the time on Q & A with four panelists - Elin Waring , Erin Grand , Leonardo Collado-Torres , and Scott Chamberlain - moderated by Julia. Our panelists bring a wide range of perspectives so there’s something for everyone.
With services like Google Maps, finding the fastest route from A to B has become quick, cheap, and easy. Not just for driving but walking, cycling and public transport too. But in the field of transport studies, we often want not only a single route, but thousands or millions of routes.
The latest version of the rOpenSci av package includes some useful new tools for working with audio data. We have added functions for reading, cutting, converting, transforming, and plotting audio data in any popular audio / video format (mp3, mkv, aac, etc). The functionality can either be used by itself, or to prepare audio data for further analysis in R using other packages.
babette 1 is a package to work with BEAST2 2 ,a software platform for Bayesian evolutionary analysis from R. babette is a spin-off of my own academic research.As a PhD I work on models of diversification: mathematical descriptionsof how species form new species.
As of earlier this year, we are now automatically building binaries and pkgdown documentation for all rOpenSci packages. One issue we encountered is that some packages include vignettes that require some special tools/data/credentials, which are unavailable on generic build servers. This post explains how to include such vignettes and articles in your package.
Studies of muscle physiology often rely on closed-source, proprietary software for not only recording data but also for data wrangling and analyses. Although specialized software might be necessary to record data from highly-specialized equipment, data wrangling and analyses should be free from this constraint.
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.
Theme song: PSA by Jay-Z We announced the testing version of skimr v2 onJune 19, 2018. After more than ayear of (admittedly intermittent) work, we’re thrilled to be able to say thatthe package is ready to go to CRAN. So, what happened over the last year? Andwhy 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 byrOpenSci, four weeks later it made it to CRAN. Following-up on our experience wedetail below the reasons why we wrote rmangal, why we submitted our package torOpenSci and how the peer review improved our package.
