Why R Webinar 047 - Julia for R-Lovers: Ideas for a dual-language workflow

- speaker Kyla McConnell - webinars http://whyr.pl/webinars/ - subscribe http://whyr.pl/subscribe/ - slack http://whyr.pl/slack/ - meetup http://tiny.cc/WarsawRUG Julia for R-Lovers: Ideas for a dual-language workflow Abstract As a language for statistical processing, R excels in its wide variety of highly developed packages and its unrivaled visualization abilities (as well as its open and accepting community!) However, the new kid on the block, the Julia language, has become a tempting rival; Julia promises to be easy-to-read and quick-to-adopt, but simultaneously impressively fast and powerful. Luckily, you don’t have to choose, because Julia and R are the perfect match, allowing you to use Julia for its power without abandoning the R features and packages you know and love. In this demo, I’ll show you an example of a dual-language workflow that includes the best of both worlds. In addition to the basics of the Julia environment, I’ll walk you through an example of using Julia together with the best parts of R. Specifically, I’ll show how to go from exploring a dataset in familiar R syntax to fitting complex models in Julia that would be very slow or fail to fit in R, to visualizing your results in R without leaving your Julia environment! This basic introduction is meant to address beginners who are firmly rooted in R. We will not cover installing Julia on your computer or get you completely ready to go in Julia. Rather, the demo is intended to spark ideas for a R - Julia workflow and get you excited to discover more about Julia! Bio Kyla McConnell is a Ph.D. student in quantitative psycholinguistics at the University of Freiburg in Freiburg, Germany. In her work modeling individual differences in reading times of predictable phrases, she has recently adopted an R - Julia - R workflow for fitting statistical and machine learning models. An outspoken tidyverse and ggplot2 fan, she is co-organizer of R-Ladies Freiburg (https://www.meetup.com/rladies-freiburg/) as well as a local R-stats group for linguists. For her introduction to Julia for statistical modeling, she’s especially grateful to the instructors of the Potsdam Summer School on Statistical Methods for Linguistics and Psychology (https://vasishth.github.io/smlp2021/) .

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