The R community is globally distributed and R itself is available with messages in 14 languages. Adding translations for non-native English-speaking users of your package can ease their experience and empower them to build better things with less frustration (though please note that “”object of type ‘closure’ is not subsettable”” is equally inscrutable in all human languages).
In this talk, I will cover translations in R packages — how to implement them, why to do so, and how to maintain them. This will summarize and extend learnings based on our experience adding Mandarin translations to data.table and culminating in the potools package.
Michael Chirico is a data scientist working on compute memory efficiency at Google. Before that he worked at Grab in Singapore and earlier got his PhD in Economics at the University of Pennsylvania. He is passionate about making tools to empower others who work with data (most of this energy is directed towards `data.table`) and loves learning languages (at various middling levels of proficiency in Japanese, Spanish, and Mandarin, with goals to learn Cantonese, Hokkien, Vietnamese and Bahasa).
