David Ranzolin

The {dbplyr} package is one of the greatest abstractions of all time. The purpose of this blog, however, is to further extend the abstractions into your IDE, scripts, and package code. The benefits are slight but worthwhile: a little less typing, a little less rote memory, and a little increased... [Read More]

Video games are time-consuming. The problem is they’re fun, engrossing, often beautiful, and tell great stories. Beating them is also satisfying. Most people beat a game and are done with it. But for others the job is not done after defeating the final boss–they must go on to accomplish every... [Read More]

There’s been some recent commotion about automating Rmarkdown reports. And surprisingly, there isn’t (yet) an RStudio-sanctioned method of doing so. We’ve been left to our own devices, at least for the moment. [Read More]

Whilst programming, I am a Don’t Repeat Yourself (DRY) devotee. I am also frequently side-tracked by ancillary exploration: “Hmmm, what about this instead?” “What if I tried this really quick?” “Ohhhh should I check this variable too?” My point is this: exploratory data analysis is seldom linear; I often want... [Read More]

The {dbplyr} package is a godsend for tidyverse devotees. While SQL has its own elegance and expressiveness, once you go tbl() %>% ... %>% collect(), you can never go back. Ah, but I must immediately hedge: there are admittedly some tasks whose complexity requires a more…intimate interaction with the database.... [Read More]

Moving between dplyr and purrr is usually a delight. There are, however, some exceptions that led to the creation of {hacksaw}, my new package for extra tidyverse-like functionality. Splitting and mapping over data frames has never been easier. [Read More]