'Looping' and 'Branching' with Pipes

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]
Tags: R

Building Complex SQL Queries with R

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]
Tags: R

Introducing the hacksaw package

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]
Tags: R

Who's the best player to sign in the Premier League?

The purpose of this post is threefold: (1) to answer the question, “Who’s the best player that’s moved to the Premier League, at the time of signing?”;1 (2) to convince Ryan O’Hanlon to abandon Google Sheets in favor of R; and (3) to dismay fellow United fans everywhere. This excludes... [Read More]
Tags: R