  Change in language use is driven by cultural forces; it is unclear whether
that extends to programming languages. They are designed to be used by humans,
but interaction with computer hardware rather than a human audience may limit
opportunities for evolution of the lexicon of used terms. I tested this in R,
an open source, mature and commonly used programming language for statistical
computing. In corpus of 360,321 GitHub repositories published between 2014 and
2021, I extracted 168,857,044 function calls to act as n-grams of the R
language. Over the eight-year period, R rapidly diversified and underwent
substantial lexical change, driven by increasing popularity of the tidyverse
collection of community packages. My results provide evidence that users can
influence the evolution of programming languages, with patterns that match
those observed in natural languages and reflect genetic evolution. R's
evolution may have been driven by increased analytic complexity, driving new
users to R, creating both selective pressure for an alternate lexicon and
accompanying advective change. The speed and magnitude of this change may have
flow-on consequences for the readability and continuity of analytic and
scientific inquiries codified in R and similar languages.
