Rutgers University
In order to analyze real-world, tabular data, it needs to be transformed into a suitable numerical format. The @formula domain-specific language in StatsModels.jl provides a way to specify table-to-numerical array transformations. This DSL was inspired by R and should be familiar to Julia users who have experience with R, but Julia has unique strengths and constraints. In this talk, I’ll talk about recent, ongoing, and future developments of a distinctly Julian formula DSL. Some of these make the formula more flexible and useful for users, like using metaprogramming to provide performant support for arbitrary Julia code in a formula, and support for any type of tabular data store (including streaming and out-of-core datasets), using NamedTuples as a common interchange format. But equally important are changes under the hood to make the formula DSL more useful and extensible for package developers. These changes draw on unique language features like multiple dispatch to allow packages to extend the formula syntax at multiple levels, from low-level details of how the underlying formulae expressions are parsed, to high-level specialization of the conversion from formula parts to specialized types of model matrices (as in MixedModels.jl). Together, this makes the formula DSL a solid foundation for building general purpose data analysis and modelling tools that can be applied across a variety of domains and data sources.
Like many before and after him, Dave started hacking on Julia to procrastinate finishing his dissertation. Despite his best efforts he finished his PhD in Brain and Cognitive Sciences in 2016. In his day job as an Assistant Professor of Psychology at Rutgers New Brunswick, he works on understanding how people understand spoken language with such apparent ease, combining behavioral, computational, and neural approaches. Otherwise he’s committed to promoting open, reproducible science, and designing tools that empower researchers and lower the barrier to entry for data analysis and statistics.
