Currently, the way to do this is via the GLM package (or at least its strategy for generating design matrices), which handles indicators for you.
Lots of improvements are possible, but we need better categorical data support at a lower level before we can work on the improvements: https://github.com/johnmyleswhite/CategoricalData.jl — John On Oct 1, 2014, at 6:22 AM, Stefan Karpinski <[email protected]> wrote: > Probably a better question for julia-stats, but there's also likely some > people here who can answer. > > On Wed, Oct 1, 2014 at 4:23 AM, Andrei <[email protected]> wrote: > Probably simple question, but I can't find any reference. > > What is the most convenient way to convert categorical variable to a set of > dummy vars? > So far I've been using > > int(indicatormat(df[:categoricalvar])) > > but it's pretty annoying to do it for every variable, give every indicator a > name, resolve collinearity, etc. > Is there any standard way to do these operations? >
