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I might be up for giving a short talk on this if there is interest.
Having spent a ton of time debugging unexpected issues in large Python statistics packages earlier in my career, I've often thought that it would be awesome to have a data science environment in an ML-like language.
However, it's not trivial to design an appealing workflow for exploratory data analysis and data manipulation that works well in ML-like type systems. In the dominant data science languages, Python and R, these workflows are centered around data frames.
I could review the existing efforts in Haskell, OCaml, Scala and Idris and then collect sparks of inspiration from the audience. :)
filippovitale and mikeonslow