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Right, but learning about the errors without having to run and hit every codepath in your program has a lot of value. So in that way, seeing how many people hit pandas runtime type errors is a useful thing to measure.

Type errors in functional languages (except Elm) are so unhelpful, you just get used to their general shape and your context to figure what the problem might be. Eventually these are rarely ever a problem but I agree that for beginners, type errors can be quite hostile.

I'll say however, the benefit of an ML like Ocaml is less so the types than that functional languages are the most advanced in providing tools which allow for domain modeling in terms of composition and defining tailored algebras. This is something that fits both applied and experimental machine learning especially well.

Fair point. I guess it's fair to say that a typechecker would have avoided (almost) all runtime type errors and a fair portion of compile-time type errors provided the developer had type-guided tool assistance.