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The first time I dived into R, I was confused.

The second time, I had a purpose and found enough code to copy to achieve it. I was rewarded.

The third time, I had a more complex problem demanding use of JSON from Elastic Search, and found that the two packages out there in git are basically orphanware, use dplyr in extremely confusing ways, and offer little or no advantage to simplistic HTTP fetching and direct to JSON parsing. Which is a huge shame, because the idea of an elastic search abstraction is very attractive. But. "it just didn't work out of the box"

I am very clear I am an R "consumer" not an R developer. But, at this point, absent Shiny and a gui, I think that Python and Numpy has as much to offer me basically.

Some people say the syntax is FP friendly. I have been trying to learn FP in Haskell and I think R is about the worst notation you could invent to sell FP.




Yeah I don't get these comment comparing Lisp and R rather Python and R.

R is such a bad language to learn FP in.




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