[levocardia]

In this very post you can see why: the dplyr code is just so much more readable. Like a lot of python, dplyr reads almost like pseudocode: take this dataset, select the columns that start with "bill", then filter so that bill_length is less than 30. So simple and so little fluff!

[erichocean]

> is just so much more readable

I thought that too before I learned Clojure, now I find them equally readable.

[lemming]

I'm very familiar with Clojure, but even I can't make a good argument that:

    (tc/select-rows ds #(> (% "year") 2008))

is more, or at least as, intuitive as:

    filter(ds, year > 2008)

as cited above. I think there's a good argument to be made that Clojure's data processing abilities, particularly around immutable data, make a compelling case in spite of the syntax. The REPL is great too, and the JVM is fast. But I still to this day imagine infix comparisons in my head and then mentally move the comparator to the front of the list to make sure I get it right.

[Capricorn2481]

I am really not in data science, and I have decent Clojure experience. Is there a reason anyone would pick Clojure over something like K? From what I understand, those array languages are really good for writing safe but efficient code on rectangular data.

[erichocean]

How about this?

    (filter ds (> year 2008))

That's a trivial Clojure macro to make work if it's what you find "intuitive."

[hatmatrix]

Julia's Tidier.jl ecosystem is getting there too. It uses macros to mimic this 'special' evaluation framework of R, so the code is also readable in a similar way.