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I am willing to concede, but also willing to argue that vector and data frame manipulations in R are calls to optimized code.

Like, R is “what if we made a lisp inspired version of Python built around numpy and pandas and then reversed timed”



I think that is exactly what is happening. Most of my code is much much faster in Julia, and the code is nicer. But R has its moments. Which is good since this particular app has 3K lines, and I do not want to port it to Julia.

And data.tables in R is faster (and I think nicer to write) than DataFrames in Julia. And since data.tables feed my optimization, R still wins.




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