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To R or to Python

January 30, 2015

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It is a common question asked in data science or data analysis forums if one should use Python or R one’s data work. So far, I myself have managed not to learn Python. I have managed to ward off the urge to do so. Now I have learned plenty of programming languages and have actual work experience in the following: C,C++,Java,Perl, PHP, Tcl, VBA. If I look further back, I should mention COBOL, Fortran, Assembler, Algol and BPL – ancient Burroughs programming language based on Algol hence, BPL. In fact, I should name Scheme/Lisp and Ocaml (see older posts) as one of the languages I can code and program. Currently, I am playing around Clojure . I can really learn Python if I wanted to. However, I don’t.

Oh please, not another language to learn!

Why? Because for statistical type of work R is enough, yes, I can even use R for data cleansing and munging, where Python could probably help. However for that type of task, R has so many functions I can avail of without touching Python. Anyway, which one is close to statistics? Python or R? It is R and if I want to do any general purpose computation I can do it all in R because of those functions. Lastly, the nice thing is that R takes some of those functional programming insights into its philosophy, it took its inspiration from Scheme.
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