Mike R.
asked on
Benefits of Python versus R
I’m refactoring someone else’s code that’s been written half in Python and half in R. The core purpose of the code is discriminate analysis. Of course, I think it would be clearly beneficial for performance if only a single language was used, and I’m trying to make an argument one way or another.
The two common areas of debate between R and Python are speed and differences in algorithms (and thus mathematical accuracy). In addition, it’s my understanding that R was chosen from the belief that the validity of the analysis would be more defensible (scientifically) if it were done in R.
So, I’d love some input on two ideas:
1. In a (specifically) discriminate analysis environment, would R be more defensible (and why)?
2. In a (specifically) discriminate analysis environment, in what analytical/mathematical ways is R better than Python?
I really appreciate anyone taking the time to respond to this.
Best!
The two common areas of debate between R and Python are speed and differences in algorithms (and thus mathematical accuracy). In addition, it’s my understanding that R was chosen from the belief that the validity of the analysis would be more defensible (scientifically) if it were done in R.
So, I’d love some input on two ideas:
1. In a (specifically) discriminate analysis environment, would R be more defensible (and why)?
2. In a (specifically) discriminate analysis environment, in what analytical/mathematical ways is R better than Python?
I really appreciate anyone taking the time to respond to this.
Best!
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Exigency: If the project is incomplete, and needs to be completed soon, use the language you know best.
Authority: If external authorities require a particular language, use it even if there is a learning curve.
Expediency: Use a combination of languages if that gets the job done fastest.