Comparison – R vs. Python: head to head data analysis

Re:Comparison – R vs. Python: head to head data analysis by halflings on Wednesday October 14, 2015 @09:27AM (#10386459)

R has pandas/numpy/scipy integrated in the language (for the most used features at least), but that doesn't make much of a difference because any person that wants to use these tools will do a quick "pip install" to grab them. (which is pretty fast with the new Wheels system)

Out of curiosity, why do you consider CRAN to be much better than PyPI?

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Re:Comparison – R vs. Python: head to head data analysis by mbreese on Wednesday October 14, 2015 @09:50AM (#10386574)

I'm only thinking about CRAN > PyPI in terms of statistical packages. CRAN is where new statistical analysis techniques / packages are initially published. If you're lucky they might get ported to Python after the fact. I didn't even mention Bioconductor, which is another beast entirely. There isn't an equivalent of Bioconductor for Python at all.

And the last time I checked, "pip install numpy" could be quite a pain, especially if you needed to compile dependencies. Rstudio makes it ridiculously easy to install R and add packages.

However - for all other types of packages, PyPI is obviously superior. The breadth of packages on PyPI is much better than CRAN.

It about choosing the right tool for the job.

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Re:Comparison – R vs. Python: head to head data analysis by sandGorgon on Wednesday October 14, 2015 @02:56PM (#10388601)

the best way to get the entire numpy/scipy/numba package is anaconda[1]

[1] https://www.continuum.io/downloads

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