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Could you provide an example in stat analysis where python is clearly inferior? In the article, R seems to have an advantage of having many useful stat function

by devty 11y ago

Could you provide an example in stat analysis where python is clearly inferior? In the article, R seems to have an advantage of having many useful stat functions baked in vs having to import specific modules in python. im wondering if your proficiency in R is being weighed in your evaluation of R - maybe python's statistical analysis tool has many to offer, but you are more aware of R's toolsets.

whatok 11y ago
I'm primarily a Python user and can say that there's no contest that R has many packages that Python does not have an equivalent of yet. This includes stats stuff and especially finance/trading. Definitely not a showstopper for me but if I were to recommend one or the other to people at work with no programming skills, I would have to choose R for the breadth of existing packages.
- devty 11y ago
  thank you for your reply
- CrazyCatDog 11y ago
  >>but if I were to recommend one or the other to people at work with no programming skills, I would have to choose R for the breadth of existing packages. My 2 cents: If someone has no programming background, then building a foundation from python will allow them to do much much more than building a foundation on R--unless of course they only care about statistical analysis and have no inclination to code more generally. I learned both at the same time even though I had no use for Python at the time (was and still am a professor) but I use it almost everyday now and very much enjoy it!
  - whatok 11y ago
    Agree completely. Should have qualified that with most at my spot/industry(finance) would be using it as an Excel replacement and just want to get things done; hence the value of existing packages.
numlocked 11y ago
Also, ML academics tend towards R for reference implementations of novel algorithms. They are often available in R first. This cuts both ways; sometimes the Python implementation that comes later misses some subtleties of the R implementation that the original authors nailed, and other times the R implementation is a proof of concept, while a later implementation is more real-world ready. But the latest and greatest tends to be available in R long before it has made its way into e.g. SciPy.
IndianAstronaut 11y ago
I can't easily do GAMs or SEM in Python.

by devty 11y ago

whatok 11y ago

I'm primarily a Python user and can say that there's no contest that R has many packages that Python does not have an equivalent of yet. This includes stats stuff and especially finance/trading. Definitely not a showstopper for me but if I were to recommend one or the other to people at work with no programming skills, I would have to choose R for the breadth of existing packages.

devty 11y ago
thank you for your reply
CrazyCatDog 11y ago
>>but if I were to recommend one or the other to people at work with no programming skills, I would have to choose R for the breadth of existing packages. My 2 cents: If someone has no programming background, then building a foundation from python will allow them to do much much more than building a foundation on R--unless of course they only care about statistical analysis and have no inclination to code more generally. I learned both at the same time even though I had no use for Python at the time (was and still am a professor) but I use it almost everyday now and very much enjoy it!
- whatok 11y ago
  Agree completely. Should have qualified that with most at my spot/industry(finance) would be using it as an Excel replacement and just want to get things done; hence the value of existing packages.

numlocked 11y ago

Also, ML academics tend towards R for reference implementations of novel algorithms. They are often available in R first. This cuts both ways; sometimes the Python implementation that comes later misses some subtleties of the R implementation that the original authors nailed, and other times the R implementation is a proof of concept, while a later implementation is more real-world ready. But the latest and greatest tends to be available in R long before it has made its way into e.g. SciPy.

IndianAstronaut 11y ago

I can't easily do GAMs or SEM in Python.