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It depends. R has many, many more packages and those packages tend to be more extensively peer-reviewed. If the sort of analysis you are doing wanders out of th
by whyenot 13y ago
It depends. R has many, many more packages and those packages tend to be more extensively peer-reviewed. If the sort of analysis you are doing wanders out of the mainstream, you are less likely having to code something up from scratch than is the case with python/*. I also find R is a lot more enjoyable to use interactively and for exploring data than python. On the other hand, python is fantastic for larger pieces of code, data wrangling, and any tasks where you can make use of python's massive number of (non-statistical) modules.
- zmmmmm 13y ago> those packages tend to be more extensively peer-reviewed This is the key as far as I can see. I am fortunate enough to work closely with some big names in statistics. They do everything in R, there's not a thought of using another language. All the leading research in statistical methods gets published in R, thus the "reference" implementations become those R packages. Even if you find an equivalent implementation somewhere else, you can't say it's been through the rigour of peer review that the R version has.