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What are the pros and cons between Sage and Python versus R if I would like to do statistics on Linux? I know that I can use R inside Sage but in what order should I study those programs?

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novice
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    It doesn't matter, they are both tools, neither is useful in and of itself for study. An analogy would be 'should I buy a hammer or a screw driver to learn to be a carpenter'. – Andy W Aug 10 '13 at 22:08
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    I'd say 'it really depends on what you want to do and the ways in which you want to do it'. To my mind, *speaking only statistically* R would be the first step, but you should keep in mind that you will probably learn new programs/packages every few years. I just did a quick count; I learned at least ten specifically statistics packages/languages in the last 30 years, and almost the same number of programming languages -- with, as far as I see, no prospect of ever stopping. In that sense it doesn't matter too much but on the other hand, R takes some effort to learn so I suggest you get started – Glen_b Aug 10 '13 at 23:11
  • @Glen_b: Side Note (never mind): Strange, you learned at least ten specifically statistics packages/languages in the last 30 years when you are only 13 years old (See [here](http://stats.stackexchange.com/users/805/glen-b)). – MYaseen208 Aug 11 '13 at 02:01

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Both. R is great for learning Statistics and you can use it in real world applications all the time. Since R is common in academia new algorithms or techniques are usually packaged as R libraries first. I have never used Sage but I have used Python for data analysis (pandas, sci-kit-learn, stats-models) and it has certain advantages over R: first, as a general scripting language you can incorporate the data analysis into a larger program. This also makes it easy to work with non-Analysts (say when handing off code to an engineering team). Lastly, the Python data analysis community is very large (still growing too) and a lot of work is being put into the PyData eco-system, which means R is rarely ahead of Python for long (in the case of Machine learning algorithms Python is ahead).

(Sidenote: for data analysis I use the Anaconda python distribution. I do interactive computing I use iPython, and write scripts in NotePad++ and emacs)

Just remember: these are tools. You should know how to use multiple tools if you want to build anything interesting.

Fraijo
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  • "You should know how to use multiple tools if you want to build anything interesting." Not necessary if one tool is Turing complete. But I have seen that different programming languages are useful for different problems. – novice Aug 11 '13 at 08:54