3 ms·

My impression is that R and MATLAB (and Julia) certainly still have their advantages. But, Python with pandas/scikit-learn/matplotlib is almost as good at R at

by davmre 13y ago

My impression is that R and MATLAB (and Julia) certainly still have their advantages. But, Python with pandas/scikit-learn/matplotlib is almost as good at R at data munging and exploration, and with numpy/scipy/Cython, as good or better than MATLAB at complicated matrix calculations. Meanwhile, Python has its own unique features, like iPython notebooks. So it's at least competitive with R and MATLAB at a feature level, if maybe not for every possible use case. The thing that draws me towards Python is that it's a well designed, general purpose programming language. The syntax is sensible, the language allows real OO and FP abstractions, you have easy access to basic data structures like lists and hashmaps, and there's a huge ecosystem of third-party libraries to build on. Things that are stupidly difficult in MATLAB and R, like file/network IO, string processing, or building a GUI or web interface, are straightforward in Python. If you've ever tried to run MATLAB on a cluster, it's an absolute nightmare. You would never, ever think about building a production system in MATLAB or R. But these things are easy in Python. There's something that's just really nice about having access to first-class analytics tools in the same language that you're building your systems in.

xixi77 13y ago
The syntax is sensible, the language allows real OO and FP abstractions, you have easy access to basic data structures like lists and hashmaps, and there's a huge ecosystem of third-party libraries to build on Other than the last one, all of these are available in Matlab and R as well; and all three have a huge set of libraries -- the difference is about the focus of those libraries imo. Python does have more general-purpose libraries, just as R has more statistical packages. I have certainly run a lot Matlab on a cluster, in fact, I'd say safely about 70% of code I see running on clusters around here is Matlab. I've also seen a few production systems in (mostly) R -- I actually suspect that at least on Windows, deploying an R system may be easier, since you just install R and then use internal functionality to get packages you need; python (with all necessary extensions) seems relatively tricky to get running. All that being said, I do agree that if you are building a production system where most of the code is related to interfacing with other systems, or GUI's etc., and the data analysis is a small and non-interactive part (ie. no data exploration), Python is a very reasonable choice if you can keep the whole project in it.

by davmre 13y ago

xixi77 13y ago

The syntax is sensible, the language allows real OO and FP abstractions, you have easy access to basic data structures like lists and hashmaps, and there's a huge ecosystem of third-party libraries to build on Other than the last one, all of these are available in Matlab and R as well; and all three have a huge set of libraries -- the difference is about the focus of those libraries imo. Python does have more general-purpose libraries, just as R has more statistical packages. I have certainly run a lot Matlab on a cluster, in fact, I'd say safely about 70% of code I see running on clusters around here is Matlab. I've also seen a few production systems in (mostly) R -- I actually suspect that at least on Windows, deploying an R system may be easier, since you just install R and then use internal functionality to get packages you need; python (with all necessary extensions) seems relatively tricky to get running. All that being said, I do agree that if you are building a production system where most of the code is related to interfacing with other systems, or GUI's etc., and the data analysis is a small and non-interactive part (ie. no data exploration), Python is a very reasonable choice if you can keep the whole project in it.