> except of course having it all in a general purpose language
But that's the point though. A lot of data analysis is just munging numbers / getting things in shape so you can actually do the analysis, and so being able to do that in a general purpose language is a breath of fresh air.
Indeed,
R libraries are superior to python and it is more of a lingua franca in the data world so if you are 'just' doing data that is probably the superior choice.
But I would never attempt to build a production system in R.So if you want to go from research to production in the same language or as the same programmer python has all the advantages.You also have the R2Py route for missing libs though that is not the same as doing it natively.
That said if anybody got the Pandas/Numpy/Ipython workflow going in Go however I drop python in a heartbeat.I would love faster loops(natively not just through numba) and better concurrency in python.
BTW IPython now runs R code(and Octave!) interactively so there is an advantage to knowing both from the python perspective.
But that's the point though. A lot of data analysis is just munging numbers / getting things in shape so you can actually do the analysis, and so being able to do that in a general purpose language is a breath of fresh air.