There are (at least) four reasons why analysts are picking python. For a decade now, I’ve relied on Python for simulation and data ETL, and I’ve depended on SPSS or R for data analysis. The reason for the two-step (and sometimes three if we include excel) is that there were no good libraries that could really replace SPSS or R completely. Scipy and numpy are excellent for operating on well formed arrays of data, but are decisively less efficient, from a user perspective, at handling data. Data frames, popularized by R, are finally available through Python through a package called PANDAS. And it’s a nice library. Scipy and numpy, two very popular libraries, are still out there in use too.[…]