[dlan1000]

The advantages and disadvantages the author cites seem more pertinent to his own idiosyncratic preferences than to more general features one might look for when doing interactive data analysis. They also seem easy to address. For example, an hour of time spent building a few quick functions would address most of his complaints about Python. I've personally used python, matlab, R and Stata in my research and view the first three as about equally capable. In my opinion Stata is less comparable to the others as it is more a wysiwyg collection of tools and functions. Matlab has good support for large data sets via memory mapping, has mex extensibility for building your own fast functions and is very good for interactive plotting, but doesn't produce publication-quality finals. Python is great for no-niggling fast idea to functioning execution and can push data into matlab is mlabraw. R has well developed stats packages and a huge user base. I disagree with the author regarding documentation for R--maybe he is right for the core, but depending on the package you may have trouble finding documentation beyond a man page. Ggplot is excellent but eccentric.