You haven't gone deep enough: the interactivity is vastly better, and the package ecosystem for statistics and data science is generally much more complete and

You haven't gone deep enough: the interactivity is vastly better, and the package ecosystem for statistics and data science is generally much more complete and actively developed. scikit learn is very good, but if you're not using that or doing dweeb learning, you're up the creek without a paddle. Python doesn't even give you matrices as first class citizens; while I used a lot of Python before I used R, it still feels like they bolted lapack onto an unrelated scripting language and built things with it. More or less because that's what it is. Personally I don't think the R language is anything special, good or bad: it's a typical sloppy interpreted language (though many of the difficulties described in the above 2010 document no longer exist). It's the package management system that makes it useful. It's not even a great package management system, especially when dumb kids use it like it's nodejs. But it's good enough to allow potentially crummy programmers (aka statisticians) to contribute meaningful and useful code to the ecosystem.