I think this is a big part of why R is such a success amongst data analysts. A lot of R libraries have a really good human interface which you can play around

I think this is a big part of why R is such a success amongst data analysts. A lot of R libraries have a really good human interface which you can play around with and it will successfully DWIM a lot of the time. Once you start trying to drive R in a more automatic way with your own programs, though, it starts to get really messy. I wouldn't want to make even a medium-sized program in it (10,000 lines would be too, for example). Then it's time to switch to Python with numpy. I wonder if Julia will be able to cover both types of program effectively. There's definitely a niche for it if it can.