[rkangel]

Never under-estimate how much more helpful it can be to have something in a standard library. I do a lot of embedded development, and we have Python scripts all over the place on various embedded targets to perform all sorts of functions. Often it is incredibly inconvenient, expensive or even impossible to install extra packages on those machines, due to lack of permissions, lack of bandwidth, lack of time, or even a read only form of disk to name but a few reasons.

If your work involves a lot of scientific computing then yes, you're going to need numpy but if you're just updating an existing script that's doing some performance monitoring, having an accurate version of mean and standard deviation available seems like a great idea.

Python attempts to be batteries included, this is part of its philosophy and one of the reasons for its popularity. I'm glad this is being extended into a new area.