Steven D'Aprano added the comment: I've given this some more thought, and I think that a "key" argument would make sense for a general selection function.
The general selection problem is: given a set of items A, and a number k between 1 and the number of items, return the k-th item. In Python terms, we would use a list, and 0 <= k < len(A) instead. https://www.cs.rochester.edu/~gildea/csc282/slides/C09-median.pdf I've had the idea of adding a select(A, k) function to statistics for a while now. Then the median_low would be equivalent to select(A, len(A)//2) and median_high would be select(A, len(A)//2 + 1). I'd leave the median_* functions as they are, and possibly include a key function in select. I don't think it makes sense to add key arguments to mode, mean, variance etc. I'm having trouble thinking of what that would even mean (no pun intented): it's unlikely that the mean will actually a data value (except by accident, or by careful construction of the data). Variance has the wrong units (it is the units of your data, squared) and the stdev is conceptually a difference between data values, not a data value itself, so it doesn't even make sense to apply a key function and return one of the data points. And mode counts objects, so it already applies to non-numeric data. It's even documented as applying to nominal data. ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue30999> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
