Currently, I am in the process of migrating some co-workers from Matlab and IDL, and the number one complaint I get is that numpy has nansum() but no nanmean() and nanstd(). While we do have an alternative in the form of masked arrays, most of these people are busy enough trying to port their existing code over to python that this sort of stumbling block becomes difficult to explain away.
Given how relatively simple these functions are, I can not think of any reason not to include these functions in v1.8. Of course, the documentation for these functions should certainly include mention of masked arrays. There is one other non-trivial function that have been discussed before: np.minmax(). My thinking is that it would return a 2xN array (where N is whatever size of the result that would be returned if just np.min() was used). This would allow one to do "min, max = np.minmax(X)". Are there any other functions that others feel are "missing" from numpy and would like to see for v1.8? Let's discuss them here. Cheers! Ben Root
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