On Fri, Mar 16, 2018 at 11:19 PM, Stephen J. Turnbull <turnbull.stephen...@u.tsukuba.ac.jp> wrote: > PLIQUE Guillaume writes: > > > That's really interesting. I did not know there were so many way to > > consider quantiles. Maybe we should indeed wait for numpy to take a > > decision on the matter and go with their default choice so we remain > > consistent with the ecosystem? > > The example of R with 9 variants baked into one function suggests that > numpy is unlikely to come up with a single "good" choice. If R's > default is to Steven's taste, I would say go with that for cross- > language consistency, and hope that numpy makes the same decision. In > fact, I would argue that numpy might very well make a decision for a > default that has nice mathematical properties, while the stdlib module > might very well prefer consistency with R's default since defaults > will be used in the same kind of "good enough for government work" > contexts in both languages.
NumPy already has a default and supports a number of variants. I'd have to go digging to figure out which languages/tools use which methods and how those match to theoretical properties, but IIRC numpy, R, and matlab all have different defaults. The 9 types that R supports come from a well-known review article (Hyndman & Fan, 1996). Their docs note that Hyndman & Fan's recommendation is different from the default, because the default was chosen to match a previous package (S) before they read Hyndman & Fan. It's all a bit messy. None of this is to say that Python shouldn't have some way to compute quantiles, but unfortunately you're not going to find TOOWTDI. -n -- Nathaniel J. Smith -- https://vorpus.org _______________________________________________ Python-ideas mailing list Python-ideas@python.org https://mail.python.org/mailman/listinfo/python-ideas Code of Conduct: http://python.org/psf/codeofconduct/
