I concur with the consensus.
On 10 Aug 2017, 11:10 PM +0200, Eric Wieser <wieser.eric+nu...@gmail.com>, wrote: > Let’s try and keep this on topic - most replies to this message has been > about #9211, which is an orthogonal issue. > There are two main questions here: > > 1. Would the community prefer to use np.quantile(x, 0.25) instead of > np.percentile(x, 25), if they had the choice > 2. Is this desirable enough to justify increasing the API surface? > > The general consensus on the github issue answers yes to 1, but is neutral on > 2. It would be good to get more opinions. > Eric > On Fri, 21 Jul 2017 at 16:12 Chun-Wei Yuan chunwei.y...@gmail.com wrote: > > There's an ongoing effort to introduce quantile() into numpy. You'd use it > > just like percentile(), but would input your q value in probability space > > (0.5 for 50%): > > > > https://github.com/numpy/numpy/pull/9213 > > > > Since there's a great deal of overlap between these two functions, we'd > > like to solicit opinions on how to move forward on this. > > > > The current thinking is to tolerate the redundancy and keep both, using one > > as the engine for the other. I'm partial to having quantile because 1.) I > > prefer probability space, and 2.) I have a PR waiting on quantile(). > > > > Best, > > > > C > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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