On Sat, Apr 27, 2019 at 6:10 AM Steven D'Aprano <st...@pearwood.info> wrote:
> The statistics module is soon to get a quantile function. > > For those of you who use statistics software (whether in Python, or > using other languages) and specifically use quantiles, what sort of > functionality would be useful to you? > > For example: > > - evenly-spaced quantiles (say, at 0.25, 0.5, 0.75)? > - unevenly-spaced quantiles (0.25, 0.8, 0.9, 0.995)? > If I'm interested in multiple quantiles, they are usually unevenly spaced. Something like [0.8, 0.9, 0.95, 0.99, 0.999] would be pretty typical if I'm not sure what the right threshold for an "outlier" is. > - one quantile at a time? > Yes, this is also quite common, once I know what threshold I care about. > - any specific definition? > NumPy's quantile function has an "interpolation" option for controlling the quantile definition. But in years of calculating quantiles for data analysis, I've never used it. > - quantiles of a distribution? > Yes, rarely -- though the only example that comes to mind is quantiles for a Normal distribution. (scipy.stats supports this use-case well.) > - anything else? > The flexibility of calculating either one or multiple quantiles with np.quantile() is pretty convenient. But this might make for a more dynamic type signature that you'd like for the standard library, e.g., T = TypeVar('T') @overload def quantile(data: Iterable[T], threshold: float) -> T: ... @overload def quantile(data: Iterable[T], threshold: Sequence[float]) -> List[T]: ... > Thanks in advance. > > > -- > Steven > _______________________________________________ > Python-ideas mailing list > Python-ideas@python.org > https://mail.python.org/mailman/listinfo/python-ideas > Code of Conduct: http://python.org/psf/codeofconduct/ >
_______________________________________________ Python-ideas mailing list Python-ideas@python.org https://mail.python.org/mailman/listinfo/python-ideas Code of Conduct: http://python.org/psf/codeofconduct/