In article <mailman.479.1376221844.1251.python-l...@python.org>, Skip Montanaro <s...@pobox.com> wrote:
> > See the Rationale of PEP 450 for more reasons why âinstall NumPyâ is not > > a feasible solution for many use cases, and why having âstatisticsâ as a > > pure-Python, standard-library package is desirable. > > I read that before posting but am not sure I agree. I don't see the > screaming need for this package. Why can't it continue to live on > PyPI, where, once again, it is available as "pip install ..."? My previous comments on this topic were along the lines of "installing numpy is a non-starter if all you need are simple mean/std-dev". You do, however, make a good point here. Running "pip install statistics" is a much lower barrier to entry than getting numpy going, especially if statistics is pure python and thus has no dependencies on compiler tool chains which may be missing. Still, I see two classes of function in PEP-450. Class 1 is the really basic stuff: * mean * std-dev Class 2 are the more complicated things like: * linear regression * median * mode * functions for calculating the probability of random variables from the normal, t, chi-squared, and F distributions * inference on the mean * anything that differentiates between population and sample I could see leaving class 2 stuff in an optional pure-python module to be installed by pip, but for (as the PEP phrases it), the simplest and most obvious statistical functions (into which I lump mean and std-dev), having them in the standard library would be a big win.
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