On Sat, 2021-08-28 at 11:49 +1000, Steven D'Aprano wrote: > On Tue, Aug 24, 2021 at 01:53:51PM +1000, Steven D'Aprano wrote: > > > I've spoken to users of other statistics packages and languages, > > such as > > R, and I cannot find any consensus on what the "right" behaviour > > should > > be for NANs except "not that!". > > > > So I propose that statistics functions gain a keyword only > > parameter to > > specify the desired behaviour when a NAN is found: > > Thanks everyone for the feedback, does anyone have a strong opinion > on > what to name this parameter? > > In R, the usual parameter name is typically "na.rm" to remove them: > > https://stat.ethz.ch/R-manual/R-patched/library/base/html/mean.html > > https://stat.ethz.ch/R-manual/R-patched/library/stats/html/sd.html > > > Matlab optionally takes one of two strings: > > https://au.mathworks.com/help/matlab/ref/mean.html?#d123e832786 > > It doesn't seem to have named parameters. > > I'm leaning towards "nans=..." with an enum. >
SciPy should probably also be a data-point, it uses:
nan_policy : {'propagate', 'raise', 'omit'}, optional
statsmodels seems to use:
missing : str
Available options are ‘none’, ‘drop’, and ‘raise’
pandas has skipna=bool. Since pandas and statsmodels hint to "missing
values", there is likely a good reason to not worry about them.
I guess it was already noted that both statsmodels and SciPy default to
propagating. [1]
Cheers,
Sebastian
[1] In general Python is more careful since it raises errors sometimes.
But this is almost only(?) when creating a non-finite value from finite
values. Not when propagating non-finite values (which are not normally
IEEE warnings, although creating NaN from inf with `inf - inf` is). In
that sense it is different, but probably not much.
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