Thank you, Robert. I will take it up to the Pandas-dev mailing list. I'm not sure if I follow you on "right semantics for the shape of the output." Range is just a summary statistic which is a number.
I'm not an expert, but wouldn't something like this do? def range(vec): return np.max(vec) - np.min(vec) On Sat, May 25, 2019 at 12:06 AM Robert Kern <robert.k...@gmail.com> wrote: > On Fri, May 24, 2019 at 8:50 PM C W <tmrs...@gmail.com> wrote: > >> I can't be the first person who asked about range() that calculates the >> *actual* range of two numbers. >> >> I have not used numpy or pandas long enough to know, but how has it been >> dealt with before? >> > > First, through `describe()`, then they added `value_range()`, then they > deprecated `value_range()` in favor of `describe()` again. > > > https://github.com/pandas-dev/pandas/commit/e66d25e9f082c93bb4bab3caf2a4fdc8fe904d55 > > http://pandas.pydata.org/pandas-docs/version/0.16.0/whatsnew.html#removal-of-prior-version-deprecations-changes > > You can ask on the pandas-dev mailing list why: > https://mail.python.org/mailman/listinfo/pandas-dev > > As for numpy, trying to come up with the right semantics for the shape of > the output is usually when such discussions die. Functions like a > statistical range calculation are expected to be like `min()` and `max()` > and allow us to apply them axis-wise (e.g. just down columns or just across > rows, or more any other axis in an N-D array). Odds are, the way that we'll > pack the two results into a single output will probably not be what you > want in half of the cases, so you'll just have to unpack anyways, and at > that point, it's just not *that* much more convenient than calling > `min()` and `max()` separately. So every time we write `xmin, xmax = > x.min(), x.max()`, we grumble a little bit, but it's just a grumble, not a > significant pain. > > pandas has other considerations, but you'll have to ask them. > > -- > Robert Kern > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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