FYI pandas followed the same pattern to deprecate float indexers (except for indexing in a Float64Index) about a year ago
see here: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0140-deprecations > On Jul 2, 2015, at 9:18 PM, <josef.p...@gmail.com> <josef.p...@gmail.com> > wrote: > > > >> On Thu, Jul 2, 2015 at 8:51 PM, Chris Barker - NOAA Federal >> <chris.bar...@noaa.gov> wrote: >> Sent from my iPhone >> >> > >> > The disadvantage I see is, that some weirder calculations would possible >> > work most of the times, but not always, >> >> >> > not sure if you can define a "tolerance" >> > reasonable here unless it is exact. >> >> You could use a relative tolerance, but you'd still have to set that. >> Better to put that decision squarely in the user's hands. >> >> > Though I guess you are right that >> > `//` will also just round silently already. >> >> Yes, but if it's in the user's code, it should be obvious -- and then >> the user can choose to round, or floor, or ceiling.... > > round, floor, ceil don't produce integers. > > I'm writing library code, and I don't have control over what everyone does. > > round, floor, ceil, and // might hide bugs or user mistakes, if we are > supposed to get something that is "like an int" but it's. 42.6 instead. > > Josef > https://en.wikipedia.org/wiki/Phrases_from_The_Hitchhiker%27s_Guide_to_the_Galaxy#Answer_to_the_Ultimate_Question_of_Life.2C_the_Universe.2C_and_Everything_.2842.29 > > >> >> -CHB >> >> > >> > - Sebastian >> > >> >> >> >> for example >> >> >> >> >> >>>>> 5.0 == 5 >> >> True >> >> >> >> >> >>>>> np.ones(10 / 2) >> >> array([ 1., 1., 1., 1., 1.]) >> >>>>> 10 / 2 == 5 >> >> True >> >> >> >> >> >> or the python 2 version >> >> >> >> >> >>>>> np.ones(10. / 2) >> >> array([ 1., 1., 1., 1., 1.]) >> >>>>> 10. / 2 == 5 >> >> True >> >> >> >> >> >> I'm using now 10 // 2, or int(10./2 + 1) but this is unconditional >> >> and doesn't raise if the numbers are not close or equal to an integer >> >> (which would be a bug) >> >> >> >> >> >> >> >> >> >> Josef >> >> >> >> >> >> >> >> >> >> _______________________________________________ >> >> NumPy-Discussion mailing list >> >> NumPy-Discussion@scipy.org >> >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> > >> > _______________________________________________ >> > NumPy-Discussion mailing list >> > NumPy-Discussion@scipy.org >> > http://mail.scipy.org/mailman/listinfo/numpy-discussion >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion
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