I can still need to bin data, e.g. when the data range is "large", or at
least not small compared to the number of data points.
Antony
2014-05-30 5:03 GMT-07:00 Yoshi Rokuko <yo...@rokuko.net>:
> Am Thu, 29 May 2014 14:14:52 -0700
> schrieb Antony Lee <antony....@berkeley.edu>:
>
> > Hi,
> > When histogramming integer data, is there an easy way to tell
> > matplotlib that I want a certain number of bins, and each bin to
> > cover an equal number of integers (except possibly the last one)?
> > (in order to avoid having some bins higher than others merely because
> > they cover more integers) I know I can pass in an explicit bins array
> > (something like list(range(min, max, (max-min)//n)) + max) but I was
> > hoping for something simpler, like hist(data, nbins=42,
> > equal_integer_coverage=True). Best,
> > Antony
>
> Int data is discrete. For discrete variables you don't need bins, you
> don't estimate the frequency distribution you know it exactly by
> counting.
>
> Of course you could do that with the hist function:
>
> >>> pl.hist(r, np.arange(min(r)-0.5, max(r)+1.5), histtype='step')
>
>
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