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From: Antony L. <ant...@be...> - 2014-05-30 15:25:44
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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...@ro...>: > Am Thu, 29 May 2014 14:14:52 -0700 > schrieb Antony Lee <ant...@be...>: > > > 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') > > > ------------------------------------------------------------------------------ > Time is money. Stop wasting it! Get your web API in 5 minutes. > www.restlet.com/download > http://p.sf.net/sfu/restlet > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |