# histogram¶

astropy.stats.histogram(a, bins=10, range=None, weights=None, **kwargs)[source] [edit on github]

Enhanced histogram function, providing adaptive binnings

This is a histogram function that enables the use of more sophisticated algorithms for determining bins. Aside from the bins argument allowing a string specified how bins are computed, the parameters are the same as numpy.histogram().

Parameters: a : array_like array of data to be histogrammed bins : int or list or str (optional) If bins is a string, then it must be one of: ‘blocks’ : use bayesian blocks for dynamic bin widths ‘knuth’ : use Knuth’s rule to determine bins ‘scott’ : use Scott’s rule to determine bins ‘freedman’ : use the Freedman-Diaconis rule to determine bins range : tuple or None (optional) the minimum and maximum range for the histogram. If not specified, it will be (x.min(), x.max()) weights : array_like, optional Not Implemented other keyword arguments are described in numpy.histogram(). hist : array The values of the histogram. See normed and weights for a description of the possible semantics. bin_edges : array of dtype float Return the bin edges (length(hist)+1).