scipy.stats.histogram(a, numbins=10, defaultlimits=None, weights=None, printextras=False)[source]

Separates the range into several bins and returns the number of instances in each bin.


a : array_like

Array of scores which will be put into bins.

numbins : int, optional

The number of bins to use for the histogram. Default is 10.

defaultlimits : tuple (lower, upper), optional

The lower and upper values for the range of the histogram. If no value is given, a range slightly larger than the range of the values in a is used. Specifically (a.min() - s, a.max() + s), where s = (1/2)(a.max() - a.min()) / (numbins - 1).

weights : array_like, optional

The weights for each value in a. Default is None, which gives each value a weight of 1.0

printextras : bool, optional

If True, if there are extra points (i.e. the points that fall outside the bin limits) a warning is raised saying how many of those points there are. Default is False.


count : ndarray

Number of points (or sum of weights) in each bin.

lowerlimit : float

Lowest value of histogram, the lower limit of the first bin.

binsize : float

The size of the bins (all bins have the same size).

extrapoints : int

The number of points outside the range of the histogram.

See also



This histogram is based on numpy’s histogram but has a larger range by default if default limits is not set.

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