- scipy.stats.histogram(a, numbins=10, defaultlimits=None, weights=None, printextras=False)¶
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 then 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.
histogram : ndarray
Number of points (or sum of weights) in each bin.
low_range : 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.
This histogram is based on numpy’s histogram but has a larger range by default if default limits is not set.