Compute a binned statistic for a set of data.
This is a generalization of a histogram function. A histogram divides the space into bins, and returns the count of the number of points in each bin. This function allows the computation of the sum, mean, median, or other statistic of the values within each bin.
New in version 0.11.0.
Parameters :  x : array_like
values : array_like
statistic : string or callable, optional
bins : int or sequence of scalars, optional
range : (float, float), optional


Returns :  statistic : array
bin_edges : array of dtype float
binnumber : 1D ndarray of ints

Notes
All but the last (righthandmost) bin is halfopen. In other words, if bins is:
[1, 2, 3, 4]
then the first bin is [1, 2) (including 1, but excluding 2) and the second [2, 3). The last bin, however, is [3, 4], which includes 4.
Examples
>>> stats.binned_statistic([1, 2, 1, 2, 4], np.arange(5), statistic='mean',
... bins=3)
(array([ 1., 2., 4.]), array([ 1., 2., 3., 4.]), array([1, 2, 1, 2, 3]))
>>> stats.binned_statistic([1, 2, 1, 2, 4], np.arange(5), statistic='mean', bins=3)
(array([ 1., 2., 4.]), array([ 1., 2., 3., 4.]), array([1, 2, 1, 2, 3]))