How to make a 1d-histogram in C++ and to fill it:

#include <boost/histogram/histogram.hpp>
#include <boost/histogram/axis.hpp>
#include <iostream>
#include <cmath>

int main(int, char**) {
    namespace bh = boost::histogram;

    /* Create a 1-d histogram with an axis that has 10 bins
     * of equal width, covering the real line in the interval
     * [-1.0, 2.0), label it 'x'.
     * Several other binning strategies are supported, see
     * documentation of axis_types.
     */
    bh::histogram h(bh::regular_axis(10, -1.0, 2.0, "x"));

    /* Fill histogram with a few entries. Values outside of
     * axis are placed in the overflow and underflow bins.
     * Normally you would loop over a source of values.
     */
    h.fill(-1.5); // put in underflow bin
    h.fill(-0.5);
    h.fill(1.1);
    h.fill(-1.0); // included, interval is semi-open
    h.fill(0.3);
    h.fill(1.7);
    h.fill(2.0);  // put in overflow bin, interval is semi-open
    h.fill(20.0); // put in overflow bin

    /* Fill histogram with a weighted count. This increases the
     * bin counter not by one, but by the specified weight.
     *
     * This call transparently causes histogram to change it memory
     * layout to store counts as doubles instead of integers. The
     * layout for weighted counts requires up to 16x more memory
     * and will cause inaccuracies of the type a + 1 == a if a is
     * sufficiently large.
     *
     * Use wfill(...) if you have to, else prefer fill(...).
     */
    h.wfill(0.1, 5.0);

    /* Print a table representation of the histogram showing the bin
     * value and a estimate of the standard deviation. Overflow and
     * Underflow bins are accessed naturally as the bins -1 and 10.
     */
    for (int i = -1; i <= h.bins(0); ++i) {
        const bh::regular_axis& a = h.axis<bh::regular_axis>(0);
        std::cout << "bin " << i
                  << " x in [" << a[i] << ", " << a[i+1] << "): "
                  << h.value(i) << " +/- " << std::sqrt(h.variance(i))
                  << std::endl;
    }
}

The program output is:

bin -1 x in [-inf, -1): 1 +/- 1
bin 0 x in [-1, -0.7): 1 +/- 1
bin 1 x in [-0.7, -0.4): 1 +/- 1
bin 2 x in [-0.4, -0.1): 0 +/- 0
bin 3 x in [-0.1, 0.2): 5 +/- 5
bin 4 x in [0.2, 0.5): 1 +/- 1
bin 5 x in [0.5, 0.8): 0 +/- 0
bin 6 x in [0.8, 1.1): 0 +/- 0
bin 7 x in [1.1, 1.4): 1 +/- 1
bin 8 x in [1.4, 1.7): 0 +/- 0
bin 9 x in [1.7, 2): 1 +/- 1
bin 10 x in [2, inf): 2 +/- 1.41421

How to make a 2d-histogram in Python and to fill it using a Numpy array:

import histogram as bh
import numpy as np

# create a 2d-histogram without underflow and overflow bins
# for polar coordinates, using a specialized polar_axis for
# the binning of the angle 'phi'
#
# radial axis with label 'radius' has 10 bins from 0.0 to 5.0
# polar axis with label 'phi' has 4 bins and a phase of 0.0
h = bh.histogram(bh.regular_axis(10, 0.0, 5.0, "radius",
                                 uoflow=False),
                 bh.polar_axis(4, 0.0, "phi"))

# fill histogram with random values, using numpy to make 
# a two-dimensional normal distribution in cartesian coordinates
x = np.random.randn(1000)             # generate x
y = np.random.randn(1000)             # generate y
rphi = np.empty((1000, 2))
rphi[:, 0] = (x ** 2 + y ** 2) ** 0.5 # compute radius
rphi[:, 1] = np.arctan2(y, x)         # compute phi
h.fill(rphi)

# access counts as a numpy array (no data is copied)
count_matrix = np.asarray(h)

print count_matrix

The program output are the counts per bin as a 2d-array:

[[37 26 33 37]
 [60 69 76 62]
 [48 80 80 77]
 [38 49 45 49]
 [22 24 20 23]
 [ 7  9  9  8]
 [ 3  2  3  3]
 [ 0  0  0  0]
 [ 0  1  0  0]
 [ 0  0  0  0]]