A function to compute the Gini coefficient, from a vector of data.

gini.py

import numpy as np

def G(v):
    """
    Found at https://stackoverflow.com/questions/39512260/calculating-gini-coefficient-in-python-numpy
    """
    bins = np.linspace(0., 100., 11)
    total = float(np.sum(v))
    yvals = []
    for b in bins:
        bin_vals = v[v <= np.percentile(v, b)]
        bin_fraction = (np.sum(bin_vals) / total) * 100.0
        yvals.append(bin_fraction)
    # perfect equality area
    pe_area = np.trapz(bins, x=bins)
    # lorenz area
    lorenz_area = np.trapz(yvals, x=bins)
    gini_val = (pe_area - lorenz_area) / float(pe_area)
    return bins, yvals, gini_val