calculating Gini coefficient in Python/numpy

Question

i\'m calculating Gini coefficient (similar to: Python - Gini coefficient calculation using Numpy) but i get an odd result. for a uniform distribution sampled from np.r

Answer 1

A slightly faster implementation (using numpy vectorization and only computing each difference once):

def gini_coefficient(x):
    """Compute Gini coefficient of array of values"""
    diffsum = 0
    for i, xi in enumerate(x[:-1], 1):
        diffsum += np.sum(np.abs(xi - x[i:]))
    return diffsum / (len(x)**2 * np.mean(x))

Note: x must be a numpy array.