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 quick note on the original methodology:

When calculating Gini coefficients directly from areas under curves with np.traps or another integration method, the first value of the Lorenz curve needs to be 0 so that the area between the origin and the second value is accounted for. The following changes to G(v) fix this:

yvals = [0]
for b in bins[1:]:

I also discussed this issue in this answer, where including the origin in those calculations provides an equivalent answer to using the other methods discussed here (which do not need 0 to be appended).

In short, when calculating Gini coefficients directly using integration, start from the origin. If using the other methods discussed here, then it's not needed.