open-risk/concentrationmetrics

A python library for the computation of various concentration, inequality and diversity indices

concentrationmetrics's Issues

Document installation

This looks like a fine library! I think it can help me a lot.

Alas, I don't know how to get it. Your documentation doesn't state how to get it, it just starts with import concentrationMetrics as cl. But neither concentrationMetrics nor concentrationmetrics (package names should be all lower-case as per PEP8!) exist on PyPI. If you want users to download a script you should tell them.

ellison_glaeser_example: TypeError: list indices must be integers or slices

tests: Warning in install.packages : package ‘IC2’ is not available for this version of R

Streamline normalization / scaling of all indexes

Provide "standard" choice by default, offer additional options via parameter

Error instead of termination

If input criteria are not of the expected form (such as that the input is not a numpy array), the object throws a message and then terminates the execution. Neither is standard or desirable. Instead, the object should throw an exception (probably AttributeError) and nothing else.

Gini formula looks wrong (but works)

Looking for the formula here http://www.openriskmanual.org/wiki/Gini_Index

It seem that this code is wrong (but it works perfectly)

(1.0 - 2.0 * np.multiply(i, weights).sum())/n + 1.0

I think the right code would be:

(2.0 * np.multiply(i/n, weights).sum()) - (n - 1.0)/n

or following the other formula

(n + 1.0)/n - (2.0 * np.multiply((n + 1 - i)/n, weights).sum())

Those two codes that match the formulas have a problem, they get the results as negative numbers

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graph_example: AttributeError: module 'networkx' has no attribute 'write_yaml'

Add Lorenz curve functionality

Integrate Lorenz curve calculation / plotting along with Gini index

tests: Failed: [pytest] section in setup.cfg files is no longer supported, change to [tool:pytest] instead.

Categorical data processing

Margalef index implemented as first example, more to follow