Coefficients to measure inequality.
Project description
Inequality Coefficients:
=====================================================================
This is small library with some implemented coefficients (or indices) intended
to measure inequality or concentration of the values in a population.
Implemented coefficients
------------
- Gini Coefficient
- Ratio top / rest
Installation
------------
This library is hosted on PyPI, so installation is straightforward. The easiest way to install type this at the command line (Linux, Mac, or Windows)::
pip install inequality_coefficients
This library also depends on numpy, but ``pip`` should take of that for you already.
Basic Usage
------------
For the simplest, typical use cases, this tells you everything you need to
know.::
import inequality_coefficients as ineq
data = array([1.7, 3.2 ...]) # data can be list of nums or numpy array
gini_coeff = ineq.gini_coeff(data)
ratio_top_rest = ineq.ratio_top10_rest(data)
Acknowledgements
-----------------
Many thanks to Felipe Ortega to open source his implementation of the Gini coefficient, available here: (https://github.com/ryanwitt/wikixray/blob/master/graphics.py).
My code is based on that implementation, although I have made some changes and added a correction for small datasets based on [Deltas, 2003](https://doi.org/10.1162/rest.2003.85.1.226).
=====================================================================
This is small library with some implemented coefficients (or indices) intended
to measure inequality or concentration of the values in a population.
Implemented coefficients
------------
- Gini Coefficient
- Ratio top / rest
Installation
------------
This library is hosted on PyPI, so installation is straightforward. The easiest way to install type this at the command line (Linux, Mac, or Windows)::
pip install inequality_coefficients
This library also depends on numpy, but ``pip`` should take of that for you already.
Basic Usage
------------
For the simplest, typical use cases, this tells you everything you need to
know.::
import inequality_coefficients as ineq
data = array([1.7, 3.2 ...]) # data can be list of nums or numpy array
gini_coeff = ineq.gini_coeff(data)
ratio_top_rest = ineq.ratio_top10_rest(data)
Acknowledgements
-----------------
Many thanks to Felipe Ortega to open source his implementation of the Gini coefficient, available here: (https://github.com/ryanwitt/wikixray/blob/master/graphics.py).
My code is based on that implementation, although I have made some changes and added a correction for small datasets based on [Deltas, 2003](https://doi.org/10.1162/rest.2003.85.1.226).
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