concentrationMetrics | python library for the computation of various concentration

by open-risk Python Version: 0.6.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | concentrationMetrics Summary

concentrationMetrics is a Python library. concentrationMetrics has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install concentrationMetrics' or download it from GitHub, PyPI.

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

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Quality

Security

License

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Support

concentrationMetrics has a low active ecosystem.

It has 23 star(s) with 13 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of concentrationMetrics is 0.6.0

Quality

concentrationMetrics has 0 bugs and 0 code smells.

Security

concentrationMetrics has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

concentrationMetrics code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

concentrationMetrics is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

concentrationMetrics releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

concentrationMetrics saves you 1069 person hours of effort in developing the same functionality from scratch.

It has 2423 lines of code, 37 functions and 33 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed concentrationMetrics and discovered the below as its top functions. This is intended to give you an instant insight into concentrationMetrics implemented functionality, and help decide if they suit your requirements.

Evaluate ellison - warping
Compute the HHI coefficient
Calculate the total size of the array
Compute the weights for the input data
Compute the lower bound and upper bound
Calls method with given data
Compute the inverse of theilization function
Computes the geomposition of the data
Simulate the sensitivity coefficient
Print the results
Simulate the correlation coefficient
Calculates the Kolmov Kolmov chain
Compute the hoover
Compute the Gini - Information Criterion
Compute the HHI coefficient
Compute the Kullback - Hessian Hessian
R Compute the Atkinson coefficient
Describe an index

Get all kandi verified functions for this library.

concentrationMetrics Key Features

No Key Features are available at this moment for concentrationMetrics.

concentrationMetrics Examples and Code Snippets

No Code Snippets are available at this moment for concentrationMetrics.

Community Discussions

No Community Discussions are available at this moment for concentrationMetrics.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install concentrationMetrics

You can install using 'pip install concentrationMetrics' or download it from GitHub, PyPI.
You can use concentrationMetrics like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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