wquantiles | weighted quantiles with Python | Analytics library

by nudomarinero Python Version: 0.6 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | wquantiles Summary

wquantiles is a Python library typically used in Analytics, Numpy, Pandas applications. wquantiles has no vulnerabilities, it has a Permissive License and it has low support. However wquantiles has 1 bugs and it build file is not available. You can install using 'pip install wquantiles' or download it from GitHub, PyPI.

[Pypi] Weighted quantiles with Python, including weighted median. This library is based on numpy, which is the only dependence. The main methods are quantile and median. The input of quantile is a numpy array (data), a numpy array of weights of one dimension and the value of the quantile (between 0 and 1) to compute. The weighting is applied along the last axis. The method median is an alias to quantile(data, weights, 0.5).

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Quality

Security

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Support

wquantiles has a low active ecosystem.

It has 41 star(s) with 10 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 6 have been closed. On average issues are closed in 50 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of wquantiles is 0.6

Quality

wquantiles has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 4 code smells.

Security

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

wquantiles code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

wquantiles 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

wquantiles releases are available to install and integrate.

Deployable package is available in PyPI.

wquantiles has no build file. You will be need to create the build yourself to build the component from source.

wquantiles saves you 1411 person hours of effort in developing the same functionality from scratch.

It has 158 lines of code, 9 functions and 5 files.

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

Top functions reviewed by kandi - BETA

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

Calculate the median of the data
Compute the quantile of a 1D array
Compute the quantile of an array

Get all kandi verified functions for this library.

wquantiles Key Features

No Key Features are available at this moment for wquantiles.

wquantiles Examples and Code Snippets

No Code Snippets are available at this moment for wquantiles.

Community Discussions

Trending Discussions on wquantiles

Verify Median Value with Area Under the Curve Calculation

QUESTION

Verify Median Value with Area Under the Curve Calculation

Asked 2021-Mar-13 at 18:20

I want to calculate the area under this curve for confirmation that the size is correct. How would one go about doing this?

I have a frequency plot below. The package utilized for this median calculation is here: https://github.com/nudomarinero/wquantiles

...

ANSWER

Answered 2021-Mar-11 at 00:57

You're looking for a cumulative sum of the normalised area and the first point where this sum is >= 0.5.

Source https://stackoverflow.com/questions/66573974

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

Vulnerabilities

No vulnerabilities reported

Install wquantiles

You can install using 'pip install wquantiles' or download it from GitHub, PyPI.
You can use wquantiles 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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