wealthtax | Scoring Wealth Tax and Increased Progressivity
kandi X-RAY | wealthtax Summary
kandi X-RAY | wealthtax Summary
wealthtax is a Python library. wealthtax has no bugs, it has no vulnerabilities and it has low support. However wealthtax build file is not available. You can download it from GitHub.
Model for Scoring Wealth Tax and Increased Progressivity in Income Tax - Python Based
Model for Scoring Wealth Tax and Increased Progressivity in Income Tax - Python Based
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Quality
Security
License
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Support
wealthtax has a low active ecosystem.
It has 3 star(s) with 4 fork(s). There are 9 watchers for this library.
It had no major release in the last 12 months.
There are 0 open issues and 16 have been closed. On average issues are closed in 65 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of wealthtax is 0.1.0
Quality
wealthtax has no bugs reported.
Security
wealthtax has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
wealthtax does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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wealthtax releases are available to install and integrate.
wealthtax has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed wealthtax and discovered the below as its top functions. This is intended to give you an instant insight into wealthtax implemented functionality, and help decide if they suit your requirements.
- Get model parameters
- Calculates pop objects for a given period
- Integrate function
- Calculate population density by age - binning
- Calculates the total taxes for a given basis
- R Compute the Tau income of an income factor
- Calculate the tau concentration of wealth
- Calculate the Gaussian distribution
- Calculates income rate for a population
- Compute the variance covariance matrix
- Calculate wealth calibration
- Computes the total cost of the total cost function
- Calculates the total amount of taxes for the TPI
- Calculates the total amount of taxes for a given portfolio
- Calculate the survival probability for an economy
- Calculates the total amount of taxes for a portfolio
- Compute the total total amount of taxes for a given economy
- Calculates the total total amount of taxes for each site
- Compute the Exponential error
- Calculates the total total amount of taxes for the income factor
- Calculates the total taxes for a given income factor
- Calculate the tax and wage pressure for a given economy
- Calculate the lump sum using the lump sum method
- Compute the arc error
- Return git versions
- Calculates the tax and wage coefficient of a wealth statistic
Get all kandi verified functions for this library.
wealthtax Key Features
No Key Features are available at this moment for wealthtax.
wealthtax Examples and Code Snippets
No Code Snippets are available at this moment for wealthtax.
Community Discussions
No Community Discussions are available at this moment for wealthtax.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install wealthtax
You can download it from GitHub.
You can use wealthtax 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.
You can use wealthtax 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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