Metadata-Version: 2.1
Name: benfordslaw_analysis
Version: 0.1.0
Summary: Use this package to analyse your data with Benford's law
Home-page: https://github.com/jurjen93/Benfords_law
Author: Jurjen de Jong
Author-email: jurjendejong93@gmail.com
License: LICENSE.txt
Description: # Benford's law analysis
        
        Benford's law is a digit-law, which states that the distribution of seperate digits in numbers follow a specific frequency.
        This specific frequency is seen in many numerical datasets, as discovered by Simon Newcomb and Frank Benford.
        You can find on [wikipedia] more information about this mysterious law.
        
        Benford's law might be helpful to detect [fraud], do [science], or just investigate the [quality of data].
        
        #### Installation
        By ```pip install benfordslaw_analysis``` you will install the package.
        
        #### Usage
        Now you can do ```from benfordslaw_analysis import analysis``` to obtain the analysis script.
        Here there is the class ```BenfordsLaw``` which you can get with ```analysis.BenfordsLaw```.
        Now you can analyse your data by making plots.
        
        For example, make a plot with Benford's law versus random data with:
        ```
        from benfordslaw_analysis.analysis import BenfordsLaw
        from random import uniform
        random_data = [uniform(-10, 10) for i in range(0,1000)]
        bl = BenfordsLaw(random_data)
        bl.plot_first_digit()
        ```
        Note that we use the Euclidean distance between the digit frequency from Benford's law and your own data as a measure
        and that we use Poisson error bars.
        
        This package is still under development. More updates and documentation will come...
        
        [wikipedia]: https://en.wikipedia.org/wiki/Benford%27s_law
        [fraud]: https://www.journalofaccountancy.com/issues/2017/apr/excel-and-benfords-law-to-detect-fraud.html
        [science]: https://towardsdatascience.com/benfords-law-in-the-gaia-universe-b5727db7a936
        [quality of data]: https://www.idfcinstitute.org/blog/2020/november/using-benfords-law-to-understand-covid-19-data-quality/
Platform: UNKNOWN
Description-Content-Type: text/markdown
