Metadata-Version: 2.1
Name: robustbase
Version: 0.2.6
Summary: A Python Based Library to Calculate Estimators (Sn, Qn, MAD, IQR)
Home-page: https://github.com/deepak7376/robustbase
Author: Deepak Yadav
Author-email: dky.united@gmail.com
License: MIT
Description: [![Downloads](https://pepy.tech/badge/robustbase)](https://pepy.tech/project/robustbase)
        [![Downloads](https://pepy.tech/badge/robustbase/month)](https://pepy.tech/project/robustbase/month)
        [![Downloads](https://pepy.tech/badge/robustbase/week)](https://pepy.tech/project/robustbase/week)
        # robustbase
        > A Python Library to Calculate Estimators.
        
        ## Installation
        
        OS X , Windows & Linux:
        
        ```sh
        pip install robustbase
        ```
        ## Usage example
        
        This package is used to calculate the following statistical estimators.
        
        * Qn scale estimator
        * Sn scale estimator
        * Median Absolute Deviation(MAD)
        * Interquartile Range (IQR)
        
        ```python
        from robustbase import Qn, Sn, mad, iqr
        import numpy as np
          
        data = np.random.rand(10)
        print(Qn(data))
        print(Sn(data))
        print(mad(data))
        print(iqr(data))
        ```
        
        ## Development setup
        
        For local development setup
        
        ```sh
        git clone https://github.com/deepak7376/robustbase
        cd robustbase
        pip install -r requirements.txt
        ```
        
        ## Meta
        
        Deepak Yadav – [@imdeepak_dky](https://twitter.com/imdeepak_dky) – dky.united@gmail.com
        
        Distributed under the MIT license. See ``LICENSE`` for more information.
        
        [https://github.com/deepak7376/robustbase/blob/master/LICENSE](https://github.com/deepak7376)
        
        ## Contributing
        
        1. Fork it (<https://github.com/deepak7376/robustbase/fork>)
        2. Create your feature branch (`git checkout -b feature/fooBar`)
        3. Commit your changes (`git commit -am 'Add some fooBar'`)
        4. Push to the branch (`git push origin feature/fooBar`)
        5. Create a new Pull Request
        
        ## References
        https://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/qn_scale.htm
        https://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/sn_scale.htm
        https://www.statisticshowto.datasciencecentral.com/median-absolute-deviation/
        https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/interquartile-range/
Keywords: Sn Qn MAD IQR
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
