Metadata-Version: 2.1
Name: zorro_df
Version: 1.1.1
Summary: Package to mask pd.DataFrame data
Home-page: https://github.com/epw505/zorro_df
Author: Ned Webster
Author-email: edwardpwebster@gmail.com
License: UNKNOWN
Description: [![codecov](https://codecov.io/gh/epw505/zorro_df/branch/master/graph/badge.svg)](https://codecov.io/gh/epw505/zorro_df)
        
        ![zorro logo](zorro_df_logo.png)
        # Zorro DF
        Zorro DF is a python package for masking pandas dataframe objects in order to 
        anonymise data. It allows you to strip away identifiable column names and string 
        values, replacing them with a generic naming convention. The package is built 
        under the scikit-learn transformer framework and hence can be plugged into any 
        scikit-learn Pipeline.
        
        The package source-code can be found at http://github.com/epw505/zorro_df
        
        ## Getting Started
        ### Requirements
        ```
        pandas>=0.25.3
        scikit-learn>=0.22.1
        ```
        
        ### Installation
        Zorro DF can be installed using `pip` with the following command:
        ```
        pip install zorro_df
        ```
        
        ## Examples
        Once the package is installed, you can load Zorro DF into your python session 
        and use the Masker object to mask your data.
        ```
        from zorro_df import mask_dataframe as mf
        
        example_masker = mf.Masker()
        example_masker.fit(data)
        masked_data = example_masker.transform(data)
        ```
        
        ## Tests
        The test suite for Zorro DF is built using `pytest` with the `pytest-mock` 
        plugin. Install both as follows.
        ```
        pip install pytest
        pip install pytest-mock
        ```
        Once they are installed, you can run the test suite from the root directory of
        Zorro Df.
        ```
        pytest tests/
        ```
        
        ## Future Development
        * Reverse masking to allow retrieval of original data
        * Additional numerical scaling techniques
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
