zorro-df 1.1.1

Package to mask pd.DataFrame data

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