Excel Anonymizer 1.1.7 | Coderz Repository

excel-anonymizer 1.1.7

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excelanonymizer 1.1.7

Excel Anonymizer
A Python script that anonymizes an Excel file and synthesizes new data in its place.

Convert your sheets with sensitive data into anonymized data.
What is Excel Anonymizer
Excel Anonymizer is a python script that helps to ensure sensitive data is properly managed and governed. It provides fast identification and anonymization for private entities in text such as credit card numbers, names, locations, phone numbers, email address, date/time, with more entities to come.
Use case
Data anonymization is crucial because it helps protect privacy and maintain confidentiality. If data is not anonymized, sensitive information such as names, addresses, contact numbers, or other identifiers linked to specific individuals could potentially be learned and misused. Hence, by obscuring or removing this personally identifiable information (PII), data can be used freely without compromising individuals’ privacy rights or breaching data protection laws and regulations.
Overview
Anonymization consists of two steps:

Identification: Identify all data fields that contain personally identifiable information (PII).
Replacement: Replace all PIIs with pseudo values that do not reveal any personal information about the individual but can be used for reference.

Excel Anonymizer uses Microsoft Presidio together with Faker framework for anonymization purposes.
Quickstart

Install the requirements
pip install presidio_analyzer
pip install presidio_anonymizer
python -m spacy download en_core_web_lg


Install the package
pip install excel-anonymizer




Note: Spacy will install a Natural Language Processing package on the first run (587.7MB).


Run the demo
excel-anonymizer ../../personal_information.xlsx



That's it!
Usage
To use Excel Anonymizer with your Excel file, simply input the file.
excel-anonymizer your_excel_file_here.xlsx

Author
Siddharth Bhatia
License: MIT License

License:

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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