Skip to main content

Anonymizes an Excel file and synthesizes new data in its place

Project description

Excel Anonymizer

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

Excel_Anonymized_Demo Convert your sheets with sensitive data into anonymized data.

What is excel_anonymizer.py

Anonymize_Excel.py 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:

  1. Identification: Identify all data fields that contain personally identifiable information (PII).
  2. 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.py uses Microsoft Presidio together with Faker framework for anonymization purposes.

Quickstart

  1. Install the requirements

    pip install presidio_analyzer
    pip install presidio_anonymizer
    python -m spacy download en_core_web_lg
    
  2. Install the package

    pip install excel-anonymizer
    
  3. 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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

excel-anonymizer-1.1.3.tar.gz (3.4 kB view details)

Uploaded Source

Built Distribution

excel_anonymizer-1.1.3-py3-none-any.whl (3.5 kB view details)

Uploaded Python 3

File details

Details for the file excel-anonymizer-1.1.3.tar.gz.

File metadata

  • Download URL: excel-anonymizer-1.1.3.tar.gz
  • Upload date:
  • Size: 3.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.13

File hashes

Hashes for excel-anonymizer-1.1.3.tar.gz
Algorithm Hash digest
SHA256 d64bf1478c5d82d60dadae9dd9d8f35114093a7f712a980620e75078c459b0a2
MD5 372cadef8e7a636a3590445055db9c22
BLAKE2b-256 0d01c060ee611c1ba9dda91eb54f24559a627e2c8700d07c09a1ca7591454cf3

See more details on using hashes here.

File details

Details for the file excel_anonymizer-1.1.3-py3-none-any.whl.

File metadata

File hashes

Hashes for excel_anonymizer-1.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 a813ea3e0f04ad74ca577ed2ec7cadf18bafd8f7e2f075ae9efed38d6fe7c70a
MD5 e855d12297d29990f22472e9238638da
BLAKE2b-256 9549d84b3e295454e09d14171bac4452ef7f58014722ef03102ab27e74cae50e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page