Datamizer for Python

This is a simple package that lets you change the sensitive data from a .CSV file creating a new file with fake data.

This allows the new data to be used for training, testing or analytics, without compromising private information.

Installation

Run the following command to install the package:

pip install datamizer  

Usage

1- Instanciate the Datamizer class, pass the path to the CSV file, and optionally the CSV delimiter.

from datamizer import Datamizer

csv_datamize = Datamizer('file.csv')

2- Use fake() to anonymize the columns with sensitive data, passing the column,provider, and optionally consistent args.

csv_datamize.fake('Username', 'user_name', consistent=True)
csv_datamize.fake('First name', 'first_name', consistent=True)
csv_datamize.fake('Last name', 'last_name', consistent=True)
csv_datamize.fake('email', 'email', consistent=True)
csv_datamize.fake('Money', 'pricetag')

3- Write a new CSV file with the fake data, passing the path to the new file and optionally index=True to include the index.

csv_datamize.write_csv('users.csv')