Feature: Add Email Generator (a new type of sdgx.data_processor)

[MooooCat]

Description

This module is a subclass of PIIGenerator, a class designed to handle the conversion and reversal of personally identifiable information (PII) in a DataFrame.

The EmailGenerator class has three important methods: fit, convert, and reverse_convert:

• The fit method is used to fit the generator to the metadata, which includes identifying the columns in the DataFrame that contain email addresses.
• The convert method removes the email columns from the DataFrame, while the reverse_convert method adds new email columns to the DataFrame.

Motivation and Context

The motivation is to provide a way to handle email addresses in a DataFrame.

This is particularly useful when dealing with datasets that contain sensitive information, such as email addresses, and need to be anonymized or de-identified.

How has this been tested?

Email Generator has been tested using a variety of test cases.

These tests include checking if the fit method correctly identifies the email columns in the DataFrame, and if the convert and reverse_convert methods correctly handle the email columns.

Types of changes

• Maintenance (no change in code, maintain the project's CI, docs, etc.)
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.