📘 Data Cleaning Exercise: Standardizing Phone Numbers

📍 Overview

In real-world datasets, information often comes in inconsistent formats. This can cause major issues when analyzing, joining, or validating data.
One common example is phone numbers:

• (905) 123-4567
• 289.234.5678
• +1 4164567890
• 365 567 8901

All of these may represent the same structure, but unless standardized, they will be treated as different values in analysis.

Another example is numbers being recorded as values that are not directly usable; e.g., "$1,999" as a dollar value is not directly usable for calcuations.

This exercise uses a small dataset of customers contact information, where each phone number is deliberately written in a different style and payment amount include dollar symbols and commas. Your goal is to standardize those numbers.

Deliverables

• Complete the two tasks in the Jupyter Notebook.
• Convert the codes in the notebook as a .py file and upload it to your GitHub repository.