Recommender Systems with Machine Learning - Geographic Filtering

The video tutorial demonstrates how to merge user and book data using user IDs, filter users based on their location in the USA and Canada, and clean the data by dropping unnecessary columns. It then shows how to display the filtered data and prepares the data for implementing the K-Nearest Neighbors (KNN) algorithm.

What does the command 'drop edge X' accomplish in the context of the data frame?

What steps were taken to filter the users from the US and Canada?