How can you create an 'index' column in a DataFrame?

Creating an 'index' column in a DataFrame can be effectively achieved using the function monotonically_increasing_id(). This function generates a unique, monotonically increasing 64-bit integer for each row in the DataFrame, which can be used as an index. It is particularly useful because the values produced by monotonically_increasing_id() do not guarantee a contiguous sequence of numbers, but they are unique across the DataFrame, making it suitable for indexing purposes without concern for duplicates.

This method aligns well with the intent of adding an index column, offering a simple and efficient solution for identifying rows uniquely. The alternative options may not serve the specific need for creating an index column in the same way:

• Using row_number() requires a window specification, which isn't necessary for a simple index column.

• The range() function is not a valid operation within a DataFrame context for generating indices, as it does not operate at the DataFrame level in this manner.

• Utilizing random() does not provide a structured indexing approach since it would generate random values that can vary on each run, making it unsuitable for consistent indexing.

Thus, employing monotonically_increasing_id() is the most straightforward and effective way to create