A data scientist of an e-commerce company is working with user data obtained from its...

Comprehensive and Detailed Explanation:

To remove specific columns from a PySpark DataFrame, the drop() method is used. This method returns a new DataFrame without the specified columns. The correct syntax for dropping multiple columns is to pass each column name as a separate argument to the drop() method.

Correct Usage:

df_user_non_pii = df_user.drop("first_name", "last_name", "email", "birthdate")

This line of code will return a new DataFrame df_user_non_pii that excludes the specified PII columns.

Explanation of Options:

A.Correct. Uses the drop() method with multiple column names passed as separate arguments, which is the standard and correct usage in PySpark.

B.Although it appears similar to Option A, if the column names are not enclosed in quotes or if there's a syntax error (e.g., missing quotes or incorrect variable names), it would result in an error. However, as written, it's identical to Option A and thus also correct.

C.Incorrect. The dropfields() method is not a method of the DataFrame class in PySpark. It's used with StructType columns to drop fields from nested structures, not top-level DataFrame columns.

D.Incorrect. Passing a single string with comma-separated column names to dropfields() is not valid syntax in PySpark.