The question asks for operations that return a new DataFrame excluding specified columns by name.

• Option B (select()): By selecting all columns except the ones to exclude, select() can achieve this. For example, storesDF.select([col for col in storesDF.columns if col not in columns_to_drop]) excludes specified columns.
• Option C (drop()): Directly removes specified columns by name, e.g., storesDF.drop('col1', 'col2').
• Other options: filter() (A) affects rows, not columns. subset() (D) is not a valid DataFrame method. dropColumn() (E) does not exist in Spark; the correct method is drop().