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Which of the following code blocks returns a copy of DataFrame transactionsDf that only includes columns transactionId, storeId, productId and f? Sample of DataFrame transactionsDf: 1.+-------------+---------+-----+-------+---------+----+ 2.|transactionId|predError|value|storeId|productId| f| 3.+-------------+---------+-----+-------+---------+----+ 4.| 1| 3| 4| 25| 1|null| 5.| 2| 6| 7| 2| 2|null| 6.| 3| 3| null| 25| 3|null| 7.+-------------+---------+-----+-------+---------+----+
Correct Answer: B
Explanation Output of correct code block: +-------------+-------+---------+----+ |transactionId|storeId|productId| f| +-------------+-------+---------+----+ | 1| 25| 1|null| | 2| 2| 2|null| | 3| 25| 3|null| +-------------+-------+---------+----+ To solve this question, you should be fmailiar with the drop() API. The order of column names does not matter - in this question the order differs in some answers just to confuse you. Also, drop() does not take a list. The *cols operator in the documentation means that all arguments passed to drop() are interpreted as column names. More info: pyspark.sql.DataFrame.drop - PySpark 3.1.2 documentation Static notebook | Dynamic notebook: See test 2