Explanation
Output of correct code block:
+---------+-------+
|predError|storeId|
+---------+-------+
| 3| 25|
+---------+-------+
This question is difficult because it requires you to understand different kinds of commands and operators. All answers are valid Spark syntax, but just one expression returns a single-row DataFrame.
For reference, here is what the incorrect answers return:
transactionsDf.filter((col("storeId")!=25) | (col("productId")==2)) returns
+-------------+---------+-----+-------+---------+----+
|transactionId|predError|value|storeId|productId| f|
+-------------+---------+-----+-------+---------+----+
| 2| 6| 7| 2| 2|null|
| 4| null| null| 3| 2|null|
| 5| null| null| null| 2|null|
| 6| 3| 2| 25| 2|null|
+-------------+---------+-----+-------+---------+----+
transactionsDf.where(col("storeId").between(3,25)) returns
+-------------+---------+-----+-------+---------+----+
|transactionId|predError|value|storeId|productId| f|
+-------------+---------+-----+-------+---------+----+
| 1| 3| 4| 25| 1|null|
| 3| 3| null| 25| 3|null|
| 4| null| null| 3| 2|null|
| 6| 3| 2| 25| 2|null|
+-------------+---------+-----+-------+---------+----+
transactionsDf.where(col("value").isNull()).select("productId", "storeId").distinct() returns
+---------+-------+
|productId|storeId|
+---------+-------+
| 3| 25|
| 2| 3|
| 2| null|
+---------+-------+
transactionsDf.select("productId", "storeId").where("storeId == 2 OR storeId != 25") returns
+---------+-------+
|productId|storeId|
+---------+-------+
| 2| 2|
| 2| 3|
+---------+-------+
Static notebook | Dynamic notebook: See test 2