Which of the following code blocks returns a 2-column DataFrame that shows the distinct values in column productId and the number of rows with that productId in DataFrame transactionsDf?

transactionsDf.groupBy("productId").count() Correct. This code block first groups DataFrame transactionsDf by column productId and then counts the rows in each group. transactionsDf.groupBy("productId").select(count("value")) Incorrect. You cannot call select on a GroupedData object (the output of a groupBy) statement. transactionsDf.count("productId") No. DataFrame.count() does not take any arguments. transactionsDf.count("productId").distinct() Wrong. Since DataFrame.count() does not take any arguments, this option cannot be right. transactionsDf.groupBy("productId").agg(col("value").count()) False. A Column object, as returned by col("value"), does not have a count() method. You can see all available methods for Column object linked in the Spark documentation below. More info: pyspark.sql.DataFrame.count — PySpark 3.1.2 documentation, pyspark.sql.Column — PySpark 3.1.2 documentation Static notebook | Dynamic notebook: See test 3,