Which of the following code blocks applies the function assessPerformance() to each row of DataFrame storesDF?
Which of the following code blocks applies the function assessPerformance() to each row of DataFrame storesDF?
To apply the function assessPerformance() to each row of the DataFrame storesDF, we should use a collect() method to retrieve all rows and then apply the function to each row using a list comprehension. This is correctly done with [assessPerformance(row) for row in storesDF.collect()].
The correct answer is D. Explanation: Option A uses the take() method to extract three rows from the DataFrame, but it applies the assessPerformance() function to each row outside of the DataFrame context. Option B attempts to apply the assessPerformance() function to each row, but it doesn't reference the row object in any way. Option C tries to apply the assessPerformance() function to the entire DataFrame but does so using an incorrect syntax. Option D correctly applies the assessPerformance() function to each row of the DataFrame using a list comprehension over the result of the collect() method. Option E is similar to D, but it will iterate over rows individually instead of using the collect() method to retrieve all rows at once. While this is still a valid approach, it may be less efficient.
There are many way to apply a function to dataframe. 1. apply, as shown in option D. but it should be apply(assessPerformance) 2. list comprehension: for row in df.collect() 3. foreach 4. map, but for RDD majorly