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You have a Snowpark DataFrame with columns 'product_id', 'customer_id', and 'sale_amount'. Some values are negative, indicating returns, and others are null. You need to replace negative values with 0 and fill null values with the average 'sale_amount' for each 'product_id'. Which of the following approaches is the MOST efficient and correct way to achieve this using Snowpark?
Correct Answer: E
Option E first replaces negative values with 0. Then, it calculates the average sales amount per product and joins it back to the original DataFrame. Finally, it fills null values with the calculated average sales amount and drops the temporary column. This is efficient because it utilizes Snowpark's DataFrame operations. other options does not handle nulls or gives errors.