SPS-C01 Exam Dumps | You have a Snowpark DataFrame called 'employee_data' with columns 'employee

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Snowflake.SPS-C01.v2026-08-07.q151
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Question 61/151

You have a Snowpark DataFrame called 'employee_data' with columns 'employee_id', 'department' , 'salary' , and 'hire date'. You need to perform the following transformations: 1. Calculate the average salary for each department. 2. For each employee, determine their salary relative to the average salary of their department (salary - average department salary). 3. Filter out employees whose salary is below the average salary for their department. 4. Display the 'employee_id', 'department' , 'salary' , and the salary difference from the average department salary. Which of the following represents a correct and efficient Snowpark implementation?

Correct Answer: E

Option E is the correct and most efficient solution. It correctly calculates the average salary per department, joins this information back to the original DataFrame, calculates the salary difference, filters the data, and selects the required columns. Using 'cor objects to refer to column names consistently improves readability and robustness. Correct use of from snowflake.snowpark.functions import avg, col. Avoid using 'collect()' to bring data to the client side. The join condition should consistently use 'col()' notation. Correct usage of employee_data[col('department')l and avg_salaries[col('avg_salary')l to specify the columns used for the calculation in the withColumn function.

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