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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q92-Q97):
NEW QUESTION # 92
Which operation would most efficiently apply element-wise multiplication to two NumPy arrays of equal size?
- A. array1.dot(array2)
- B. numpy.outer()
- C. numpy.matrix()
- D. array1 * array2
Answer: D
NEW QUESTION # 93
Why is it important to define and apply validation rules consistently across all stages of a data pipeline?
- A. It reduces processing time by skipping null checks
- B. It guarantees compatibility with visualization tools
- C. It prevents the propagation of corrupted or invalid data
- D. It automatically optimizes SQL queries
Answer: B
NEW QUESTION # 94
What is the best approach when comparing SQL NULL values with Python data during conditional checks?
- A. Use Python's None and SQL's IS NULL clause
- B. Convert all NULL to string before comparison
- C. Replace NULL with zero before importing
- D. Use == None directly in SQL queries
Answer: A
NEW QUESTION # 95
Which of the following correctly demonstrates the use of parameterized queries using Python's sqlite3 module?
- A. cursor.execute("SELECT * FROM users WHERE id = " + user_id)
- B. cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
- C. cursor.execute("SELECT * FROM users WHERE id = ?", user_id)
- D. cursor.execute("SELECT * FROM users WHERE id = ':id'", {'id': user_id})
Answer: B
NEW QUESTION # 96
What is the benefit of using the __name__ == "__main__" construct in Python scripts?
- A. It prevents modules from being imported
- B. It defines the main function in Python
- C. It allows selective execution of code when run as a script
- D. It allows access to all global variables
Answer: C
NEW QUESTION # 97
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