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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a built-in function in Python? Give an example.
💡 Hint: Think about functions that don't need import.
Question 2
Easy
Explain what NumPy is used for.
💡 Hint: Consider its role in data science.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
Which of the following is a built-in Python function?
- custom_function()
- sum()
- my_function()
💡 Hint: Think about which one you can use without defining it.
Question 2
True or False: NumPy is slower than standard Python lists.
- True
- False
💡 Hint: Consider the context in data handling.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Create a script that uses both a list comprehension and NumPy to compute squares of numbers from 0 to 999. Compare execution time and memory usage.
💡 Hint: Make sure to include print statements to show results.
Question 2
Consider a dataset that requires frequent statistical analysis. Discuss and propose which libraries you'd use for efficiency and why.
💡 Hint: Think about speed and functionalities needed in data analysis.
Challenge and get performance evaluation