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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Create a 1D NumPy array containing numbers 1 to 5.
💡 Hint: Use `np.array` to create an array.
Question 2
Easy
What is the output of np.array([1, 2, 3]).mean()?
💡 Hint: Consider what the mean of {1, 2, 3} is.
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
What does the command np.array([5, 10, 15]) do?
- Creates a list with values 5
- 10
- and 15
- Creates a NumPy array with values 5
- 10
- and 15
- Creates a dictionary with values 5
- 10
- and 15
💡 Hint: Consider what the prefix 'np' indicates.
Question 2
True or False: An ndarray can contain elements of different data types.
- True
- False
💡 Hint: Think about the structure of data in NumPy.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given two NumPy arrays, a = np.array([1, 2, 3]) and b = np.array([4, 5, 6]), write a function that returns their element-wise product.
💡 Hint: Think of how NumPy allows operations on arrays directly.
Question 2
Create a 2D NumPy array representing a dataset of 3 different plants with 4 features each, and compute the standard deviation of each feature.
💡 Hint: Take advantage of NumPy’s abilities to handle multidimensional data.
Challenge and get performance evaluation