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WGU Foundations of Computer Science Sample Questions:

1. What is the expected output of calling .shape on a NumPy 2D array?

A) The type of elements in the array
B) The sum of the dimensions of the array
C) The number of rows and columns in the 2D array
D) The total number of elements in the array

2. How can a user subset a NumPy array bmi to only include values over 23?

A) bmi.get_values(>23)
B) bmi[bmi > 23]
C) bmi.select(23)
D) bmi.where(bmi > 23)

3. Which line of code below contains an error in the use of NumPy?

A) print(wgu_list)
B) import numpy as np
C) wgu_list = np.quicksort(arr)
D) arr = np.array([3, 2, 0, 1])

4. What is the main advantage of using NumPy arrays over regular Python lists for data analysis?

A) NumPy arrays can perform calculations over entire collections of values.
B) NumPy arrays can bring different types into the array at the same time.
C) NumPy arrays can only hold elements of the same type.
D) NumPy arrays can concatenate lists by default.

5. What happens if you try to create a NumPy array with different types?

A) The array will be created with no issues.
B) The array will contain a single type, converting all elements to that type.
C) The array will be split into multiple arrays, one for each type.
D) The array will be created, but calculations will not be possible.

Solutions: