Quiz8

Which method can reshape a flat NumPy array into a 2D multiplication table?

• np.reshape()

• np.flat()

• np.array_split()

• np.flatten()

What is conditional replacement in NumPy?

• Replacing all elements of an array

• Replacing elements only if they meet a condition

• Reshaping the array conditionally

• Using np.where() to copy an array

What will be the output?
import numpy as np

arr = np.arange(9).reshape(3,3)

arr[arr%2==0] = -1

print(arr)

• All values replaced with -1

• Only even values replaced with -1

• Only odd values replaced with -1

• Only odd values replaced with 1

String-based formatting of NumPy arrays is useful for:

• Saving arrays as CSV

• Printing arrays in a custom style

• Converting arrays to strings permanently

• Performing matrix multiplication

Min-max scaling transforms data values into the range:

• [0, ∞)

• [-1, 1]

• [0, 1]

• Any arbitrary range

Which function can be used to sort elements in a slice of a NumPy array?

• np.order()

• np.sort()

• np.arrange()

• np.reorder()

arr = np.array([9,3,7,1,5])

print(np.sort(arr))

what will be the output?

• [9 3 7 1 5]

• [1 3 5 7 9]

• [5 7 9 1 3]

• [1,3,5,7,9]

Which slicing extracts the 2nd row of a 3×3 NumPy array arr?

• arr[1]

• arr[:,1]

• arr[2,:]

• arr[:1]

For a 4×4 array arr, what does arr[:2, :2] return?

• Last 2 rows and columns

• First 2 rows and first 2 columns

• Full 4×4 array

• A single value

Boolean masking in NumPy means:

• Creating arrays of 0s and 1s

• Selecting elements that satisfy a condition

• Filtering arrays using slicing and indexing only

• Using np.bool() for conversion