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- Numpy - Array Creation
- numpy.arange() in Python
- numpy.zeros() in Python
- NumPy - Create array filled with all ones
- NumPy - linspace() Function
- numpy.eye() in Python
- Creating a one-dimensional NumPy array
- How to create an empty and a full NumPy array
- Create a Numpy array filled with all zeros - Python
- How to generate 2-D Gaussian array using NumPy?
- How to create a vector in Python using NumPy
- Python - Numpy fromrecords() method
- NumPy Copy and View of Array
- How to Copy NumPy array into another array?
- Appending values at the end of an NumPy array
- How to swap columns of a given NumPy array?
- Insert a new axis within a NumPy array
- numpy.hstack() in Python
- numpy.vstack() in python
- Joining NumPy Array
- Combining a One and a Two-Dimensional NumPy Array
- Numpy np.ma.concatenate() method-Python
- Numpy dstack() method-Python
- Splitting Arrays in NumPy
- How to compare two NumPy arrays?
- Find the union of two NumPy arrays
- Find unique rows in a NumPy array
- Numpy np.unique() method-Python
- numpy.trim_zeros() in Python
Advanced NumPy
Question 1
What does the np.broadcast_to() function do?
- A
Replicates a scalar value into an array
- B
Broadcasts an array to a new shape without copying data
- C
Concatenates two arrays along an axis
- D
Transposes an array
Question 2
Which function is used to calculate the QR decomposition of a matrix in NumPy?
- A
np.linalg.svd()
- B
np.linalg.qr()
- C
np.linalg.eig()
- D
np.linalg.solve()
Question 3
What will be the output of this code?
import numpy as np
arr = np.array([[1, 2], [3, 4]])
result = np.kron(arr, np.eye(2))
print(result)
- A
[[1. 0. 2. 0.]
[0. 1. 0. 2.]
[3. 0. 4. 0.]
[0. 3. 0. 4.]]
- B
[[1. 2.]
[3. 4.]]
- C
[[1. 0.]
[0. 2.]
[3. 0.]
[0. 4.]]
- D
[[1. 0. 2. 0.]
[0. 1. 0. 2.]
[3. 0. 4. 0.]
[0. 3. 0. 4.]]
Question 4
Which function computes the eigenvalues and eigenvectors of a matrix?
- A
np.linalg.det()
- B
np.linalg.inv()
- C
np.linalg.eig()
- D
np.linalg.qr()
Question 5
What does the np.pad() function do in NumPy?
- A
Creates a zero-padded array
- B
Adds padding to an array along specified dimensions
- C
Aligns two arrays for concatenation
- D
Splits an array into blocks
Question 6
What will be the output of this code?
import numpy as np
arr = np.array([[1, 2], [3, 4]])
result = np.linalg.svd(arr)
print([x.shape for x in result])
- A
[(2, 2), (2,), (2, 2)]
- B
[(2, 2), (1,), (2, 2)]
- C
[(2, 2), (2,), (2, 1)]
- D
Error
Question 7
What does the np.ma.masked_array() function do?
- A
Masks an array based on a condition
- B
Combines two arrays
- C
Creates a Boolean mask of an array
- D
Reshapes an array
Question 8
Which of the following is not a valid use of np.random.Generator?
- A
Generating random numbers with a specified seed
- B
Generating samples from a normal distribution
- C
Generating pseudorandom numbers for cryptography
- D
Generating random integers
Question 9
What does the np.unique() function return when return_counts=True is specified?
- A
Unique elements only
- B
A tuple of unique elements and their counts
- C
The first occurrence of each unique element
- D
An Error
Question 10
Which function in NumPy is used to calculate the Frobenius norm of a matrix?
- A
np.linalg.norm()
- B
np.linalg.det()
- C
np.linalg.inv()
- D
np.linalg.qr()
There are 10 questions to complete.