Numpy

import numpy as np

arr = np.array([1, 2, 3, 4])

print(arr[1])

• 1

• 2

• 3

• 4

Iimport numpy as np

arr = np.array(42)

print(arr)

• 42

• 4

• 2

• 24

What is the purpose of NumPy in Python?

• To do numerical calculations

• To do scientific computing

• Both A and B

• None of the mentioned above

NumPy package is capable to do fast operations on arrays.

• True

• False

NumPy arrays can be ___.

• Indexed

• Sliced

• Iterated

• All of the mentioned above

Which of the following is not a library in python

• pandas

• matplotlib

• numpy

• Visualization

import numpy as np

x = np.array([[0, 1], [2, 3]])

np.transpose(x)

• array([[0, 2], [1, 3]])

• array([[0, 1], [2, 3]])

• array([[2, 3], [0, 1]])

• None of the mentioned

Observe the following code and identify what will be the outcome?

a = np.array([10, 20, 30, 40])

b = np.array([18, 15, 14])

c = np.array([25, 24, 26, 28, 23])

x, y, z = np.ix_(a, b, c)

print(x)

• [[[10]]

  [[20]]

  [[30]]

  [[40]]]

• [[[1]]

  [[2]]

  [[3]]

  [[4]]

  [[5]]]

• [[[18]]

  [[15]]

  [[[14]]]

• [[[25]]

  [[24]]

  [[[26]]]

Answer explanation

To acquire the result for each n-uplet, the ix_ function can be used to mix different vectors together in one operation. In this case, if you wish to compute all of the a+b*c for all of the triplets derived from each of the vectors a, b, and c.

from numpy import random

x = random.randint(100)

print(x)

• 56

• 26

• 40

• All mentioned

NumPy is often used along with packages like?

• Node.js

• Matplotlib

• SciPy

• Both B and C