Question in numpy (Vectorized comparison) (usejupyter notebook)

In [2]: import numpy as np

In [ ]: np.random.seed(0)

START YOUR CODE

# Create a 3 by 3 numpy array with random float numbers sampledfrom a normal distribution (mean=0, std=1)

a = None

# Find how many elements are greater than or equal to 0.5 inarray a.

# Hint: numpy array can be directly compared with constantnumbers; In Python, True == 1, and False == 0

count = None

# Find the indices of all elements in array a that are greaterthan or equal to 0.5

# Hint: use np.argwhere()

indices = None

END YOUR CODE

## DO NOT CHANGE THE CODE BELOW ##

assert isinstance(a, np.ndarray)

print('a = {}'.format(a))

print('count = {}'.format(count))

print('indices = {}'.format(indices))

Expected output

a =	[[ 1.76405235 0.40015721 0.97873798] [ 2.2408932 1.86755799 -0.97727788] [ 0.95008842 -0.15135721 -0.10321885]]
count =	5
indices =	[[0, 0], [0, 2], [1, 0], [1, 1], [2, 0]]

Answer rating: 100% (QA)

To solve this problem you can use the following code import numpy as np ... View the full answer