np.zeros() for zero-filled arrays in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.zeros with shape and dtype

What is the output of this code snippet?

import numpy as np
arr = np.zeros((2, 3), dtype=int)
print(arr)

NumPy

import numpy as np
arr = np.zeros((2, 3), dtype=int)
print(arr)

A

[[0. 0. 0.]
 [0. 0. 0.]]

B

[[0 0 0]
 [0 0 0]]

C

[[0 0 0 0]
 [0 0 0 0]]

D [0 0 0 0 0 0]

💡 Hint

Check the shape and data type specified in np.zeros.

np.zeros creates an array of zeros with the given shape and data type. Here, shape is (2,3) and dtype is int, so the output is a 2x3 array of integer zeros.

❓ data_output

intermediate

Number of elements in np.zeros array

How many elements are in the array created by this code?

import numpy as np
arr = np.zeros((4, 5))
print(arr.size)

NumPy

import numpy as np
arr = np.zeros((4, 5))
print(arr.size)

A 20

B 9

C 10

D 5

💡 Hint

Multiply the dimensions of the shape to find total elements.

The shape (4,5) means 4 rows and 5 columns, so total elements = 4 * 5 = 20.

🔧 Debug

advanced

Identify the error in np.zeros usage

What error does this code produce?

import numpy as np
arr = np.zeros(3, 4)
print(arr)

NumPy

import numpy as np
arr = np.zeros(3, 4)
print(arr)

A TypeError: data type not understood

B TypeError: 'int' object is not iterable

C TypeError: zeros() missing 1 required positional argument: 'dtype'

D TypeError: zeros() takes 1 positional argument but 2 were given

💡 Hint

Check the function signature of np.zeros.

np.zeros expects the first argument to be the shape as a single tuple or int. Passing two separate ints causes a TypeError about argument count.

🚀 Application

advanced

Create a 3D zero-filled array and check shape

Which option creates a 3D zero-filled array with shape (2, 3, 4) and prints its shape correctly?

A

arr = np.zeros([2, 3, 4])
print(arr.shape)

B

arr = np.zeros(2, 3, 4)
print(arr.shape)

C

arr = np.zeros((2, 3, 4))
print(arr.shape)

D

arr = np.zeros({2, 3, 4})
print(arr.shape)

💡 Hint

np.zeros expects shape as a tuple or list as first argument.

Option C correctly passes a tuple as shape. Option C uses a list which also works but is less common. Option C passes multiple arguments causing error. Option C uses a set which is unordered and invalid.

🧠 Conceptual

expert

Memory size of np.zeros array

Given this code:

import numpy as np
arr = np.zeros((1000, 1000), dtype=np.float64)
print(arr.nbytes)

What is the output value printed?

NumPy

import numpy as np
arr = np.zeros((1000, 1000), dtype=np.float64)
print(arr.nbytes)

A 8000000

B 4000000

C 1000000

D 16000000

💡 Hint

Each float64 uses 8 bytes. Multiply by total elements.

The array has 1,000,000 elements (1000*1000). Each float64 uses 8 bytes. Total bytes = 1,000,000 * 8 = 8,000,000 bytes.