np.save() and np.load() for binary in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of loading a saved NumPy array?

Consider the following code that saves and loads a NumPy array using np.save() and np.load(). What will be printed?

NumPy

import numpy as np
arr = np.array([10, 20, 30])
np.save('test_array.npy', arr)
loaded_arr = np.load('test_array.npy')
print(loaded_arr)

A [10, 20, 30]

B [[10 20 30]]

C [10 20 30]

D Error: File not found

💡 Hint

Remember that np.save() stores the array in binary format and np.load() restores it exactly.

The np.save() function saves the array in a binary file. When loaded back with np.load(), it returns the original array with the same shape and values. Printing the array shows it without commas as in option C.

❓ data_output

intermediate

How many elements are in the loaded array?

Given the code below, how many elements does the loaded array contain?

NumPy

import numpy as np
arr = np.arange(12).reshape(3,4)
np.save('matrix.npy', arr)
loaded = np.load('matrix.npy')
print(loaded.size)

A 3

B Error: AttributeError

C 4

D 12

💡 Hint

The size attribute returns the total number of elements in the array.

The original array has shape (3,4), so total elements = 3 * 4 = 12. The loaded array keeps the same shape and size.

🔧 Debug

advanced

What error occurs when loading a non-existent file with np.load()?

What error will this code raise?

NumPy

import numpy as np
loaded = np.load('missing_file.npy')

A FileNotFoundError

B TypeError

C ValueError

D SyntaxError

💡 Hint

Think about what happens when you try to open a file that does not exist.

Trying to load a file that does not exist raises a FileNotFoundError in Python.

🧠 Conceptual

advanced

Which option correctly describes the file format used by np.save()?

What type of file does np.save() create when saving an array?

A A binary file in NumPy's .npy format

B A text file with comma-separated values

C A JSON file with array data

D An XML file describing the array

💡 Hint

The file is designed for fast loading and saving of NumPy arrays.

np.save() writes the array to a binary file with the .npy extension, which stores metadata and data efficiently.

🚀 Application

expert

What is the shape of the loaded array after saving and loading a 3D array?

Given the code below, what will be the shape of the loaded array?

NumPy

import numpy as np
arr = np.ones((2,3,4))
np.save('3d_array.npy', arr)
loaded_arr = np.load('3d_array.npy')
print(loaded_arr.shape)

A (3, 4, 2)

B (2, 3, 4)

C (24,)

D (2, 12)

💡 Hint

The shape of the array is preserved exactly when saved and loaded with np.save and np.load.

The original array has shape (2, 3, 4). Saving and loading with np.save and np.load keeps the shape unchanged.