np.savez() for multiple arrays in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.savez() and np.load() for multiple arrays

What will be the output of the following code snippet?

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])

np.savez('data.npz', first=arr1, second=arr2)
loaded = np.load('data.npz')
print(list(loaded.keys()))

NumPy

import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])

np.savez('data.npz', first=arr1, second=arr2)
loaded = np.load('data.npz')
print(list(loaded.keys()))

A ['first', 'second']

B ['data']

C ['0', '1']

D ['arr1', 'arr2']

💡 Hint

Think about how the arrays are named when saved with np.savez using keyword arguments.

When using np.savez with named arguments, the keys in the loaded file correspond to those names. Here, the arrays are saved with keys 'first' and 'second'.

❓ data_output

intermediate

Number of arrays saved in .npz file

Given the code below, how many arrays are stored inside the saved data.npz file?

import numpy as np

x = np.arange(5)
y = np.arange(5, 10)
z = np.arange(10, 15)

np.savez('data.npz', x=x, y=y, z=z)

NumPy

import numpy as np

x = np.arange(5)
y = np.arange(5, 10)
z = np.arange(10, 15)

np.savez('data.npz', x=x, y=y, z=z)
loaded = np.load('data.npz')
print(len(loaded.files))

A 1

B 3

C 2

D 0

💡 Hint

Count how many arrays are passed as named arguments to np.savez.

Three arrays are saved with keys 'x', 'y', and 'z', so the file contains 3 arrays.

🔧 Debug

advanced

Error when loading .npz file without closing

What error will occur when running this code?

import numpy as np

arr = np.array([1, 2, 3])
np.savez('file.npz', arr)
loaded = np.load('file.npz')
loaded.close()
print(loaded['arr'])

NumPy

import numpy as np

arr = np.array([1, 2, 3])
np.savez('file.npz', arr)
loaded = np.load('file.npz')
loaded.close()
print(loaded['arr'])

A No error, prints [1 2 3]

B KeyError: 'arr'

C AttributeError: 'NpzFile' object has no attribute 'close'

D ValueError: I/O operation on closed file.

💡 Hint

Consider what happens if you try to access data after closing the file object.

After calling loaded.close(), the file is closed. Accessing loaded['arr'] tries to read from a closed file, causing a ValueError.

🚀 Application

advanced

Saving multiple arrays with and without names

Which option correctly saves two arrays a and b into a single .npz file with keys 'a' and 'b' respectively?

NumPy

import numpy as np
a = np.array([10, 20])
b = np.array([30, 40])

A np.savez('file.npz', a, b)

B np.savez('file.npz', {'a': a, 'b': b})

C np.savez('file.npz', a=a, b=b)

D np.savez('file.npz', ['a', a], ['b', b])

💡 Hint

Remember how keyword arguments work in Python functions.

Using keyword arguments like a=a and b=b assigns keys 'a' and 'b' in the saved file. Other options are invalid syntax or incorrect usage.

🧠 Conceptual

expert

Difference between np.savez() and np.savez_compressed()

Which statement best describes the difference between np.savez() and np.savez_compressed()?

A <code>np.savez_compressed()</code> saves arrays with compression, reducing file size but increasing save/load time.

B <code>np.savez()</code> compresses arrays automatically, while <code>np.savez_compressed()</code> does not.

C Both functions save arrays without compression; the difference is in file format.

D <code>np.savez()</code> saves arrays as text files, <code>np.savez_compressed()</code> saves as binary.

💡 Hint

Think about compression and its effect on file size and speed.

np.savez_compressed() compresses the arrays to reduce file size but this can make saving and loading slower. np.savez() saves without compression.