How To Save Multiple Numpy Arrays

NumPy is a powerful Python framework for numerical computing that supports massive, multi-dimensional arrays and matrices and offers a number of mathematical functions for modifying the arrays. It is an essential store for Python activities involving scientific computing, data analysis, and machine learning.

What is a Numpy array?

A NumPy array is a multi-dimensional data structure in Python used for numerical computations. It is similar to a list, but it allows for more efficient storage and manipulation of numerical data.

Saving Multiple Numpy Arrays

Saving multiple NumPy arrays into a single file can be necessary when you want to store related data together or when you need to share or distribute multiple arrays as a single unit. It helps in organizing your data and simplifies the process of loading and accessing the arrays later on. We will discuss some methods to do the same:

Creating Sample Arrays

Three different arrays array1,array2, and array3 are created.

Python3

import numpy as np

# Create some sample NumPy arrays
array1 = np.array([1, 2, 3, 4, 5])
array2 = np.array([10, 20, 30, 40, 50])
array3 = np.array([0.1, 0.2, 0.3, 0.4, 0.5])

Using np.savez() function

The numpy.savez function is used to save these arrays into a single .npz file called ‘multiple_arrays.npz’. The arrays are named inside the .npz file, and you can access them by their names when loading the file.

Python3

# Save the arrays into a single .npz file
np.savez('multiple_arrays.npz', array1=array1, array2=array2, array3=array3)

Loading the Arrays back

Python3

# Load the arrays from the .npz file
loaded_data = np.load('multiple_arrays.npz')

# Access individual arrays by their names
loaded_array1 = loaded_data['array1']
loaded_array2 = loaded_data['array2']
loaded_array3 = loaded_data['array3']

# Now you can use the loaded arrays as needed
print(loaded_array1)
print(loaded_array2)
print(loaded_array3)

Output:

[1 2 3 4 5]
[10 20 30 40 50]
[0.1 0.2 0.3 0.4 0.5]

Using np.savez_compressed

We will save the three arrays into a single compressed file named ‘multiple_arrays_compressed.npz’

Python3

np.savez_compressed('multiple_arrays_compressed.npz', array1=array1, array2=array2, array3=array3)

Loading the the arrays back

Python3

# Load the saved arrays
data = np.load('multiple_arrays_compressed.npz')
loaded_array1 = data['array1']
loaded_array2 = data['array2']
loaded_array3 = data['array3']

print(loaded_array1)
print(loaded_array2)
print(loaded_array3)

Output:

[1 2 3 4 5]
[10 20 30 40 50]
[0.1 0.2 0.3 0.4 0.5]

How saving multiple array is different from saving single array using np.save?

Saving multiple arrays using np.savez_compressed() allows you to store multiple arrays into a single compressed file, reducing disk space usage and improving efficiency during storage and transfer. In contrast, saving a single array using np.save() generates an uncompressed binary file, which may be less efficient for storing multiple arrays or when storage space is a concern. Additionally, np.savez_compressed() requires specifying keys for each array, while np.save() only needs the array and the file name.