Python - How To Declare 3D Array in Python

99

In this tutorial, we will discuss methods to declare 3-dimensional arrays in Python.

Declare 3D List Using List Comprehensions in Python

As far as the basic functionality is concerned, the lists do the same job as arrays in Python. The is a way of performing complex operations on lists. List comprehensions can also be used to declare a 3D array. The following code example shows us how we can use the list comprehensions to declare a 3D array in Python.

n = 3  distance = [[[0 for k in range(n)] for j in range(n)] for i in range(n)]  print(distance) 

Output:

[[[0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0]]] 

In the above code, we first declare the number of dimensions and then initialize a list of n dimensions using list comprehensions.

Declare 3D List Using Multiplication Method in Python

The list comprehension method works fine, but it is a bit code extensive. If we want to minimize our code, we can use another approach called the multiplication method. The following code example shows us how to use the multiplication method to declare a 3D array in Python.

distance=[[[0]*n]*n]*n  print(distance) 

Output:

[[[0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0]]] 

The above code does the same thing as list comprehensions but reduces the code drastically.

Declare 3D Array Using the NumPy Package in Python

If we want to perform some operations specifically on arrays in Python, we had better use the . It is a package specifically designed to work with arrays in Python.

NumPy is an external package and does not come pre-installed with Python. We need to install it before using it. The command to install the NumPy package is given below.

pip install numpy 

The following code example shows how we can declare a 3-dimensional array in Python using the NumPy package.

import numpy as np  i = 3 j = 3 k = 3  new_array= np.zeros((i, j, k))  print(new_array) 

Output:

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

In the above code, we first declare the number of elements in each dimension of the array with i, j, and k. After that, we pass these dimensions to np.zeros() to initialize a 3D array. The gives us an array and fills every element with a 0.