Python program to create 3D list.

In Python, a 3D list is also called a three-dimensional array (list of lists of lists). It can be visualized as a cube or a set of tables stacked together. It is commonly used to represent data with three indices, such as a matrix of images (height, width, depth) or storing data for multiple 2D grids.

In this article, we will learn how to create a 3D list. While Python doesn't have built-in support for multi-dimensional arrays like other programming languages, we can create and manipulate 3D lists using nested lists and loops.

Using Nested Loops

The most straightforward way to create a 3D list is using nested loops. In the following example, we create a 3D list with sequential numbers starting from 1 ?

# Create a 3D list with dimensions 2x2x3
dimensions = (2, 2, 3)
x = 1
result = []

for i in range(dimensions[0]):
    layer = []
    for j in range(dimensions[1]):
        row = []
        for k in range(dimensions[2]):
            row.append(x)
            x += 1
        layer.append(row)
    result.append(layer)

print("3D list with sequential numbers:")
print(result)

3D list with sequential numbers:
[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]

Using List Comprehension

Python list comprehension offers a more concise way to create lists in a single line. It combines loops and conditional statements, making it more efficient than traditional loop methods.

Syntax

newlist = [expression for item in iterable if condition == True]

For a 3D list, we use nested list comprehensions. Here's an example creating a 2×3×4 list filled with zeros ?

# Create a 3D list of size 2x3x4 filled with zeros
x, y, z = 2, 3, 4
result = [[[0 for _ in range(z)] for _ in range(y)] for _ in range(x)]

print("3D list filled with zeros:")
print(result)

3D list filled with zeros:
[[[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]]

Using NumPy (Alternative Approach)

For more complex operations, NumPy provides better support for multi-dimensional arrays ?

import numpy as np

# Create a 3D array using NumPy
arr_3d = np.zeros((2, 3, 4), dtype=int)
print("3D array using NumPy:")
print(arr_3d)

# Create with sequential numbers
arr_sequential = np.arange(1, 25).reshape(2, 3, 4)
print("\n3D array with sequential numbers:")
print(arr_sequential)

3D array using NumPy:
[[[0 0 0 0]
  [0 0 0 0]
  [0 0 0 0]]

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

3D array with sequential numbers:
[[[ 1  2  3  4]
  [ 5  6  7  8]
  [ 9 10 11 12]]

 [[13 14 15 16]
  [17 18 19 20]
  [21 22 23 24]]]

Comparison

Conclusion

Python offers multiple ways to create 3D lists: nested loops for clarity, list comprehension for conciseness, and NumPy for advanced mathematical operations. Choose the method that best fits your specific use case and performance requirements.