In Python, a 3D array is a data structure that can hold a collection of elements organized in a three-dimensional grid-like structure. It is an extension of a 2D array, where each element in the 3D array is identified by its indices in three dimensions: row, column, and depth.
A 3D array can be visualized as a stack of 2D arrays. It can be used to represent volumetric data or any data that requires three-dimensional indexing. Each element in the 3D array is accessed using three indices.
Here’s an example of a simple 3D array with dimensions 2x3x4:
[
[
[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]
],
[
[13, 14, 15, 16],
[17, 18, 19, 20],
[21, 22, 23, 24]
]
]
3D array Python example
In Python, you can create a 3D array using nested lists or by using libraries like NumPy. Here’s the syntax for creating a 3D array using both approaches:
Using nested lists:
# Create a 3D array using nested lists
array_3d = [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]
The above example, array_3d
is a 3D array created using nested lists. It contains two 2D arrays, each with two rows and three columns.
Using NumPy arrays:
import numpy as np
# Create a 3D array using NumPy
array_3d = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
In the above example, array_3d
is a 3D array created using the NumPy library. The np.array()
function is used to convert the nested lists into a NumPy array.
Here’s an example of creating, accessing, and modifying a 3D array in Python using nested lists:
# Create a 3D array using nested lists
array_3d = [
[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
[[10, 11, 12], [13, 14, 15], [16, 17, 18]],
[[19, 20, 21], [22, 23, 24], [25, 26, 27]]
]
# Accessing elements in the 3D array
print(array_3d[1][2][0]) # Output: 16
# Modifying elements in the 3D array
array_3d[0][1][2] = 99
print(array_3d)
Or using NumPy:
import numpy as np
# Create a 3D array using NumPy
array_3d = np.array([
[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
[[10, 11, 12], [13, 14, 15], [16, 17, 18]],
[[19, 20, 21], [22, 23, 24], [25, 26, 27]]
])
# Accessing elements in the 3D array
print(array_3d[1, 2, 0]) # Output: 16
# Modifying elements in the 3D array
array_3d[0, 1, 2] = 99
print(array_3d)
Output:
Comment if you have any doubts or suggestions on this Python Array topic.
Note: IDE: PyCharm 2021.3.3 (Community Edition)
Windows 10
Python 3.10.1
All Python Examples are in Python 3, so Maybe its different from python 2 or upgraded versions.