Working with Multidimensional Arrays
NumPy makes it easy to work with multidimensional arrays, including creating, manipulating, stacking, and splitting them. Multidimensional arrays are widely used in data processing, image analysis, and numerical computations.
Creating 2D and 3D Arrays
Creating 2D Arrays
A 2D array can be created using a list of lists.
import numpy as np
# Create a 2D array
array_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print("2D Array:\n", array_2d)Output:
2D Array:
[[1 2 3]
[4 5 6]
[7 8 9]]Creating 3D Arrays
A 3D array can be created using a list of lists of lists.
# Create a 3D array
array_3d = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
print("3D Array:\n", array_3d)Output:
3D Array:
[[[1 2]
[3 4]]
[[5 6]
[7 8]]]Manipulating Multidimensional Arrays
Reshaping Arrays
Reshape an array to change its dimensions without altering data.
# Reshape a 1D array into a 2D array
array = np.arange(1, 10)
reshaped = array.reshape(3, 3)
print("Reshaped Array:\n", reshaped)Output:
Reshaped Array:
[[1 2 3]
[4 5 6]
[7 8 9]]Transposing Arrays
Transpose a 2D array to swap rows and columns.
# Transpose a 2D array
transposed = array_2d.T
print("Transposed Array:\n", transposed)Output:
Transposed Array:
[[1 4 7]
[2 5 8]
[3 6 9]]Stacking Arrays
Vertical Stacking
Combine arrays vertically using vstack().
# Vertical stacking
array1 = np.array([1, 2, 3])
array2 = np.array([4, 5, 6])
stacked = np.vstack((array1, array2))
print("Vertically Stacked Array:\n", stacked)Output:
Vertically Stacked Array:
[[1 2 3]
[4 5 6]]Horizontal Stacking
Combine arrays horizontally using hstack().
# Horizontal stacking
stacked_h = np.hstack((array1, array2))
print("Horizontally Stacked Array:", stacked_h)Output:
Horizontally Stacked Array: [1 2 3 4 5 6]Splitting Arrays
Splitting Arrays into Smaller Arrays
Split arrays into smaller arrays using split().
# Split an array into three parts
array = np.array([1, 2, 3, 4, 5, 6])
split_arrays = np.split(array, 3)
print("Split Arrays:", split_arrays)Output:
Split Arrays: [array([1, 2]), array([3, 4]), array([5, 6])]Splitting 2D Arrays
# Split a 2D array along rows
split_rows = np.vsplit(array_2d, 3)
print("Row-wise Split:", split_rows)
# Split a 2D array along columns
split_cols = np.hsplit(array_2d, 3)
print("Column-wise Split:", split_cols)Output:
Row-wise Split: [array([[1, 2, 3]]), array([[4, 5, 6]]), array([[7, 8, 9]])]
Column-wise Split: [array([[1], [4], [7]]), array([[2], [5], [8]]), array([[3], [6], [9]])]Try It Yourself
Problem 1: Create and Manipulate a 2D Array
Create a 2D array with shape (4, 4). Reshape it into a (2, 8) array and then transpose it.
Show Code
import numpy as np
# Create a 2D array
array = np.arange(1, 17).reshape(4, 4)
# Reshape and transpose
reshaped = array.reshape(2, 8)
transposed = reshaped.T
print("Original Array:\n", array)
print("Reshaped Array:\n", reshaped)
print("Transposed Array:\n", transposed)Problem 2: Stack and Split Arrays
Create two 1D arrays with values from 1 to 6 and stack them vertically. Then, split the resulting array into two smaller arrays.
Show Code
import numpy as np
# Create arrays
array1 = np.array([1, 2, 3])
array2 = np.array([4, 5, 6])
# Stack vertically
stacked = np.vstack((array1, array2))
# Split the stacked array
split_arrays = np.vsplit(stacked, 2)
print("Stacked Array:\n", stacked)
print("Split Arrays:", split_arrays)