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Select elements from 3D NumPy array using Fancy indexing

Fancy Indexing:

Write a NumPy program that creates a 3D NumPy array and uses fancy indexing to select elements from specific rows and columns.

Sample Solution:

Python Code:

import numpy as np

# Create a 3D NumPy array of shape (3, 4, 5)
array_3d = np.random.randint(0, 100, size=(3, 4, 5))

# Define the row and column indices to select specific elements
row_indices = np.array([0, 1, 2])
col_indices = np.array([1, 2, 3])

# Use fancy indexing to select elements from specific rows and columns
selected_elements = array_3d[row_indices[:, np.newaxis], col_indices]

# Print the original 3D array and the selected elements
print('Original 3D array:\n', array_3d)
print('Row indices:\n', row_indices)
print('Column indices:\n', col_indices)
print('Selected elements:\n', selected_elements)

Output:

Original 3D array:
 [[[43 98 13 67 64]
  [ 9 88 72 87 34]
  [27 93  0 91 83]
  [40 48 50 71 81]]

 [[83  2 37 73 97]
  [ 8 60  2 72 68]
  [95 40 71 47 95]
  [55  3 18 17 46]]

 [[78 87 23 30 51]
  [67 57  8 18 72]
  [79 78 67 23 51]
  [44 82 68 33 89]]]
Row indices:
 [0 1 2]
Column indices:
 [1 2 3]
Selected elements:
 [[[ 9 88 72 87 34]
  [27 93  0 91 83]
  [40 48 50 71 81]]

 [[ 8 60  2 72 68]
  [95 40 71 47 95]
  [55  3 18 17 46]]

 [[67 57  8 18 72]
  [79 78 67 23 51]
  [44 82 68 33 89]]]

Explanation:

  • Import Libraries:
    • Imported numpy as np for array creation and manipulation.
  • Create 3D NumPy Array:
    • Create a 3D NumPy array named array_3d with random integers ranging from 0 to 99 and a shape of (3, 4, 5).
  • Define Row and Column Indices:
    • Defined row_indices and col_indices arrays to specify the rows and columns from which to select elements.
  • Fancy Indexing:
    • Used fancy indexing to select elements from array_3d based on row_indices and col_indices.
  • Print Results:
    • Print the original 3D array, the row and column indices, and the selected elements to verify the indexing operation.

Python-Numpy Code Editor: