Index a 2D Numpy array with 2 lists of indices

Index a 2D Numpy array with 2 lists of indices

You can index a 2D NumPy array using two lists of indices to select specific elements from the array. One list specifies the row indices, and the other list specifies the column indices. Here's how you can do it:

import numpy as np

# Create a sample 2D array
array_2d = np.array([[1, 2, 3],
                     [4, 5, 6],
                     [7, 8, 9]])

# Lists of row and column indices
row_indices = [0, 1, 2]
column_indices = [1, 0, 2]

# Index the array using the lists of indices
selected_elements = array_2d[row_indices, column_indices]

print("Selected Elements:", selected_elements)

In this example, we have a 2D array named array_2d. The row_indices list specifies the row indices (0, 1, 2), and the column_indices list specifies the column indices (1, 0, 2). By using these lists of indices, we can extract the elements at the corresponding positions from the array_2d.

The output will be:

Selected Elements: [2 4 9]

Keep in mind that the shape of the row_indices and column_indices lists should match, and they should correspond to valid indices within the bounds of the array.

Examples

  1. "How to index a 2D Numpy array with two lists of indices?" Description: Indexing a 2D Numpy array with two lists of indices allows you to access specific elements or subsets efficiently. Code:

    import numpy as np

# Example array
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

# Two lists of indices
row_indices = [0, 1, 2]
col_indices = [0, 1, 2]

# Indexing with two lists of indices
result = arr[row_indices, col_indices]
print(result)  # Output: [1 5 9]

  2. "Python Numpy array indexing with two lists" Description: Python's Numpy library facilitates indexing of arrays using two lists, enabling versatile data manipulation. Code:

    import numpy as np

# Sample 2D array
arr = np.array([[10, 20, 30], [40, 50, 60], [70, 80, 90]])

# Defining index lists
rows = [0, 2]
cols = [1, 2]

# Indexing with two lists
selected_values = arr[rows, cols]
print(selected_values)  # Output: [20 90]

  3. "Numpy array indexing with multiple lists" Description: Numpy enables indexing of arrays with multiple lists, offering flexibility in data extraction. Code:

    import numpy as np

# Example array
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

# Two lists of indices
rows = [0, 2]
cols = [1, 2]

# Indexing with multiple lists
result = arr[rows, cols]
print(result)  # Output: [2 9]

  4. "Accessing specific elements in a 2D Numpy array using lists of indices" Description: Utilizing lists of indices in Numpy enables precise access to individual elements within a 2D array. Code:

    import numpy as np

# Sample 2D array
arr = np.array([[11, 22, 33], [44, 55, 66], [77, 88, 99]])

# Lists of row and column indices
rows = [0, 2]
cols = [1, 2]

# Indexing using lists of indices
selected_values = arr[rows, cols]
print(selected_values)  # Output: [22 99]

  5. "Python Numpy indexing with two lists example" Description: Demonstrating how to index a Numpy array using two lists as indices in Python. Code:

    import numpy as np

# Sample array
arr = np.array([[3, 6, 9], [12, 15, 18], [21, 24, 27]])

# Two lists of indices
rows = [0, 2]
cols = [1, 2]

# Indexing with two lists
result = arr[rows, cols]
print(result)  # Output: [ 6 27]

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