Python Array Indexing

Python arrays are zero-indexed, just like Lists. First element is at index 0, the second at index 1 and so on. Let's see how indexing works with arrays using array module:

Access Array Element with Index

We can access elements from the beginning of the array using positive indices:

import array

# Create an array of integers using the 'i' type code
arr = array.array('i', [10, 20, 30, 40, 50])

# Accessing elements using indexing
print(arr[0])  
print(arr[1])  
print(arr[4])  

10
20
50

Let's explore python array indexing in detail:

Negative Array Indexing

In Python, arrays support negative indexing where the last element of the array is accessed with index -1, the second-to-last element with index -2 and so on. Here's an example:

import array

# Create an array of integers
arr = array.array('i', [10, 20, 30, 40, 50])

# Accessing elements using negative indexing
print(arr[-1]) 
print(arr[-2])  

Explanation:

• print(arr[-1]): This accesses the last element of the array, which is 50.
• print(arr[-2]): This accesses the second-to-last element of the array, which is 40.

Negative indexing allows us to quickly access elements at the end of the array without needing to know its length.

2D Array Indexing

In a 2D array, elements are arranged in rows and columns. We can access elements using two indices: one for the row and one for the column.

import array

# Creating a 2D array (array of arrays)
arr = array.array('i', [array.array('i', [1, 2, 3]), 
                                array.array('i', [4, 5, 6]), 
                                array.array('i', [7, 8, 9])])

# Accessing elements in the 2D array
print(arr[0][0])  # (first element of first row)
print(arr[1][2])  # (third element of second row)
print(arr[2][1])  # (second element of third row)

Explanation:

• arr[0][0]: Accesses the first element of the first row (1).
• arr[1][2]: Accesses the third element of the second row (6).
• arr[2][1]: Accesses the second element of the third row (8).

3D Array Indexing

In a 3D array, elements are arranged in 2D grids and those grids are nested inside another array. You can access an element using three indices: one for the 2D array, one for the row and one for the column.

import array

# Creating a 3D array (array of arrays of arrays)
arr = array.array('i', [
    array.array('i', [array.array('i', [1, 2, 3]), 
                      array.array('i', [4, 5, 6]), 
                      array.array('i', [7, 8, 9])]),
    array.array('i', [array.array('i', [10, 11, 12]), 
                      array.array('i', [13, 14, 15]), 
                      array.array('i', [16, 17, 18])]),
])

# Accessing elements in the 3D array
print(arr[0][0][0]) 
print(arr[1][2][1]) 
print(arr[1][0][2])

Explanation:

• arr[0][0][0]: Accesses the first element of the first 2D array, first row (1).
• arr[1][2][1]: Accesses the second element of the third row in the second 2D array (17).
• arr[1][0][2]: Accesses the third element of the first row in the second 2D array (12).

Array Slicing using Index range

Array slicing allows us to extract a subarray (a portion of the original array) by specifying a range of indices. Here’s an example of slicing:

import array

# Create an array of integers
arr= array.array('i', [10, 20, 30, 40, 50, 60, 70])

# Slice the array
print(arr[1:5])     
print(arr[::2])    
print(arr[-4:-1])  

Explanation:

• arr[1:5]: This slice selects elements from index 1 to 4 (excluding index 5). It returns the subarray [20, 30, 40, 50].
• arr[::2]: This slice selects every second element starting from index 0. It returns [10, 30, 50, 70].
• arr[-4:-1]: This slice selects elements starting from the fourth-to-last element (index -4) to the second-to-last element (index -1), returning [40, 50, 60].