Python Program to get the subarray from an array using a specified range of indices

An array is a homogeneous data structure used to store elements of the same data type. Each element is identified by a key or index value. Python provides several ways to extract subarrays from arrays using specified index ranges.

What is a Subarray?

A subarray is a continuous portion of elements from an array. For example, if we have an array:

numbers = [9, 3, 1, 6, 9]
print("Original array:", numbers)

Original array: [9, 3, 1, 6, 9]

The possible subarrays include:

[9, 3]
[9, 3, 1] 
[3, 1, 6, 9]

Arrays in Python

Python offers three main approaches to work with arrays:

• Lists Native Python data structure: [1, 2, 3, 4, 5]

• Array module Typed arrays: array('i', [1, 2, 3, 4])

• NumPy arrays Scientific computing: array([1, 2, 3, 4])

All these arrays are indexed from 0 to (n-1). We'll use Python's slicing feature to extract subarrays.

Slicing Syntax

Python slicing follows this syntax:

iterable_obj[start:stop:step]

Where:

• Start Starting index (default: 0)

• Stop Ending index (exclusive, default: length of object)

• Step Increment value (default: 1)

Using List Slicing

Lists support slicing to extract subarrays using list[start:end:step] syntax:

# Creating array
data = [2, 5, 6, 7, 1, 9, 2, 0]
print("The original array is:", data)

# Get subarray from index 1 to 7
result = data[1:7]
print("The subarray is:", result)

The original array is: [2, 5, 6, 7, 1, 9, 2, 0]
The subarray is: [5, 6, 7, 1, 9, 2]

Using NumPy Arrays

NumPy arrays also support slicing with the same syntax. The slicing returns a view of the original array:

import numpy as np

# Creating NumPy array
numbers = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
print("The original array is:", numbers)

# Get subarray from index 1 to 4
result = numbers[1:4]
print("The subarray is:", result)

The original array is: [1 2 3 4 5 6 7 8 9]
The subarray is: [2 3 4]

Using Array Module

The array module provides typed arrays that also support slicing operations:

import array

# Creating array with integer type
data = array.array('i', [1, 2, 3, 4, 5, 6, 7, 8, 9])
print("The original array is:", data)

# Get subarray from index 1 to 8
result = data[1:8]
print("The subarray is:", result)

The original array is: array('i', [1, 2, 3, 4, 5, 6, 7, 8, 9])
The subarray is: array('i', [2, 3, 4, 5, 6, 7, 8])

Comparison

Conclusion

Python slicing provides a uniform way to extract subarrays across different array types. Use NumPy for numerical operations and large datasets, while lists work well for general programming tasks.