Arrays are data structures that store multiple values of the same type in a single variable. In Python, arrays are used when you need to perform operations on large volumes of data efficiently.

1. What is an Array?

An array is a collection of items stored at contiguous memory locations. All elements in an array must be of the same data type.

In Python, you can use:

• list: A versatile built-in data structure that acts as an array.
• array module: Used for type-restricted arrays.
• NumPy library: For multidimensional arrays and numerical computations.

2. Why Use Arrays?

• Efficient for storing and accessing large amounts of data.
• Supports element-wise operations.
• Ideal for numerical and scientific computations.

3. Arrays with the array Module

Importing the Array Module

To use arrays, you must first import the array module.

import array

Creating an Array

Syntax

array.array(typecode, [elements])

• typecode: Specifies the type of elements in the array.
  • 'i': Integer
  • 'f': Float
  • 'd': Double (larger floating-point numbers)
• [elements]: The list of elements to initialize the array.

Example

import array

# Create an array of integers
numbers = array.array('i', [1, 2, 3, 4, 5])
print(numbers) # Outputs: array('i', [1, 2, 3, 4, 5])

5. Accessing Elements

You can access elements of an array using their index (starting from 0).

print(numbers[0]) # Outputs: 1
print(numbers[3]) # Outputs: 4

6. Modifying Elements

You can update elements at a specific index.

numbers[1] = 10
print(numbers) # Outputs: array('i', [1, 10, 3, 4, 5])

Adding Elements

• append(): Add a single element to the end of the array.
• extend(): Add multiple elements from an iterable.

numbers.append(6) # Adds 6 to the array
print(numbers) # Outputs: array('i', [1, 10, 3, 4, 5, 6])

numbers.extend([7, 8]) # Adds 7 and 8
print(numbers) # Outputs: array('i', [1, 10, 3, 4, 5, 6, 7, 8])

Removing Elements

• remove(): Removes the first occurrence of a value.
• pop(): Removes an element by index (default is the last element).

numbers.remove(10) # Removes the first occurrence of 10
print(numbers) # Outputs: array('i', [1, 3, 4, 5, 6, 7, 8])

numbers.pop(2) # Removes the element at index 2
print(numbers) # Outputs: array('i', [1, 3, 5, 6, 7, 8])

Limitations of the array Module

• Only supports single-dimensional arrays.
• Limited data type support compared to libraries like NumPy.

When to Use NumPy

• If you need to perform mathematical operations on arrays.
• For multidimensional arrays or matrices.
• For better performance in scientific computing.

import numpy as np

arr = np.array([1, 2, 3, 4])
print(arr + 5) # Adds 5 to each element

Python does not have built-in support for Arrays, but Python Lists can be used instead.