Introduction to Array in Python

Grokking Python Fundamentals

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Introduction to Array in Python

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Arrays in Python are a collection of elements of the same type, stored in contiguous memory locations. Unlike lists, which can store elements of different types, arrays in Python are designed to handle homogeneous data types, making them more efficient for certain types of numerical computations and data storage tasks.

Arrays are particularly useful when dealing with large volumes of data that require performance-sensitive handling. In Python, arrays can be handled using the array module, which provides the necessary functionality to perform operations like traversals, insertions, deletions, searches, and updates efficiently.

Syntax of Array

To work with arrays in Python, you first need to import the array module. Here's how you can define an array:

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'byte_code' is the type code that defines the type of array elements.
[ele1, ele2, ele3, ...] represents the array of elements

Understanding Type Codes

When creating an array, the type code is crucial as it directly influences the physical size in memory and the operations allowed on the array. Here is a table summarizing common type codes:

Type Code	C Type	Python Type	Minimum Size (Bytes)
`'b'`	signed char	int	1
`'B'`	unsigned char	int	1
`'u'`	Py_UNICODE	Unicode character	2 (or 4)
`'h'`	signed short	int	2
`'H'`	unsigned short	int	2
`'i'`	signed int	int	2
`'I'`	unsigned int	int	2
`'l'`	signed long	int	4
`'L'`	unsigned long	int	4
`'f'`	float	float	4
`'d'`	double	float	8

Understanding Array Indexing in Python

Array indexing is a fundamental concept in Python, as it allows you to access, modify, and manipulate elements directly by referring to their position within the array.

Each element in an array is assigned a unique index, which represents its position. These indices start at 0 for the first element and increase by 1 for each subsequent element.

How Array Indexing Works

Here's a breakdown of how indexing works in arrays and how you can use it to access elements:

Positive Indexing: This is the most direct way to reference an element. The index starts at 0 for the first element, 1 for the second element, and so on up to n-1 for the last element, where n is the number of elements in the array.
Negative Indexing: Python also supports negative indexing for arrays, which allows you to access elements from the end of the array backwards. Here, -1 refers to the last element, -2 to the second last, and so on.

Example of Array Indexing

Here's a simple example to illustrate both positive and negative indexing in a Python array:

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Explanation:

a[0] and a[1]: These are examples of positive indexing. a[0] accesses the first element (10), and a[1] accesses the second element (20).
a[-1] and a[-2]: These illustrate negative indexing. a[-1] accesses the last element (50), and a[-2] accesses the second last element (40).

Traverse - Printing Array Elements

Traversing an array involves accessing each element in sequence and performing an operation such as printing. This is fundamental for displaying the array's contents or for further processing of its elements.

Example

Here, we will print each element of an integer array.

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Explanation:

import array as arr: Imports the array module and gives it the alias arr for ease of use.
a = arr.array('i', [1, 2, 3, 4, 5]): Initializes an array a with the type code 'i', indicating the elements are integers. The array is initialized with the values 1, 2, 3, 4, and 5.
The for loop: Iterates through each element in the array a. The print function outputs each element followed by a space, thanks to end=' ', which overrides the default newline end character.

Insertion - Adding Elements

Insertion involves adding an element at a specific index. This operation shifts subsequent elements to the right, modifying the array's structure.

Example

In this example, we will insert the number 10 at the second position of the array.

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Explanation:

a.insert(1, 10): Inserts the integer 10 at index 1. The existing elements from that position onward are shifted right.
a.tolist(): Converts the array to a list for easier reading when printing.

Deletion - Removing Elements

Deletion removes an element at a specified index, which shifts subsequent elements to the left.

Example

In this example, we will remove the element at the second position from the array.

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Explanation:

a.pop(1): Removes the element at index 1, which is 10, from the array a.
The remaining elements shift left to fill the gap.

Search - Finding Elements

You can search for an element by its value to retrieve its index in the array.

Example

In this example, we will find the index of the element 3 in the array.

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Explanation:

a.index(3): Searches for the first occurrence of the integer 3 in the array a and returns its index, which is 2.

Update - Modifying Elements

Updating an array involves changing the value of an element at a specified index.

Example

In this example, we will change the third element to 20 in the array.

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Explanation:

a[2] = 20: Modifies the element at index 2 (originally 3) to 20.
This operation directly alters the content of the array at the specified index, demonstrating the mutable nature of Python arrays.

These examples comprehensively demonstrate basic operations on arrays in Python, showing how to manipulate array data effectively. These operations form the foundation for working with arrays in applications that require efficient data handling.

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