Data structures form the backbone of programming, enabling efficient storage, organization, and manipulation of data in Python. In this article, we delve into the significance of data structures and their pivotal role in software development. From lists and tuples to dictionaries and sets, Python offers a rich repertoire of built-in data structures.
Understanding these data structures is essential for mastering Python programming and developing efficient algorithms. Through examples and explanations, we unravel the intricacies of data structures in Python, equipping readers with the knowledge and skills necessary to tackle real-world problems and optimize their code effectively.
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Here are examples of different types of data structures in Python:
List:
Definition: Lists are ordered collections of items in Python, represented by square brackets []. They can contain elements of different data types and are mutable, meaning their contents can be changed after creation.
Syntax:
my_list = [item1, item2, item3, …]
Example:
names_list = [‘Faisal’, ‘Ali’, ‘Mehwish’, ‘Kamran’, ‘Yasir’]
Tuple:
Definition: Tuples are ordered collections of items similar to lists, but they are immutable, meaning their contents cannot be changed after creation. Tuples are represented by parentheses ().
Syntax:
my_tuple = (item1, item2, item3, …)
Example:
names_tuple = (‘Faisal’, ‘Ali’, ‘Mehwish’, ‘Kamran’, ‘Yasir’)
Dictionary:
Definition: Dictionaries are unordered collections of key-value pairs in Python, represented by curly braces {}. Each key-value pair maps the key to its corresponding value, and dictionaries are mutable.
Syntax:
my_dict = {‘key1’: value1, ‘key2’: value2, ‘key3’: value3, …}
Example:
names_dict = {‘Faisal’: 28, ‘Ali’: 30, ‘Mehwish’: 25, ‘Kamran’: 35, ‘Yasir’: 29}
Set:
Definition: Sets are unordered collections of unique elements in Python, represented by curly braces {}. Sets do not allow duplicate elements, and they are mutable.
Syntax:
my_set = {item1, item2, item3, …}
Example:
names_set = {‘Faisal’, ‘Ali’, ‘Mehwish’, ‘Kamran’, ‘Yasir’}
These examples showcase the usage of different types of data structures in Python, providing flexibility and efficiency in storing and manipulating data.
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