Understanding the Difference Between Data Types and Data Structures in Python
In Python programming, it’s essential to grasp the concepts of data types and data structures. While they both deal with organizing and manipulating data, they serve different purposes. In this article, we will explore the difference between data types and data structures in Python, providing examples to help you understand their distinctions and applications.
Data Types: Building Blocks of Data
Data types in Python represent the different kinds of values that can be stored and manipulated in a program. They define the nature of the data and the operations that can be performed on it. Python offers several built-in data types, including integers, floating-point numbers, strings, booleans, and more.
Data Structures: Organizing and Managing Data
While data types deal with individual values, data structures focus on organizing and managing collections of data. They provide mechanisms to store and manipulate multiple elements, allowing for more complex data representations. Python offers various built-in data structures, such as lists, tuples, dictionaries, sets, and more.
Task 1 — Give the Difference between List, Tuple and Set. Do Hands-on and provide screenshots as per your understanding
Lists:
Ordered collection of elements enclosed in square brackets ([]).
Mutable, meaning elements can be added, removed, or modified after creation.
Allows duplicate values.
Elements can be accessed using indexing.
Lists are commonly used when you need to store and manipulate a collection of items in a specific order.
Tuples:
Ordered collection of elements enclosed in parentheses ().
Immutable, meaning elements cannot be modified after creation.
Allows duplicate values.
Elements can be accessed using indexing.
Tuples are suitable when you want to store a collection of values that should not be changed.
Sets:
An unordered collection of unique elements enclosed in curly braces ({}).
Mutable, meaning elements can be added or removed after creation.
Does not allow duplicate values.
Elements cannot be accessed using indexing.
Sets are useful when you want to store a collection of unique elements and perform operations like union, intersection, and difference.\
Task 2 — Create the Dictionary and use Dictionary methods to print your favourite tool just by using the keys of the Dictionary
Python code:
Task 3 — Create a List of cloud service providers
Write a program to add Digital Ocean to the list of cloud_providers and sort the list in alphabetical order.
By using the append() function, we add "Digital Ocean" to the cloud_providers list. Then, we use the sort() function to sort the list in alphabetical order. Finally, we print the updated list, which now includes "Digital Ocean."
In this article, we explored the differences between lists, tuples, and sets in Python. We learned about their characteristics, use cases, and demonstrated hands-on examples to solidify our understanding.