Day 14 : Python Data Types and Data Structures for DevOps

What are data types in Python?

Data types are categories or classifications of data items that define the kind of value stored and the operations that can be performed on them. In Python programming, data types are implemented as classes, and variables are instances (objects) of these classes. This means that every piece of data in Python is treated as an object.

Python provides several built-in data types that are available by default:

1. Numeric: These include integers, complex numbers, and floating-point numbers. Integers represent whole numbers, while floating-point numbers represent decimal numbers. Complex numbers have a real and imaginary part.

   Example:

    x = 10  # Integer
    y = 3.14  # Float
    z = 2 + 3j  # Complex
   

2. Sequential: Sequential data types include strings, lists, and tuples. They are ordered collections of elements, meaning the order of elements is preserved.

   Example:

    text = "Hello, World!"  # String
    numbers = [1, 2, 3, 4, 5]  # List
    coordinates = (10, 20)  # Tuple
   

3. Boolean: Boolean data type represents truth values, which can be either True or False. It is commonly used for logical operations and comparisons.

   Example:

    is_valid = True
    is_greater = 10 > 5
   

4. Set: Sets are unordered collections of unique elements. They are useful for tasks like membership testing and eliminating duplicate entries from a collection.

   Example:

    unique_numbers = {1, 2, 3, 4, 5}
    vowels = {'a', 'e', 'i', 'o', 'u'}
   

5. Dictionaries: Dictionaries are collections of key-value pairs. They allow efficient retrieval of values based on keys and are commonly used for tasks like mapping and organizing data.

   Example:

    student = {'name': 'Yash', 'age': 22, 'grade': 'A'}
   

These data types form the foundation of Python programming and are essential for storing and manipulating data in Python applications.

What are Python's core data structures and how are they utilized?

Data Structures are fundamental ways of organizing data for efficient access. They form the backbone of programming languages and Python offers simplified learning of these structures.

• Lists: Ordered collections similar to arrays, allowing flexible storage of different data types.

  Lists: Ordered collection

    my_list = [1, 2, 3, 4, 5]
  

• Tuple: Immutable collections akin to lists, ensuring elements cannot be added or removed once created.

  Tuple: Immutable collection

    my_tuple = (10, 20, 30, 40, 50)
  

• Dictionary: Unordered collections acting as hash tables, offering constant time complexity. Unlike other data types, dictionaries store key-value pairs for optimized data storage.

  Dictionary: Unordered collection of key-value pairs

    my_dict = {'name': 'Yash', 'age': 22, 'city': 'Indore'}