Python Data Structures Lists, Tuples, Dictionaries, Sets
Absolutely! Python provides several built-in data structures to work with different types of data efficiently. Here's a brief overview of each:
Lists:
Ordered collection of items.
Mutable (can be changed).
Elements can be of different data types.
Accessed by index.
Created using square brackets [].
Example:
Python Code
my_list = [1, 2, 3, 'hello', True]
Tuples:
Ordered collection of items.
Immutable (cannot be changed).
Elements can be of different data types.
Accessed by index.
Created using parentheses ().
Example:
Python Code
my_tuple = (1, 2, 3, 'hello', True)
Dictionaries:
Collection of key-value pairs.
Unordered.
Mutable.
Accessed by key.
Keys must be unique and immutable, values can be mutable or immutable.
Created using curly braces {} or the dict() constructor.
Example:
Python Code
my_dict = {'name': 'John', 'age': 30, 'city': 'New York'}
Sets:
Unordered collection of unique items.
Mutable.
Elements must be immutable.
Can perform set operations like union, intersection, difference, etc.
Created using curly braces {} or the set() constructor.
Example:
Python Code
my_set = {1, 2, 3, 4, 5}
Each of these data structures has its own characteristics and use cases, allowing you to choose the one that best fits your needs based on factors such as mutability, ordering, uniqueness, and performance requirements.