02. data structures.md

Data Structures

Lists

• for dynamic arrays, stacks, queues
• Lists are ordered collections of items.
• They are created using square brackets [].
• Lists can contain elements of different data types.
• example

  my_list = [1, 2, 3, "hello", True]

• common operations
  • accessing elements by index
    • my_list[0] returns the first element
  • slicing
    • my_list[1:3] returns a new list with elements 2 and 3
  • adding elements
    • my_list.append(4) adds 4 to the end
  • removing elements
    • my_list.remove(2) removes the first occurrence of 2

Tuples

• immutable and can used when ordered collection of itmes are needed
• tuples are similar to lists but immutable(cannot be modified once created)
• they are created using parentheses ()
• tuples can also contain elements of different data types
• example

  my_tuple = (1, 2, 3, "wolrd")

• common operations
  • accessing elements by index
    • my_tuple[0] returns the first element
  • tuple packing and unpacking
    • x, y = my_tuple

Dictionaries

• uesful for key-value pair storage and quick lookups
• store data in key-value pairs
• created using curly vraces {} or the dict() constructor
• 키로 사용 가능한 데이터 타입은 해시 가능한(Hashable) 데이터 타입이어야 함. 해시 가능한 타입은 불변(immutable)하고 해시 가능한 함수를 지워하는 타입
• example

  my_dict = {"name": "Alice", "age": 30, "city": "New York"}

• common operations
  • accessing values by key
    • my_dict["name"] returns "Alice"
  • adding key-value pairs
    • my_dict["email"] = "alice@exmaple.com"
  • removing key_value pairs
    • del my_dict["age"]

Sets

• for unique value stroage and set operations
  • set operations: union, intersection, complement, difference, symmetric difference, subset, superset, disjoin sets
• unordered collections of unique elements
• created using curly braces {} or the set()
• example

  my_set = {1, 2, 3, 3, 4}

• common operations
  • adding elements
    • my_set.add(5)
  • removing elements
    • my_set.remove(3)
  • set operations like union, intersection, and difference
    • my_set.union(other_set)

Strings

• sequences of characters and are used for text processing
• can be created using single, double, or triple quotes
• example

  my_string = "Hello, World!"

• common operations
  • slicing
  • concatenation
  • string methods like split(), strip(), replace()

Lists, Tuples, Dictionaries, and Sets Comprehensions

• Python provides a concise way to create these data structures using comprehensions
• comprehensions allow to create new data structures by specifying a set of expressions
• example

  squares = [x**2 for x in range(1, 6)]