Python Data Structures: Lists, Tuples, and Sets

Overview

• Lists: Ordered collections of values.
• Tuples: Immutable ordered collections.
• Sets: Unordered collections of unique values.

Lists

Creating Lists

• Use square brackets [] to define a list.
• Example:

  courses = ["History", "Math", "Physics", "Comp Sci"]
  

Common Operations

• Length: Use len() to find the number of items in a list.

  len(courses)  # Returns 4
  

• Accessing Items: Use zero-based indexing.

  courses[0]  # Returns "History"
  courses[3]  # Returns "Comp Sci"
  

• Negative Indexing: Access items from the end of the list.

  courses[-1]  # Returns "Comp Sci"
  

Slicing Lists

• Access a range of values.

  courses[0:2]  # Returns ["History", "Math"]
  courses[2:]   # Returns ["Physics", "Comp Sci"]
  

Modifying Lists

• Append: Add an item to the end of the list.

  courses.append("Art")
  

• Insert: Add an item at a specific index.

  courses.insert(0, "Art")  # Inserts "Art" at index 0
  

• Extend: Add multiple items from another list.

  courses.extend(["Art", "Education"])
  

• Remove: Remove an item by value.

  courses.remove("Math")
  

• Pop: Remove an item by index (default is the last item).

  popped_course = courses.pop()
  

Sorting and Reversing Lists

• Reverse: Reverse the order of items.

  courses.reverse()
  

• Sort: Sort items in ascending order.

  courses.sort()
  

• Sorted Function: Returns a sorted list without modifying the original.

  sorted_courses = sorted(courses)
  

Built-in Functions

• Min/Max/Sum: Get minimum, maximum, or sum of a list.

  min(numbers), max(numbers), sum(numbers)
  

Membership Testing

• Check if an item exists in a list.

  "Art" in courses
  

Looping Through Lists

• Use for loops to iterate through a list.

  for item in courses:
      print(item)
  

• Enumerate: Get indexes along with values.

  for index, course in enumerate(courses):
      print(index, course)
  

Joining and Splitting Lists

• Join list items into a string.

  course_string = ', '.join(courses)
  

• Split a string back into a list.

  new_list = course_string.split(', ')
  

Tuples

• Definition: Similar to lists but immutable.
• Creation: Use parentheses () instead of square brackets.

  courses_tuple = ("History", "Math", "Physics")
  

• Modification: Cannot change values, append, or remove items.
• Use Case: For collections of values that should not change.

Sets

• Definition: Unordered collection of unique items.
• Creation: Use curly braces {} or set() function.

  courses_set = {"History", "Math", "Physics"}
  

• Membership Testing: Check if an item exists, faster than lists.

  "Math" in courses_set
  

• Operations:
  • Union: Combine two sets.
  • Intersection: Common items in both sets.
  • Difference: Items in one set but not the other.

Creating Empty Data Structures

• Empty List: [] or list().
• Empty Tuple: () or tuple().
• Empty Set: set() (not {} as it creates an empty dictionary).

Conclusion

• Understanding lists, tuples, and sets is crucial for managing data in Python. Questions can be left in the comments.