Python Basics: Data Structures
Master lists, tuples, sets, and dictionaries to organize and manipulate data like a pro!
1. Lists: Ordered & Mutable
A list stores ordered, changeable items (like a shopping list).
CRUD Operations
| Operation | Code Example | Result/Action |
|---|---|---|
| Create | fruits = ["apple", "banana", "cherry"] | Creates a list. |
| Read | print(fruits[1]) | Output: banana (index 1). |
| Update | fruits[0] = "avocado" | Replaces "apple" with "avocado". |
| Delete | fruits.pop(2) or del fruits[2] | Removes "cherry". |
Useful Methods:
append("mango"): Add to end.insert(1, "orange"): Insert at index.remove("banana"): Delete by value.sort(): Sort alphabetically.
Example:
groceries = ["milk", "eggs"]
groceries.append("bread") # Create
print(groceries[0]) # Read: "milk"
groceries[1] = "cheese" # Update: Replace "eggs"
groceries.remove("milk") # Delete
print(groceries) # Output: ["cheese", "bread"]
2. Tuples: Ordered & Immutable
A tuple stores ordered, unchangeable items (like coordinates).
CRUD Operations
| Operation | Code Example | Notes |
|---|---|---|
| Create | colors = ("red", "green", "blue") | Use parentheses. |
| Read | print(colors[-1]) | Output: blue (last item). |
| Update | ❌ Not allowed (immutable). | Use a list if you need changes. |
| Delete | ❌ Can’t delete items. | Delete entire tuple: del colors. |
Use Cases:
- Store constants (e.g., days of the week).
- Return multiple values from a function.
Example:
dimensions = (1920, 1080)
print(f"Width: {dimensions[0]}") # Output: Width: 1920
3. Sets: Unordered & Unique
A set stores unordered, unique items (like a math set).
CRUD Operations
| Operation | Code Example | Action |
|---|---|---|
| Create | scores = {90, 85, 90} | Duplicates auto-removed: {90, 85}. |
| Read | ❌ No indexing (unordered). | Loop to access: for s in scores. |
| Update | scores.add(95) | Add item. |
| Delete | scores.remove(85) | Remove item. |
Useful Methods:
union(),intersection(): Combine sets.discard(): Remove without errors.
Example:
student_ids = {101, 102, 103}
student_ids.add(104) # Create
student_ids.remove(101) # Delete
print(102 in student_ids) # Check existence: True
4. Dictionaries: Key-Value Pairs
A dictionary stores data as key-value pairs (like a locker system).
CRUD Operations
| Operation | Code Example | Action |
|---|---|---|
| Create | student = {"name": "Alex", "age": 12} | Use curly braces. |
| Read | print(student["name"]) | Output: Alex. |
| Update | student["age"] = 13 | Modify value. |
| Delete | del student["age"] | Remove key-value pair. |
Useful Methods:
keys(): Get all keys.values(): Get all values.get("name"): Safely retrieve values.
Example:
book = {
"title": "Python for Kids",
"author": "Jason R. Briggs",
"year": 2012
}
book["pages"] = 344 # Create new key
print(book["author"]) # Read: "Jason R. Briggs"
book["year"] = 2023 # Update
del book["pages"] # Delete
Real-World Project: To-Do List Manager
todos = []
while True:
task = input("Add a task (or 'quit'): ")
if task == "quit":
break
todos.append({"task": task, "done": False})
print("\nYour To-Do List:")
for idx, item in enumerate(todos):
status = "✓" if item["done"] else "◻"
print(f"{idx + 1}. {status} {item['task']}")
Common Mistakes
- ❌ Using
list[wrong_index]→ IndexError. - ❌ Modifying tuples → TypeError.
- ❌ Assuming set/dictionary order → Unordered!
Comparison Table
| Feature | List | Tuple | Set | Dictionary |
|---|---|---|---|---|
| Ordered | Yes | Yes | No | No (Py3.7+: insertion order preserved) |
| Mutable | Yes | No | Yes | Yes (keys are immutable) |
| Duplicates | Allowed | Allowed | No | Keys: No, Values: Yes |
Practice Quiz
Which data structure uses key-value pairs?
Answer: Dictionary.
What’s the output?
numbers = {1, 2, 2, 3}
print(numbers)
Answer: {1, 2, 3}.
Fix the error:
my_tuple = (10, 20)
my_tuple[0] = 30
Answer: Tuples are immutable. Use a list instead.
Fun Activity: Create a Word Counter
word = "mississippi"
counter = {}
for letter in word:
if letter in counter:
counter[letter] += 1
else:
counter[letter] = 1
print(counter) # Output: {'m': 1, 'i': 4, 's': 4, 'p': 2}
What’s Next?
Learn functions to organize your code into reusable blocks!
Tags:
python