Topic 2: Tuples and Sets

Python for All: Discover, Learn, and Master Lesson 4: Data Structures – Introduction Topic 2: Tuples and Sets

Tuples

1. Introduction

A tuple is an ordered, immutable collection of elements. Its immutability ensures that, once created, the elements within a tuple cannot be altered.

2. Creating Tuples

Tuples are created using parentheses () and separating items with commas.

python

colors = ("red", "blue", "green")

A tuple with a single item has a trailing comma to differentiate it from a regular value.

python

single_element_tuple = ("red",)

3. Accessing Elements

Like lists, elements in a tuple can be accessed by their index.

python

print(colors[0])  # Outputs: red

4. Tuple Operations

Concatenation: You can concatenate tuples.

python

more_colors = colors + ("yellow", "pink")
print(more_colors)  # Outputs: ('red', 'blue', 'green', 'yellow', 'pink')

Repetition: Tuples can be repeated.

python

doubled_colors = colors * 2
print(doubled_colors)  # Outputs: ('red', 'blue', 'green', 'red', 'blue', 'green')

Membership: Check if an item exists in a tuple.

python

print("red" in colors)  # Outputs: True

Length: Find the number of items in a tuple.

python

print(len(colors))  # Outputs: 3

5. Tuple Methods

Since tuples are immutable, they have fewer built-in methods compared to lists.

index(): Return the index of the first occurrence of a value.

python

position = colors.index("green")
print(position)  # Outputs: 2

count(): Count the occurrences of a value in the tuple.

python

num_red = colors.count("red")
print(num_red)  # Outputs: 1

Sets

1. Introduction

A set is an unordered collection of unique items. Sets are used for membership testing, removing duplicates from sequences, and mathematical operations like unions, intersections, and differences.

2. Creating Sets

Sets are created using curly braces {}.

python

fruits = {"apple", "banana", "cherry"}

Using the set() function, you can create sets from other data types:

python

list_fruits = ["apple", "banana", "cherry", "apple"]
fruits_set = set(list_fruits)
print(fruits_set)  # Outputs: {'cherry', 'banana', 'apple'}

3. Set Operations

Add: Add an item to the set.

python

fruits.add("grape")
print(fruits)  # Outputs: {'grape', 'cherry', 'banana', 'apple'}

Remove: Remove an item from the set. Raises an error if the element doesn’t exist.

python

fruits.remove("banana")

Discard: Remove an item from the set. Doesn’t raise an error if the element doesn’t exist.

python

fruits.discard("banana")

Pop: Remove and return a random element from the set.

python

random_fruit = fruits.pop()

Clear: Remove all elements from the set.

python

fruits.clear()

Union: Combine two sets.

python

fruits = {"apple", "banana", "cherry"}
berries = {"strawberry", "blueberry"}
all_fruits = fruits.union(berries)

Intersection: Find common items between two sets.

python

common_fruits = fruits.intersection(berries)

Difference: Get items that exist only in the first set and not in the second.

python

exclusive_fruits = fruits.difference(berries)

4. Conclusion

Both tuples and sets are fundamental data structures in Python. Tuples offer immutable, ordered collections, making them ideal for fixed sequences of items. In contrast, sets provide powerful tools for handling unique items and conducting set-theoretic operations, making them invaluable for various computational tasks. Familiarity with both structures broadens your capabilities as a Python programmer.

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