Since a set is an unordered collection, you can't access its elements by index because they don't have indices. However, you can verify whether an element exists within the set using the `in` keyword.

It's especially handy to use the `in` keyword with a **for loop**. Let's check out an example.

set_1 = {"green", "red", "white", "blue", "black"}

for i in set_1:
    print(i)

set_ = {"green", "red", "white", "blue", "black"}

print("red" in set_)
print("yellow" in set_)

In this course, you'll get to know the fundamental data structures of the Python programming language. We'll explore how to utilize Python's native data structures like lists, dictionaries, tuples, and sets to tackle different challenges.

What is a list? A list is an ordered collection that can be modified. It also allows for duplicate elements.

What is a dictionary? A dictionary is an ordered collection that can be changed, but it doesn't allow duplicate entries. It consists of `key:value` pairs, which are used to optimize its structure.

What is a tuple? A tuple is an ordered collection that cannot be altered. It can have duplicate elements. While it's similar to a list, the values in a tuple can be of any type and are indexed by integers. Although not mandatory, it's common to enclose the values of a tuple in parentheses, making them easier to understand in Python.

What is a set? In Python, a `set` is an unordered collection that is both `iterable` and `mutable`, with no repeated elements. While the order of items in a set isn't fixed, it can include a variety of elements. A key benefit of using sets over lists is their highly efficient method for determining if an element exists within the set.

Python Data Structures

Accessing the Elements of a Set

Tarea

Python Data Structures

Accessing the Elements of a Set

Tarea