Python Dictionaries and Sets: Organize Named Data and Remove Duplicates

When we start learning Python, lists are often one of the first data structures we use:

student = ["Laura", 24, "Medellín"]

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This works, but what does each position represent?

We need to remember that:

• Position 0 contains the name.
• Position 1 contains the age.
• Position 2 contains the city.

A dictionary provides a clearer alternative because every value is identified by a descriptive key.

Creating a dictionary

A dictionary stores information as key-value pairs:

student = {
    "name": "Laura",
    "age": 24,
    "city": "Medellín"
}

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Instead of asking for the value at position 0, we can ask directly for the value associated with "name":

print(student["name"])

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Output:

Laura

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A useful way to remember the difference is:

A list position tells you where a value is. A dictionary key tells you what the value means.

Updating and adding information

Python dictionaries are mutable, so their content can change after creation.

To update an existing value:

product = {
    "name": "Keyboard",
    "price": 120000
}

product["price"] = 110000

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To add a new key-value pair, use the same syntax with a key that does not exist yet:

product["available"] = True

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The resulting dictionary is:

{
    "name": "Keyboard",
    "price": 110000,
    "available": True
}

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Safely reading values with get()

Using square brackets requires the key to exist:

print(student["email"])

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If "email" is missing, Python raises a KeyError.

The get() method provides a safer alternative:

print(student.get("email"))

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It returns None when the key is missing.

You can also define a default value:

print(student.get("email", "Not registered"))

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Output:

Not registered

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To check whether a key exists, use the in operator:

if "city" in student:
    print(student["city"])

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Keys, values, and pairs

Python provides three useful dictionary methods:

course = {
    "name": "Python Basics",
    "duration": "4 weeks",
    "format": "Online"
}

print(course.keys())
print(course.values())
print(course.items())

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They provide different views of the same information:

• keys() returns the keys.
• values() returns the stored values.
• items() returns complete key-value pairs.

Looping through a dictionary

The items() method is especially useful when working with a for loop:

capitals = {
    "Colombia": "Bogotá",
    "Peru": "Lima",
    "Argentina": "Buenos Aires"
}

for country, capital in capitals.items():
    print(f"{country}: {capital}")

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Output:

Colombia: Bogotá
Peru: Lima
Argentina: Buenos Aires

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During every iteration, Python assigns the current key to country and its associated value to capital.

What is a set?

A set is a collection that stores unique values.

Consider this list:

languages = ["Python", "Rust", "Python", "JavaScript", "Rust"]

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We can remove repeated values by converting it into a set:

unique_languages = set(languages)

print(unique_languages)

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The set keeps only one occurrence of each language.

Sets are useful when you need to:

• Remove duplicate values.
• Check whether a value is present.
• Compare groups of elements.
• Work with unique categories or identifiers.

Unlike lists, sets do not support indexes or slicing.

An important detail

Empty braces create an empty dictionary:

empty_dictionary = {}

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To create an empty set, use set():

empty_set = set()

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This is a common source of confusion for Python beginners.

Which structure should you choose?

Use a list when position and order are important.

Use a dictionary when every value should have a descriptive name.

Use a set when you need unique values and repetitions do not matter.

Understanding this distinction makes programs easier to read, maintain, and extend.

The original Spanish guide includes a step-by-step explanation with additional examples:

https://tucodigocotidiano.yarumaltech.com/leer_guias/diccionarios-y-conjuntos-datos-con-nombre-y-sin-duplicados/

What was more confusing when you first learned Python: dictionaries or sets?