Dictionaries

Master Python dictionaries - key-value collections for fast lookups. Learn creation, access, modification, iteration, and advanced dictionary techniques.

Dictionaries in Python

Dictionaries are collections of key-value pairs. Since Python 3.7+, they maintain insertion order. They provide fast lookups and are one of Python’s most versatile data structures.

Dictionaries use keys to access values, unlike lists which use numeric indices.

Creating Dictionaries

Using Curly Braces

# Form 1: With curly braces {}
persona = {
    "nombre": "Juan",
    "edad": 30,
    "ciudad": "Madrid"
}

Using dict() Constructor

# Form 2: With dict()
carro = dict(marca="Toyota", modelo="Corolla", año=2020)

Empty Dictionary

vacio = {}
# or: vacio = dict()

Accessing Values

Direct Access with Brackets

print(persona["nombre"])  # Juan

# ❌ KeyError if key doesn't exist
# print(persona["apellido"])  # KeyError

Safe Access with get()

# Safe way: use get() - returns None if key doesn't exist
print(persona.get("apellido"))  # None

# Provide a default value
print(persona.get("apellido", "No disponible"))  # "No disponible"

Always use get() when you’re not sure if a key exists. It prevents KeyError exceptions.

Adding and Modifying Elements

# Add new key-value pair
persona["apellido"] = "Pérez"

# Modify existing value
persona["edad"] = 31

print(persona)
# {'nombre': 'Juan', 'edad': 31, 'ciudad': 'Madrid', 'apellido': 'Pérez'}

Removing Elements

del - Remove by Key

del persona["ciudad"]  # Removes the 'ciudad' key

Removes a key-value pair. Raises KeyError if key doesn’t exist.

pop() - Remove and Return

eliminado = persona.pop("apellido")
print(eliminado)  # Pérez

Removes a key and returns its value. Can provide a default if key doesn’t exist.

clear() - Empty Dictionary

persona.clear()  # Removes all items
print(persona)   # {}

Removes all items from the dictionary.

Checking Key Existence

if "nombre" in persona:
    print("La clave 'nombre' existe")

if "telefono" not in persona:
    print("No hay teléfono registrado")

Important Dictionary Methods

keys() - Get All Keys

estudiante = {
    "nombre": "Ana",
    "edad": 22,
    "carrera": "Ingeniería"
}

claves = estudiante.keys()
print(claves)  # dict_keys(['nombre', 'edad', 'carrera'])

values() - Get All Values

valores = estudiante.values()
print(valores)  # dict_values(['Ana', 22, 'Ingeniería'])

items() - Get Key-Value Pairs

items = estudiante.items()
print(items)
# dict_items([('nombre', 'Ana'), ('edad', 22), ('carrera', 'Ingeniería')])

Iterating Over Dictionaries

Iterate Over Keys (Default)

for clave in estudiante:
    print(clave)
# Output: nombre, edad, carrera

Iterate Over Values

for valor in estudiante.values():
    print(valor)
# Output: Ana, 22, Ingeniería

Iterate Over Key-Value Pairs

for clave, valor in estudiante.items():
    print(f"{clave}: {valor}")
# Output:
# nombre: Ana
# edad: 22
# carrera: Ingeniería

Use items() when you need both keys and values - it’s more efficient than accessing values separately.

Nested Dictionaries

Dictionaries can contain other dictionaries:

empresa = {
    "empleado1": {
        "nombre": "Carlos",
        "puesto": "Desarrollador",
        "salario": 50000
    },
    "empleado2": {
        "nombre": "María",
        "puesto": "Diseñadora",
        "salario": 45000
    }
}

# Access nested values
print(empresa["empleado1"]["nombre"])  # Carlos

Copying Dictionaries

Wrong Way (Reference)

original = {"a": 1, "b": 2}

# ❌ This doesn't copy, just creates a reference
copia_mala = original
copia_mala["c"] = 3
print(original)  # {'a': 1, 'b': 2, 'c': 3} - original modified!

Correct Ways

# ✅ Method 1: use copy()
copia_buena = original.copy()

# ✅ Method 2: use dict() constructor
copia_buena = dict(original)

Always use copy() or dict() to create independent copies of dictionaries.

Merging Dictionaries

Using the | Operator (Python 3.9+)

dict1 = {"a": 1, "b": 2}
dict2 = {"c": 3, "d": 4}

combinado = dict1 | dict2
print(combinado)  # {'a': 1, 'b': 2, 'c': 3, 'd': 4}

Using update() Method

dict1 = {"a": 1, "b": 2}
dict2 = {"c": 3, "d": 4}

# Modifies dict1 in-place
dict1.update(dict2)
print(dict1)  # {'a': 1, 'b': 2, 'c': 3, 'd': 4}

Default Values with defaultdict

Use defaultdict to automatically create default values:

from collections import defaultdict

# If you access a key that doesn't exist, creates a default value
contador = defaultdict(int)  # int() returns 0
contador["manzanas"] += 1
contador["naranjas"] += 3

print(contador)
# defaultdict(<class 'int'>, {'manzanas': 1, 'naranjas': 3})

defaultdict is perfect for counters, grouping items, or building nested structures.

Dictionary Comprehension

Create dictionaries in a compact, elegant way:

Basic Comprehension

# Create dictionary with comprehension
cuadrados = {x: x ** 2 for x in range(1, 6)}
print(cuadrados)  # {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

With Condition

# Only include even numbers
pares = {x: x ** 2 for x in range(10) if x % 2 == 0}
print(pares)  # {0: 0, 2: 4, 4: 16, 6: 36, 8: 64}

Practical Example: Student Registration

Here’s a real-world example using dictionaries:

listaEstudiantesRiwi = []

ingresarOtroEstudiante = "si"
while ingresarOtroEstudiante == "si":
    print("Nuevo estudiante")
    nombre = input("ingrese el nombre =>")
    apellido = input("ingrese el apellido =>")
    edad = input("ingrese la edad =>")
    direccion = input("ingrese la direccion =>")
    correo = input("ingrese su correo =>")

    estudiante = {
        "nombre": nombre,
        "apellido": apellido,
        "edad": edad,
        "direccion": direccion,
        "correo": correo
    }
    
    listaEstudiantesRiwi.append(estudiante)
    respuesta = input("vas a ingresar otro estudiante? =>")
    
    if respuesta != "si":
        ingresarOtroEstudiante = False

# Display all students
for estudiante in listaEstudiantesRiwi:
    print(f"""
        Nombre=> {estudiante["nombre"]}
        Apellido=> {estudiante["apellido"]}
        Edad=> {estudiante["edad"]}
        Correo=> {estudiante["correo"]}
        Direccion=> {estudiante["direccion"]}
    """)

Common Dictionary Patterns

Count Occurrences

from collections import defaultdict

palabras = ["manzana", "banana", "manzana", "cereza", "banana"]
contador = defaultdict(int)

for palabra in palabras:
    contador[palabra] += 1

print(dict(contador))  # {'manzana': 2, 'banana': 2, 'cereza': 1}

Group Items

from collections import defaultdict

estudiantes = [
    {"nombre": "Ana", "carrera": "Ingeniería"},
    {"nombre": "Luis", "carrera": "Medicina"},
    {"nombre": "María", "carrera": "Ingeniería"}
]

grupos = defaultdict(list)
for estudiante in estudiantes:
    grupos[estudiante["carrera"]].append(estudiante["nombre"])

print(dict(grupos))
# {'Ingeniería': ['Ana', 'María'], 'Medicina': ['Luis']}

Swap Keys and Values

original = {"a": 1, "b": 2, "c": 3}
invertido = {valor: clave for clave, valor in original.items()}
print(invertido)  # {1: 'a', 2: 'b', 3: 'c'}

Key Takeaways

• Dictionaries use keys for fast value lookups (O(1) average)
• Keys must be immutable (strings, numbers, tuples)
• Since Python 3.7+, dictionaries maintain insertion order
• Use get() for safe access to avoid KeyError
• items() is the best way to iterate over key-value pairs
• Dictionary comprehensions create dictionaries elegantly
• defaultdict simplifies working with missing keys

Dictionaries are ideal when you need fast lookups by key, when data has natural key-value relationships, or when you’re counting or grouping items.