A dictionary is a built-in Python data structure used to store key-value pairs. Dictionaries are:

• Unordered (before Python 3.7), Ordered (from Python 3.7+)
• Mutable (modifiable)
• Keys must be unique and immutable (strings, numbers, tuples)
• Values can be any data type

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1. Creating a Dictionary

Dictionaries are defined using curly braces {}, with key-value pairs separated by colons :.

Example: Creating Dictionaries

# Empty dictionary
empty_dict = {}

# Dictionary with data
person = {
    "name": "Alice",
    "age": 25,
    "job": "Engineer"
}

# Dictionary with mixed data types
mixed_dict = {
    1: "one",
    "two": 2,
    (3, 4): "tuple key"
}

print(person)
print(mixed_dict)

Output:

{'name': 'Alice', 'age': 25, 'job': 'Engineer'}
{1: 'one', 'two': 2, (3, 4): 'tuple key'}

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2. Accessing Dictionary Elements

Values are accessed using keys (not indexes like lists or tuples).

Example: Accessing Values

person = {"name": "Alice", "age": 25, "job": "Engineer"}

print(person["name"])  # Alice
print(person.get("age"))  # 25

Using .get() to Avoid Errors

print(person.get("salary"))  # Returns None instead of an error

Output:

None

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3. Modifying a Dictionary

Dictionaries are mutable, allowing you to update, add, or remove elements.

(a) Changing Values

person["age"] = 26
print(person)

Output:

{'name': 'Alice', 'age': 26, 'job': 'Engineer'}

(b) Adding New Key-Value Pairs

person["city"] = "New York"
print(person)

Output:

{'name': 'Alice', 'age': 26, 'job': 'Engineer', 'city': 'New York'}

(c) Removing Elements

del person["job"]  # Delete a specific key
print(person)

removed_value = person.pop("city")  # Remove and return value
print(removed_value)

person.clear()  # Remove all items
print(person)

Output:

{'name': 'Alice', 'age': 26}
New York
{}

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4. Looping Through a Dictionary

Dictionaries support different ways of looping.

(a) Looping Through Keys

person = {"name": "Alice", "age": 25, "job": "Engineer"}

for key in person:
    print(key)  # Prints keys

Output:

name
age
job

(b) Looping Through Values

for value in person.values():
    print(value)

Output:

Alice
25
Engineer

(c) Looping Through Key-Value Pairs

for key, value in person.items():
    print(key, ":", value)

Output:

name : Alice
age : 25
job : Engineer

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5. Dictionary Methods

Method	Description
keys()	Returns all keys
values()	Returns all values
items()	Returns key-value pairs
get(key)	Gets the value for a key
pop(key)	Removes key and returns value
update(dict)	Updates dictionary with another dictionary
clear()	Removes all elements

Example: Using Dictionary Methods

person = {"name": "Alice", "age": 25}

print(person.keys())   # dict_keys(['name', 'age'])
print(person.values()) # dict_values(['Alice', 25])
print(person.items())  # dict_items([('name', 'Alice'), ('age', 25)])

person.update({"age": 26, "city": "New York"})
print(person)  # {'name': 'Alice', 'age': 26, 'city': 'New York'}

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6. Checking if a Key Exists

if "age" in person:
    print("Age key exists!")

Output:

Age key exists!

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7. Nested Dictionaries

A dictionary can contain another dictionary.

Example: Nested Dictionary

students = {
    "Alice": {"age": 25, "grade": "A"},
    "Bob": {"age": 24, "grade": "B"}
}

print(students["Alice"]["grade"])  # A

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8. Dictionary Comprehensions

Similar to list comprehensions, dictionary comprehensions create dictionaries in a compact way.

Example: Creating a Dictionary Using Comprehension

squares = {x: x**2 for x in range(1, 6)}
print(squares)

Output:

{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

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9. Merging Two Dictionaries

From Python 3.9+, dictionaries can be merged using |.

Example: Merging Dictionaries

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

merged_dict = dict1 | dict2
print(merged_dict)

Output:

{'a': 1, 'b': 2, 'c': 3, 'd': 4}

For older Python versions:

pythonCopyEditdict1.update(dict2)
print(dict1)

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10. Copying a Dictionary

To avoid modifying the original dictionary, use copy().

original = {"name": "Alice", "age": 25}
copy_dict = original.copy()
copy_dict["age"] = 26

print(original)  # {'name': 'Alice', 'age': 25}
print(copy_dict) # {'name': 'Alice', 'age': 26}

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11. Removing Duplicates from a Dictionary

Using dictionary comprehension:

data = {"a": 1, "b": 2, "c": 1, "d": 3}
unique_values = {k: v for k, v in data.items() if list(data.values()).count(v) == 1}
print(unique_values)

Output:

{'b': 2, 'd': 3}

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12. When to Use a Dictionary?

Use dictionaries when:

• You need key-value pairs (e.g., storing user data).
• You want fast lookups (dictionaries are optimized for this).
• You need unordered but structured data.

Avoid dictionaries when:

• Order matters and you want sequential access (use lists).
• Keys may change frequently (keys must be immutable).