Dictionaries in Python

Dictionaries are one of the most powerful and commonly used data structures in Python. They store data in the form of key-value pairs, making them perfect for representing structured information like user profiles, product information, API responses, and configuration settings.

A dictionary is mutable, unordered (Python 3.7+ maintains insertion order), and highly optimized for fast lookup.

What Is a Dictionary?

A dictionary stores information in pairs, where:

• Key → A unique identifier
• Value → The information associated with that key

Dictionaries use { } curly brackets.

student = {
    "name": "Sreekanth",
    "age": 25,
    "country": "USA"
}

Dictionaries allow you to structure real-world data in a clean way.

Why Use Dictionaries?

Dictionaries are extremely useful because:

• They store information in a structured way
• Fast access using keys (O(1) time)
• Keys are easy to remember
• Values can be any data type (lists, tuples, other dictionaries)
• Data can be updated without recreating the entire structure

Creating Dictionaries

person = {"name": "John", "age": 30}

empty_dict = {}      # empty dictionary

details = dict(name="Alice", age=22)   # using dict()

Accessing Dictionary Values

You can access values by using keys inside square brackets or using the get() method.

student = {"name": "Sreekanth", "age": 25}

print(student["name"])       # Sreekanth
print(student.get("age"))    # 25

Using get() is safer because it does not throw an error if a key doesn't exist.

Modifying Dictionary Values

Dictionaries are mutable, so values can be changed easily.

student = {"name": "Sreekanth", "age": 25}

student["age"] = 26      # updating value
student["country"] = "USA"   # adding new key-value pair

print(student)

Removing Items From a Dictionary

data = {"a": 1, "b": 2, "c": 3}

data.pop("b")       # removes key 'b'
data.popitem()      # removes last item
del data["a"]       # removes key 'a'
data.clear()        # empty dictionary

Looping Through a Dictionary

You can loop through keys, values, or both.

info = {"name": "Sree", "age": 25}

for key in info:
    print(key, info[key])      # key and value

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

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

Checking if a Key Exists

product = {"id": 101, "name": "Laptop"}

if "name" in product:
    print("Key found!")

Nested Dictionaries

Dictionaries inside dictionaries are commonly used to store complex structured data (like JSON).

student = {
    "name": "Sree",
    "marks": {"math": 90, "science": 95, "english": 88}
}

print(student["marks"]["science"])   # 95

Real-World Example: JSON-like API Response

user = {
    "id": 101,
    "username": "dataplexa",
    "profile": {
        "followers": 1200,
        "following": 300
    }
}

print(user["profile"]["followers"])

Real-World Example: Product Information

product = {
    "name": "Wireless Mouse",
    "price": 799,
    "stock": 25
}

print("Product:", product["name"])
print("Price:", product["price"])

📝 Practice Exercises

1. Create a dictionary of 3 students with keys name, age, and grade.
2. Write a program to update the price of a product stored in a dictionary.
3. Check whether a key "email" exists in a dictionary.
4. Create a nested dictionary representing departments and employee counts.
5. Loop through a dictionary and print all key-value pairs in a clean format.

✅ Practice Answers

Answer 1:

student = {"name": "Ravi", "age": 20, "grade": "A"}
print(student)

Answer 2:

product = {"name": "Keyboard", "price": 1200}
product["price"] = 999
print(product)

Answer 3:

data = {"user": "Sree", "age": 25}

if "email" in data:
    print("Exists")
else:
    print("Not found")

Answer 4:

departments = {
    "IT": 10,
    "HR": 5,
    "Finance": 7
}
print(departments)

Answer 5:

info = {"name": "Sree", "country": "USA"}

for k, v in info.items():
    print(k, "=", v)