Python Coding Day 18 | Understanding Python Dictionaries and Nesting (Beginner-Friendly Guide)

📘 Understanding Python Dictionaries and Nesting (Beginner-Friendly Guide)

Watch the lesson tutorial  🔻

Python dictionaries are one of the most powerful data structures in Python. They allow you to store information in key–value pairs, making your programs easy to read and manage.

In this article, we’ll walk through:

• What dictionaries are

• How to retrieve, add, and edit items

• How to loop through dictionaries

• What nesting means (lists inside dictionaries, dictionaries inside lists, etc.)

• Examples explained clearly and simply

🔥 What Is a Dictionary in Python?

A Python dictionary stores data as key–value pairs, like a real dictionary where you search a word (key) to find its meaning (value).

Python

programming_dictionary = {
  "Bug": "An error in a program that prevents the program from running as expected.", 
  "Function": "A piece of code that you can easily call over and over again.",
}

✔ Explanation:

• "Bug" is a key

• "An error in a program..." is the value

• Dictionaries use { } curly brackets.

🔍 Retrieving Items From a Dictionary

Python

print(programming_dictionary["Function"])

✔ When you use a key inside square brackets, Python returns the matching value.

➕ Adding New Items

Python

programming_dictionary["Loop"] = "The action of doing something over and over again."

✔ This adds a new key–value pair to the dictionary.

🧹 Creating an Empty Dictionary

Python

empty_dictionary = {}

✔ Useful when you want to start fresh and add data later.

✏ Editing an Existing Key

Python

programming_dictionary["Bug"] = "A moth in your computer."

✔ This updates the value linked to the key "Bug".

🔄 Looping Through a Dictionary

Python

for key in programming_dictionary:
  print(key)
  print(programming_dictionary[key])

✔ Explanation:

• The loop runs through each key in the dictionary.

• First it prints the key.

• Then it prints the value using programming_dictionary[key].

🧩 Understanding Nesting in Python

Python allows us to combine data structures inside each other.

This is called Nesting.

Let’s look at the examples one by one.

1️⃣ Nesting a Dictionary in a Dictionary

Python

capitals = {
  "France": "Paris",
  "Germany": "Berlin",
}

✔ A simple dictionary with countries as keys and capitals as values.

2️⃣ Nesting a List Inside a Dictionary

Python

travel_log = {
  "France": ["Paris", "Lille", "Dijon"],
  "Germany": ["Berlin", "Hamburg", "Stuttgart"],
}

✔ Explanation:

• "France" → key

• ["Paris", "Lille", "Dijon"] → list of cities

• Useful for storing multiple pieces of information under one key.

3️⃣ Nesting a Dictionary Inside a Dictionary

Python

travel_log = {
  "France": {"cities_visited": ["Paris", "Lille", "Dijon"], "total_visits": 12},
  "Germany": {"cities_visited": ["Berlin", "Hamburg", "Stuttgart"], "total_visits": 5},
}

✔ Explanation:

Each country contains:

• a list (cities_visited)

• a number (total_visits)

This structure is detailed and perfect for real data storage.

4️⃣ Nesting Dictionaries Inside a List

Python

travel_log = [
  {
    "country": "France", 
    "cities_visited": ["Paris", "Lille", "Dijon"], 
    "total_visits": 12,
  },
  {
    "country": "Germany",
    "cities_visited": ["Berlin", "Hamburg", "Stuttgart"],
    "total_visits": 5,
  },
]

✔ Explanation:

• Each { ... } block is a dictionary.

• All dictionaries are stored inside a list.

• This format is common in APIs, JSON data, and real-world applications.

🎯 Final Summary

Python dictionaries allow you to:

• Store data in key–value format

• Access items quickly

• Add, remove, and update values

• Loop through keys and values

• Combine lists and dictionaries using nesting

These techniques are essential for building real-world applications like:

• ✔ data processing

• ✔ storing user information

• ✔ working with APIs

• ✔ organizing large datasets

Run Today's Lesson Codes on Colabs (Click Here)

- by Chirana Nimnaka