Python Dictionaries Explained: Beginner’s Complete Guide with Examples

Introduction

Python dictionaries are one of the most powerful data structures in Python. They allow you to store data in key-value pairs, making it easy to access, update, and manage information efficiently.

In this guide, we’ll explore everything a beginner needs to know about Python dictionaries, including creation, access, update, deletion, nested dictionaries, and interview questions.

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What is a Python Dictionary?

A dictionary in Python is a collection of key-value pairs.

• Keys are unique and immutable (strings, numbers, tuples).
• Values can be any data type (string, number, list, tuple, dictionary, boolean, etc.).
• Dictionaries are mutable, meaning you can change, add, or delete items.

Example:

user_info = {
    "name": "Nishtha",
    "age": 25,
    "learning": "Python"
}

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Creating a Dictionary with Multiple Data Types

user_info = {
    "key": "value",
    "name": "Nishtha",
    "subjects": ["Maths", "English", "Science"],
    "topics": ("List", "Dict", "Maps"),
    "learning": "Python",
    "age": 25,
    "is_girl": True,
    "salary": 50000.89
}
print(user_info)

• Strings for simple values.
• List for multiple items.
• Tuple for fixed items.
• Boolean, integer, float for different data types.

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Accessing Keys, Values, and Items

print('All keys:', user_info.keys())
print('All values:', user_info.values())
print('All key-value pairs:', user_info.items())

• Use keys(), values(), and items() to access dictionary elements.
• Convert to list for easier indexing: list(user_info.keys())

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Accessing Values Safely

print(user_info["name"])  # Direct access
print(user_info.get("name"))  # Safe access
print(user_info.get("phone", "Not available"))  # Returns default if key doesn't exist

• [] raises KeyError if key doesn’t exist.
• get() is safer and can return a default value.

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Adding and Updating Keys

# Add a single key
user_info["city"] = "Delhi"

# Add multiple keys
user_info.update({"country": "India", "ID": "101"})

# Update existing key
user_info.update({"country": "Sweden"})

# Add multiple keys at once
user_info.update({"Occupation": "Software Engineer", "Nick name": "Nish"})

print(user_info)

• Assignment (=) for single keys
• update() for multiple keys

Note: update() modifies the dictionary in place and returns None

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Removing Keys and Items

# Remove specific key and get its value
removed_age = user_info.pop("age")
print("Removed age:", removed_age)

# Remove the last inserted key-value pair
last_item = user_info.popitem()
print("Removed last item:", last_item)

# Delete a specific key
del user_info["salary"]
print(user_info)

# Clear all items
user_info.clear()
print("Dictionary after clear():", user_info)

• pop(key) – removes a specific key and returns its value
• popitem() – removes the last inserted key-value pair
• del key – deletes a specific key
• clear() – empties the entire dictionary

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Nested Dictionaries

A nested dictionary is a dictionary inside another dictionary.

student = {
    "name": "Nishtha Jain",
    "subjects": {
        "Physics": 99,
        "Chemistry": 98,
        "Maths": 99
    }
}

# Access nested value
print("Maths marks:", student["subjects"]["Maths"])

# Safe access
chemistry_marks = student.get("subjects", {}).get("Chemistry")
print("Chemistry marks (safe access):", chemistry_marks)

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Iterating Through a Dictionary

# Iterate through keys
for key in user_info:
    print(key)

# Iterate through values
for value in user_info.values():
    print(value)

# Iterate through key-value pairs
for key, value in user_info.items():
    print(key, ":", value)

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Key Takeaways

1. Dictionaries store data in key-value pairs.
2. Access values using [] or get().
3. Add/update keys using assignment or update().
4. Remove keys/items using pop(), popitem(), del, or clear().
5. Dictionary keys must be unique and immutable.
6. Values can be any data type, including lists, tuples, or nested dictionaries.
7. Use list() to convert keys, values, or items to lists.

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Conclusion

Python dictionaries are flexible, powerful, and beginner-friendly. They are widely used in real-world applications, from storing user profiles to configuration data.

Happy Learning !