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Dictionaries in Python

Hello, Python enthusiasts! Today, we’re embarking on a journey to unravel the fascinating world of dictionaries in Python. Dictionaries are a versatile collection type in Python that allow us to store and retrieve data in a unique way. Join me, DataSagar, as we explore this essential data structure.

Understanding Dictionaries

Imagine a dictionary as a real-world book filled with words and their corresponding definitions. Similarly, in Python, a dictionary is a collection of key-value pairs. These key-value pairs allow you to map each key to a specific value, creating a powerful way to organize and access data.

In a list, elements are accessed by integer indices, much like addresses in memory. In contrast, dictionaries use keys as the “addresses” to access their values. Keys are usually characters, but they can be of any immutable type, such as strings or numbers. Values, on the other hand, contain the actual data you want to store.

To create a dictionary, we use curly braces {}. Each key is followed by a colon : and its corresponding value. Pairs of key-value are separated by commas.

album_release_dates = {
    "Back in Black": 1980,
    "The Dark Side Of The Moon": 1973,
    "The Bodyguard": 1992

Here, album_release_dates is our dictionary, and it contains album titles as keys and their release years as values.

Visualizing Dictionaries

To better understand dictionaries, think of them as tables with two columns: one for keys and another for values. This visual representation helps us grasp the concept of dictionaries easily.

“Back in Black”1980
“The Dark Side Of The Moon”1973
“The Bodyguard”1992

Accessing Values

To access a value in a dictionary, use the key as if it were an index. This allows you to retrieve the corresponding value.

back_in_black_release = album_release_dates["Back in Black"]  # Retrieves the value 1980

You can access any value in the dictionary by providing its key as the argument. For instance, using the key "The Dark Side Of The Moon" returns 1973.

Modifying Dictionaries

Dictionaries are not static; you can add, modify, or remove key-value pairs. Let’s see how:

Adding an Entry

To add a new entry to a dictionary, simply assign a value to a new key.

album_release_dates["Graduation"] = 2007  # Adds a new key-value pair

Now, our dictionary contains one more entry:

    "Back in Black": 1980,
    "The Dark Side Of The Moon": 1973,
    "The Bodyguard": 1992,
    "Graduation": 2007

Deleting an Entry

To remove a key-value pair from a dictionary, use the del statement.

del album_release_dates["The Bodyguard"]  # Deletes the entry for "The Bodyguard"

The dictionary will no longer include “The Bodyguard.”

Checking for Key Existence

To verify if a key exists in a dictionary, use the in keyword.

if "Back in Black" in album_release_dates:
    print("Not found!")

This code checks if the key “Back in Black” exists in the dictionary. If it does, it prints “Found!”; otherwise, it prints “Not found!”

Retrieving Keys and Values

You can retrieve all the keys or values from a dictionary using built-in methods.

keys = album_release_dates.keys()    # Retrieves all the keys
values = album_release_dates.values()  # Retrieves all the values

keys will contain a list-like object with all the keys, while values will contain a list-like object with all the values.

Dictionaries are a vital data structure in Python, providing a versatile way to organize and access data using key-value pairs. They offer a unique approach to mapping data, making them an essential tool for any Python developer.

In this article, we’ve explored the fundamentals of dictionaries, including creating, accessing, modifying, and checking for key existence. We’ve also seen how to retrieve keys and values from dictionaries.

As you continue your Python journey, remember that dictionaries are a powerful tool in your programming arsenal. So, keep experimenting, practicing, and stay tuned for more exciting content from

Happy coding!

The author of this blog post is a technology fellow, an IT entrepreneur, and Educator in Kathmandu Nepal. With his keen interest in Data Science and Business Intelligence, he writes on random topics occasionally in the DataSagar blog.
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