Unlocking the Magic of Python Dictionaries: Your Ultimate Beginner's Guide- w9school

Master Python dictionaries effortlessly! Explore key-value wonders in this ultimate beginner's guide. Start your Python journey today.

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Python Dictionaries

Dictionary

Python dictionaries are data structures that store key-value pairs. They are also known as associative arrays or hash maps in other programming languages. Python dictionaries are mutable, unordered, and can be nested. Python dictionaries are used to store data values in key:value pairs. A Python dictionary is a collection which is ordered*, changeable and do not allow duplicates. As of Python version 3.7, dictionaries are ordered. In Python 3.6 and earlier, dictionaries are unordered.

In Python dictionaries, keys must be unique and immutable (strings, numbers, or tuples). Values can be of any data type (strings, numbers, lists, dictionaries, etc.). Python dictionaries are commonly used to store and retrieve data based on specific keys, allowing for efficient lookup operations.

In Python, dictionaries are written with curly brackets, and have keys and values:

Example

Create and print a dictionary:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
print(thisdict)

Now Try it Yourself

Python Dictionary Items

Python dictionary items are ordered, changeable, and does not allow duplicates.

Python dictionary items are presented in key:value pairs, and can be referred to by using the key name.

Example

Print the "brand" value of the dictionary:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
print(thisdict["brand"])

Now Try it Yourself

Ordered or Unordered?

As of Python version 3.7, Python dictionaries are ordered. In Python 3.6 and earlier, dictionaries are unordered.

When we say that python dictionaries are ordered, it means that the items have a defined order, and that order will not change.

Unordered means that the items does not have a defined order, you cannot refer to an item by using an index.

Changeable

Python dictionaries are changeable, meaning that we can change, add or remove items after the dictionary has been created.

Duplicates Not Allowed

Python dictionaries cannot have two items with the same key:

Example

Duplicate values will overwrite existing values:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964,
  "year": 2020
}
print(thisdict)

Now Try it Yourself

Python Dictionary Length

To determine how many items a python dictionary has, use the len() function:

Example

Print the number of items in the dictionary:

print(len(thisdict))

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Python dictionary Items - Data Types

The values in dictionary items can be of any data type:

Example

String, int, boolean, and list data types:

thisdict = {
  "brand": "Ford",
  "electric": False,
  "year": 1964,
  "colors": ["red", "white", "blue"]
}

Now Try it Yourself

type()

From Python's perspective, dictionaries are defined as objects with the data type 'dict':

<class 'dict'>

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Example

Print the data type of a dictionary:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
print(type(thisdict))

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The dict() Constructor

It is also possible to use the dict() constructor to make a dictionary.

Example

Using the dict() method to make a dictionary:

thisdict = dict(name = "John", age = 36, country = "Norway")
print(thisdict)

Now Try it Yourself

Python Collections (Arrays)

There are four collection data types in the Python programming language:

List is a collection which is ordered and changeable. Allows duplicate members.
Tuple is a collection which is ordered and unchangeable. Allows duplicate members.
Set is a collection which is unordered, unchangeable*, and unindexed. No duplicate members.
Dictionary is a collection which is ordered** and changeable. No duplicate members.

*Set items are unchangeable, but you can remove and/or add items whenever you like.

**As of Python version 3.7, dictionaries are ordered. In Python 3.6 and earlier, dictionaries are unordered.

When choosing a collection type, it is useful to understand the properties of that type. Choosing the right type for a particular data set could mean retention of meaning, and, it could mean an increase in efficiency or security.

Python - Access Dictionary Items

Accessing Items

You can access the items of a dictionary by referring to its key name, inside square brackets:

Example

Get the value of the "model" key:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
x = thisdict["model"]

Now Try it Yourself

There is also a method called get() that will give you the same result:

Example

Get the value of the "model" key:

x = thisdict.get("model")

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Get Keys

The keys() method will return a list of all the keys in the dictionary.

Example

Get a list of the keys:

x = thisdict.keys()

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The list of the keys is a view of the dictionary, meaning that any changes done to the dictionary will be reflected in the keys list.

Example

Add a new item to the original dictionary, and see that the keys list gets updated as well:

car = {
"brand": "Ford",
"model": "Mustang",
"year": 1964
}

x = car.keys()

print(x) #before the change

car["color"] = "white"

print(x) #after the change

Now Try it Yourself

Python - Change Dictionary Items

Change Values

You can change the value of a specific item by referring to its key name:

Example

Change the "year" to 2018:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict["year"] = 2018

Now Try it Yourself

Update Python Dictionary

The update() method will update the dictionary with the items from the given argument.

The argument must be a dictionary, or an iterable object with key:value pairs.

Example

Update the "year" of the car by using the update() method:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict.update({"year": 2023})

Now Try it Yourself

Python - Add Dictionary Items

Adding Items

Adding an item to the dictionary is done by using a new index key and assigning a value to it:

Example

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict["color"] = "red"
print(thisdict)

Now Try it Yourself

Update Python Dictionary

The update() method will update the dictionary with the items from a given argument. If the item does not exist, the item will be added.

The argument must be a dictionary, or an iterable object with key:value pairs.

Example

Add a color item to the dictionary by using the update() method:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict.update({"color": "red"})

Now Try it Yourself

Python - Remove Dictionary Items

Removing Items

There are several methods to remove items from a dictionary:

Example

The pop() method removes the item with the specified key name:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict.pop("model")
print(thisdict)

Now Try it Yourself

Example

The popitem() method removes the last inserted item (in versions before 3.7, a random item is removed instead):

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict.popitem()
print(thisdict)

Now Try it Yourself

Example

The del keyword removes the item with the specified key name:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
del thisdict["model"]
print(thisdict)

Now Try it Yourself

Example

The del keyword can also delete the dictionary completely:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
del thisdict
print(thisdict) #this will cause an error because "thisdict" no longer exists.

Now Try it Yourself

Example

The clear() method empties the dictionary:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
thisdict.clear()
print(thisdict)

Now Try it Yourself

Python - Loop Dictionaries

Loop Through a Python Dictionary

You can loop through a dictionary by using a for loop.

When looping through a python dictionary, the return value are the keys of the python dictionary, but there are methods to return the values as well.

Example

Print all key names in the dictionary, one by one:

for x in thisdict:
  print(x)

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Example

Print all values in the dictionary, one by one:

for x in thisdict:
  print(thisdict[x])

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Example

You can also use the values() method to return values of a dictionary:

for x in thisdict.values():
  print(x)

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Example

You can use the keys() method to return the keys of a dictionary:

for x in thisdict.keys():
  print(x)

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Example

Loop through both keys and values, by using the items() method:

for x, y in thisdict.items():
  print(x, y)

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Python - Copy Dictionaries

Copy a Python Dictionary

You cannot copy a dictionary simply by typing dict2 = dict1, because: dict2 will only be a reference to dict1, and changes made in dict1 will automatically also be made in dict2.

There are ways to make a copy, one way is to use the built-in Dictionary method copy().

Example

Make a copy of a dictionary with the copy() method:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
mydict = thisdict.copy()
print(mydict)

Now Try it Yourself

Another way to make a copy is to use the built-in function dict().

Example

Make a copy of a dictionary with the dict() function:

thisdict = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}
mydict = dict(thisdict)
print(mydict)

Now Try it Yourself

Python - Nested Dictionaries

Nested Python Dictionaries

A dictionary can contain dictionaries, this is called nested dictionaries.

Example

Create a dictionary that contain three dictionaries:

myfamily = {
  "child1" : {
    "name" : "Emil",
    "year" : 2004
  },
  "child2" : {
    "name" : "Tobias",
    "year" : 2007
  },
  "child3" : {
    "name" : "Linus",
    "year" : 2011
  }
}

Now Try it Yourself

Or, if you want to add three dictionaries into a new dictionary:

Example

Create three python dictionaries, then create one python dictionary that will contain the other three python dictionaries:

child1 = {
  "name" : "Emil",
  "year" : 2004
}
child2 = {
  "name" : "Tobias",
  "year" : 2007
}
child3 = {
  "name" : "Linus",
  "year" : 2011
}

myfamily = {
  "child1" : child1,
  "child2" : child2,
  "child3" : child3
}

Now Try it Yourself

Access Items in Nested Python Dictionaries

To access items from a nested dictionary, you use the name of the dictionaries, starting with the outer dictionary:

Example

Print the name of child 2:

print(myfamily["child2"]["name"])

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Python Dictionary Methods

Python has a set of built-in methods that you can use on dictionaries.

Method	Description
clear()	Removes all the elements from the dictionary
copy()	Returns a copy of the dictionary
fromkeys()	Returns a dictionary with the specified keys and value
get()	Returns the value of the specified key
items()	Returns a list containing a tuple for each key value pair
keys()	Returns a list containing the dictionary's keys
pop()	Removes the element with the specified key
popitem()	Removes the last inserted key-value pair
setdefault()	Returns the value of the specified key. If the key does not exist: insert the key, with the specified value
update()	Updates the dictionary with the specified key-value pairs
values()	Returns a list of all the values in the dictionary

Benefits of using Python-Dictionaries

Python dictionaries offer several benefits, making them a versatile and powerful data structure.

Here are some of the key benefits of using Python dictionaries:

1. Efficient Data Retrieval: Dictionaries provide a fast and efficient way to retrieve values based on their keys.

Instead of searching through the entire data structure, dictionaries use a hash function to directly locate the value associated with a given key.

This makes dictionary lookups very efficient, even for large datasets.

2. Flexible Key-Value Mapping: Dictionaries allow you to map keys to corresponding values, enabling you to organize and access data in a meaningful way.

This flexibility is particularly useful when dealing with complex data structures or when you need to associate specific information with unique identifiers.

3. Dynamic and Mutable: Dictionaries are mutable, meaning you can modify, add, or remove key-value pairs after the dictionary is created.

This dynamic nature allows you to update your data as needed, making dictionaries suitable for scenarios where data changes frequently.

4. Versatile Data Types: Python dictionaries can store values of any data type, including numbers, strings, lists, tuples, and even other dictionaries.

This versatility allows you to represent complex relationships and structures within a single data structure.

5. No Fixed Order: Dictionaries in Python are unordered, which means the order of elements is not guaranteed.

This characteristic is beneficial when you don't need to rely on the sequence of items and prefer faster lookup times over maintaining a specific order.

6. Fast Membership Testing: Checking for the existence of a key in a dictionary is very efficient.

Python uses hash tables internally for dictionaries, making membership testing (e.g., using the `in` operator) faster compared to other data structures,

especially as the size of the dictionary grows.

7. Efficient Key-Value Manipulation: Python dictionaries provide built-in methods and operations to manipulate key-value pairs.

You can easily add new key-value pairs, update existing values, remove items, iterate over keys or values, and

perform various operations to manage and transform dictionary data efficiently.

Overall, Python dictionaries offer a powerful combination of efficiency, flexibility, and versatility, making them a go-to choice for organizing and accessing data in Python programs.