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Python Data Structures
course content

Course Content

Python Data Structures

Python Data Structures

1. List
Creating a ListNested ListChallenge: Create a ListList IndexingList LengthLists are MutableAppend() MethodInsert() MethodDeleting ElementsRemoving ElementsList Comprehensions
2. Dictionary
Creating a DictionaryChallenge: Craft the DictionaryExtraction of InformationAdding ItemsDel KeywordPop() MethodPopitem() MethodClear() MethodDictionary Comprehensions
3. Tuple
Creating a Tuple Accessing Elements of a TupleConcatenation of Tuples Delete a Tuple Update a TupleAdding Items Challenge: Concatenate Tuples
4. Set
Creating a SetAdd() MethodUpdate() MethodAccessing the Elements of a SetRemove() and Discard() MethodsClear() Method
5. For deleting
Test grid chapterTest 2

bookDictionary Comprehensions

Dictionary comprehensions offer a succinct way to create dictionaries in Python. They are built in the same way as list comprehensions but with some exceptions.

Basic Dictionary Comprehension

At its heart, a basic dictionary comprehension lets you construct a new dictionary by applying an expression to each key-value pair in an iterable variable.

Syntax:

What it does: For every item in iterable, it evaluates both key_expression and value_expression to create a new key-value pair in the dictionary.

Note

In contrast to lists, dictionaries require curly braces instead of square brackets. Additionally, in a dictionary comprehension, you specify both a key and a value separated by a colon, as in key:value, rather than just a single value.

Here, for each number x in the range 0 through 4, we create a key-value pair where the key is the number and the value is its square.

It's equivalent to:


              
123456

            
squared_dict = {}

for x in (0, 1, 2, 3, 4):
    squared_dict[x] = x * x

print(squared_dict)
copy

Dictionary Comprehension with Condition

This variation allows you to introduce a condition to your dictionary comprehension, functioning as a filter. Only items that meet the condition are processed and added to the new dictionary.

Syntax: {key_expression: value_expression for item in iterable if condition}

What it does: For every item in iterable, if the condition is True, it evaluates both key_expression and value_expression and adds the resulting key-value pair to the dictionary.

In this instance, we only construct key-value pairs for numbers from the range 0 through 5 if they're even. The value represents the square of the key.

This example is equivalent to:


              
1234567

            
even_dict = {}

for x in (0, 1, 2, 3, 4):
    if x % 2 == 0:
        even_dict[x] = x * x

print(even_dict)
copy

Dictionary comprehensions, like list comprehentions, are a more efficient and "Pythonic" way to craft dictionaries, often proving quicker in execution when compared to traditional loop methods.

Task

Given a dictionary with cities and their respective populations, use dictionary comprehension to create a new dictionary that only contains cities with populations greater than a specified number.

Note

The expression for city, population in cities_popul.items() iterates over each key-value pair from the dictionary. During each loop, city holds the name of a city from the dictionary and population captures its associated population value.

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Section 2. Chapter 9
toggle bottom row

bookDictionary Comprehensions

Dictionary comprehensions offer a succinct way to create dictionaries in Python. They are built in the same way as list comprehensions but with some exceptions.

Basic Dictionary Comprehension

At its heart, a basic dictionary comprehension lets you construct a new dictionary by applying an expression to each key-value pair in an iterable variable.

Syntax:

What it does: For every item in iterable, it evaluates both key_expression and value_expression to create a new key-value pair in the dictionary.

Note

In contrast to lists, dictionaries require curly braces instead of square brackets. Additionally, in a dictionary comprehension, you specify both a key and a value separated by a colon, as in key:value, rather than just a single value.

Here, for each number x in the range 0 through 4, we create a key-value pair where the key is the number and the value is its square.

It's equivalent to:


              
123456

            
squared_dict = {}

for x in (0, 1, 2, 3, 4):
    squared_dict[x] = x * x

print(squared_dict)
copy

Dictionary Comprehension with Condition

This variation allows you to introduce a condition to your dictionary comprehension, functioning as a filter. Only items that meet the condition are processed and added to the new dictionary.

Syntax: {key_expression: value_expression for item in iterable if condition}

What it does: For every item in iterable, if the condition is True, it evaluates both key_expression and value_expression and adds the resulting key-value pair to the dictionary.

In this instance, we only construct key-value pairs for numbers from the range 0 through 5 if they're even. The value represents the square of the key.

This example is equivalent to:


              
1234567

            
even_dict = {}

for x in (0, 1, 2, 3, 4):
    if x % 2 == 0:
        even_dict[x] = x * x

print(even_dict)
copy

Dictionary comprehensions, like list comprehentions, are a more efficient and "Pythonic" way to craft dictionaries, often proving quicker in execution when compared to traditional loop methods.

Task

Given a dictionary with cities and their respective populations, use dictionary comprehension to create a new dictionary that only contains cities with populations greater than a specified number.

Note

The expression for city, population in cities_popul.items() iterates over each key-value pair from the dictionary. During each loop, city holds the name of a city from the dictionary and population captures its associated population value.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 9
toggle bottom row

bookDictionary Comprehensions

Dictionary comprehensions offer a succinct way to create dictionaries in Python. They are built in the same way as list comprehensions but with some exceptions.

Basic Dictionary Comprehension

At its heart, a basic dictionary comprehension lets you construct a new dictionary by applying an expression to each key-value pair in an iterable variable.

Syntax:

What it does: For every item in iterable, it evaluates both key_expression and value_expression to create a new key-value pair in the dictionary.

Note

In contrast to lists, dictionaries require curly braces instead of square brackets. Additionally, in a dictionary comprehension, you specify both a key and a value separated by a colon, as in key:value, rather than just a single value.

Here, for each number x in the range 0 through 4, we create a key-value pair where the key is the number and the value is its square.

It's equivalent to:


              
123456

            
squared_dict = {}

for x in (0, 1, 2, 3, 4):
    squared_dict[x] = x * x

print(squared_dict)
copy

Dictionary Comprehension with Condition

This variation allows you to introduce a condition to your dictionary comprehension, functioning as a filter. Only items that meet the condition are processed and added to the new dictionary.

Syntax: {key_expression: value_expression for item in iterable if condition}

What it does: For every item in iterable, if the condition is True, it evaluates both key_expression and value_expression and adds the resulting key-value pair to the dictionary.

In this instance, we only construct key-value pairs for numbers from the range 0 through 5 if they're even. The value represents the square of the key.

This example is equivalent to:


              
1234567

            
even_dict = {}

for x in (0, 1, 2, 3, 4):
    if x % 2 == 0:
        even_dict[x] = x * x

print(even_dict)
copy

Dictionary comprehensions, like list comprehentions, are a more efficient and "Pythonic" way to craft dictionaries, often proving quicker in execution when compared to traditional loop methods.

Task

Given a dictionary with cities and their respective populations, use dictionary comprehension to create a new dictionary that only contains cities with populations greater than a specified number.

Note

The expression for city, population in cities_popul.items() iterates over each key-value pair from the dictionary. During each loop, city holds the name of a city from the dictionary and population captures its associated population value.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Dictionary comprehensions offer a succinct way to create dictionaries in Python. They are built in the same way as list comprehensions but with some exceptions.

Basic Dictionary Comprehension

At its heart, a basic dictionary comprehension lets you construct a new dictionary by applying an expression to each key-value pair in an iterable variable.

Syntax:

What it does: For every item in iterable, it evaluates both key_expression and value_expression to create a new key-value pair in the dictionary.

Note

In contrast to lists, dictionaries require curly braces instead of square brackets. Additionally, in a dictionary comprehension, you specify both a key and a value separated by a colon, as in key:value, rather than just a single value.

Here, for each number x in the range 0 through 4, we create a key-value pair where the key is the number and the value is its square.

It's equivalent to:


              
123456

            
squared_dict = {}

for x in (0, 1, 2, 3, 4):
    squared_dict[x] = x * x

print(squared_dict)
copy

Dictionary Comprehension with Condition

This variation allows you to introduce a condition to your dictionary comprehension, functioning as a filter. Only items that meet the condition are processed and added to the new dictionary.

Syntax: {key_expression: value_expression for item in iterable if condition}

What it does: For every item in iterable, if the condition is True, it evaluates both key_expression and value_expression and adds the resulting key-value pair to the dictionary.

In this instance, we only construct key-value pairs for numbers from the range 0 through 5 if they're even. The value represents the square of the key.

This example is equivalent to:


              
1234567

            
even_dict = {}

for x in (0, 1, 2, 3, 4):
    if x % 2 == 0:
        even_dict[x] = x * x

print(even_dict)
copy

Dictionary comprehensions, like list comprehentions, are a more efficient and "Pythonic" way to craft dictionaries, often proving quicker in execution when compared to traditional loop methods.

Task

Given a dictionary with cities and their respective populations, use dictionary comprehension to create a new dictionary that only contains cities with populations greater than a specified number.

Note

The expression for city, population in cities_popul.items() iterates over each key-value pair from the dictionary. During each loop, city holds the name of a city from the dictionary and population captures its associated population value.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 9
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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