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Lære List Comprehansions with Conditions | List and Dictionary Comprehensions
Python Loops Tutorial
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Python Loops Tutorial

Python Loops Tutorial

1. The For Loop
2. The while Loop
3. Nested Loops
4. List and Dictionary Comprehensions

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List Comprehansions with Conditions

List comprehensions allow you to filter and process elements efficiently. The syntax:

python

This syntax helps you create a new list by including only elements that meet a specified condition.

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travel_wishlist = [ ['Paris', 'France', 2000], ['Tokyo', 'Japan', 3000], ['New York', 'USA', 2500], ['Kyoto', 'Japan', 1500], ['Sydney', 'Australia', 4000] ] japanese_cities = [] for city in travel_wishlist: if city[1] == 'Japan': japanese_cities.append(city[0]) print(japanese_cities) # Output: ['Tokyo', 'Kyoto']
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This code uses a for loop and an if condition to iterate through travel_wishlist and check if the country is "Japan". If the condition is true, the city name is added to japanese_cities.

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travel_wishlist = [ ['Paris', 'France', 2000], ['Tokyo', 'Japan', 3000], ['New York', 'USA', 2500], ['Kyoto', 'Japan', 1500], ['Sydney', 'Australia', 4000] ] japanese_cities = [city[0] for city in travel_wishlist if city[1] == 'Japan'] print(japanese_cities) # Output: ['Tokyo', 'Kyoto']
copy

This example achieves the same result as the previous one but in a more concise way. The list comprehension extracts city names where the country is "Japan" in a single line of code.

Oppgave

Swipe to start coding

You are managing a travel_wishlist, where each destination includes details such as the city name and estimated cost. Your goal is to create a filtered list of cities based on budget constraints.

  • Extract city names from travel_wishlist.
  • Include only cities where the estimated cost is less than $2500.
  • Use a list comprehension to achieve this efficiently.
  • Store the filtered city names in the affordable_cities list.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 4. Kapittel 2
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book
List Comprehansions with Conditions

List comprehensions allow you to filter and process elements efficiently. The syntax:

python

This syntax helps you create a new list by including only elements that meet a specified condition.

1234567891011121314
travel_wishlist = [ ['Paris', 'France', 2000], ['Tokyo', 'Japan', 3000], ['New York', 'USA', 2500], ['Kyoto', 'Japan', 1500], ['Sydney', 'Australia', 4000] ] japanese_cities = [] for city in travel_wishlist: if city[1] == 'Japan': japanese_cities.append(city[0]) print(japanese_cities) # Output: ['Tokyo', 'Kyoto']
copy

This code uses a for loop and an if condition to iterate through travel_wishlist and check if the country is "Japan". If the condition is true, the city name is added to japanese_cities.

12345678910
travel_wishlist = [ ['Paris', 'France', 2000], ['Tokyo', 'Japan', 3000], ['New York', 'USA', 2500], ['Kyoto', 'Japan', 1500], ['Sydney', 'Australia', 4000] ] japanese_cities = [city[0] for city in travel_wishlist if city[1] == 'Japan'] print(japanese_cities) # Output: ['Tokyo', 'Kyoto']
copy

This example achieves the same result as the previous one but in a more concise way. The list comprehension extracts city names where the country is "Japan" in a single line of code.

Oppgave

Swipe to start coding

You are managing a travel_wishlist, where each destination includes details such as the city name and estimated cost. Your goal is to create a filtered list of cities based on budget constraints.

  • Extract city names from travel_wishlist.
  • Include only cities where the estimated cost is less than $2500.
  • Use a list comprehension to achieve this efficiently.
  • Store the filtered city names in the affordable_cities list.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 4. Kapittel 2
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Vi beklager at noe gikk galt. Hva skjedde?
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