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Loop Techniques

Nested loops are loops within loops, particularly useful when dealing with multi-dimensional data, such as a list of lists. Imagine you have a dataset representing scores from multiple games, where each game has scores for both teams.


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games_scores = [
    [24, 21],  # Game 1: Team A vs Team B
    [30, 27],  # Game 2: Team A vs Team B
    [17, 20]   # Game 3: Team A vs Team B
]

# Calculate the total score for each game
for game in games_scores:
    total_score = 0
    for score in game:
        total_score += score
    print(f"Total score for the game: {total_score}")

In this example, the outer loop iterates over each game, while the inner loop iterates over the scores within that game to calculate the total score.

List comprehensions provide a concise way to create lists, often more readable and efficient than traditional loops. You can use them to perform operations on each element of a list and generate a new list. Suppose you want to calculate the average score for each game from the games_scores dataset:


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games_scores = [
    [24, 21],
    [30, 27],
    [17, 20] 
]

average_scores = [sum(game) / len(game) for game in games_scores]
print(f"Average scores for each game: {average_scores}")

This list comprehension iterates over each game, calculates the average score, and stores the result in a new list.

You can also use nested loops within list comprehensions to perform more complex operations. For example, if you want to flatten a list of lists into a single list of scores:


python

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Complete a function filter_high_scoring_games that filters a list of game records to find all games where the total score exceeded a given threshold. Use list comprehensions to achieve this efficiently.

Inputs:

games: A list of dictionaries, each representing a game with keys such as away_score and home_score.
score_threshold: An integer representing the score threshold.

Steps:

Filter Games: Use a list comprehension to iterate over the list of games and filter out those where the combined score of away_score and home_score exceeds score_threshold.
Return Filtered List: Return the list of filtered games.

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Loop Techniques


              123456789101112
            
games_scores = [
    [24, 21],  # Game 1: Team A vs Team B
    [30, 27],  # Game 2: Team A vs Team B
    [17, 20]   # Game 3: Team A vs Team B
]

# Calculate the total score for each game
for game in games_scores:
    total_score = 0
    for score in game:
        total_score += score
    print(f"Total score for the game: {total_score}")

In this example, the outer loop iterates over each game, while the inner loop iterates over the scores within that game to calculate the total score.


              12345678
            
games_scores = [
    [24, 21],
    [30, 27],
    [17, 20] 
]

average_scores = [sum(game) / len(game) for game in games_scores]
print(f"Average scores for each game: {average_scores}")

This list comprehension iterates over each game, calculates the average score, and stores the result in a new list.

You can also use nested loops within list comprehensions to perform more complex operations. For example, if you want to flatten a list of lists into a single list of scores:


python

Opgave

Swipe to start coding

Inputs:

games: A list of dictionaries, each representing a game with keys such as away_score and home_score.
score_threshold: An integer representing the score threshold.

Steps:

Filter Games: Use a list comprehension to iterate over the list of games and filter out those where the combined score of away_score and home_score exceeds score_threshold.
Return Filtered List: Return the list of filtered games.

Løsning

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder

Var alt klart?

Tak for dine kommentarer!

Sektion 2. Kapitel 3

Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder