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.
123456789101112games_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:
12345678games_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:
all_scores = [score for game in games_scores for score in game]
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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 asaway_score
andhome_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
andhome_score
exceedsscore_threshold
. - Return Filtered List: Return the list of filtered games.
Solution
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Loop Techniques
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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.
123456789101112games_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:
12345678games_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:
all_scores = [score for game in games_scores for score in game]
Swipe to start coding
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 asaway_score
andhome_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
andhome_score
exceedsscore_threshold
. - Return Filtered List: Return the list of filtered games.
Solution
Thanks for your feedback!
Awesome!
Completion rate improved to 10single