Challenge: Compute Average Test Scores by School District
Understanding the average test scores by school district is a crucial step in evaluating the effectiveness of education policies. By examining how students perform across different districts, policymakers can identify areas that may require additional resources or targeted interventions. This type of analysis helps ensure that educational opportunities are equitable and that no district is left behind due to systemic disparities.
1234567891011students = [ {"district": "North", "test_score": 82}, {"district": "South", "test_score": 77}, {"district": "North", "test_score": 91}, {"district": "East", "test_score": 68}, {"district": "South", "test_score": 85}, {"district": "East", "test_score": 74}, {"district": "West", "test_score": 88}, {"district": "West", "test_score": 92}, {"district": "North", "test_score": 75}, ]
To determine the average test score for each district, you need to group students by their district and then calculate the mean score for each group. This process involves iterating through the dataset, collecting scores for each district, and then dividing the total score by the number of students in that district. Such aggregation is a common technique in data analysis, allowing you to summarize complex datasets and extract actionable insights for policy evaluation.
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Given a list of student records, each containing a district and a test score, compute the average test score for each district. Return a dictionary mapping each district to its average score.
- Initialize structures to track the total score and count of students for each district.
- Iterate through each student record and update the totals and counts for their district.
- Compute the average for each district by dividing the total score by the number of students in that district.
- Return a dictionary with districts as keys and their average scores as values.
Solución
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Understanding the average test scores by school district is a crucial step in evaluating the effectiveness of education policies. By examining how students perform across different districts, policymakers can identify areas that may require additional resources or targeted interventions. This type of analysis helps ensure that educational opportunities are equitable and that no district is left behind due to systemic disparities.
1234567891011students = [ {"district": "North", "test_score": 82}, {"district": "South", "test_score": 77}, {"district": "North", "test_score": 91}, {"district": "East", "test_score": 68}, {"district": "South", "test_score": 85}, {"district": "East", "test_score": 74}, {"district": "West", "test_score": 88}, {"district": "West", "test_score": 92}, {"district": "North", "test_score": 75}, ]
To determine the average test score for each district, you need to group students by their district and then calculate the mean score for each group. This process involves iterating through the dataset, collecting scores for each district, and then dividing the total score by the number of students in that district. Such aggregation is a common technique in data analysis, allowing you to summarize complex datasets and extract actionable insights for policy evaluation.
Swipe to start coding
Given a list of student records, each containing a district and a test score, compute the average test score for each district. Return a dictionary mapping each district to its average score.
- Initialize structures to track the total score and count of students for each district.
- Iterate through each student record and update the totals and counts for their district.
- Compute the average for each district by dividing the total score by the number of students in that district.
- Return a dictionary with districts as keys and their average scores as values.
Solución
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