Bucket Test Scores
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Let’s say you’re given a dataframe of standardized test scores from high schoolers from grades 9 to 12 called df_grades.
Given the dataset, write code function in Pandas called bucket_test_scores to return the cumulative percentage of students that received scores within the buckets of <50, <75, <90, <100.
Example:
Input:
print(df_grades)
| user_id | grade | test score |
|---|---|---|
| 1 | 10 | 85 |
| 2 | 10 | 60 |
| 3 | 11 | 90 |
| 4 | 10 | 30 |
| 5 | 11 | 99 |
Output:
def bucket_test_scores(df_grades) ->
| grade | test score | percentage |
|---|---|---|
| 10 | <50 | 33% |
| 10 | <75 | 66% |
| 10 | <90 | 100% |
| 10 | <100 | 100% |
| 11 | <50 | 0% |
| 11 | <75 | 0% |
| 11 | <90 | 50% |
| 11 | <100 | 100% |
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