Low Approval Problem Audit

Easy

A curriculum analytics team collects community reactions for each coding problem and wants to identify low-approval items that may require editorial revision. Table: problem_feedback problem_id: unique identifier for a problem likes: number of positive reactions dislikes: number of negative reactions Definition: approval_rate = likes / (likes + dislikes) A problem is considered low-approval when approval_rate is strictly less than 60%. If likes + dislikes = 0, the approval rate is undefined; ignore that problem for this report. Task: Return the IDs of all low-approval problems. Output requirements: Return exactly one column: problem_id Sort by problem_id in ascending order Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

problem_feedback:
| problem_id | likes | dislikes |
|------------|-------|----------|
| 6          | 1290  | 425      |
| 11         | 2677  | 8659     |
| 1          | 4446  | 2760     |
| 7          | 8569  | 6086     |
| 13         | 2050  | 4164     |
| 10         | 9002  | 7446     |

Output

[
  {"problem_id":7},
  {"problem_id":10},
  {"problem_id":11},
  {"problem_id":13}
]

Explanation

Problems 7, 10, 11, and 13 have approval rates below 60%. Problems 1 and 6 are at or above 60%, so they are excluded.

Example 2

Input

problem_feedback:
| problem_id | likes | dislikes |
|------------|-------|----------|
| 100        | 3     | 2        |
| 101        | 6     | 4        |
| 102        | 59    | 41       |
| 103        | 599   | 401      |

Output

[
  {"problem_id":100},
  {"problem_id":102},
  {"problem_id":103}
]

Explanation

Problem 101 is exactly 60%, so it is not low-approval. The others are strictly below 60%.

Example 3

Input

problem_feedback:
| problem_id | likes | dislikes |
|------------|-------|----------|
| 201        | 0     | 0        |
| 202        | 0     | 9        |
| 203        | 8     | 0        |
| 204        | 6     | 4        |

Output

[
  {"problem_id":202}
]

Explanation

Problem 201 has undefined approval rate (0 total votes), so it is ignored. Problem 203 is 100% and problem 204 is exactly 60%, so neither is returned.

Constraints

0 <= number of rows in problem_feedback <= 300000
problem_feedback.problem_id values are unique
1 <= problem_id <= 1000000000
0 <= likes <= 1000000000
0 <= dislikes <= 1000000000
A row is low-approval iff likes / (likes + dislikes) < 0.60
Rows with likes + dislikes = 0 must be ignored
Return exactly one column: problem_id
Sort by problem_id ascending
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with one column: problem_id

problem_feedback: | problem_id | likes | dislikes | |------------|-------|----------| | 6 | 1290 | 425 | | 11 | 2677 | 8659 | | 1 | 4446 | 2760 | | 7 | 8569 | 6086 | | 13 | 2050 | 4164 | | 10 | 9002 | 7446 |

problem_feedback: | problem_id | likes | dislikes | |------------|-------|----------| | 100 | 3 | 2 | | 101 | 6 | 4 | | 102 | 59 | 41 | | 103 | 599 | 401 |

problem_feedback: | problem_id | likes | dislikes | |------------|-------|----------| | 201 | 0 | 0 | | 202 | 0 | 9 | | 203 | 8 | 0 | | 204 | 6 | 4 |