Exclusive Flagship Buyer Report

Easy

You are given two relational tables used by a commerce analytics platform. Table: product product_id: unique product identifier product_name: product label unit_price: listed unit price Table: sales seller_id: seller account identifier product_id: product identifier sold in the transaction buyer_id: buyer account identifier sale_date: transaction date quantity: units purchased in this sale row price: recorded line-item price Business rule: A buyer is considered eligible if they purchased at least one product named "Nimbus X" The same buyer must never have purchased any product named "Orion One" Task: Return all eligible buyer_id values. Each buyer_id should appear only once. Sort the result by buyer_id in ascending order. Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

product:
| product_id | product_name | unit_price |
|------------|--------------|------------|
| 1          | Nimbus X     | 1000       |
| 2          | Orion One    | 1300       |
| 3          | Aero Lite    | 700        |

sales:
| seller_id | product_id | buyer_id | sale_date   | quantity | price |
|-----------|------------|----------|-------------|----------|-------|
| 10        | 1          | 1        | 2024-01-03  | 1        | 1000  |
| 11        | 3          | 1        | 2024-01-08  | 1        | 700   |
| 12        | 1          | 2        | 2024-01-11  | 1        | 1000  |
| 13        | 2          | 2        | 2024-01-12  | 1        | 1300  |
| 14        | 3          | 3        | 2024-01-20  | 2        | 1400  |

Output

[
  {"buyer_id":1}
]

Explanation

Buyer 1 bought Nimbus X and never bought Orion One. Buyer 2 bought both and is excluded. Buyer 3 never bought Nimbus X.

Example 2

Input

product:
| product_id | product_name | unit_price |
|------------|--------------|------------|
| 100        | Nimbus X     | 950        |
| 200        | Orion One    | 1200       |
| 300        | Echo Mini    | 500        |

sales:
| seller_id | product_id | buyer_id | sale_date   | quantity | price |
|-----------|------------|----------|-------------|----------|-------|
| 7         | 100        | 40       | 2025-02-01  | 1        | 950   |
| 7         | 100        | 40       | 2025-02-01  | 1        | 950   |
| 9         | 300        | 41       | 2025-02-09  | 1        | 500   |
| 8         | 100        | 42       | 2025-02-10  | 1        | 950   |
| 8         | 200        | 42       | 2025-02-15  | 1        | 1200  |

Output

[
  {"buyer_id":40}
]

Explanation

Duplicate purchases do not change eligibility. Buyer 40 still appears once.

Example 3

Input

product:
| product_id | product_name | unit_price |
|------------|--------------|------------|
| 5          | Nimbus X     | 990        |
| 6          | Orion One    | 1250       |
| 7          | Nova Pad     | 780        |

sales:
| seller_id | product_id | buyer_id | sale_date   | quantity | price |
|-----------|------------|----------|-------------|----------|-------|
| 1         | 6          | 11       | 2023-11-01  | 1        | 1250  |
| 2         | 7          | 12       | 2023-11-02  | 1        | 780   |
| 3         | 5          | 13       | 2023-11-03  | 1        | 990   |

Output

[
  {"buyer_id":13}
]

Explanation

Only buyer 13 satisfies target purchase without forbidden purchase.

Constraints

2 <= number of rows in product <= 1,000
1 <= number of rows in sales <= 10,000
1 <= product_id <= 1,000,000,000
1 <= buyer_id <= 1,000,000,000
1 <= seller_id <= 1,000,000,000
1 <= quantity <= 100,000
1 <= price <= 1,000,000,000
product.product_id is unique
sales.product_id references product.product_id
Both product names "Nimbus X" and "Orion One" appear in product
sales can contain duplicate rows
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with one column: buyer_id

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Exclusive Flagship Buyer Report

Easy

You are given two relational tables used by a commerce analytics platform. Table: product product_id: unique product identifier product_name: product label unit_price: listed unit price Table: sales seller_id: seller account identifier product_id: product identifier sold in the transaction buyer_id: buyer account identifier sale_date: transaction date quantity: units purchased in this sale row price: recorded line-item price Business rule: A buyer is considered eligible if they purchased at least one product named "Nimbus X" The same buyer must never have purchased any product named "Orion One" Task: Return all eligible buyer_id values. Each buyer_id should appear only once. Sort the result by buyer_id in ascending order. Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

product:
| product_id | product_name | unit_price |
|------------|--------------|------------|
| 1          | Nimbus X     | 1000       |
| 2          | Orion One    | 1300       |
| 3          | Aero Lite    | 700        |

sales:
| seller_id | product_id | buyer_id | sale_date   | quantity | price |
|-----------|------------|----------|-------------|----------|-------|
| 10        | 1          | 1        | 2024-01-03  | 1        | 1000  |
| 11        | 3          | 1        | 2024-01-08  | 1        | 700   |
| 12        | 1          | 2        | 2024-01-11  | 1        | 1000  |
| 13        | 2          | 2        | 2024-01-12  | 1        | 1300  |
| 14        | 3          | 3        | 2024-01-20  | 2        | 1400  |

Output

[
  {"buyer_id":1}
]

Explanation

Buyer 1 bought Nimbus X and never bought Orion One. Buyer 2 bought both and is excluded. Buyer 3 never bought Nimbus X.

Example 2

Input

product:
| product_id | product_name | unit_price |
|------------|--------------|------------|
| 100        | Nimbus X     | 950        |
| 200        | Orion One    | 1200       |
| 300        | Echo Mini    | 500        |

sales:
| seller_id | product_id | buyer_id | sale_date   | quantity | price |
|-----------|------------|----------|-------------|----------|-------|
| 7         | 100        | 40       | 2025-02-01  | 1        | 950   |
| 7         | 100        | 40       | 2025-02-01  | 1        | 950   |
| 9         | 300        | 41       | 2025-02-09  | 1        | 500   |
| 8         | 100        | 42       | 2025-02-10  | 1        | 950   |
| 8         | 200        | 42       | 2025-02-15  | 1        | 1200  |

Output

[
  {"buyer_id":40}
]

Explanation

Duplicate purchases do not change eligibility. Buyer 40 still appears once.

Example 3

Input

product:
| product_id | product_name | unit_price |
|------------|--------------|------------|
| 5          | Nimbus X     | 990        |
| 6          | Orion One    | 1250       |
| 7          | Nova Pad     | 780        |

sales:
| seller_id | product_id | buyer_id | sale_date   | quantity | price |
|-----------|------------|----------|-------------|----------|-------|
| 1         | 6          | 11       | 2023-11-01  | 1        | 1250  |
| 2         | 7          | 12       | 2023-11-02  | 1        | 780   |
| 3         | 5          | 13       | 2023-11-03  | 1        | 990   |

Output

[
  {"buyer_id":13}
]

Explanation

Only buyer 13 satisfies target purchase without forbidden purchase.

Constraints

2 <= number of rows in product <= 1,000
1 <= number of rows in sales <= 10,000
1 <= product_id <= 1,000,000,000
1 <= buyer_id <= 1,000,000,000
1 <= seller_id <= 1,000,000,000
1 <= quantity <= 100,000
1 <= price <= 1,000,000,000
product.product_id is unique
sales.product_id references product.product_id
Both product names "Nimbus X" and "Orion One" appear in product
sales can contain duplicate rows
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with one column: buyer_id