00:00:00

Description

Editorial

Exclusive Flagship Buyer Report

EASY10 pts

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

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

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

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.

Accepted0/0·0% Acceptance

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

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

sales =

[{"seller_id":10,"product_id":1,"buyer_id":1,"sale_date":"2024-01-03","quantity":1,"price":1000},{"seller_id":11,"product_id":3,"buyer_id":1,"sale_date":"2024-01-08","quantity":1,"price":700},{"seller_id":12,"product_id":1,"buyer_id":2,"sale_date":"2024-01-11","quantity":1,"price":1000},{"seller_id":13,"product_id":2,"buyer_id":2,"sale_date":"2024-01-12","quantity":1,"price":1300},{"seller_id":14,"product_id":3,"buyer_id":3,"sale_date":"2024-01-20","quantity":2,"price":1400}]

product =

[{"product_id":1,"product_name":"Nimbus X","unit_price":1000},{"product_id":2,"product_name":"Orion One","unit_price":1300},{"product_id":3,"product_name":"Aero Lite","unit_price":700}]

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101

00:00:00

Description

Editorial

Exclusive Flagship Buyer Report

EASY10 pts

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

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

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

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.

Accepted0/0·0% Acceptance

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

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

sales =

product =

[{"product_id":1,"product_name":"Nimbus X","unit_price":1000},{"product_id":2,"product_name":"Orion One","unit_price":1300},{"product_id":3,"product_name":"Aero Lite","unit_price":700}]

Exclusive Flagship Buyer Report

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Exclusive Flagship Buyer Report

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