Most Orders Customer

Easy

You are given transactional data from an online ordering system. Table Orders has one row per order: order_number: unique order identifier customer_number: identifier of the customer who placed that order Your task is to return the customer_number of the customer who placed the highest number of orders. The test data guarantees exactly one customer has a strictly higher order count than every other customer. Output requirements: Return exactly one column named customer_number. Return exactly one row. Submissions are supported in: SQL (SQLite 3.27.2) Python (Pandas)

Example 1

Input

Orders:
| order_number | customer_number |
|--------------|-----------------|
| 1            | 1               |
| 2            | 2               |
| 3            | 3               |
| 4            | 3               |

Output

[{"customer_number":3}]

Explanation

Customer 3 appears twice, while customers 1 and 2 appear once each.

Example 2

Input

Orders:
| order_number | customer_number |
|--------------|-----------------|
| 10           | 42              |
| 11           | 42              |
| 12           | 11              |
| 13           | 11              |
| 14           | 42              |
| 15           | 7               |

Output

[{"customer_number":42}]

Explanation

Customer 42 has three orders, which is more than all others.

Example 3

Input

Orders:
| order_number | customer_number |
|--------------|-----------------|
| 100          | 9001            |

Output

[{"customer_number":9001}]

Explanation

With one recorded order, customer 9001 is trivially the top customer.

Constraints

1 <= number of rows in Orders <= 300,000
1 <= order_number <= 2,000,000,000
1 <= customer_number <= 2,000,000,000
Orders.order_number is unique
Exactly one customer has the strictly largest order count
Output must contain exactly one column named customer_number
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a one-row DataFrame with one column named customer_number

Loading problem...

Preparing your editor. You can read the problem while it loads.

Most Orders Customer

Easy

You are given transactional data from an online ordering system. Table Orders has one row per order: order_number: unique order identifier customer_number: identifier of the customer who placed that order Your task is to return the customer_number of the customer who placed the highest number of orders. The test data guarantees exactly one customer has a strictly higher order count than every other customer. Output requirements: Return exactly one column named customer_number. Return exactly one row. Submissions are supported in: SQL (SQLite 3.27.2) Python (Pandas)

Example 1

Input

Orders:
| order_number | customer_number |
|--------------|-----------------|
| 1            | 1               |
| 2            | 2               |
| 3            | 3               |
| 4            | 3               |

Output

[{"customer_number":3}]

Explanation

Customer 3 appears twice, while customers 1 and 2 appear once each.

Example 2

Input

Orders:
| order_number | customer_number |
|--------------|-----------------|
| 10           | 42              |
| 11           | 42              |
| 12           | 11              |
| 13           | 11              |
| 14           | 42              |
| 15           | 7               |

Output

[{"customer_number":42}]

Explanation

Customer 42 has three orders, which is more than all others.

Example 3

Input

Orders:
| order_number | customer_number |
|--------------|-----------------|
| 100          | 9001            |

Output

[{"customer_number":9001}]

Explanation

With one recorded order, customer 9001 is trivially the top customer.

Constraints

1 <= number of rows in Orders <= 300,000
1 <= order_number <= 2,000,000,000
1 <= customer_number <= 2,000,000,000
Orders.order_number is unique
Exactly one customer has the strictly largest order count
Output must contain exactly one column named customer_number
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a one-row DataFrame with one column named customer_number