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Problem

Table: Orders

+-----------------+----------+
| Column Name     | Type     |
+-----------------+----------+
| order_number    | int      |
| customer_number | int      |
+-----------------+----------+

order_number is the primary key for this table.
This table contains information about the order ID and the customer ID.

Write an SQL query to find the customer_number for the customer who has placed the largest number of orders.

The test cases are generated so that exactly one customer will have placed more orders than any other customer.

Examples

Example 1:

Input: Orders table:

+--------------+-----------------+
| order_number | customer_number |
+--------------+-----------------+
| 1            | 1               |
| 2            | 2               |
| 3            | 3               |
| 4            | 3               |
+--------------+-----------------+

Output:

+-----------------+
| customer_number |
+-----------------+
| 3               |
+-----------------+

Explanation: The customer with number 3 has two orders, which is greater than either customer 1 or 2 because each of them only has one order. So the result is customer_number 3.

Follow up

What if more than one customer has the largest number of orders, can you find all the customer_number in this case?

Solution

Method 1 - Using Count, Sorting Count and Limit 1

Code

[{"language":"SQL","code":"SELECT customer_number\nFROM Orders\nGROUP BY customer_number\nORDER BY COUNT(*) DESC\nLIMIT 1;","lang":"sql"},{"language":"Python","code":"import pandas as pd\n\ndef largest_orders(orders: pd.DataFrame) -> pd.DataFrame:\n    return orders['customer_number'].mode().to_frame()","lang":"python"}]

Method 2 - Using Subquery to Get Max and Then Filter by count=max

Code

[{"language":"SQL","code":"SELECT customer_number\nFROM orders\nGROUP BY customer_number\nHAVING COUNT(order_number) = (\n\tSELECT COUNT(order_number) cnt\n\tFROM orders\n\tGROUP BY customer_number\n\tORDER BY cnt DESC\n\tLIMIT 1\n)","lang":"sql"},{"language":"Pandas","code":"import pandas as pd\n\ndef largest_orders(orders: pd.DataFrame) -> pd.DataFrame:\n    # Group by customer_number and count the number of orders for each customer\n    customer_order_counts = orders.groupby('customer_number')['order_number'].count().reset_index()\n    \n    # Find the customer with the largest number of orders\n    max_orders_customer = customer_order_counts[customer_order_counts['order_number'] == customer_order_counts['order_number'].max()][['customer_number']]\n    \n    return max_orders_customer","lang":"python"}]

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