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183. Customers Who Never Order
Description
Table: Customers
+-------------+---------+ | Column Name | Type | +-------------+---------+ | id | int | | name | varchar | +-------------+---------+ id is the primary key (column with unique values) for this table. Each row of this table indicates the ID and name of a customer.
Table: Orders
+-------------+------+ | Column Name | Type | +-------------+------+ | id | int | | customerId | int | +-------------+------+ id is the primary key (column with unique values) for this table. customerId is a foreign key (reference columns) of the ID from the Customers table. Each row of this table indicates the ID of an order and the ID of the customer who ordered it.
Write a solution to find all customers who never order anything.
Return the result table in any order.
The result format is in the following example.
Example 1:
Input: Customers table: +----+-------+ | id | name | +----+-------+ | 1 | Joe | | 2 | Henry | | 3 | Sam | | 4 | Max | +----+-------+ Orders table: +----+------------+ | id | customerId | +----+------------+ | 1 | 3 | | 2 | 1 | +----+------------+ Output: +-----------+ | Customers | +-----------+ | Henry | | Max | +-----------+
Solutions
Solution 1: NOT IN
List all customer IDs of existing orders, and use NOT IN to find customers who are not in the list.
Solution 2: LEFT JOIN
Use LEFT JOIN to join the tables and return the data where CustomerId is NULL.
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import pandas as pd def find_customers(customers: pd.DataFrame, orders: pd.DataFrame) -> pd.DataFrame: # Select the customers whose 'id' is not present in the orders DataFrame's 'customerId' column. df = customers[~customers["id"].isin(orders["customerId"])] # Build a DataFrame that only contains the 'name' column and rename it as 'Customers'. df = df[["name"]].rename(columns={"name": "Customers"}) return df -
# Write your MySQL query statement below SELECT name AS Customers FROM Customers WHERE id NOT IN ( SELECT customerId FROM Orders );