"content":"<p>Table: <code>Customers</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| id | int |\n| name | varchar |\n+-------------+---------+\nid is the primary key (column with unique values) for this table.\nEach row of this table indicates the ID and name of a customer.\n</pre>\n\n<p> </p>\n\n<p>Table: <code>Orders</code></p>\n\n<pre>\n+-------------+------+\n| Column Name | Type |\n+-------------+------+\n| id | int |\n| customerId | int |\n+-------------+------+\nid is the primary key (column with unique values) for this table.\ncustomerId is a foreign key (reference columns) of the ID from the Customers table.\nEach row of this table indicates the ID of an order and the ID of the customer who ordered it.\n</pre>\n\n<p> </p>\n\n<p>Write a solution to find all customers who never order anything.</p>\n\n<p>Return the result table in <strong>any order</strong>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong> \nCustomers table:\n+----+-------+\n| id | name |\n+----+-------+\n| 1 | Joe |\n| 2 | Henry |\n| 3 | Sam |\n| 4 | Max |\n+----+-------+\nOrders table:\n+----+------------+\n| id | customerId |\n+----+------------+\n| 1 | 3 |\n| 2 | 1 |\n+----+------------+\n<strong>Output:</strong> \n+-----------+\n| Customers |\n+-----------+\n| Henry |\n| Max |\n+-----------+\n</pre>\n",
"translatedContent":"<p><code>Customers</code> 表：</p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| id | int |\n| name | varchar |\n+-------------+---------+\n在 SQL 中，id 是该表的主键。\n该表的每一行都表示客户的 ID 和名称。</pre>\n\n<p><code>Orders</code> 表：</p>\n\n<pre>\n+-------------+------+\n| Column Name | Type |\n+-------------+------+\n| id | int |\n| customerId | int |\n+-------------+------+\n在 SQL 中，id 是该表的主键。\ncustomerId 是 Customers 表中 ID 的外键( Pandas 中的连接键)。\n该表的每一行都表示订单的 ID 和订购该订单的客户的 ID。</pre>\n\n<p> </p>\n\n<p>找出所有从不点任何东西的顾客。</p>\n\n<p>以 <strong>任意顺序</strong> 返回结果表。</p>\n\n<p>结果格式如下所示。</p>\n\n<p> </p>\n\n<p><strong>示例 1：</strong></p>\n\n<pre>\n<b>输入：</b>\nCustomers table:\n+----+-------+\n| id | name |\n+----+-------+\n| 1 | Joe |\n| 2 | Henry |\n| 3 | Sam |\n| 4 | Max |\n+----+-------+\nOrders table:\n+----+------------+\n| id | customerId |\n+----+------------+\n| 1 | 3 |\n| 2 | 1 |\n+----+------------+\n<b>输出：</b>\n+-----------+\n| Customers |\n+-----------+\n| Henry |\n| Max |\n+-----------+</pre>\n",
"metaData":"{\"mysql\":[\"Create table If Not Exists Customers (id int, name varchar(255))\",\"Create table If Not Exists Orders (id int, customerId int)\"],\"mssql\":[\"Create table Customers (id int, name varchar(255))\",\"Create table Orders (id int, customerId int)\"],\"oraclesql\":[\"Create table Customers (id int, name varchar(255))\",\"Create table Orders (id int, customerId int)\"],\"database\":true,\"name\":\"find_customers\",\"pythondata\":[\"Customers = pd.DataFrame([], columns=['id', 'name']).astype({'id':'Int64', 'name':'object'})\",\"Orders = pd.DataFrame([], columns=['id', 'customerId']).astype({'id':'Int64', 'customerId':'Int64'})\"],\"manual\":false,\"postgresql\":[\"Create table If Not Exists Customers (id int, name varchar(255))\",\"Create table If Not Exists Orders (id int, customerId int)\"],\"database_schema\":{\"Customers\":{\"id\":\"INT\",\"name\":\"VARCHAR(255)\"},\"Orders\":{\"id\":\"INT\",\"customerId\":\"INT\"}}}",
