leetcode-problemset/leetcode-cn/originData/employees-whose-manager-left-the-company.json

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        "question": {
            "questionId": "2127",
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            "categoryTitle": "Database",
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            "title": "Employees Whose Manager Left the Company",
            "titleSlug": "employees-whose-manager-left-the-company",
            "content": "<p>Table: <code>Employees</code></p>\n\n<pre>\n+-------------+----------+\n| Column Name | Type     |\n+-------------+----------+\n| employee_id | int      |\n| name        | varchar  |\n| manager_id  | int      |\n| salary      | int      |\n+-------------+----------+\nIn SQL, employee_id is the primary key for this table.\nThis table contains information about the employees, their salary, and the ID of their manager. Some employees do not have a manager (manager_id is null). \n</pre>\n\n<p>&nbsp;</p>\n\n<p>Find the IDs of the employees whose salary is strictly less than <code>$30000</code> and whose manager left the company. When a manager leaves the company, their information is deleted from the <code>Employees</code> table, but the reports still have their <code>manager_id</code> set to the manager that left.</p>\n\n<p>Return the result table ordered by <code>employee_id</code>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input: </strong> \nEmployees table:\n+-------------+-----------+------------+--------+\n| employee_id | name      | manager_id | salary |\n+-------------+-----------+------------+--------+\n| 3           | Mila      | 9          | 60301  |\n| 12          | Antonella | null       | 31000  |\n| 13          | Emery     | null       | 67084  |\n| 1           | Kalel     | 11         | 21241  |\n| 9           | Mikaela   | null       | 50937  |\n| 11          | Joziah    | 6          | 28485  |\n+-------------+-----------+------------+--------+\n<strong>Output:</strong> \n+-------------+\n| employee_id |\n+-------------+\n| 11          |\n+-------------+\n\n<strong>Explanation:</strong> \nThe employees with a salary less than $30000 are 1 (Kalel) and 11 (Joziah).\nKalel&#39;s manager is employee 11, who is still in the company (Joziah).\nJoziah&#39;s manager is employee 6, who left the company because there is no row for employee 6 as it was deleted.\n</pre>\n",
            "translatedTitle": "上级经理已离职的公司员工",
            "translatedContent": "<p>表: <code>Employees</code></p>\n\n<pre>\n+-------------+----------+\n| Column Name | Type     |\n+-------------+----------+\n| employee_id | int      |\n| name        | varchar  |\n| manager_id  | int      |\n| salary      | int      |\n+-------------+----------+\n在 SQL 中，employee_id 是这个表的主键。\n这个表包含了员工，他们的薪水和上级经理的id。\n有一些员工没有上级经理（其 manager_id 是空值）。\n</pre>\n\n<p>&nbsp;</p>\n\n<p>查找这些员工的id，他们的薪水严格少于<code>$30000</code>&nbsp;并且他们的上级经理已离职。当一个经理离开公司时，他们的信息需要从员工表中删除掉，但是表中的员工的<code>manager_id</code> &nbsp;这一列还是设置的离职经理的id&nbsp;。</p>\n\n<p>返回的结果按照<code>employee_id&nbsp;</code>从小到大排序。</p>\n\n<p>查询结果如下所示：</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例：</strong></p>\n\n<pre>\n<strong>输入：</strong>\nEmployees table:\n+-------------+-----------+------------+--------+\n| employee_id | name      | manager_id | salary |\n+-------------+-----------+------------+--------+\n| 3           | Mila      | 9          | 60301  |\n| 12          | Antonella | null       | 31000  |\n| 13          | Emery     | null       | 67084  |\n| 1           | Kalel     | 11         | 21241  |\n| 9           | Mikaela   | null       | 50937  |\n| 11          | Joziah    | 6          | 28485  |\n+-------------+-----------+------------+--------+\n<strong>输出：</strong>\n+-------------+\n| employee_id |\n+-------------+\n| 11          |\n+-------------+\n\n<strong>解释：</strong>\n薪水少于 30000 美元的员工有 1 号(Kalel) 和 11号 (Joziah)。\nKalel 的上级经理是 11 号员工，他还在公司上班(他是 Joziah )。\nJoziah 的上级经理是 6 号员工，他已经离职，因为员工表里面已经没有 6 号员工的信息了，它被删除了。\n</pre>\n",
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                    "code": "import pandas as pd\n\ndef find_employees(employees: pd.DataFrame) -> pd.DataFrame:\n    ",
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            "sampleTestCase": "{\"headers\": {\"Employees\": [\"employee_id\", \"name\", \"manager_id\", \"salary\"]}, \"rows\": {\"Employees\": [[3, \"Mila\", 9, 60301], [12, \"Antonella\", null, 31000], [13, \"Emery\", null, 67084], [1, \"Kalel\", 11, 21241], [9, \"Mikaela\", null, 50937], [11, \"Joziah\", 6, 28485]]}}",
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                "insert into Employees (employee_id, name, manager_id, salary) values ('3', 'Mila', '9', '60301')",
                "insert into Employees (employee_id, name, manager_id, salary) values ('12', 'Antonella', 'None', '31000')",
                "insert into Employees (employee_id, name, manager_id, salary) values ('13', 'Emery', 'None', '67084')",
                "insert into Employees (employee_id, name, manager_id, salary) values ('1', 'Kalel', '11', '21241')",
                "insert into Employees (employee_id, name, manager_id, salary) values ('9', 'Mikaela', 'None', '50937')",
                "insert into Employees (employee_id, name, manager_id, salary) values ('11', 'Joziah', '6', '28485')"
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