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leetcode-problemset/leetcode-cn/originData/employees-whose-manager-left-the-company.json
2023-12-09 19:57:46 +08:00

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{
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"question": {
"questionId": "2127",
"questionFrontendId": "1978",
"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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"lang": "Pandas",
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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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"exampleTestcases": "{\"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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