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小墨
2025-09-29 14:43:44 +08:00
parent 2862a227c4
commit 13f2098086
4409 changed files with 168933 additions and 166256 deletions
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leetcode-cn/originData/reformat-department-table.json
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@@ -12,12 +12,12 @@
"translatedContent": "<p>表&nbsp;<code>Department</code>：</p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| id | int |\n| revenue | int |\n| month | varchar |\n+---------------+---------+\n在 SQL 中，(id, month) 是表的联合主键。\n这个表格有关于每个部门每月收入的信息。\n月份（month）可以取下列值 [\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"]。\n</pre>\n\n<p>&nbsp;</p>\n\n<p>重新格式化表格，使得&nbsp;<strong>每个月&nbsp;</strong>都有一个部门 id 列和一个收入列。</p>\n\n<p>以 <strong>任意顺序</strong> 返回结果表。</p>\n\n<p>结果格式如以下示例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1：</strong></p>\n\n<pre>\n<b>输入：</b>\nDepartment table:\n+------+---------+-------+\n| id | revenue | month |\n+------+---------+-------+\n| 1 | 8000 | Jan |\n| 2 | 9000 | Jan |\n| 3 | 10000 | Feb |\n| 1 | 7000 | Feb |\n| 1 | 6000 | Mar |\n+------+---------+-------+\n<b>输出：</b>\n+------+-------------+-------------+-------------+-----+-------------+\n| id | Jan_Revenue | Feb_Revenue | Mar_Revenue | ... | Dec_Revenue |\n+------+-------------+-------------+-------------+-----+-------------+\n| 1 | 8000 | 7000 | 6000 | ... | null |\n| 2 | 9000 | null | null | ... | null |\n| 3 | null | 10000 | null | ... | null |\n+------+-------------+-------------+-------------+-----+-------------+\n<b>解释：</b>四月到十二月的收入为空。 \n请注意，结果表共有 13 列（1 列用于部门 ID，其余 12 列用于各个月份）。</pre>\n",
"isPaidOnly": false,
"difficulty": "Easy",
"likes": 258,
"likes": 272,
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"similarQuestions": "[]",
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{
"name": "Database",
@@ -40,6 +40,12 @@
"code": "/* Write your T-SQL query statement below */",
"__typename": "CodeSnippetNode"
},
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"lang": "PostgreSQL",
"langSlug": "postgresql",
"code": "-- Write your PostgreSQL query statement below",
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"lang": "Oracle",
"langSlug": "oraclesql",
@@ -51,15 +57,9 @@
"langSlug": "pythondata",
"code": "import pandas as pd\n\ndef reformat_table(department: pd.DataFrame) -> pd.DataFrame:\n ",
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