update

README.md

@@ -1,6 +1,6 @@
 # 力扣题库（完整版）
 
-> 最后更新日期： **2025.05.25**
+> 最后更新日期： **2025.09.02**
 >
 > 使用脚本前请务必仔细完整阅读本 `README.md` 文件
 

leetcode-cn/originData/classes-with-at-least-5-students.json

@@ -0,0 +1,96 @@
+{
+    "data": {
+        "question": {
+            "questionId": "596",
+            "questionFrontendId": "596",
+            "categoryTitle": "Database",
+            "boundTopicId": 1418,
+            "title": "Classes With at Least 5 Students",
+            "titleSlug": "classes-with-at-least-5-students",
+            "content": "<p>Table: <code>Courses</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    |\n+-------------+---------+\n| student     | varchar |\n| class       | varchar |\n+-------------+---------+\n(student, class) is the primary key (combination of columns with unique values) for this table.\nEach row of this table indicates the name of a student and the class in which they are enrolled.\n</pre>\n\n<p>&nbsp;</p>\n\n<p>Write a solution to find all the classes that have <strong>at least five students</strong>.</p>\n\n<p>Return the result table in <strong>any order</strong>.</p>\n\n<p>The&nbsp;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> \nCourses table:\n+---------+----------+\n| student | class    |\n+---------+----------+\n| A       | Math     |\n| B       | English  |\n| C       | Math     |\n| D       | Biology  |\n| E       | Math     |\n| F       | Computer |\n| G       | Math     |\n| H       | Math     |\n| I       | Math     |\n+---------+----------+\n<strong>Output:</strong> \n+---------+\n| class   |\n+---------+\n| Math    |\n+---------+\n<strong>Explanation:</strong> \n- Math has 6 students, so we include it.\n- English has 1 student, so we do not include it.\n- Biology has 1 student, so we do not include it.\n- Computer has 1 student, so we do not include it.\n</pre>\n",
+            "translatedTitle": "超过 5 名学生的课",
+            "translatedContent": "<p>表:&nbsp;<code>Courses</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    |\n+-------------+---------+\n| student     | varchar |\n| class       | varchar |\n+-------------+---------+\n(student, class)是该表的主键（不同值的列的组合）。\n该表的每一行表示学生的名字和他们注册的班级。\n</pre>\n\n<p>&nbsp;</p>\n\n<p>查询&nbsp;<strong>至少有 5 个学生</strong> 的所有班级。</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>&nbsp;</p>\n\n<p><strong class=\"example\">示例 1:</strong></p>\n\n<pre>\n<strong>输入:</strong> \nCourses table:\n+---------+----------+\n| student | class    |\n+---------+----------+\n| A       | Math     |\n| B       | English  |\n| C       | Math     |\n| D       | Biology  |\n| E       | Math     |\n| F       | Computer |\n| G       | Math     |\n| H       | Math     |\n| I       | Math     |\n+---------+----------+\n<strong>输出:</strong> \n+---------+ \n| class &nbsp; | \n+---------+ \n| Math &nbsp; &nbsp;| \n+---------+\n<strong>解释: </strong>\n-数学课有 6 个学生，所以我们包括它。\n-英语课有 1 名学生，所以我们不包括它。\n-生物课有 1 名学生，所以我们不包括它。\n-计算机课有 1 个学生，所以我们不包括它。</pre>\n",
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+                    "__typename": "CodeSnippetNode"
+                },
+                {
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+                    "langSlug": "pythondata",
+                    "code": "import pandas as pd\n\ndef find_classes(courses: pd.DataFrame) -> pd.DataFrame:\n    ",
+                    "__typename": "CodeSnippetNode"
+                },
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+                    "lang": "PostgreSQL",
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+                    "code": "-- Write your PostgreSQL query statement below",
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+                }
+            ],
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+            "sampleTestCase": "{\"headers\": {\"Courses\": [\"student\", \"class\"]}, \"rows\": {\"Courses\": [[\"A\", \"Math\"], [\"B\", \"English\"], [\"C\", \"Math\"], [\"D\", \"Biology\"], [\"E\", \"Math\"], [\"F\", \"Computer\"], [\"G\", \"Math\"], [\"H\", \"Math\"], [\"I\", \"Math\"]]}}",
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+            "judgerAvailable": true,
+            "judgeType": "large",
+            "mysqlSchemas": [
+                "Create table If Not Exists Courses (student varchar(255), class varchar(255))",
+                "Truncate table Courses",
+                "insert into Courses (student, class) values ('A', 'Math')",
+                "insert into Courses (student, class) values ('B', 'English')",
+                "insert into Courses (student, class) values ('C', 'Math')",
+                "insert into Courses (student, class) values ('D', 'Biology')",
+                "insert into Courses (student, class) values ('E', 'Math')",
+                "insert into Courses (student, class) values ('F', 'Computer')",
+                "insert into Courses (student, class) values ('G', 'Math')",
+                "insert into Courses (student, class) values ('H', 'Math')",
+                "insert into Courses (student, class) values ('I', 'Math')"
+            ],
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+            "editorType": "CKEDITOR",
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+            "style": "LEETCODE",
+            "exampleTestcases": "{\"headers\": {\"Courses\": [\"student\", \"class\"]}, \"rows\": {\"Courses\": [[\"A\", \"Math\"], [\"B\", \"English\"], [\"C\", \"Math\"], [\"D\", \"Biology\"], [\"E\", \"Math\"], [\"F\", \"Computer\"], [\"G\", \"Math\"], [\"H\", \"Math\"], [\"I\", \"Math\"]]}}",
+            "__typename": "QuestionNode"
+        }
+    }
+}

leetcode-cn/originData/find-covid-recovery-patients.json

@@ -0,0 +1,106 @@
+{
+    "data": {
+        "question": {
+            "questionId": "3932",
+            "questionFrontendId": "3586",
+            "categoryTitle": "Database",
+            "boundTopicId": 3701001,
+            "title": "Find COVID Recovery Patients",
+            "titleSlug": "find-covid-recovery-patients",
+            "content": "<p>Table: <code>patients</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    |\n+-------------+---------+\n| patient_id  | int     |\n| patient_name| varchar |\n| age         | int     |\n+-------------+---------+\npatient_id is the unique identifier for this table.\nEach row contains information about a patient.\n</pre>\n\n<p>Table: <code>covid_tests</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    |\n+-------------+---------+\n| test_id     | int     |\n| patient_id  | int     |\n| test_date   | date    |\n| result      | varchar |\n+-------------+---------+\ntest_id is the unique identifier for this table.\nEach row represents a COVID test result. The result can be Positive, Negative, or Inconclusive.\n</pre>\n\n<p>Write a solution to find patients who have <strong>recovered from COVID</strong> - patients who tested positive but later tested negative.</p>\n\n<ul>\n\t<li>A patient is considered recovered if they have <strong>at least one</strong> <strong>Positive</strong> test followed by at least one <strong>Negative</strong> test on a <strong>later date</strong></li>\n\t<li>Calculate the <strong>recovery time</strong> in days as the <strong>difference</strong> between the <strong>first positive test</strong> and the <strong>first negative test</strong> after that <strong>positive test</strong></li>\n\t<li><strong>Only include</strong> patients who have both positive and negative test results</li>\n</ul>\n\n<p>Return <em>the result table ordered by </em><code>recovery_time</code><em> in <strong>ascending</strong> order, then by </em><code>patient_name</code><em> in <strong>ascending</strong> order</em>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example:</strong></p>\n\n<div class=\"example-block\">\n<p><strong>Input:</strong></p>\n\n<p>patients table:</p>\n\n<pre class=\"example-io\">\n+------------+--------------+-----+\n| patient_id | patient_name | age |\n+------------+--------------+-----+\n| 1          | Alice Smith  | 28  |\n| 2          | Bob Johnson  | 35  |\n| 3          | Carol Davis  | 42  |\n| 4          | David Wilson | 31  |\n| 5          | Emma Brown   | 29  |\n+------------+--------------+-----+\n</pre>\n\n<p>covid_tests table:</p>\n\n<pre class=\"example-io\">\n+---------+------------+------------+--------------+\n| test_id | patient_id | test_date  | result       |\n+---------+------------+------------+--------------+\n| 1       | 1          | 2023-01-15 | Positive     |\n| 2       | 1          | 2023-01-25 | Negative     |\n| 3       | 2          | 2023-02-01 | Positive     |\n| 4       | 2          | 2023-02-05 | Inconclusive |\n| 5       | 2          | 2023-02-12 | Negative     |\n| 6       | 3          | 2023-01-20 | Negative     |\n| 7       | 3          | 2023-02-10 | Positive     |\n| 8       | 3          | 2023-02-20 | Negative     |\n| 9       | 4          | 2023-01-10 | Positive     |\n| 10      | 4          | 2023-01-18 | Positive     |\n| 11      | 5          | 2023-02-15 | Negative     |\n| 12      | 5          | 2023-02-20 | Negative     |\n+---------+------------+------------+--------------+\n</pre>\n\n<p><strong>Output:</strong></p>\n\n<pre class=\"example-io\">\n+------------+--------------+-----+---------------+\n| patient_id | patient_name | age | recovery_time |\n+------------+--------------+-----+---------------+\n| 1          | Alice Smith  | 28  | 10            |\n| 3          | Carol Davis  | 42  | 10            |\n| 2          | Bob Johnson  | 35  | 11            |\n+------------+--------------+-----+---------------+\n</pre>\n\n<p><strong>Explanation:</strong></p>\n\n<ul>\n\t<li><strong>Alice Smith (patient_id = 1):</strong>\n\n\t<ul>\n\t\t<li>First positive test: 2023-01-15</li>\n\t\t<li>First negative test after positive: 2023-01-25</li>\n\t\t<li>Recovery time: 25 - 15 = 10 days</li>\n\t</ul>\n\t</li>\n\t<li><strong>Bob Johnson (patient_id = 2):</strong>\n\t<ul>\n\t\t<li>First positive test: 2023-02-01</li>\n\t\t<li>Inconclusive test on 2023-02-05 (ignored for recovery calculation)</li>\n\t\t<li>First negative test after positive: 2023-02-12</li>\n\t\t<li>Recovery time: 12 - 1 = 11 days</li>\n\t</ul>\n\t</li>\n\t<li><strong>Carol Davis (patient_id = 3):</strong>\n\t<ul>\n\t\t<li>Had negative test on 2023-01-20 (before positive test)</li>\n\t\t<li>First positive test: 2023-02-10</li>\n\t\t<li>First negative test after positive: 2023-02-20</li>\n\t\t<li>Recovery time: 20 - 10 = 10 days</li>\n\t</ul>\n\t</li>\n\t<li><strong>Patients not included:</strong>\n\t<ul>\n\t\t<li>David Wilson (patient_id = 4): Only has positive tests, no negative test after positive</li>\n\t\t<li>Emma Brown (patient_id = 5): Only has negative tests, never tested positive</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>Output table is ordered by recovery_time in ascending order, and then by patient_name in ascending order.</p>\n</div>\n",
+            "translatedTitle": "寻找 COVID 康复患者",
+            "translatedContent": "<p>表：<code>patients</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    |\n+-------------+---------+\n| patient_id  | int     |\n| patient_name| varchar |\n| age         | int     |\n+-------------+---------+\npatient_id 是这张表的唯一主键。\n每一行表示一个患者的信息。\n</pre>\n\n<p>表：<code>covid_tests</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    |\n+-------------+---------+\n| test_id     | int     |\n| patient_id  | int     |\n| test_date   | date    |\n| result      | varchar |\n+-------------+---------+\ntest_id 是这张表的唯一主键。\n每一行代表一个 COVID 检测结果。结果可以是阳性、阴性或不确定。\n</pre>\n\n<p>编写一个解决方案以找到从 COVID 中康复的患者——那些曾经检测呈阳性但后来检测呈阴性的患者。</p>\n\n<ul>\n\t<li>患者如果 <strong>至少有一次阳性</strong> 检测结果后，在&nbsp;<strong>之后的日期</strong> 至少有一次 <strong>阴性</strong> 检测结果，则被认为已康复。</li>\n\t<li>计算从 <strong>首次阳性检测</strong> 结果到 <strong>该阳性检测</strong> 后的 <strong>首次阴性检测结果</strong> 之间的 <strong>康复时间</strong>（以天为单位）</li>\n\t<li><strong>仅包括&nbsp;</strong>同时具有阳性及阴性检测结果的患者</li>\n</ul>\n\n<p>返回结果表以<em>&nbsp;</em><code>recovery_time</code><em> </em><strong>升序 </strong>排序，然后以<em>&nbsp;</em><code>patient_name</code><em> </em><strong>升序&nbsp;</strong>排序。</p>\n\n<p>结果格式如下所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong class=\"example\">示例：</strong></p>\n\n<div class=\"example-block\">\n<p><strong>输入：</strong></p>\n\n<p>patients 表：</p>\n\n<pre class=\"example-io\">\n+------------+--------------+-----+\n| patient_id | patient_name | age |\n+------------+--------------+-----+\n| 1          | Alice Smith  | 28  |\n| 2          | Bob Johnson  | 35  |\n| 3          | Carol Davis  | 42  |\n| 4          | David Wilson | 31  |\n| 5          | Emma Brown   | 29  |\n+------------+--------------+-----+\n</pre>\n\n<p>covid_tests 表：</p>\n\n<pre class=\"example-io\">\n+---------+------------+------------+--------------+\n| test_id | patient_id | test_date  | result       |\n+---------+------------+------------+--------------+\n| 1       | 1          | 2023-01-15 | Positive     |\n| 2       | 1          | 2023-01-25 | Negative     |\n| 3       | 2          | 2023-02-01 | Positive     |\n| 4       | 2          | 2023-02-05 | Inconclusive |\n| 5       | 2          | 2023-02-12 | Negative     |\n| 6       | 3          | 2023-01-20 | Negative     |\n| 7       | 3          | 2023-02-10 | Positive     |\n| 8       | 3          | 2023-02-20 | Negative     |\n| 9       | 4          | 2023-01-10 | Positive     |\n| 10      | 4          | 2023-01-18 | Positive     |\n| 11      | 5          | 2023-02-15 | Negative     |\n| 12      | 5          | 2023-02-20 | Negative     |\n+---------+------------+------------+--------------+\n</pre>\n\n<p><strong>输出：</strong></p>\n\n<pre class=\"example-io\">\n+------------+--------------+-----+---------------+\n| patient_id | patient_name | age | recovery_time |\n+------------+--------------+-----+---------------+\n| 1          | Alice Smith  | 28  | 10            |\n| 3          | Carol Davis  | 42  | 10            |\n| 2          | Bob Johnson  | 35  | 11            |\n+------------+--------------+-----+---------------+\n</pre>\n\n<p><strong>解释：</strong></p>\n\n<ul>\n\t<li><strong>Alice Smith (patient_id = 1):</strong>\n\n\t<ul>\n\t\t<li>首次阳性检测：2023-01-15</li>\n\t\t<li>阳性检测后的首次阴性检测：2023-01-25</li>\n\t\t<li>康复时间：25 - 15 = 10 天</li>\n\t</ul>\n\t</li>\n\t<li><strong>Bob Johnson (patient_id = 2):</strong>\n\t<ul>\n\t\t<li>首次阳性检测：2023-02-01</li>\n\t\t<li>测试结果不明确：2023-02-05（忽略计算康复时间）</li>\n\t\t<li>阳性检测后的首次阴性检测：2023-02-12</li>\n\t\t<li>康复时间：12 - 1 = 11 天</li>\n\t</ul>\n\t</li>\n\t<li><strong>Carol Davis (patient_id = 3):</strong>\n\t<ul>\n\t\t<li>检测呈阴性：2023-01-20（在阳性检测前）</li>\n\t\t<li>首次阳性检测：2023-02-10</li>\n\t\t<li>阳性检测后的首次阴性检测：2023-02-20</li>\n\t\t<li>康复时间：20 - 10 = 10 天</li>\n\t</ul>\n\t</li>\n\t<li><strong>没有包含的患者：</strong>\n\t<ul>\n\t\t<li>David Wilson（patient_id = 4）：只有阳性检测，之后没有阴性检测。</li>\n\t\t<li>Emma Brown（patient_id = 5）：只有阴性检测，从未有阳性检测。</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>输出表以 recovery_time 升序排序，然后以 patient_name 升序排序。</p>\n</div>\n",
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+            "sampleTestCase": "{\"headers\":{\"patients\":[\"patient_id\",\"patient_name\",\"age\"],\"covid_tests\":[\"test_id\",\"patient_id\",\"test_date\",\"result\"]},\"rows\":{\"patients\":[[1,\"Alice Smith\",28],[2,\"Bob Johnson\",35],[3,\"Carol Davis\",42],[4,\"David Wilson\",31],[5,\"Emma Brown\",29]],\"covid_tests\":[[1,1,\"2023-01-15\",\"Positive\"],[2,1,\"2023-01-25\",\"Negative\"],[3,2,\"2023-02-01\",\"Positive\"],[4,2,\"2023-02-05\",\"Inconclusive\"],[5,2,\"2023-02-12\",\"Negative\"],[6,3,\"2023-01-20\",\"Negative\"],[7,3,\"2023-02-10\",\"Positive\"],[8,3,\"2023-02-20\",\"Negative\"],[9,4,\"2023-01-10\",\"Positive\"],[10,4,\"2023-01-18\",\"Positive\"],[11,5,\"2023-02-15\",\"Negative\"],[12,5,\"2023-02-20\",\"Negative\"]]}}",
+            "metaData": "{\"mysql\":[\"CREATE TABLE patients (\\n    patient_id INT,\\n    patient_name VARCHAR(255),\\n    age INT\\n)\",\"CREATE TABLE covid_tests (\\n    test_id INT,\\n    patient_id INT,\\n    test_date DATE,\\n    result VARCHAR(50)\\n)\"],\"mssql\":[\"CREATE TABLE patients (\\n    patient_id INT,\\n    patient_name VARCHAR(255),\\n    age INT\\n)\",\"CREATE TABLE covid_tests (\\n    test_id INT,\\n    patient_id INT,\\n    test_date DATE,\\n    result VARCHAR(50)\\n)\"],\"oraclesql\":[\"CREATE TABLE patients (\\n    patient_id NUMBER,\\n    patient_name VARCHAR2(255),\\n    age NUMBER\\n)\",\"CREATE TABLE covid_tests (\\n    test_id NUMBER,\\n    patient_id NUMBER,\\n    test_date DATE,\\n    result VARCHAR2(50)\\n)\",\"ALTER SESSION SET nls_date_format='YYYY-MM-DD'\"],\"database\":true,\"name\":\"find_covid_recovery_patients\",\"postgresql\":[\"CREATE TABLE patients (\\n    patient_id INTEGER,\\n    patient_name VARCHAR(255),\\n    age INTEGER\\n);\\n\",\"CREATE TABLE covid_tests (\\n    test_id INTEGER,\\n    patient_id INTEGER,\\n    test_date DATE,\\n    result VARCHAR(50)\\n);\\n\"],\"pythondata\":[\"patients = pd.DataFrame({\\n    'patient_id': pd.Series(dtype='int'),\\n    'patient_name': pd.Series(dtype='str'),\\n    'age': pd.Series(dtype='int')\\n})\",\"covid_tests = pd.DataFrame({\\n    'test_id': pd.Series(dtype='int'),\\n    'patient_id': pd.Series(dtype='int'),\\n    'test_date': pd.Series(dtype='datetime64[ns]'),\\n    'result': pd.Series(dtype='str')\\n})\"],\"database_schema\":{\"patients\":{\"patient_id\":\"INT\",\"patient_name\":\"VARCHAR(255)\",\"age\":\"INT\"},\"covid_tests\":{\"test_id\":\"INT\",\"patient_id\":\"INT\",\"test_date\":\"DATE\",\"result\":\"VARCHAR(50)\"}}}",
+            "judgerAvailable": true,
+            "judgeType": "large",
+            "mysqlSchemas": [
+                "CREATE TABLE patients (\n    patient_id INT,\n    patient_name VARCHAR(255),\n    age INT\n)",
+                "CREATE TABLE covid_tests (\n    test_id INT,\n    patient_id INT,\n    test_date DATE,\n    result VARCHAR(50)\n)",
+                "Truncate table patients",
+                "insert into patients (patient_id, patient_name, age) values ('1', 'Alice Smith', '28')",
+                "insert into patients (patient_id, patient_name, age) values ('2', 'Bob Johnson', '35')",
+                "insert into patients (patient_id, patient_name, age) values ('3', 'Carol Davis', '42')",
+                "insert into patients (patient_id, patient_name, age) values ('4', 'David Wilson', '31')",
+                "insert into patients (patient_id, patient_name, age) values ('5', 'Emma Brown', '29')",
+                "Truncate table covid_tests",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('1', '1', '2023-01-15', 'Positive')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('2', '1', '2023-01-25', 'Negative')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('3', '2', '2023-02-01', 'Positive')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('4', '2', '2023-02-05', 'Inconclusive')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('5', '2', '2023-02-12', 'Negative')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('6', '3', '2023-01-20', 'Negative')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('7', '3', '2023-02-10', 'Positive')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('8', '3', '2023-02-20', 'Negative')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('9', '4', '2023-01-10', 'Positive')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('10', '4', '2023-01-18', 'Positive')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('11', '5', '2023-02-15', 'Negative')",
+                "insert into covid_tests (test_id, patient_id, test_date, result) values ('12', '5', '2023-02-20', 'Negative')"
+            ],
+            "enableRunCode": true,
+            "envInfo": "{\"mysql\":[\"MySQL\",\"<p>\\u7248\\u672c\\uff1a<code>MySQL 8.0<\\/code><\\/p>\"],\"mssql\":[\"MS SQL Server\",\"<p>mssql server 2019.<\\/p>\"],\"oraclesql\":[\"Oracle\",\"<p>Oracle Sql 11.2.<\\/p>\"],\"pythondata\":[\"Pandas\",\"<p>Python 3.10 with Pandas 2.2.2 and NumPy 1.26.4<\\/p>\"],\"postgresql\":[\"PostgreSQL\",\"<p>PostgreSQL 16<\\/p>\"]}",
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+            "editorType": "CKEDITOR",
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+            "style": "LEETCODE",
+            "exampleTestcases": "{\"headers\":{\"patients\":[\"patient_id\",\"patient_name\",\"age\"],\"covid_tests\":[\"test_id\",\"patient_id\",\"test_date\",\"result\"]},\"rows\":{\"patients\":[[1,\"Alice Smith\",28],[2,\"Bob Johnson\",35],[3,\"Carol Davis\",42],[4,\"David Wilson\",31],[5,\"Emma Brown\",29]],\"covid_tests\":[[1,1,\"2023-01-15\",\"Positive\"],[2,1,\"2023-01-25\",\"Negative\"],[3,2,\"2023-02-01\",\"Positive\"],[4,2,\"2023-02-05\",\"Inconclusive\"],[5,2,\"2023-02-12\",\"Negative\"],[6,3,\"2023-01-20\",\"Negative\"],[7,3,\"2023-02-10\",\"Positive\"],[8,3,\"2023-02-20\",\"Negative\"],[9,4,\"2023-01-10\",\"Positive\"],[10,4,\"2023-01-18\",\"Positive\"],[11,5,\"2023-02-15\",\"Negative\"],[12,5,\"2023-02-20\",\"Negative\"]]}}",
+            "__typename": "QuestionNode"
+        }
+    }
+}

leetcode-cn/originData/find-loyal-customers.json

@@ -0,0 +1,98 @@
+{
+    "data": {
+        "question": {
+            "questionId": "4025",
+            "questionFrontendId": "3657",
+            "categoryTitle": "Database",
+            "boundTopicId": 3761718,
+            "title": "Find Loyal Customers",
+            "titleSlug": "find-loyal-customers",
+            "content": "<p>Table: <code>customer_transactions</code></p>\n\n<pre>\n+------------------+---------+\n| Column Name      | Type    | \n+------------------+---------+\n| transaction_id   | int     |\n| customer_id      | int     |\n| transaction_date | date    |\n| amount           | decimal |\n| transaction_type | varchar |\n+------------------+---------+\ntransaction_id is the unique identifier for this table.\ntransaction_type can be either &#39;purchase&#39; or &#39;refund&#39;.\n</pre>\n\n<p>Write a solution to find <strong>loyal customers</strong>. A customer is considered <strong>loyal</strong> if they meet ALL the following criteria:</p>\n\n<ul>\n\t<li>Made <strong>at least</strong>&nbsp;<code><font face=\"monospace\">3</font></code>&nbsp;purchase transactions.</li>\n\t<li>Have been active for <strong>at least</strong> <code>30</code> days.</li>\n\t<li>Their <strong>refund rate</strong> is less than <code>20%</code> .</li>\n</ul>\n\n<p>Return <em>the result table&nbsp;ordered by</em> <code>customer_id</code> <em>in <strong>ascending</strong> order</em>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example:</strong></p>\n\n<div class=\"example-block\">\n<p><strong>Input:</strong></p>\n\n<p>customer_transactions table:</p>\n\n<pre class=\"example-io\">\n+----------------+-------------+------------------+--------+------------------+\n| transaction_id | customer_id | transaction_date | amount | transaction_type |\n+----------------+-------------+------------------+--------+------------------+\n| 1              | 101         | 2024-01-05       | 150.00 | purchase         |\n| 2              | 101         | 2024-01-15       | 200.00 | purchase         |\n| 3              | 101         | 2024-02-10       | 180.00 | purchase         |\n| 4              | 101         | 2024-02-20       | 250.00 | purchase         |\n| 5              | 102         | 2024-01-10       | 100.00 | purchase         |\n| 6              | 102         | 2024-01-12       | 120.00 | purchase         |\n| 7              | 102         | 2024-01-15       | 80.00  | refund           |\n| 8              | 102         | 2024-01-18       | 90.00  | refund           |\n| 9              | 102         | 2024-02-15       | 130.00 | purchase         |\n| 10             | 103         | 2024-01-01       | 500.00 | purchase         |\n| 11             | 103         | 2024-01-02       | 450.00 | purchase         |\n| 12             | 103         | 2024-01-03       | 400.00 | purchase         |\n| 13             | 104         | 2024-01-01       | 200.00 | purchase         |\n| 14             | 104         | 2024-02-01       | 250.00 | purchase         |\n| 15             | 104         | 2024-02-15       | 300.00 | purchase         |\n| 16             | 104         | 2024-03-01       | 350.00 | purchase         |\n| 17             | 104         | 2024-03-10       | 280.00 | purchase         |\n| 18             | 104         | 2024-03-15       | 100.00 | refund           |\n+----------------+-------------+------------------+--------+------------------+\n</pre>\n\n<p><strong>Output:</strong></p>\n\n<pre class=\"example-io\">\n+-------------+\n| customer_id |\n+-------------+\n| 101         |\n| 104         |\n+-------------+\n</pre>\n\n<p><strong>Explanation:</strong></p>\n\n<ul>\n\t<li><strong>Customer 101</strong>:\n\n\t<ul>\n\t\t<li>Purchase transactions: 4 (IDs: 1, 2, 3, 4)&nbsp;</li>\n\t\t<li>Refund transactions: 0</li>\n\t\t<li>Refund rate: 0/4 = 0% (less than 20%)&nbsp;</li>\n\t\t<li>Active period: Jan 5 to Feb 20 = 46 days (at least 30 days)&nbsp;</li>\n\t\t<li>Qualifies as loyal&nbsp;</li>\n\t</ul>\n\t</li>\n\t<li><strong>Customer 102</strong>:\n\t<ul>\n\t\t<li>Purchase transactions: 3 (IDs: 5, 6, 9)&nbsp;</li>\n\t\t<li>Refund transactions: 2 (IDs: 7, 8)</li>\n\t\t<li>Refund rate: 2/5 = 40% (exceeds 20%)&nbsp;</li>\n\t\t<li>Not loyal&nbsp;</li>\n\t</ul>\n\t</li>\n\t<li><strong>Customer 103</strong>:\n\t<ul>\n\t\t<li>Purchase transactions: 3 (IDs: 10, 11, 12)&nbsp;</li>\n\t\t<li>Refund transactions: 0</li>\n\t\t<li>Refund rate: 0/3 = 0% (less than 20%)&nbsp;</li>\n\t\t<li>Active period: Jan 1 to Jan 3 = 2 days (less than 30 days)&nbsp;</li>\n\t\t<li>Not loyal&nbsp;</li>\n\t</ul>\n\t</li>\n\t<li><strong>Customer 104</strong>:\n\t<ul>\n\t\t<li>Purchase transactions: 5 (IDs: 13, 14, 15, 16, 17)&nbsp;</li>\n\t\t<li>Refund transactions: 1 (ID: 18)</li>\n\t\t<li>Refund rate: 1/6 = 16.67% (less than 20%)&nbsp;</li>\n\t\t<li>Active period: Jan 1 to Mar 15 = 73 days (at least 30 days)&nbsp;</li>\n\t\t<li>Qualifies as loyal&nbsp;</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>The result table is ordered by customer_id in ascending order.</p>\n</div>\n",
+            "translatedTitle": "寻找忠实客户",
+            "translatedContent": "<p>表：<code>customer_transactions</code></p>\n\n<pre>\n+------------------+---------+\n| Column Name      | Type    | \n+------------------+---------+\n| transaction_id   | int     |\n| customer_id      | int     |\n| transaction_date | date    |\n| amount           | decimal |\n| transaction_type | varchar |\n+------------------+---------+\ntransaction_id 是这张表的唯一主键。\ntransaction_type 可以是 “purchase” 或 “refund”。\n</pre>\n\n<p>编写一个解决方案来查找 <strong>忠实客户</strong>。如果满足下述所有条件，可以认为该客户是 <strong>忠实</strong> 客户：</p>\n\n<ul>\n\t<li>进行了 <strong>至少</strong>&nbsp;<code><font face=\"monospace\">3</font></code>&nbsp;次购买交易。</li>\n\t<li>活跃了&nbsp;<strong>至少</strong>&nbsp;<code>30</code>&nbsp;天。</li>\n\t<li>他们的 <strong>退款率</strong>&nbsp;少于&nbsp;<code>20%</code>。</li>\n</ul>\n\n<p>返回结果表以&nbsp;<code>customer_id</code> <strong>升序</strong>&nbsp;排序。</p>\n\n<p>结果格式如下所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong class=\"example\">示例：</strong></p>\n\n<div class=\"example-block\">\n<p><strong>输入：</strong></p>\n\n<p>customer_transactions 表：</p>\n\n<pre class=\"example-io\">\n+----------------+-------------+------------------+--------+------------------+\n| transaction_id | customer_id | transaction_date | amount | transaction_type |\n+----------------+-------------+------------------+--------+------------------+\n| 1              | 101         | 2024-01-05       | 150.00 | purchase         |\n| 2              | 101         | 2024-01-15       | 200.00 | purchase         |\n| 3              | 101         | 2024-02-10       | 180.00 | purchase         |\n| 4              | 101         | 2024-02-20       | 250.00 | purchase         |\n| 5              | 102         | 2024-01-10       | 100.00 | purchase         |\n| 6              | 102         | 2024-01-12       | 120.00 | purchase         |\n| 7              | 102         | 2024-01-15       | 80.00  | refund           |\n| 8              | 102         | 2024-01-18       | 90.00  | refund           |\n| 9              | 102         | 2024-02-15       | 130.00 | purchase         |\n| 10             | 103         | 2024-01-01       | 500.00 | purchase         |\n| 11             | 103         | 2024-01-02       | 450.00 | purchase         |\n| 12             | 103         | 2024-01-03       | 400.00 | purchase         |\n| 13             | 104         | 2024-01-01       | 200.00 | purchase         |\n| 14             | 104         | 2024-02-01       | 250.00 | purchase         |\n| 15             | 104         | 2024-02-15       | 300.00 | purchase         |\n| 16             | 104         | 2024-03-01       | 350.00 | purchase         |\n| 17             | 104         | 2024-03-10       | 280.00 | purchase         |\n| 18             | 104         | 2024-03-15       | 100.00 | refund           |\n+----------------+-------------+------------------+--------+------------------+\n</pre>\n\n<p><strong>输出：</strong></p>\n\n<pre class=\"example-io\">\n+-------------+\n| customer_id |\n+-------------+\n| 101         |\n| 104         |\n+-------------+\n</pre>\n\n<p><strong>解释：</strong></p>\n\n<ul>\n\t<li><strong>客户 101</strong>:\n\n\t<ul>\n\t\t<li>购买交易：4 (IDs: 1, 2, 3, 4)&nbsp;</li>\n\t\t<li>退款交易：0</li>\n\t\t<li>退款率：0/4 = 0%（少于 20%）</li>\n\t\t<li>活跃时期：1 月&nbsp;5 日到 2 月 20 日 = 46 天（至少 30 天）</li>\n\t\t<li>符合忠诚客户条件</li>\n\t</ul>\n\t</li>\n\t<li><strong>客户 102</strong>:\n\t<ul>\n\t\t<li>购买交易：3 (IDs: 5, 6, 9)&nbsp;</li>\n\t\t<li>退款交易：2 (IDs: 7, 8)</li>\n\t\t<li>退款率：2/5 = 40% (超过&nbsp;20%)&nbsp;</li>\n\t\t<li>不符合忠诚客户条件</li>\n\t</ul>\n\t</li>\n\t<li><strong>客户 103</strong>:\n\t<ul>\n\t\t<li>购买交易：3 (IDs: 10, 11, 12)&nbsp;</li>\n\t\t<li>退款交易：0</li>\n\t\t<li>退款率：0/3 = 0%（少于 20%）</li>\n\t\t<li>活跃时期：1 月 1 日到 1 月 3 日 =&nbsp;2 天（少于 30 天）</li>\n\t\t<li>不符合忠诚客户条件</li>\n\t</ul>\n\t</li>\n\t<li><strong>客户 104</strong>:\n\t<ul>\n\t\t<li>购买交易：5 (IDs: 13, 14, 15, 16, 17)&nbsp;</li>\n\t\t<li>退款交易：1 (ID: 18)</li>\n\t\t<li>退款率：1/6 = 16.67%（少于 20%）</li>\n\t\t<li>活跃时期：1 月 1 日到 3 月 15 日 = 73 天（至少 30 天）</li>\n\t\t<li>符合忠诚客户条件</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>结果表以 customer_id 升序排序。</p>\n</div>\n",
+            "isPaidOnly": false,
+            "difficulty": "Medium",
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+            "codeSnippets": [
+                {
+                    "lang": "MySQL",
+                    "langSlug": "mysql",
+                    "code": "# Write your MySQL query statement below",
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+                },
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+                    "langSlug": "pythondata",
+                    "code": "import pandas as pd\n\ndef find_loyal_customers(customer_transactions: pd.DataFrame) -> pd.DataFrame:\n    ",
+                    "__typename": "CodeSnippetNode"
+                },
+                {
+                    "lang": "PostgreSQL",
+                    "langSlug": "postgresql",
+                    "code": "-- Write your PostgreSQL query statement below",
+                    "__typename": "CodeSnippetNode"
+                }
+            ],
+            "stats": "{\"totalAccepted\": \"216\", \"totalSubmission\": \"318\", \"totalAcceptedRaw\": 216, \"totalSubmissionRaw\": 318, \"acRate\": \"67.9%\"}",
+            "hints": [],
+            "solution": null,
+            "status": null,
+            "sampleTestCase": "{\"headers\":{\"customer_transactions\":[\"transaction_id\",\"customer_id\",\"transaction_date\",\"amount\",\"transaction_type\"]},\"rows\":{\"customer_transactions\":[[1,101,\"2024-01-05\",150.00,\"purchase\"],[2,101,\"2024-01-15\",200.00,\"purchase\"],[3,101,\"2024-02-10\",180.00,\"purchase\"],[4,101,\"2024-02-20\",250.00,\"purchase\"],[5,102,\"2024-01-10\",100.00,\"purchase\"],[6,102,\"2024-01-12\",120.00,\"purchase\"],[7,102,\"2024-01-15\",80.00,\"refund\"],[8,102,\"2024-01-18\",90.00,\"refund\"],[9,102,\"2024-02-15\",130.00,\"purchase\"],[10,103,\"2024-01-01\",500.00,\"purchase\"],[11,103,\"2024-01-02\",450.00,\"purchase\"],[12,103,\"2024-01-03\",400.00,\"purchase\"],[13,104,\"2024-01-01\",200.00,\"purchase\"],[14,104,\"2024-02-01\",250.00,\"purchase\"],[15,104,\"2024-02-15\",300.00,\"purchase\"],[16,104,\"2024-03-01\",350.00,\"purchase\"],[17,104,\"2024-03-10\",280.00,\"purchase\"],[18,104,\"2024-03-15\",100.00,\"refund\"]]}}",
+            "metaData": "{\"mysql\":[\"CREATE TABLE if not exists customer_transactions (\\n    transaction_id INT,\\n    customer_id INT,\\n    transaction_date DATE,\\n    amount DECIMAL(10,2),\\n    transaction_type VARCHAR(20)\\n)\"],\"mssql\":[\"CREATE TABLE customer_transactions (\\n    transaction_id INT,\\n    customer_id INT,\\n    transaction_date DATE,\\n    amount DECIMAL(10,2),\\n    transaction_type VARCHAR(20)\\n)\"],\"oraclesql\":[\"CREATE TABLE customer_transactions (\\n    transaction_id NUMBER,\\n    customer_id NUMBER,\\n    transaction_date DATE,\\n    amount NUMBER(10,2),\\n    transaction_type VARCHAR2(20)\\n)\",\"ALTER SESSION SET nls_date_format='YYYY-MM-DD'\"],\"database\":true,\"name\":\"find_loyal_customers\",\"postgresql\":[\"CREATE TABLE IF NOT EXISTS customer_transactions (\\n    transaction_id SERIAL PRIMARY KEY,\\n    customer_id INT NOT NULL,\\n    transaction_date DATE NOT NULL,\\n    amount NUMERIC(10,2) NOT NULL,\\n    transaction_type VARCHAR(20) NOT NULL\\n);\"],\"pythondata\":[\"customer_transactions = pd.DataFrame({\\n    \\\"transaction_id\\\": pd.Series(dtype=\\\"int\\\"),\\n    \\\"customer_id\\\": pd.Series(dtype=\\\"int\\\"),\\n    \\\"transaction_date\\\": pd.Series(dtype=\\\"datetime64[ns]\\\"),\\n    \\\"amount\\\": pd.Series(dtype=\\\"float\\\"),\\n    \\\"transaction_type\\\": pd.Series(dtype=\\\"string\\\")\\n})\"],\"database_schema\":{\"customer_transactions\":{\"transaction_id\":\"INT\",\"customer_id\":\"INT\",\"transaction_date\":\"DATE\",\"amount\":\"DECIMAL(10, 2)\",\"transaction_type\":\"VARCHAR(20)\"}}}",
+            "judgerAvailable": true,
+            "judgeType": "large",
+            "mysqlSchemas": [
+                "CREATE TABLE if not exists customer_transactions (\n    transaction_id INT,\n    customer_id INT,\n    transaction_date DATE,\n    amount DECIMAL(10,2),\n    transaction_type VARCHAR(20)\n)",
+                "Truncate table customer_transactions",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('1', '101', '2024-01-05', '150.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('2', '101', '2024-01-15', '200.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('3', '101', '2024-02-10', '180.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('4', '101', '2024-02-20', '250.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('5', '102', '2024-01-10', '100.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('6', '102', '2024-01-12', '120.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('7', '102', '2024-01-15', '80.0', 'refund')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('8', '102', '2024-01-18', '90.0', 'refund')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('9', '102', '2024-02-15', '130.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('10', '103', '2024-01-01', '500.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('11', '103', '2024-01-02', '450.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('12', '103', '2024-01-03', '400.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('13', '104', '2024-01-01', '200.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('14', '104', '2024-02-01', '250.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('15', '104', '2024-02-15', '300.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('16', '104', '2024-03-01', '350.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('17', '104', '2024-03-10', '280.0', 'purchase')",
+                "insert into customer_transactions (transaction_id, customer_id, transaction_date, amount, transaction_type) values ('18', '104', '2024-03-15', '100.0', 'refund')"
+            ],
+            "enableRunCode": true,
+            "envInfo": "{\"mysql\":[\"MySQL\",\"<p>\\u7248\\u672c\\uff1a<code>MySQL 8.0<\\/code><\\/p>\"],\"mssql\":[\"MS SQL Server\",\"<p>mssql server 2019.<\\/p>\"],\"oraclesql\":[\"Oracle\",\"<p>Oracle Sql 11.2.<\\/p>\"],\"pythondata\":[\"Pandas\",\"<p>Python 3.10 with Pandas 2.2.2 and NumPy 1.26.4<\\/p>\"],\"postgresql\":[\"PostgreSQL\",\"<p>PostgreSQL 16<\\/p>\"]}",
+            "book": null,
+            "isSubscribed": false,
+            "isDailyQuestion": false,
+            "dailyRecordStatus": null,
+            "editorType": "CKEDITOR",
+            "ugcQuestionId": null,
+            "style": "LEETCODE",
+            "exampleTestcases": "{\"headers\":{\"customer_transactions\":[\"transaction_id\",\"customer_id\",\"transaction_date\",\"amount\",\"transaction_type\"]},\"rows\":{\"customer_transactions\":[[1,101,\"2024-01-05\",150.00,\"purchase\"],[2,101,\"2024-01-15\",200.00,\"purchase\"],[3,101,\"2024-02-10\",180.00,\"purchase\"],[4,101,\"2024-02-20\",250.00,\"purchase\"],[5,102,\"2024-01-10\",100.00,\"purchase\"],[6,102,\"2024-01-12\",120.00,\"purchase\"],[7,102,\"2024-01-15\",80.00,\"refund\"],[8,102,\"2024-01-18\",90.00,\"refund\"],[9,102,\"2024-02-15\",130.00,\"purchase\"],[10,103,\"2024-01-01\",500.00,\"purchase\"],[11,103,\"2024-01-02\",450.00,\"purchase\"],[12,103,\"2024-01-03\",400.00,\"purchase\"],[13,104,\"2024-01-01\",200.00,\"purchase\"],[14,104,\"2024-02-01\",250.00,\"purchase\"],[15,104,\"2024-02-15\",300.00,\"purchase\"],[16,104,\"2024-03-01\",350.00,\"purchase\"],[17,104,\"2024-03-10\",280.00,\"purchase\"],[18,104,\"2024-03-15\",100.00,\"refund\"]]}}",
+            "__typename": "QuestionNode"
+        }
+    }
+}