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https://gitee.com/coder-xiaomo/leetcode-problemset
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100 lines
10 KiB
JSON
100 lines
10 KiB
JSON
{
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"question": {
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"questionId": "1174",
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"questionFrontendId": "1084",
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"boundTopicId": null,
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"title": "Sales Analysis III",
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"titleSlug": "sales-analysis-iii",
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"content": "<p>Table: <code>Product</code></p>\n\n<pre>\n+--------------+---------+\n| Column Name | Type |\n+--------------+---------+\n| product_id | int |\n| product_name | varchar |\n| unit_price | int |\n+--------------+---------+\nproduct_id is the primary key (column with unique values) of this table.\nEach row of this table indicates the name and the price of each product.\n</pre>\n\n<p>Table: <code>Sales</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| seller_id | int |\n| product_id | int |\n| buyer_id | int |\n| sale_date | date |\n| quantity | int |\n| price | int |\n+-------------+---------+\nThis table can have duplicate rows.\nproduct_id is a foreign key (reference column) to the Product table.\nEach row of this table contains some information about one sale.\n</pre>\n\n<p> </p>\n\n<p>Write a solution to report the <strong>products</strong> that were <strong>only</strong> sold in the first quarter of <code>2019</code>. That is, between <code>2019-01-01</code> and <code>2019-03-31</code> inclusive.</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> \nProduct table:\n+------------+--------------+------------+\n| product_id | product_name | unit_price |\n+------------+--------------+------------+\n| 1 | S8 | 1000 |\n| 2 | G4 | 800 |\n| 3 | iPhone | 1400 |\n+------------+--------------+------------+\nSales table:\n+-----------+------------+----------+------------+----------+-------+\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n+-----------+------------+----------+------------+----------+-------+\n| 1 | 1 | 1 | 2019-01-21 | 2 | 2000 |\n| 1 | 2 | 2 | 2019-02-17 | 1 | 800 |\n| 2 | 2 | 3 | 2019-06-02 | 1 | 800 |\n| 3 | 3 | 4 | 2019-05-13 | 2 | 2800 |\n+-----------+------------+----------+------------+----------+-------+\n<strong>Output:</strong> \n+-------------+--------------+\n| product_id | product_name |\n+-------------+--------------+\n| 1 | S8 |\n+-------------+--------------+\n<strong>Explanation:</strong> \nThe product with id 1 was only sold in the spring of 2019.\nThe product with id 2 was sold in the spring of 2019 but was also sold after the spring of 2019.\nThe product with id 3 was sold after spring 2019.\nWe return only product 1 as it is the product that was only sold in the spring of 2019.\n</pre>\n",
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"difficulty": "Easy",
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"similarQuestions": "[{\"title\": \"Sales Analysis II\", \"titleSlug\": \"sales-analysis-ii\", \"difficulty\": \"Easy\", \"translatedTitle\": null}]",
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"exampleTestcases": "{\"headers\":{\"Product\":[\"product_id\",\"product_name\",\"unit_price\"],\"Sales\":[\"seller_id\",\"product_id\",\"buyer_id\",\"sale_date\",\"quantity\",\"price\"]},\"rows\":{\"Product\":[[1,\"S8\",1000],[2,\"G4\",800],[3,\"iPhone\",1400]],\"Sales\":[[1,1,1,\"2019-01-21\",2,2000],[1,2,2,\"2019-02-17\",1,800],[2,2,3,\"2019-06-02\",1,800],[3,3,4,\"2019-05-13\",2,2800]]}}",
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"categoryTitle": "Database",
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{
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"name": "Database",
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"lang": "MySQL",
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"langSlug": "mysql",
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"code": "# Write your MySQL query statement below\n",
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},
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{
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"lang": "MS SQL Server",
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"langSlug": "mssql",
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"code": "/* Write your T-SQL query statement below */\n",
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"lang": "Oracle",
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"code": "/* Write your PL/SQL query statement below */\n",
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"__typename": "CodeSnippetNode"
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},
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{
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"lang": "Pandas",
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"langSlug": "pythondata",
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"code": "import pandas as pd\n\ndef sales_analysis(product: pd.DataFrame, sales: pd.DataFrame) -> pd.DataFrame:\n ",
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"__typename": "CodeSnippetNode"
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},
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{
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"lang": "PostgreSQL",
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"langSlug": "postgresql",
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"code": "-- Write your PostgreSQL query statement below\n",
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"__typename": "CodeSnippetNode"
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}
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"solution": {
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"id": "2070",
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"__typename": "ArticleNode"
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},
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"status": null,
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"sampleTestCase": "{\"headers\":{\"Product\":[\"product_id\",\"product_name\",\"unit_price\"],\"Sales\":[\"seller_id\",\"product_id\",\"buyer_id\",\"sale_date\",\"quantity\",\"price\"]},\"rows\":{\"Product\":[[1,\"S8\",1000],[2,\"G4\",800],[3,\"iPhone\",1400]],\"Sales\":[[1,1,1,\"2019-01-21\",2,2000],[1,2,2,\"2019-02-17\",1,800],[2,2,3,\"2019-06-02\",1,800],[3,3,4,\"2019-05-13\",2,2800]]}}",
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"metaData": "{\"mysql\": [\"Create table If Not Exists Product (product_id int, product_name varchar(10), unit_price int)\", \"Create table If Not Exists Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)\"], \"mssql\": [\"Create table Product (product_id int, product_name varchar(10), unit_price int)\", \"Create table Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)\"], \"oraclesql\": [\"Create table Product (product_id int, product_name varchar(10), unit_price int)\", \"Create table Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)\", \"ALTER SESSION SET nls_date_format='YYYY-MM-DD'\"], \"database\": true, \"name\": \"sales_analysis\", \"pythondata\": [\"Product = pd.DataFrame([], columns=['product_id', 'product_name', 'unit_price']).astype({'product_id':'Int64', 'product_name':'object', 'unit_price':'Int64'})\", \"Sales = pd.DataFrame([], columns=['seller_id', 'product_id', 'buyer_id', 'sale_date', 'quantity', 'price']).astype({'seller_id':'Int64', 'product_id':'Int64', 'buyer_id':'Int64', 'sale_date':'datetime64[ns]', 'quantity':'Int64', 'price':'Int64'})\"], \"postgresql\": [\"Create table If Not Exists Product (product_id int, product_name varchar(10), unit_price int)\\n\", \"Create table If Not Exists Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)\"], \"database_schema\": {\"Product\": {\"product_id\": \"INT\", \"product_name\": \"VARCHAR(10)\", \"unit_price\": \"INT\"}, \"Sales\": {\"seller_id\": \"INT\", \"product_id\": \"INT\", \"buyer_id\": \"INT\", \"sale_date\": \"DATE\", \"quantity\": \"INT\", \"price\": \"INT\"}}}",
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"judgeType": "large",
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"Create table If Not Exists Product (product_id int, product_name varchar(10), unit_price int)",
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"Create table If Not Exists Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)",
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"Truncate table Product",
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"insert into Product (product_id, product_name, unit_price) values ('1', 'S8', '1000')",
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"insert into Product (product_id, product_name, unit_price) values ('2', 'G4', '800')",
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"insert into Product (product_id, product_name, unit_price) values ('3', 'iPhone', '1400')",
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"Truncate table Sales",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('1', '1', '1', '2019-01-21', '2', '2000')",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('1', '2', '2', '2019-02-17', '1', '800')",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('2', '2', '3', '2019-06-02', '1', '800')",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('3', '3', '4', '2019-05-13', '2', '2800')"
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],
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"enableRunCode": true,
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"envInfo": "{\"mysql\": [\"MySQL\", \"<p><code>MySQL 8.0</code>.</p>\"], \"mssql\": [\"MS SQL Server\", \"<p><code>mssql server 2019</code>.</p>\"], \"oraclesql\": [\"Oracle\", \"<p><code>Oracle Sql 11.2</code>.</p>\"], \"pythondata\": [\"Pandas\", \"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0</p>\"], \"postgresql\": [\"PostgreSQL\", \"<p>PostgreSQL 16</p>\"]}",
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}
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