Table: Products
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| new_price | int |\n| change_date | date |\n+---------------+---------+\n(product_id, change_date) is the primary key (combination of columns with unique values) of this table.\nEach row of this table indicates that the price of some product was changed to a new price at some date.\n\n
\n\n
Write a solution to find the prices of all products on 2019-08-16. Assume the price of all products before any change is 10.
Return the result table in any order.
\n\nThe result format is in the following example.
\n\n\n
Example 1:
\n\n\nInput: \nProducts table:\n+------------+-----------+-------------+\n| product_id | new_price | change_date |\n+------------+-----------+-------------+\n| 1 | 20 | 2019-08-14 |\n| 2 | 50 | 2019-08-14 |\n| 1 | 30 | 2019-08-15 |\n| 1 | 35 | 2019-08-16 |\n| 2 | 65 | 2019-08-17 |\n| 3 | 20 | 2019-08-18 |\n+------------+-----------+-------------+\nOutput: \n+------------+-------+\n| product_id | price |\n+------------+-------+\n| 2 | 50 |\n| 1 | 35 |\n| 3 | 10 |\n+------------+-------+\n\n", "translatedTitle": "指定日期的产品价格", "translatedContent": "
产品数据表: Products
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| new_price | int |\n| change_date | date |\n+---------------+---------+\n(product_id, change_date) 是此表的主键（具有唯一值的列组合）。\n这张表的每一行分别记录了 某产品 在某个日期 更改后 的新价格。\n\n
\n\n
编写一个解决方案，找出在 2019-08-16 时全部产品的价格，假设所有产品在修改前的价格都是 10 。
以 任意顺序 返回结果表。
\n\n结果格式如下例所示。
\n\n\n\n
示例 1:
\n\n\n输入：\nProducts 表:\n+------------+-----------+-------------+\n| product_id | new_price | change_date |\n+------------+-----------+-------------+\n| 1 | 20 | 2019-08-14 |\n| 2 | 50 | 2019-08-14 |\n| 1 | 30 | 2019-08-15 |\n| 1 | 35 | 2019-08-16 |\n| 2 | 65 | 2019-08-17 |\n| 3 | 20 | 2019-08-18 |\n+------------+-----------+-------------+\n输出：\n+------------+-------+\n| product_id | price |\n+------------+-------+\n| 2 | 50 |\n| 1 | 35 |\n| 3 | 10 |\n+------------+-------+\n", "isPaidOnly": false, "difficulty": "Medium", "likes": 149, "dislikes": 0, "isLiked": null, "similarQuestions": "[]", "contributors": [], "langToValidPlayground": "{\"cpp\": false, \"java\": false, \"python\": false, \"python3\": false, \"mysql\": false, \"mssql\": false, \"oraclesql\": false, \"c\": false, \"csharp\": false, \"javascript\": false, \"typescript\": false, \"bash\": false, \"php\": false, \"swift\": false, \"kotlin\": false, \"dart\": false, \"golang\": false, \"ruby\": false, \"scala\": false, \"html\": false, \"pythonml\": false, \"rust\": false, \"racket\": false, \"erlang\": false, \"elixir\": false, \"pythondata\": false, \"react\": false, \"vanillajs\": false, \"postgresql\": false}", "topicTags": [ { "name": "Database", "slug": "database", "translatedName": "数据库", "__typename": "TopicTagNode" } ], "companyTagStats": null, "codeSnippets": [ { "lang": "MySQL", "langSlug": "mysql", "code": "# Write your MySQL query statement below", "__typename": "CodeSnippetNode" }, { "lang": "MS SQL Server", "langSlug": "mssql", "code": "/* Write your T-SQL query statement below */", "__typename": "CodeSnippetNode" }, { "lang": "Oracle", "langSlug": "oraclesql", "code": "/* Write your PL/SQL query statement below */", "__typename": "CodeSnippetNode" }, { "lang": "Pandas", "langSlug": "pythondata", "code": "import pandas as pd\n\ndef price_at_given_date(products: pd.DataFrame) -> pd.DataFrame:\n ", "__typename": "CodeSnippetNode" }, { "lang": "PostgreSQL", "langSlug": "postgresql", "code": "-- Write your PostgreSQL query statement below", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"24.7K\", \"totalSubmission\": \"44.2K\", \"totalAcceptedRaw\": 24695, \"totalSubmissionRaw\": 44232, \"acRate\": \"55.8%\"}", "hints": [], "solution": null, "status": null, "sampleTestCase": "{\"headers\":{\"Products\":[\"product_id\",\"new_price\",\"change_date\"]},\"rows\":{\"Products\":[[1,20,\"2019-08-14\"],[2,50,\"2019-08-14\"],[1,30,\"2019-08-15\"],[1,35,\"2019-08-16\"],[2,65,\"2019-08-17\"],[3,20,\"2019-08-18\"]]}}", "metaData": "{\"mysql\":[\"Create table If Not Exists Products (product_id int, new_price int, change_date date)\"],\"mssql\":[\"Create table Products (product_id int, new_price int, change_date date)\"],\"oraclesql\":[\"Create table Products (product_id int, new_price int, change_date date)\",\"ALTER SESSION SET nls_date_format='YYYY-MM-DD'\"],\"database\":true,\"name\":\"price_at_given_date\",\"pythondata\":[\"Products = pd.DataFrame([], columns=['product_id', 'new_price', 'change_date']).astype({'product_id':'Int64', 'new_price':'Int64', 'change_date':'datetime64[ns]'})\"],\"postgresql\":[\"\\nCreate table If Not Exists Products (product_id int, new_price int, change_date date)\"],\"database_schema\":{\"Products\":{\"product_id\":\"INT\",\"new_price\":\"INT\",\"change_date\":\"DATE\"}}}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [ "Create table If Not Exists Products (product_id int, new_price int, change_date date)", "Truncate table Products", "insert into Products (product_id, new_price, change_date) values ('1', '20', '2019-08-14')", "insert into Products (product_id, new_price, change_date) values ('2', '50', '2019-08-14')", "insert into Products (product_id, new_price, change_date) values ('1', '30', '2019-08-15')", "insert into Products (product_id, new_price, change_date) values ('1', '35', '2019-08-16')", "insert into Products (product_id, new_price, change_date) values ('2', '65', '2019-08-17')", "insert into Products (product_id, new_price, change_date) values ('3', '20', '2019-08-18')" ], "enableRunCode": true, "envInfo": "{\"mysql\":[\"MySQL\",\"
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