leetcode-problemset/leetcode-cn/originData/average-selling-price.json

{
    "data": {
        "question": {
            "questionId": "1390",
            "questionFrontendId": "1251",
            "categoryTitle": "Database",
            "boundTopicId": 41811,
            "title": "Average Selling Price",
            "titleSlug": "average-selling-price",
            "content": "<p>Table: <code>Prices</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name   | Type    |\n+---------------+---------+\n| product_id    | int     |\n| start_date    | date    |\n| end_date      | date    |\n| price         | int     |\n+---------------+---------+\n(product_id, start_date, end_date) is the primary key (combination of columns with unique values) for this table.\nEach row of this table indicates the price of the product_id in the period from start_date to end_date.\nFor each product_id there will be no two overlapping periods. That means there will be no two intersecting periods for the same product_id.\n</pre>\n\n<p>&nbsp;</p>\n\n<p>Table: <code>UnitsSold</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name   | Type    |\n+---------------+---------+\n| product_id    | int     |\n| purchase_date | date    |\n| units         | int     |\n+---------------+---------+\nThis table may contain duplicate rows.\nEach row of this table indicates the date, units, and product_id of each product sold. \n</pre>\n\n<p>&nbsp;</p>\n\n<p>Write a solution to find the average selling price for each product. <code>average_price</code> should be <strong>rounded to 2 decimal places</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> \nPrices table:\n+------------+------------+------------+--------+\n| product_id | start_date | end_date   | price  |\n+------------+------------+------------+--------+\n| 1          | 2019-02-17 | 2019-02-28 | 5      |\n| 1          | 2019-03-01 | 2019-03-22 | 20     |\n| 2          | 2019-02-01 | 2019-02-20 | 15     |\n| 2          | 2019-02-21 | 2019-03-31 | 30     |\n+------------+------------+------------+--------+\nUnitsSold table:\n+------------+---------------+-------+\n| product_id | purchase_date | units |\n+------------+---------------+-------+\n| 1          | 2019-02-25    | 100   |\n| 1          | 2019-03-01    | 15    |\n| 2          | 2019-02-10    | 200   |\n| 2          | 2019-03-22    | 30    |\n+------------+---------------+-------+\n<strong>Output:</strong> \n+------------+---------------+\n| product_id | average_price |\n+------------+---------------+\n| 1          | 6.96          |\n| 2          | 16.96         |\n+------------+---------------+\n<strong>Explanation:</strong> \nAverage selling price = Total Price of Product / Number of products sold.\nAverage selling price for product 1 = ((100 * 5) + (15 * 20)) / 115 = 6.96\nAverage selling price for product 2 = ((200 * 15) + (30 * 30)) / 230 = 16.96\n</pre>\n",
            "translatedTitle": "平均售价",
            "translatedContent": "<p>表：<code>Prices</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name   | Type    |\n+---------------+---------+\n| product_id    | int     |\n| start_date    | date    |\n| end_date      | date    |\n| price         | int     |\n+---------------+---------+\n(product_id，start_date，end_date) 是 <code>prices</code> 表的主键（具有唯一值的列的组合）。\n<code>prices</code> 表的每一行表示的是某个产品在一段时期内的价格。\n每个产品的对应时间段是不会重叠的，这也意味着同一个产品的价格时段不会出现交叉。</pre>\n\n<p>&nbsp;</p>\n\n<p>表：<code>UnitsSold</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name   | Type    |\n+---------------+---------+\n| product_id    | int     |\n| purchase_date | date    |\n| units         | int     |\n+---------------+---------+\n<span style=\"white-space: pre-wrap;\">该表可能包含重复数据</span>。\n<span style=\"white-space: pre-wrap;\">该</span>表的每一行表示的是每种产品的出售日期，单位和产品 id。</pre>\n\n<p>&nbsp;</p>\n\n<p>编写解决方案以查找每种产品的平均售价。<code>average_price</code> 应该 <strong>四舍五入到小数点后两位</strong>。</p>\n\n<p>返回结果表 <strong>无顺序要求</strong> 。</p>\n\n<p>结果格式如下例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1：</strong></p>\n\n<pre>\n<strong>输入：</strong>\nPrices table:\n+------------+------------+------------+--------+\n| product_id | start_date | end_date   | price  |\n+------------+------------+------------+--------+\n| 1          | 2019-02-17 | 2019-02-28 | 5      |\n| 1          | 2019-03-01 | 2019-03-22 | 20     |\n| 2          | 2019-02-01 | 2019-02-20 | 15     |\n| 2          | 2019-02-21 | 2019-03-31 | 30     |\n+------------+------------+------------+--------+\nUnitsSold table:\n+------------+---------------+-------+\n| product_id | purchase_date | units |\n+------------+---------------+-------+\n| 1          | 2019-02-25    | 100   |\n| 1          | 2019-03-01    | 15    |\n| 2          | 2019-02-10    | 200   |\n| 2          | 2019-03-22    | 30    |\n+------------+---------------+-------+\n<strong>输出：</strong>\n+------------+---------------+\n| product_id | average_price |\n+------------+---------------+\n| 1          | 6.96          |\n| 2          | 16.96         |\n+------------+---------------+\n<strong>解释：</strong>\n平均售价 = 产品总价 / 销售的产品数量。\n产品 1 的平均售价 = ((100 * 5)+(15 * 20) )/ 115 = 6.96\n产品 2 的平均售价 = ((200 * 15)+(30 * 30) )/ 230 = 16.96</pre>\n",
            "isPaidOnly": false,
            "difficulty": "Easy",
            "likes": 110,
            "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 average_selling_price(prices: pd.DataFrame, units_sold: pd.DataFrame) -> pd.DataFrame:\n    ",
                    "__typename": "CodeSnippetNode"
                },
                {
                    "lang": "PostgreSQL",
                    "langSlug": "postgresql",
                    "code": "-- Write your PostgreSQL query statement below",
                    "__typename": "CodeSnippetNode"
                }
            ],
            "stats": "{\"totalAccepted\": \"36.8K\", \"totalSubmission\": \"64.6K\", \"totalAcceptedRaw\": 36788, \"totalSubmissionRaw\": 64602, \"acRate\": \"56.9%\"}",
            "hints": [],
            "solution": null,
            "status": null,
            "sampleTestCase": "{\"headers\":{\"Prices\":[\"product_id\",\"start_date\",\"end_date\",\"price\"],\"UnitsSold\":[\"product_id\",\"purchase_date\",\"units\"]},\"rows\":{\"Prices\":[[1,\"2019-02-17\",\"2019-02-28\",5],[1,\"2019-03-01\",\"2019-03-22\",20],[2,\"2019-02-01\",\"2019-02-20\",15],[2,\"2019-02-21\",\"2019-03-31\",30]],\"UnitsSold\":[[1,\"2019-02-25\",100],[1,\"2019-03-01\",15],[2,\"2019-02-10\",200],[2,\"2019-03-22\",30]]}}",
            "metaData": "{\"mysql\":[\"Create table If Not Exists Prices (product_id int, start_date date, end_date date, price int)\",\"Create table If Not Exists UnitsSold (product_id int, purchase_date date, units int)\"],\"mssql\":[\"Create table Prices (product_id int, start_date date, end_date date, price int)\",\"Create table UnitsSold (product_id int, purchase_date date, units int)\"],\"oraclesql\":[\"Create table Prices (product_id int, start_date date, end_date date, price int)\",\"Create table UnitsSold (product_id int, purchase_date date, units int)\",\"ALTER SESSION SET nls_date_format='YYYY-MM-DD'\"],\"database\":true,\"name\":\"average_selling_price\",\"pythondata\":[\"Prices = pd.DataFrame([], columns=['product_id', 'start_date', 'end_date', 'price']).astype({'product_id':'Int64', 'start_date':'datetime64[ns]', 'end_date':'datetime64[ns]', 'price':'Int64'})\",\"UnitsSold = pd.DataFrame([], columns=['product_id', 'purchase_date', 'units']).astype({'product_id':'Int64', 'purchase_date':'datetime64[ns]', 'units':'Int64'})\"],\"postgresql\":[\"\\nCreate table If Not Exists Prices (product_id int, start_date date, end_date date, price int)\\n\",\"Create table If Not Exists UnitsSold (product_id int, purchase_date date, units int)\"],\"database_schema\":{\"Prices\":{\"product_id\":\"INT\",\"start_date\":\"DATE\",\"end_date\":\"DATE\",\"price\":\"INT\"},\"UnitsSold\":{\"product_id\":\"INT\",\"purchase_date\":\"DATE\",\"units\":\"INT\"}}}",
            "judgerAvailable": true,
            "judgeType": "large",
            "mysqlSchemas": [
                "Create table If Not Exists Prices (product_id int, start_date date, end_date date, price int)",
                "Create table If Not Exists UnitsSold (product_id int, purchase_date date, units int)",
                "Truncate table Prices",
                "insert into Prices (product_id, start_date, end_date, price) values ('1', '2019-02-17', '2019-02-28', '5')",
                "insert into Prices (product_id, start_date, end_date, price) values ('1', '2019-03-01', '2019-03-22', '20')",
                "insert into Prices (product_id, start_date, end_date, price) values ('2', '2019-02-01', '2019-02-20', '15')",
                "insert into Prices (product_id, start_date, end_date, price) values ('2', '2019-02-21', '2019-03-31', '30')",
                "Truncate table UnitsSold",
                "insert into UnitsSold (product_id, purchase_date, units) values ('1', '2019-02-25', '100')",
                "insert into UnitsSold (product_id, purchase_date, units) values ('1', '2019-03-01', '15')",
                "insert into UnitsSold (product_id, purchase_date, units) values ('2', '2019-02-10', '200')",
                "insert into UnitsSold (product_id, purchase_date, units) values ('2', '2019-03-22', '30')"
            ],
            "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 2.0.2 and NumPy 1.25.0<\\/p>\"],\"postgresql\":[\"PostgreSQL\",\"<p>PostgreSQL 16<\\/p>\"]}",
            "book": null,
            "isSubscribed": false,
            "isDailyQuestion": false,
            "dailyRecordStatus": null,
            "editorType": "CKEDITOR",
            "ugcQuestionId": null,
            "style": "LEETCODE",
            "exampleTestcases": "{\"headers\":{\"Prices\":[\"product_id\",\"start_date\",\"end_date\",\"price\"],\"UnitsSold\":[\"product_id\",\"purchase_date\",\"units\"]},\"rows\":{\"Prices\":[[1,\"2019-02-17\",\"2019-02-28\",5],[1,\"2019-03-01\",\"2019-03-22\",20],[2,\"2019-02-01\",\"2019-02-20\",15],[2,\"2019-02-21\",\"2019-03-31\",30]],\"UnitsSold\":[[1,\"2019-02-25\",100],[1,\"2019-03-01\",15],[2,\"2019-02-10\",200],[2,\"2019-03-22\",30]]}}",
            "__typename": "QuestionNode"
        }
    }
}