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99 lines
9.1 KiB
JSON
99 lines
9.1 KiB
JSON
{
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"question": {
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"questionId": "1155",
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"questionFrontendId": "1070",
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"boundTopicId": null,
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"title": "Product Sales Analysis III",
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"titleSlug": "product-sales-analysis-iii",
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"content": "<p>Table: <code>Sales</code></p>\n\n<pre>\n+-------------+-------+\n| Column Name | Type |\n+-------------+-------+\n| sale_id | int |\n| product_id | int |\n| year | int |\n| quantity | int |\n| price | int |\n+-------------+-------+\n(sale_id, year) is the primary key (combination of columns with unique values) of this table.\nproduct_id is a foreign key (reference column) to <code>Product</code> table.\nEach row of this table shows a sale on the product product_id in a certain year.\nNote that the price is per unit.\n</pre>\n\n<p> </p>\n\n<p>Table: <code>Product</code></p>\n\n<pre>\n+--------------+---------+\n| Column Name | Type |\n+--------------+---------+\n| product_id | int |\n| product_name | varchar |\n+--------------+---------+\nproduct_id is the primary key (column with unique values) of this table.\nEach row of this table indicates the product name of each product.\n</pre>\n\n<p> </p>\n\n<p>Write a solution to select the <strong>product id</strong>, <strong>year</strong>, <strong>quantity</strong>, and <strong>price</strong> for the <strong>first year</strong> of every product sold.</p>\n\n<p>Return the resulting 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> \nSales table:\n+---------+------------+------+----------+-------+\n| sale_id | product_id | year | quantity | price |\n+---------+------------+------+----------+-------+ \n| 1 | 100 | 2008 | 10 | 5000 |\n| 2 | 100 | 2009 | 12 | 5000 |\n| 7 | 200 | 2011 | 15 | 9000 |\n+---------+------------+------+----------+-------+\nProduct table:\n+------------+--------------+\n| product_id | product_name |\n+------------+--------------+\n| 100 | Nokia |\n| 200 | Apple |\n| 300 | Samsung |\n+------------+--------------+\n<strong>Output:</strong> \n+------------+------------+----------+-------+\n| product_id | first_year | quantity | price |\n+------------+------------+----------+-------+ \n| 100 | 2008 | 10 | 5000 |\n| 200 | 2011 | 15 | 9000 |\n+------------+------------+----------+-------+\n</pre>\n",
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"translatedTitle": null,
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"isPaidOnly": false,
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"difficulty": "Medium",
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"likes": 292,
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"similarQuestions": "[{\"title\": \"Product Sales Analysis II\", \"titleSlug\": \"product-sales-analysis-ii\", \"difficulty\": \"Easy\", \"translatedTitle\": null}, {\"title\": \"Product Sales Analysis IV\", \"titleSlug\": \"product-sales-analysis-iv\", \"difficulty\": \"Medium\", \"translatedTitle\": null}, {\"title\": \"Product Sales Analysis V\", \"titleSlug\": \"product-sales-analysis-v\", \"difficulty\": \"Easy\", \"translatedTitle\": null}]",
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"exampleTestcases": "{\"headers\":{\"Sales\":[\"sale_id\",\"product_id\",\"year\",\"quantity\",\"price\"],\"Product\":[\"product_id\",\"product_name\"]},\"rows\":{\"Sales\":[[1,100,2008,10,5000],[2,100,2009,12,5000],[7,200,2011,15,9000]],\"Product\":[[100,\"Nokia\"],[200,\"Apple\"],[300,\"Samsung\"]]}}",
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"categoryTitle": "Database",
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"contributors": [],
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"topicTags": [
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{
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"name": "Database",
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"slug": "database",
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"codeSnippets": [
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{
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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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"__typename": "CodeSnippetNode"
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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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"__typename": "CodeSnippetNode"
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},
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{
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"lang": "Oracle",
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"langSlug": "oraclesql",
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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(sales: pd.DataFrame, product: 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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],
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"stats": "{\"totalAccepted\": \"87K\", \"totalSubmission\": \"202.8K\", \"totalAcceptedRaw\": 86956, \"totalSubmissionRaw\": 202782, \"acRate\": \"42.9%\"}",
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"hints": [],
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"solution": {
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"id": "2133",
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"canSeeDetail": true,
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"paidOnlyVideo": true,
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},
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"status": null,
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"sampleTestCase": "{\"headers\":{\"Sales\":[\"sale_id\",\"product_id\",\"year\",\"quantity\",\"price\"],\"Product\":[\"product_id\",\"product_name\"]},\"rows\":{\"Sales\":[[1,100,2008,10,5000],[2,100,2009,12,5000],[7,200,2011,15,9000]],\"Product\":[[100,\"Nokia\"],[200,\"Apple\"],[300,\"Samsung\"]]}}",
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"metaData": "{\"mysql\": [\"Create table If Not Exists Sales (sale_id int, product_id int, year int, quantity int, price int)\", \"Create table If Not Exists Product (product_id int, product_name varchar(10))\"], \"mssql\": [\"Create table Sales (sale_id int, product_id int, year int, quantity int, price int)\", \"Create table Product (product_id int, product_name varchar(10))\"], \"oraclesql\": [\"Create table Sales (sale_id int, product_id int, year int, quantity int, price int)\", \"Create table Product (product_id int, product_name varchar(10))\"], \"database\": true, \"name\": \"sales_analysis\", \"pythondata\": [\"Sales = pd.DataFrame([], columns=['sale_id', 'product_id', 'year', 'quantity', 'price']).astype({'sale_id':'Int64', 'product_id':'Int64', 'year':'Int64', 'quantity':'Int64', 'price':'Int64'})\", \"Product = pd.DataFrame([], columns=['product_id', 'product_name']).astype({'product_id':'Int64', 'product_name':'object'})\"], \"postgresql\": [\"Create table If Not Exists Sales (sale_id int, product_id int, year int, quantity int, price int)\\n\", \"Create table If Not Exists Product (product_id int, product_name varchar(10))\"], \"database_schema\": {\"Sales\": {\"sale_id\": \"INT\", \"product_id\": \"INT\", \"year\": \"INT\", \"quantity\": \"INT\", \"price\": \"INT\"}, \"Product\": {\"product_id\": \"INT\", \"product_name\": \"VARCHAR(10)\"}}}",
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"judgerAvailable": true,
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"judgeType": "large",
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"mysqlSchemas": [
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"Create table If Not Exists Sales (sale_id int, product_id int, year int, quantity int, price int)",
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"Create table If Not Exists Product (product_id int, product_name varchar(10))",
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"Truncate table Sales",
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"insert into Sales (sale_id, product_id, year, quantity, price) values ('1', '100', '2008', '10', '5000')",
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"insert into Sales (sale_id, product_id, year, quantity, price) values ('2', '100', '2009', '12', '5000')",
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"insert into Sales (sale_id, product_id, year, quantity, price) values ('7', '200', '2011', '15', '9000')",
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"Truncate table Product",
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"insert into Product (product_id, product_name) values ('100', 'Nokia')",
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"insert into Product (product_id, product_name) values ('200', 'Apple')",
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"insert into Product (product_id, product_name) values ('300', 'Samsung')"
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],
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"enableRunCode": true,
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"enableTestMode": false,
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"enableDebugger": false,
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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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"libraryUrl": null,
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