Table: Signups
\n+----------------+----------+\n| Column Name | Type |\n+----------------+----------+\n| user_id | int |\n| time_stamp | datetime |\n+----------------+----------+\nuser_id is the column of unique values for this table.\nEach row contains information about the signup time for the user with ID user_id.\n\n\n
\n\n
Table: Confirmations
\n+----------------+----------+\n| Column Name | Type |\n+----------------+----------+\n| user_id | int |\n| time_stamp | datetime |\n| action | ENUM |\n+----------------+----------+\n(user_id, time_stamp) is the primary key (combination of columns with unique values) for this table.\nuser_id is a foreign key (reference column) to the Signups table.\naction is an ENUM (category) of the type ('confirmed', 'timeout')\nEach row of this table indicates that the user with ID user_id requested a confirmation message at time_stamp and that confirmation message was either confirmed ('confirmed') or expired without confirming ('timeout').\n\n\n\n\n
The confirmation rate of a user is the number of 'confirmed' messages divided by the total number of requested confirmation messages. The confirmation rate of a user that did not request any confirmation messages is 0. Round the confirmation rate to two decimal places.
Write a solution to find the confirmation rate of each user.
\n\nReturn the result table in any order.
\n\nThe result format is in the following example.
\n\n\n
Example 1:
\n\n\nInput: \nSignups table:\n+---------+---------------------+\n| user_id | time_stamp |\n+---------+---------------------+\n| 3 | 2020-03-21 10:16:13 |\n| 7 | 2020-01-04 13:57:59 |\n| 2 | 2020-07-29 23:09:44 |\n| 6 | 2020-12-09 10:39:37 |\n+---------+---------------------+\nConfirmations table:\n+---------+---------------------+-----------+\n| user_id | time_stamp | action |\n+---------+---------------------+-----------+\n| 3 | 2021-01-06 03:30:46 | timeout |\n| 3 | 2021-07-14 14:00:00 | timeout |\n| 7 | 2021-06-12 11:57:29 | confirmed |\n| 7 | 2021-06-13 12:58:28 | confirmed |\n| 7 | 2021-06-14 13:59:27 | confirmed |\n| 2 | 2021-01-22 00:00:00 | confirmed |\n| 2 | 2021-02-28 23:59:59 | timeout |\n+---------+---------------------+-----------+\nOutput: \n+---------+-------------------+\n| user_id | confirmation_rate |\n+---------+-------------------+\n| 6 | 0.00 |\n| 3 | 0.00 |\n| 7 | 1.00 |\n| 2 | 0.50 |\n+---------+-------------------+\nExplanation: \nUser 6 did not request any confirmation messages. The confirmation rate is 0.\nUser 3 made 2 requests and both timed out. The confirmation rate is 0.\nUser 7 made 3 requests and all were confirmed. The confirmation rate is 1.\nUser 2 made 2 requests where one was confirmed and the other timed out. The confirmation rate is 1 / 2 = 0.5.\n\n", "translatedTitle": "确认率", "translatedContent": "
表: Signups
\n+----------------+----------+\n| Column Name | Type |\n+----------------+----------+\n| user_id | int |\n| time_stamp | datetime |\n+----------------+----------+\nUser_id是该表的主键。\n每一行都包含ID为user_id的用户的注册时间信息。\n\n\n
\n\n
表: Confirmations
\n+----------------+----------+\n| Column Name | Type |\n+----------------+----------+\n| user_id | int |\n| time_stamp | datetime |\n| action | ENUM |\n+----------------+----------+\n(user_id, time_stamp)是该表的主键。\nuser_id是一个引用到注册表的外键。\naction是类型为('confirmed'， 'timeout')的ENUM\n该表的每一行都表示ID为user_id的用户在time_stamp请求了一条确认消息，该确认消息要么被确认('confirmed')，要么被过期('timeout')。\n\n\n\n\n
用户的 确认率 是 'confirmed' 消息的数量除以请求的确认消息的总数。没有请求任何确认消息的用户的确认率为 0 。确认率四舍五入到 小数点后两位 。
编写一个SQL查询来查找每个用户的 确认率 。
\n
\n以 任意顺序 返回结果表。
\n
\n查询结果格式如下所示。
\n
\n示例1:
\n输入：\nSignups 表:\n+---------+---------------------+\n| user_id | time_stamp |\n+---------+---------------------+\n| 3 | 2020-03-21 10:16:13 |\n| 7 | 2020-01-04 13:57:59 |\n| 2 | 2020-07-29 23:09:44 |\n| 6 | 2020-12-09 10:39:37 |\n+---------+---------------------+\nConfirmations 表:\n+---------+---------------------+-----------+\n| user_id | time_stamp | action |\n+---------+---------------------+-----------+\n| 3 | 2021-01-06 03:30:46 | timeout |\n| 3 | 2021-07-14 14:00:00 | timeout |\n| 7 | 2021-06-12 11:57:29 | confirmed |\n| 7 | 2021-06-13 12:58:28 | confirmed |\n| 7 | 2021-06-14 13:59:27 | confirmed |\n| 2 | 2021-01-22 00:00:00 | confirmed |\n| 2 | 2021-02-28 23:59:59 | timeout |\n+---------+---------------------+-----------+\n输出: \n+---------+-------------------+\n| user_id | confirmation_rate |\n+---------+-------------------+\n| 6 | 0.00 |\n| 3 | 0.00 |\n| 7 | 1.00 |\n| 2 | 0.50 |\n+---------+-------------------+\n解释:\n用户 6 没有请求任何确认消息。确认率为 0。\n用户 3 进行了 2 次请求，都超时了。确认率为 0。\n用户 7 提出了 3 个请求，所有请求都得到了确认。确认率为 1。\n用户 2 做了 2 个请求，其中一个被确认，另一个超时。确认率为 1 / 2 = 0.5。\n", "isPaidOnly": false, "difficulty": "Medium", "likes": 58, "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 confirmation_rate(signups: pd.DataFrame, confirmations: pd.DataFrame) -> pd.DataFrame:\n ", "__typename": "CodeSnippetNode" }, { "lang": "PostgreSQL", "langSlug": "postgresql", "code": "-- Write your PostgreSQL query statement below", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"17.6K\", \"totalSubmission\": \"28.4K\", \"totalAcceptedRaw\": 17602, \"totalSubmissionRaw\": 28350, \"acRate\": \"62.1%\"}", "hints": [], "solution": null, "status": null, "sampleTestCase": "{\"headers\": {\"Signups\": [\"user_id\", \"time_stamp\"], \"Confirmations\": [\"user_id\", \"time_stamp\", \"action\"]}, \"rows\": {\"Signups\": [[3, \"2020-03-21 10:16:13\"], [7, \"2020-01-04 13:57:59\"], [2, \"2020-07-29 23:09:44\"], [6, \"2020-12-09 10:39:37\"]], \"Confirmations\": [[3, \"2021-01-06 03:30:46\", \"timeout\"], [3, \"2021-07-14 14:00:00\", \"timeout\"], [7, \"2021-06-12 11:57:29\", \"confirmed\"], [7, \"2021-06-13 12:58:28\", \"confirmed\"], [7, \"2021-06-14 13:59:27\", \"confirmed\"], [2, \"2021-01-22 00:00:00\", \"confirmed\"], [2, \"2021-02-28 23:59:59\", \"timeout\"]]}}", "metaData": "{\"mysql\":[\"Create table If Not Exists Signups (user_id int, time_stamp datetime)\",\"Create table If Not Exists Confirmations (user_id int, time_stamp datetime, action ENUM('confirmed','timeout'))\"],\"mssql\":[\"Create table Signups (user_id int, time_stamp datetime)\",\"Create table Confirmations (user_id int, time_stamp datetime, action VARCHAR(10) NOT NULL CHECK (action IN ('confirmed','timeout')))\"],\"oraclesql\":[\"Create table Signups (user_id int, time_stamp date)\",\"Create table Confirmations (user_id int, time_stamp date, action VARCHAR(10) NOT NULL CHECK (action IN ('confirmed','timeout')))\",\"ALTER SESSION SET nls_date_format='YYYY-MM-DD HH24:MI:SS'\"],\"database\":true,\"name\":\"confirmation_rate\",\"pythondata\":[\"Signups = pd.DataFrame([], columns=['user_id', 'time_stamp']).astype({'user_id':'Int64', 'time_stamp':'datetime64[ns]'})\",\"Confirmations = pd.DataFrame([], columns=['user_id', 'time_stamp', 'action']).astype({'user_id':'Int64', 'time_stamp':'datetime64[ns]', 'action':'object'})\"],\"postgresql\":[\"Create table If Not Exists Signups (user_id int, time_stamp timestamp)\\n\",\"Create table If Not Exists Confirmations (user_id int, time_stamp timestamp, action VARCHAR(30) CHECK (action IN ('confirmed','timeout')))\\n\"],\"database_schema\":{\"Signups\":{\"user_id\":\"INT\",\"time_stamp\":\"DATETIME\"},\"Confirmations\":{\"user_id\":\"INT\",\"time_stamp\":\"DATETIME\",\"action\":\"ENUM('confirmed', 'timeout')\"}}}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [ "Create table If Not Exists Signups (user_id int, time_stamp datetime)", "Create table If Not Exists Confirmations (user_id int, time_stamp datetime, action ENUM('confirmed','timeout'))", "Truncate table Signups", "insert into Signups (user_id, time_stamp) values ('3', '2020-03-21 10:16:13')", "insert into Signups (user_id, time_stamp) values ('7', '2020-01-04 13:57:59')", "insert into Signups (user_id, time_stamp) values ('2', '2020-07-29 23:09:44')", "insert into Signups (user_id, time_stamp) values ('6', '2020-12-09 10:39:37')", "Truncate table Confirmations", "insert into Confirmations (user_id, time_stamp, action) values ('3', '2021-01-06 03:30:46', 'timeout')", "insert into Confirmations 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"exampleTestcases": "{\"headers\": {\"Signups\": [\"user_id\", \"time_stamp\"], \"Confirmations\": [\"user_id\", \"time_stamp\", \"action\"]}, \"rows\": {\"Signups\": [[3, \"2020-03-21 10:16:13\"], [7, \"2020-01-04 13:57:59\"], [2, \"2020-07-29 23:09:44\"], [6, \"2020-12-09 10:39:37\"]], \"Confirmations\": [[3, \"2021-01-06 03:30:46\", \"timeout\"], [3, \"2021-07-14 14:00:00\", \"timeout\"], [7, \"2021-06-12 11:57:29\", \"confirmed\"], [7, \"2021-06-13 12:58:28\", \"confirmed\"], [7, \"2021-06-14 13:59:27\", \"confirmed\"], [2, \"2021-01-22 00:00:00\", \"confirmed\"], [2, \"2021-02-28 23:59:59\", \"timeout\"]]}}",
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