{ "data": { "question": { "questionId": "1827", "questionFrontendId": "1683", "boundTopicId": null, "title": "Invalid Tweets", "titleSlug": "invalid-tweets", "content": "

Table: Tweets

\n\n
\n+----------------+---------+\n| Column Name    | Type    |\n+----------------+---------+\n| tweet_id       | int     |\n| content        | varchar |\n+----------------+---------+\ntweet_id is the primary key (column with unique values) for this table.\nThis table contains all the tweets in a social media app.\n
\n\n

 

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Write a solution to find the IDs of the invalid tweets. The tweet is invalid if the number of characters used in the content of the tweet is strictly greater than 15.

\n\n

Return the result table in any order.

\n\n

The result format is in the following example.

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Example 1:

\n\n
\nInput: \nTweets table:\n+----------+----------------------------------+\n| tweet_id | content                          |\n+----------+----------------------------------+\n| 1        | Vote for Biden                   |\n| 2        | Let us make America great again! |\n+----------+----------------------------------+\nOutput: \n+----------+\n| tweet_id |\n+----------+\n| 2        |\n+----------+\nExplanation: \nTweet 1 has length = 14. It is a valid tweet.\nTweet 2 has length = 32. It is an invalid tweet.\n
\n", "translatedTitle": null, "translatedContent": null, "isPaidOnly": false, "difficulty": "Easy", "likes": 698, "dislikes": 230, "isLiked": null, "similarQuestions": "[]", "exampleTestcases": "{\"headers\":{\"Tweets\":[\"tweet_id\",\"content\"]},\"rows\":{\"Tweets\":[[1,\"Vote for Biden\"],[2,\"Let us make America great again!\"]]}}", "categoryTitle": "Database", "contributors": [], "topicTags": [ { "name": "Database", "slug": "database", "translatedName": null, "__typename": "TopicTagNode" } ], "companyTagStats": null, "codeSnippets": [ { "lang": "MySQL", "langSlug": "mysql", "code": "# Write your MySQL query statement below\n", "__typename": "CodeSnippetNode" }, { "lang": "MS SQL Server", "langSlug": "mssql", "code": "/* Write your T-SQL query statement below */\n", "__typename": "CodeSnippetNode" }, { "lang": "Oracle", "langSlug": "oraclesql", "code": "/* Write your PL/SQL query statement below */\n", "__typename": "CodeSnippetNode" }, { "lang": "Pandas", "langSlug": "pythondata", "code": "import pandas as pd\n\ndef invalid_tweets(tweets: pd.DataFrame) -> pd.DataFrame:\n ", "__typename": "CodeSnippetNode" }, { "lang": "PostgreSQL", "langSlug": "postgresql", "code": "-- Write your PostgreSQL query statement below\n", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"236.7K\", \"totalSubmission\": \"279.9K\", \"totalAcceptedRaw\": 236718, \"totalSubmissionRaw\": 279903, \"acRate\": \"84.6%\"}", "hints": [], "solution": { "id": "1940", "canSeeDetail": false, "paidOnly": true, "hasVideoSolution": false, "paidOnlyVideo": true, "__typename": "ArticleNode" }, "status": null, "sampleTestCase": "{\"headers\":{\"Tweets\":[\"tweet_id\",\"content\"]},\"rows\":{\"Tweets\":[[1,\"Vote for Biden\"],[2,\"Let us make America great again!\"]]}}", "metaData": "{\"mysql\": [\"Create table If Not Exists Tweets(tweet_id int, content varchar(50))\"], \"mssql\": [\"Create table Tweets(tweet_id int, content varchar(50))\"], \"oraclesql\": [\"Create table Tweets(tweet_id int, content varchar(50))\"], \"database\": true, \"name\": \"invalid_tweets\", \"pythondata\": [\"Tweets = pd.DataFrame([], columns=['tweet_id', 'content']).astype({'tweet_id':'Int64', 'content':'object'})\"], \"postgresql\": [\"Create table If Not Exists Tweets(tweet_id int, content varchar(50))\"], \"database_schema\": {\"Tweets\": {\"tweet_id\": \"INT\", \"content\": \"VARCHAR(50)\"}}}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [ "Create table If Not Exists Tweets(tweet_id int, content varchar(50))", "Truncate table Tweets", "insert into Tweets (tweet_id, content) values ('1', 'Vote for Biden')", "insert into Tweets (tweet_id, content) values ('2', 'Let us make America great again!')" ], "enableRunCode": true, "enableTestMode": false, "enableDebugger": false, "envInfo": "{\"mysql\": [\"MySQL\", \"

MySQL 8.0.

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mssql server 2019.

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Oracle Sql 11.2.

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Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0

\"], \"postgresql\": [\"PostgreSQL\", \"

PostgreSQL 16

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