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88 lines
8.4 KiB
JSON
88 lines
8.4 KiB
JSON
{
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"data": {
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"question": {
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"questionId": "3711",
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"questionFrontendId": "3374",
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"boundTopicId": null,
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"title": "First Letter Capitalization II",
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"titleSlug": "first-letter-capitalization-ii",
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"content": "<p>Table: <code>user_content</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| content_id | int |\n| content_text| varchar |\n+-------------+---------+\ncontent_id is the unique key for this table.\nEach row contains a unique ID and the corresponding text content.\n</pre>\n\n<p>Write a solution to transform the text in the <code>content_text</code> column by applying the following rules:</p>\n\n<ul>\n\t<li>Convert the <strong>first letter</strong> of each word to <strong>uppercase</strong> and the <strong>remaining</strong> letters to <strong>lowercase</strong></li>\n\t<li>Special handling for words containing special characters:\n\t<ul>\n\t\t<li>For words connected with a hyphen <code>-</code>, <strong>both parts</strong> should be <strong>capitalized</strong> (<strong>e.g.</strong>, top-rated → Top-Rated)</li>\n\t</ul>\n\t</li>\n\t<li>All other <strong>formatting</strong> and <strong>spacing</strong> should remain <strong>unchanged</strong></li>\n</ul>\n\n<p>Return <em>the result table that includes both the original <code>content_text</code> and the modified text following the above rules</em>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example:</strong></p>\n\n<div class=\"example-block\">\n<p><strong>Input:</strong></p>\n\n<p>user_content table:</p>\n\n<pre class=\"example-io\">\n+------------+---------------------------------+\n| content_id | content_text |\n+------------+---------------------------------+\n| 1 | hello world of SQL |\n| 2 | the QUICK-brown fox |\n| 3 | modern-day DATA science |\n| 4 | web-based FRONT-end development |\n+------------+---------------------------------+\n</pre>\n\n<p><strong>Output:</strong></p>\n\n<pre class=\"example-io\">\n+------------+---------------------------------+---------------------------------+\n| content_id | original_text | converted_text |\n+------------+---------------------------------+---------------------------------+\n| 1 | hello world of SQL | Hello World Of Sql |\n| 2 | the QUICK-brown fox | The Quick-Brown Fox |\n| 3 | modern-day DATA science | Modern-Day Data Science |\n| 4 | web-based FRONT-end development | Web-Based Front-End Development |\n+------------+---------------------------------+---------------------------------+\n</pre>\n\n<p><strong>Explanation:</strong></p>\n\n<ul>\n\t<li>For content_id = 1:\n\t<ul>\n\t\t<li>Each word's first letter is capitalized: "Hello World Of Sql"</li>\n\t</ul>\n\t</li>\n\t<li>For content_id = 2:\n\t<ul>\n\t\t<li>Contains the hyphenated word "QUICK-brown" which becomes "Quick-Brown"</li>\n\t\t<li>Other words follow normal capitalization rules</li>\n\t</ul>\n\t</li>\n\t<li>For content_id = 3:\n\t<ul>\n\t\t<li>Hyphenated word "modern-day" becomes "Modern-Day"</li>\n\t\t<li>"DATA" is converted to "Data"</li>\n\t</ul>\n\t</li>\n\t<li>For content_id = 4:\n\t<ul>\n\t\t<li>Contains two hyphenated words: "web-based" → "Web-Based"</li>\n\t\t<li>And "FRONT-end" → "Front-End"</li>\n\t</ul>\n\t</li>\n</ul>\n</div>\n",
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"translatedTitle": null,
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"translatedContent": null,
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"isPaidOnly": false,
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"difficulty": "Hard",
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"likes": 10,
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"dislikes": 1,
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"isLiked": null,
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"similarQuestions": "[]",
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"exampleTestcases": "{\"headers\":{\"user_content\":[\"content_id\",\"content_text\"]},\"rows\":{\"user_content\":[[1,\"hello world of SQL\"],[2,\"the QUICK-brown fox\"],[3,\"modern-day DATA science\"],[4,\"web-based FRONT-end development\"]]}}",
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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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"translatedName": null,
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"__typename": "TopicTagNode"
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}
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],
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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 capitalize_content(user_content: 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\": \"788\", \"totalSubmission\": \"973\", \"totalAcceptedRaw\": 788, \"totalSubmissionRaw\": 973, \"acRate\": \"81.0%\"}",
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"hints": [],
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"solution": null,
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"status": null,
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"sampleTestCase": "{\"headers\":{\"user_content\":[\"content_id\",\"content_text\"]},\"rows\":{\"user_content\":[[1,\"hello world of SQL\"],[2,\"the QUICK-brown fox\"],[3,\"modern-day DATA science\"],[4,\"web-based FRONT-end development\"]]}}",
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"metaData": "{\"mysql\": [\"CREATE TABLE If not exists user_content (\\n content_id INT,\\n content_text VARCHAR(255)\\n)\"], \"mssql\": [\"CREATE TABLE user_content (\\n content_id INT,\\n content_text VARCHAR(255)\\n)\"], \"oraclesql\": [\"CREATE TABLE user_content (\\n content_id NUMBER,\\n content_text VARCHAR2(255)\\n)\"], \"database\": true, \"name\": \"capitalize_content\", \"pythondata\": [\"user_content = pd.DataFrame({\\n 'content_id': pd.Series(dtype='int'),\\n 'content_text': pd.Series(dtype='str')\\n})\"], \"postgresql\": [\"CREATE TABLE IF NOT EXISTS user_content (\\n content_id SERIAL PRIMARY KEY,\\n content_text VARCHAR(255)\\n);\\n\"], \"database_schema\": {\"user_content\": {\"content_id\": \"INT\", \"content_text\": \"VARCHAR(255)\"}}}",
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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 user_content (\n content_id INT,\n content_text VARCHAR(255)\n)",
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"Truncate table user_content",
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"insert into user_content (content_id, content_text) values ('1', 'hello world of SQL')",
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"insert into user_content (content_id, content_text) values ('2', 'the QUICK-brown fox')",
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"insert into user_content (content_id, content_text) values ('3', 'modern-day DATA science')",
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"insert into user_content (content_id, content_text) values ('4', 'web-based FRONT-end development')"
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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 2.2.2 and NumPy 1.26.4</p>\"], \"postgresql\": [\"PostgreSQL\", \"<p>PostgreSQL 16</p>\"]}",
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"libraryUrl": null,
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"challengeQuestion": null,
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"__typename": "QuestionNode"
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}
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} |