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https://gitee.com/coder-xiaomo/leetcode-problemset
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60 lines
4.9 KiB
JSON
60 lines
4.9 KiB
JSON
{
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"data": {
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"question": {
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"questionId": "3339",
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"questionFrontendId": "3055",
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"boundTopicId": null,
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"title": "Top Percentile Fraud",
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"titleSlug": "top-percentile-fraud",
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"content": null,
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"translatedTitle": null,
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"translatedContent": null,
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"isPaidOnly": true,
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"difficulty": "Medium",
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"likes": 1,
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"dislikes": 3,
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"isLiked": null,
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"similarQuestions": "[]",
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"exampleTestcases": "{\"headers\":{\"Fraud\":[\"policy_id\",\"state\",\"fraud_score\"]},\"rows\":{\"Fraud\":[[1,\"California\",0.92],[2,\"California\",0.68],[3,\"California\",0.17],[4,\"New York\",0.94],[5,\"New York\",0.81],[6,\"New York\",0.77],[7,\"Texas\",0.98],[8,\"Texas\",0.97],[9,\"Texas\",0.96],[10,\"Florida\",0.97],[11,\"Florida\",0.98],[12,\"Florida\",0.78],[13,\"Florida\",0.88],[14,\"Florida\",0.66]]}}",
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"categoryTitle": "Database",
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"contributors": [],
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"topicTags": [],
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"companyTagStats": null,
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"codeSnippets": null,
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"stats": "{\"totalAccepted\": \"141\", \"totalSubmission\": \"210\", \"totalAcceptedRaw\": 141, \"totalSubmissionRaw\": 210, \"acRate\": \"67.1%\"}",
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"hints": [],
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"solution": null,
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"status": null,
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"sampleTestCase": "{\"headers\":{\"Fraud\":[\"policy_id\",\"state\",\"fraud_score\"]},\"rows\":{\"Fraud\":[[1,\"California\",0.92],[2,\"California\",0.68],[3,\"California\",0.17],[4,\"New York\",0.94],[5,\"New York\",0.81],[6,\"New York\",0.77],[7,\"Texas\",0.98],[8,\"Texas\",0.97],[9,\"Texas\",0.96],[10,\"Florida\",0.97],[11,\"Florida\",0.98],[12,\"Florida\",0.78],[13,\"Florida\",0.88],[14,\"Florida\",0.66]]}}",
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"metaData": "{\"mysql\": [\"Create table If Not Exists Fraud (policy_id int, state varchar(50), fraud_score decimal(5,2))\"], \"mssql\": [\"Create table Fraud (policy_id int, state varchar(50), fraud_score decimal(5,2))\"], \"oraclesql\": [\"Create table Fraud (policy_id int, state varchar(50), fraud_score decimal(10,2))\"], \"database\": true, \"name\": \"top_percentile_fraud\", \"pythondata\": [\"Fraud = pd.DataFrame([], columns=['policy_id', 'state', 'fraud_score']).astype({'policy_id':'Int64', 'state':'object', 'fraud_score':'Float64'})\\n\"], \"postgresql\": [\"Create table If Not Exists Fraud (policy_id int, state varchar(50), fraud_score decimal(5,2))\\n\"], \"database_schema\": {\"Fraud\": {\"policy_id\": \"INT\", \"state\": \"VARCHAR(50)\", \"fraud_score\": \"DECIMAL(5, 2)\"}}}",
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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 Fraud (policy_id int, state varchar(50), fraud_score decimal(5,2))",
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"Truncate table Fraud",
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"insert into Fraud (policy_id, state, fraud_score) values ('1', 'California', '0.92')",
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"insert into Fraud (policy_id, state, fraud_score) values ('2', 'California', '0.68')",
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"insert into Fraud (policy_id, state, fraud_score) values ('3', 'California', '0.17')",
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"insert into Fraud (policy_id, state, fraud_score) values ('4', 'New York', '0.94')",
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"insert into Fraud (policy_id, state, fraud_score) values ('5', 'New York', '0.81')",
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"insert into Fraud (policy_id, state, fraud_score) values ('6', 'New York', '0.77')",
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"insert into Fraud (policy_id, state, fraud_score) values ('7', 'Texas', '0.98')",
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"insert into Fraud (policy_id, state, fraud_score) values ('8', 'Texas', '0.97')",
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"insert into Fraud (policy_id, state, fraud_score) values ('9', 'Texas', '0.96')",
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"insert into Fraud (policy_id, state, fraud_score) values ('10', 'Florida', '0.97')",
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"insert into Fraud (policy_id, state, fraud_score) values ('11', 'Florida', '0.98')",
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"insert into Fraud (policy_id, state, fraud_score) values ('12', 'Florida', '0.78')",
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"insert into Fraud (policy_id, state, fraud_score) values ('13', 'Florida', '0.88')",
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"insert into Fraud (policy_id, state, fraud_score) values ('14', 'Florida', '0.66')"
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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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"adminUrl": null,
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"challengeQuestion": null,
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"__typename": "QuestionNode"
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}
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}
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} |