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55 lines
6.6 KiB
JSON
55 lines
6.6 KiB
JSON
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"question": {
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"questionId": "3065",
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"questionFrontendId": "2879",
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"categoryTitle": "pandas",
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"boundTopicId": 2467489,
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"title": "Display the First Three Rows",
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"titleSlug": "display-the-first-three-rows",
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"content": "<pre>\nDataFrame: <code>employees</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| employee_id | int |\n| name | object |\n| department | object |\n| salary | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to display the <strong>first <code>3</code> </strong>rows<strong> </strong>of this DataFrame.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\n</strong>DataFrame employees\n+-------------+-----------+-----------------------+--------+\n| employee_id | name | department | salary |\n+-------------+-----------+-----------------------+--------+\n| 3 | Bob | Operations | 48675 |\n| 90 | Alice | Sales | 11096 |\n| 9 | Tatiana | Engineering | 33805 |\n| 60 | Annabelle | InformationTechnology | 37678 |\n| 49 | Jonathan | HumanResources | 23793 |\n| 43 | Khaled | Administration | 40454 |\n+-------------+-----------+-----------------------+--------+\n<strong>Output:</strong>\n+-------------+---------+-------------+--------+\n| employee_id | name | department | salary |\n+-------------+---------+-------------+--------+\n| 3 | Bob | Operations | 48675 |\n| 90 | Alice | Sales | 11096 |\n| 9 | Tatiana | Engineering | 33805 |\n+-------------+---------+-------------+--------+\n<strong>Explanation:</strong> \nOnly the first 3 rows are displayed.</pre>\n",
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"translatedTitle": "显示前三行",
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"translatedContent": "<pre>\nDataFrame: <code>employees</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| employee_id | int |\n| name | object |\n| department | object |\n| salary | int |\n+-------------+--------+\n</pre>\n\n<p>编写一个解决方案，显示这个 DataFrame 的<strong> 前 <code>3</code> </strong>行。</p>\n\n<p> </p>\n\n<p><b>示例 1:</b></p>\n\n<pre>\n<strong>输入：\n</strong>DataFrame employees\n+-------------+-----------+-----------------------+--------+\n| employee_id | name | department | salary |\n+-------------+-----------+-----------------------+--------+\n| 3 | Bob | Operations | 48675 |\n| 90 | Alice | Sales | 11096 |\n| 9 | Tatiana | Engineering | 33805 |\n| 60 | Annabelle | InformationTechnology | 37678 |\n| 49 | Jonathan | HumanResources | 23793 |\n| 43 | Khaled | Administration | 40454 |\n+-------------+-----------+-----------------------+--------+\n<b>输出：</b>\n+-------------+---------+-------------+--------+\n| employee_id | name | department | salary |\n+-------------+---------+-------------+--------+\n| 3 | Bob | Operations | 48675 |\n| 90 | Alice | Sales | 11096 |\n| 9 | Tatiana | Engineering | 33805 |\n+-------------+---------+-------------+--------+\n<b>解释：</b>\n只有前 3 行被显示。</pre>\n",
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"difficulty": "Easy",
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"langSlug": "pythondata",
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"code": "import pandas as pd\n\ndef selectFirstRows(employees: pd.DataFrame) -> pd.DataFrame:\n ",
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"Consider using a built-in function in pandas library to retrieve the initial rows."
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"sampleTestCase": "{\"headers\":{\"employees\":[\"employee_id\",\"name\",\"department\",\"salary\"]},\"rows\":{\"employees\":[[3,\"Bob\",\"Operations\",48675],[90,\"Alice\",\"Sales\",11096],[9,\"Tatiana\",\"Engineering\",33805],[60,\"Annabelle\",\"InformationTechnology\",37678],[49,\"Jonathan\",\"HumanResources\",23793],[43,\"Khaled\",\"Administration\",40454]]}}",
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"exampleTestcases": "{\"headers\":{\"employees\":[\"employee_id\",\"name\",\"department\",\"salary\"]},\"rows\":{\"employees\":[[3,\"Bob\",\"Operations\",48675],[90,\"Alice\",\"Sales\",11096],[9,\"Tatiana\",\"Engineering\",33805],[60,\"Annabelle\",\"InformationTechnology\",37678],[49,\"Jonathan\",\"HumanResources\",23793],[43,\"Khaled\",\"Administration\",40454]]}}",
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