{ "data": { "question": { "questionId": "3066", "questionFrontendId": "2881", "boundTopicId": null, "title": "Create a New Column", "titleSlug": "create-a-new-column", "content": "
\nDataFrame employees
\n+-------------+--------+\n| Column Name | Type. |\n+-------------+--------+\n| name | object |\n| salary | int. |\n+-------------+--------+\n
\n\nA company plans to provide its employees with a bonus.
\n\nWrite a solution to create a new column name bonus
that contains the doubled values of the salary
column.
The result format is in the following example.
\n\n\n
Example 1:
\n\n\nInput:\nDataFrame employees\n+---------+--------+\n| name | salary |\n+---------+--------+\n| Piper | 4548 |\n| Grace | 28150 |\n| Georgia | 1103 |\n| Willow | 6593 |\n| Finn | 74576 |\n| Thomas | 24433 |\n+---------+--------+\nOutput:\n+---------+--------+--------+\n| name | salary | bonus |\n+---------+--------+--------+\n| Piper | 4548 | 9096 |\n| Grace | 28150 | 56300 |\n| Georgia | 1103 | 2206 |\n| Willow | 593 | 13186 |\n| Finn | 74576 | 149152 |\n| Thomas | 24433 | 48866 |\n+---------+--------+--------+\nExplanation: \nA new column bonus is created by doubling the value in the column salary.\n", "translatedTitle": null, "translatedContent": null, "isPaidOnly": false, "difficulty": "Easy", "likes": 5, "dislikes": 2, "isLiked": null, "similarQuestions": "[]", "exampleTestcases": "{\"headers\":{\"employees\":[\"name\",\"salary\"]},\"rows\":{\"employees\":[[\"Piper\",4548],[\"Grace\",28150],[\"Georgia\",1103],[\"Willow\",6593],[\"Finn\",74576],[\"Thomas\",24433]]}}", "categoryTitle": "Algorithms", "contributors": [], "topicTags": [], "companyTagStats": null, "codeSnippets": [ { "lang": "Pandas", "langSlug": "pythondata", "code": "import pandas as pd\n\ndef createBonusColumn(employees: pd.DataFrame) -> pd.DataFrame:\n ", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"315\", \"totalSubmission\": \"337\", \"totalAcceptedRaw\": 315, \"totalSubmissionRaw\": 337, \"acRate\": \"93.5%\"}", "hints": [ "Consider using the `[]` brackets with the new column name at the left side of the assignment. The calculation of the value is done element-wise." ], "solution": { "id": "2103", "canSeeDetail": true, "paidOnly": false, "hasVideoSolution": false, "paidOnlyVideo": true, "__typename": "ArticleNode" }, "status": null, "sampleTestCase": "{\"headers\":{\"employees\":[\"name\",\"salary\"]},\"rows\":{\"employees\":[[\"Piper\",4548],[\"Grace\",28150],[\"Georgia\",1103],[\"Willow\",6593],[\"Finn\",74576],[\"Thomas\",24433]]}}", "metaData": "{\n \"pythondata\": [\n \"employees = pd.DataFrame([], columns=['name', 'salary']).astype({'name':'object', 'salary':'Int64'})\"\n ],\n \"database\": true,\n \"name\": \"createBonusColumn\",\n \"languages\": [\n \"pythondata\"\n ]\n}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [], "enableRunCode": true, "enableTestMode": false, "enableDebugger": true, "envInfo": "{\"pythondata\": [\"Pandas\", \"
Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0
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