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59 lines
3.9 KiB
JSON
59 lines
3.9 KiB
JSON
{
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"question": {
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"questionId": "3075",
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"questionFrontendId": "2883",
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"boundTopicId": null,
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"title": "Drop Missing Data",
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"titleSlug": "drop-missing-data",
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"content": "<pre>\nDataFrame students\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n</pre>\n\n<p>There are some rows having missing values in the <code>name</code> column.</p>\n\n<p>Write a solution to remove the rows with missing values.</p>\n\n<p>The result format is in the following example.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\n</strong>+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 32 | Piper | 5 |\n| 217 | None | 19 |\n| 779 | Georgia | 20 |\n| 849 | Willow | 14 |\n+------------+---------+-----+\n<strong>Output:\n</strong>+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 32 | Piper | 5 |\n| 779 | Georgia | 20 | \n| 849 | Willow | 14 | \n+------------+---------+-----+\n<strong>Explanation:</strong> \nStudent with id 217 havs empty value in the name column, so it will be removed.</pre>\n",
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"difficulty": "Easy",
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"likes": 25,
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"dislikes": 1,
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"exampleTestcases": "{\"headers\":{\"students\":[\"student_id\",\"name\",\"age\"]},\"rows\":{\"students\":[[32,\"Piper\",5],[217,null,19],[779,\"Georgia\",20],[849,\"Willow\",14]]}}",
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"categoryTitle": "pandas",
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"codeSnippets": [
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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 dropMissingData(students: pd.DataFrame) -> pd.DataFrame:\n ",
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}
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"hints": [
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"Consider using a build-in function in pandas library to remove the rows with missing values based on specified data."
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],
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"solution": {
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"id": "2108",
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"status": null,
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"sampleTestCase": "{\"headers\":{\"students\":[\"student_id\",\"name\",\"age\"]},\"rows\":{\"students\":[[32,\"Piper\",5],[217,null,19],[779,\"Georgia\",20],[849,\"Willow\",14]]}}",
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"metaData": "{\n \"pythondata\": [\n \"students = pd.DataFrame([], columns=['student_id', 'name', 'age']).astype({'student_id':'Int64', 'name':'object', 'age':'Int64'})\"\n ],\n \"database\": true,\n \"name\": \"dropMissingData\",\n \"languages\": [\n \"pythondata\"\n ]\n}",
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"envInfo": "{\"pythondata\": [\"Pandas\", \"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0</p>\"]}",
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