{
    "data": {
        "question": {
            "questionId": "3075",
            "questionFrontendId": "2883",
            "boundTopicId": null,
            "title": "Drop Missing Data",
            "titleSlug": "drop-missing-data",
            "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>&nbsp;</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",
            "translatedTitle": null,
            "translatedContent": null,
            "isPaidOnly": false,
            "difficulty": "Easy",
            "likes": 25,
            "dislikes": 1,
            "isLiked": null,
            "similarQuestions": "[]",
            "exampleTestcases": "{\"headers\":{\"students\":[\"student_id\",\"name\",\"age\"]},\"rows\":{\"students\":[[32,\"Piper\",5],[217,null,19],[779,\"Georgia\",20],[849,\"Willow\",14]]}}",
            "categoryTitle": "pandas",
            "contributors": [],
            "topicTags": [],
            "companyTagStats": null,
            "codeSnippets": [
                {
                    "lang": "Pandas",
                    "langSlug": "pythondata",
                    "code": "import pandas as pd\n\ndef dropMissingData(students: pd.DataFrame) -> pd.DataFrame:\n    ",
                    "__typename": "CodeSnippetNode"
                }
            ],
            "stats": "{\"totalAccepted\": \"10.1K\", \"totalSubmission\": \"15.5K\", \"totalAcceptedRaw\": 10102, \"totalSubmissionRaw\": 15505, \"acRate\": \"65.2%\"}",
            "hints": [
                "Consider using a build-in function in pandas library to remove the rows with missing values based on specified data."
            ],
            "solution": {
                "id": "2108",
                "canSeeDetail": true,
                "paidOnly": false,
                "hasVideoSolution": false,
                "paidOnlyVideo": true,
                "__typename": "ArticleNode"
            },
            "status": null,
            "sampleTestCase": "{\"headers\":{\"students\":[\"student_id\",\"name\",\"age\"]},\"rows\":{\"students\":[[32,\"Piper\",5],[217,null,19],[779,\"Georgia\",20],[849,\"Willow\",14]]}}",
            "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}",
            "judgerAvailable": true,
            "judgeType": "large",
            "mysqlSchemas": [],
            "enableRunCode": true,
            "enableTestMode": false,
            "enableDebugger": false,
            "envInfo": "{\"pythondata\": [\"Pandas\", \"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0</p>\"]}",
            "libraryUrl": null,
            "adminUrl": null,
            "challengeQuestion": null,
            "__typename": "QuestionNode"
        }
    }
}