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            "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": "删去丢失的数据",
            "translatedContent": "<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>在 <code>name</code> 列里有一些具有缺失值的行。</p>\n\n<p>编写一个解决方案，删除具有缺失值的行。</p>\n\n<p>返回结果格式如下示例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><b>示例 1:</b></p>\n\n<pre>\n<strong>输入：\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>输出：\n</strong>+------------+---------+-----+\n| student_id | name    | age |\n+------------+---------+-----+\n| 32         | Piper   | 5   |\n| 779        | Georgia | 20  | \n| 849        | Willow  | 14  | \n+------------+---------+-----+\n<b>解释：\n</b>学号为 217 的学生所在行在 name 列中有空值，因此这一行将被删除。</pre>\n",
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                    "code": "import pandas as pd\n\ndef dropMissingData(students: pd.DataFrame) -> pd.DataFrame:\n    ",
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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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