Drop Missing Data
<pre>
DataFrame students
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| student_id  | int    |
| name        | object |
| age         | int    |
+-------------+--------+
</pre>

<p>There are some rows having missing values in the <code>name</code> column.</p>

<p>Write a solution to remove the rows with missing values.</p>

<p>The result format is in the following example.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<pre>
<strong>Input:
</strong>+------------+---------+-----+
| student_id | name    | age |
+------------+---------+-----+
| 32         | Piper   | 5   |
| 217        | None    | 19  |
| 779        | Georgia | 20  |
| 849        | Willow  | 14  |
+------------+---------+-----+
<strong>Output:
</strong>+------------+---------+-----+
| student_id | name    | age |
+------------+---------+-----+
| 32         | Piper   | 5   |
| 779        | Georgia | 20  | 
| 849        | Willow  | 14  | 
+------------+---------+-----+
<strong>Explanation:</strong> 
Student with id 217 havs empty value in the name column, so it will be removed.</pre>

[]
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{
  "pythondata": [
    "students = pd.DataFrame([], columns=['student_id', 'name', 'age']).astype({'student_id':'Int64', 'name':'object', 'age':'Int64'})"
  ],
  "database": true,
  "name": "dropMissingData",
  "languages": [
    "pythondata"
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{"pythondata": ["Pandas", "<p>Python 3.10 with Pandas 2.2.2 and NumPy 1.26.4</p>"]}
[]