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100016. Drop Missing Data

DataFrame students
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| student_id  | int    |
| name        | object |
| age         | int    |
+-------------+--------+

There are some rows having missing values in the name column.

Write a solution to remove the rows with missing values.

The result format is in the following example.

 

Example 1:

Input:
+------------+-------+-----+
| student_id | name  | age |
+------------+-------+-----+
| 32         | Piper | 5   |
| 217        | Grace | 19  |
| 779        | None  | 20  |
| 849        | None  | 14  |
+------------+-------+-----+
Output:
+------------+-------+-----+
| student_id | name  | age |
+------------+-------+-----+
| 32         | Piper | 5   |
| 217        | Grace | 19  |
+------------+-------+-----+
Explanation: 
Students with ids 779 and 849 have empty values in the name column, so they will be removed.

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import pandas as pd def dropMissingData(students: pd.DataFrame) -> pd.DataFrame:

pythondata 解法, 执行用时: 276 ms, 内存消耗: 59.8 MB, 提交时间: 2023-10-07 10:31:03

'''
丢弃name为None的行
'''
import pandas as pd

def dropMissingData(students: pd.DataFrame) -> pd.DataFrame:
    return students.dropna()

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