Since Drop the missing data so use .dropna
IntuitionSince  we need to drop values that are null or none so use .dropna and we need to drop none value rows based on the column name.ApproachSo use .dropna(
# Intuition
<!-- Describe your first thoughts on how to solve this problem. -->
Since  we need to drop values that are `null or none` so use `.dropna` and we need to drop none value rows based on the column `name`.
# Approach
<!-- Describe your approach to solving the problem. -->
So use `.dropna(subset=['name'])` so it will drop the values which have `null or none` based on subset field of name. 
# Complexity
- Time complexity:
<!-- Add your time complexity here, e.g. $$O(n)$$ -->

- Space complexity:
<!-- Add your space complexity here, e.g. $$O(n)$$ -->

# Code
```pythondata []
import pandas as pd

def dropMissingData(students: pd.DataFrame) -> pd.DataFrame:
    return students.dropna(subset=['name'])
```
['Pandas']