Straight forward solution to remove the rows with missing values.
IntuitionApproachComplexity
Time complexity:

Space complexity:
Code
# Intuition
<!-- Describe your first thoughts on how to solve this problem. -->

# Approach
<!-- Describe your approach to solving the problem. -->

# 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:
    dataframe = pd.DataFrame(students)
    dataframe.dropna(subset=['name'],inplace=True)
    return dataframe

data = {
    'student_id': [32, 217, 779, 849],
    'name': ['Piper', None, 'Georgia', 'Willow'],
    'age': [5, 19, 20, 14]
}
response = dropMissingData(data)
print(response)
```
['Pandas']