My 23rd Problem (pd)
ApproachUse the dropna() function in pandas to remove rows where the "name" column has missing values (None/NaN)!Complexity
Time complexity:O(n)

Space complexi

# Approach
<!-- Describe your approach to solving the problem. -->
Use the dropna() function in pandas to remove rows where the "name" column has missing values (None/NaN)! 
# Complexity
- Time complexity: $$O(n)$$
<!-- Add your time complexity here, e.g. $$O(n)$$ -->

- Space complexity: $$O(1)$$
<!-- 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']