Easy Solution Beginner Friendly || Pandas || LIne By Line Explanation |||
Intuition\nThe problem appears to ask for a solution to remove rows with missing values in a specific column (\'name\') in a given Pandas DataFrame named \'stud
# Intuition\nThe problem appears to ask for a solution to remove rows with missing values in a specific column (\'name\') in a given Pandas DataFrame named \'students\'.\n\n# Approach\nTo solve this problem, we can utilize the Pandas library in Python. We can use the `.notnull()` method on the \'name\' column of the \'students\' DataFrame to identify rows with non-null values in the \'name\' column. Then, we can create a new DataFrame containing only those rows.\n\n# Complexity\n- Time complexity:\n  - The time complexity depends on the size of the \'students\' DataFrame but can be considered as O(n), where n is the number of rows in the DataFrame.\n\n- Space complexity:\n  - The space complexity is O(n) as we are creating a new DataFrame containing only the rows with non-null \'name\' values.\n\n# Code\n```python\nimport pandas as pd\n\ndef dropMissingData(students: pd.DataFrame) -> pd.DataFrame:\n    return pd.DataFrame(students)[students[\'name\'].notnull()]\n
['Pandas']