*If you wish, you can replace your original DataFrame, using flights=flights.fillna(" ") Solution 2: Remove rows with empty values If there are only a few null values and you know that deleting values ...

To handle missing values in Python: 1. Detect Missing Data: Use `isnull()` or `isna()` to locate missing values. 2. Drop Missing Values: Use `dropna()` to remove rows or columns with NaN values.