How to correctly fill in the missing values ​​of binary features?

Question

Python

For example, if the attribute is gender, and the table contains empty values ​​in the gender column.
Or a feature with the values ​​"City" and "Village", describing where the object is located.
If you translate "City" into 1, and "Village" into 0, then what to do with empty fields.

Answer 1

Your choice:
1. Fill in with the most frequent
2. Predict the missing value based on other features
3. Make "Missing" a separate feature value