Replacing missing values with constants
While removing missing data entirely maybe a correct approach in many situations, this may result in a lot of information being omitted from your models.
You may find categorical columns where the missing value is a valid piece of information in itself, such as someone refusing to answer a question in a survey. In these cases, you can fill all missing values with a new category entirely, for example 'No response given'.
Este exercício faz parte do curso
Feature Engineering for Machine Learning in Python
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Print the count of occurrences
print(so_survey_df['Gender']____)