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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'.

Bu egzersiz

Feature Engineering for Machine Learning in Python

kursunun bir parçasıdır
Kursu Görüntüle

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Print the count of occurrences
print(so_survey_df['Gender']____)
Kodu Düzenle ve Çalıştır