Imputing Defaults with fillna()

How do we replace missing numeric and string values with custom default values using a dictionary?

Intermediate⏱ 2 Minutes⭐ 340 XP

🤔 THE QUESTION

How do we replace missing numeric and string values with custom default values using a dictionary?

💡 WHAT IS IT?

fillna() substitutes NULL entries with specified constants, either across all columns or using a column-to-value map.

🎯 WHAT IS IT USED FOR?

Imputing missing features for machine learning and ensuring reporting dashboards display clean fallback labels.

💻 EXAMPLE

df = df.fillna({"age": 0, "status": "UNKNOWN"})

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