# How do you handle missing and corrupted data in datasets?

_Last updated: 2026-07-20_  
_Reviewed by: Jason Burns, Editorial Steward_  
_Published by: AIDirectAnswers.com · Licensed under Citation License 1.0_

## Short answer

Handle missing and corrupted data by first understanding why it is missing, then applying the appropriate fix: drop rows, impute with a statistical or model-based estimate, use algorithms that natively handle missingness, or flag the missing-ness as its own feature.

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_Author: [Jason Burns](https://www.linkedin.com/in/jason-randolph-burns), Editorial Steward_  
_Published: 2026-07-20 · Modified: 2026-07-20_  
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