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This article is part of The Definitive Guide to Importing and Preparing Data.

There may be times when you need to remove respondents (rows) from a dataset (e.g., they should have been screened out but weren't, are over-quota, have given inconsistent answers, are outliers, speedsters, or straight-liners).

You can either hide or remove respondents from a dataset in Crunch, the process of hiding them is called Exclusion.

In the web app

• See: Data cleaning - exclusions, recoding, and fixing variable types
• See also: Creating Exclusions

Crunch Automation

• SET EXCLUSION command

Using R

• Filtering Data vignette
• exclusion() for hiding respondents
• dropRows() for deleting respondents