Exclusion filters express logic that defines a set of rows that should be dropped from the dataset. The rows aren't permanently deleted—you can recover them at any time by removing the exclusion filter—but they are omitted from all views and calculations, as if they had been deleted.
exclusion(x)
exclusion(x) <- valueexclusion returns a CrunchFilter if there is one,
else NULL. The setter returns x with the filter set.
Note that exclusion filters work opposite from how "normal" filters work. That is, a regular filter expression defines the subset of rows to operate on: it says "keep these rows." An exclusion filter defines which rows to omit. Applying a filter expression as a query filter will have the opposite effect if applied as an exclusion. Indeed, applying it as both query filter and exclusion at the same time will result in 0 rows.