filter

Return rows with matching conditions

Use filter() find rows/cases where conditions are true. Unlike base subsetting with [, rows where the condition evaluates to NA are dropped.

Usage

filter(.data, ...)

Details

Note that dplyr is not yet smart enough to optimise filtering optimisation on grouped datasets that don't need grouped calculations. For this reason, filtering is often considerably faster on ungroup()ed data.

Useful filter functions

• ==, >, >= etc

• &, |, !, xor()

• is.na()

• between(), near()

Tidy data

When applied to a data frame, row names are silently dropped. To preserve, convert to an explicit variable with tibble::rownames_to_column().

Scoped filtering

The three scoped variants (filter_all(), filter_if() and filter_at()) make it easy to apply a filtering condition to a selection of variables.

See Also

filter_all(), filter_if() and filter_at().

Other single table verbs: arrange, mutate, select, slice, summarise

Aliases

• filter

Examples

# NOT RUN {
filter(starwars, species == "Human")
filter(starwars, mass > 1000)

# Multiple criteria
filter(starwars, hair_color == "none" & eye_color == "black")
filter(starwars, hair_color == "none" | eye_color == "black")

# Multiple arguments are equivalent to and
filter(starwars, hair_color == "none", eye_color == "black")
# }