Package Documentation

Every R function provided by a Core R package or an add-on package distributed through CRAN must come with documentation (AKA, a help file). This documentation always follows the same general structure. Below, you see the documentation for the arrange() function from the dplyr package.

arrange R Documentation

Order rows using column values

Description

arrange() orders the rows of a data frame by the values of selected columns.

Unlike other dplyr verbs, arrange() largely ignores grouping; you need to explicitly mention grouping variables (or use .by_group = TRUE) in order to group by them, and functions of variables are evaluated once per data frame, not once per group.

Usage

arrange(.data, ..., .by_group = FALSE)

## S3 method for class 'data.frame'
arrange(.data, ..., .by_group = FALSE, .locale = NULL)

Arguments

Details

Missing values

Unlike base sorting with sort(), NA are:

  • always sorted to the end for local data, even when wrapped with desc().

  • treated differently for remote data, depending on the backend.

Value

An object of the same type as .data. The output has the following properties:

  • All rows appear in the output, but (usually) in a different place.

  • Columns are not modified.

  • Groups are not modified.

  • Data frame attributes are preserved.

Methods

This function is a generic, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.

The following methods are currently available in loaded packages: no methods found.

See Also

Other single table verbs: filter(), mutate(), reframe(), rename(), select(), slice(), summarise()

Examples

arrange(mtcars, cyl, disp)
arrange(mtcars, desc(disp))

# grouped arrange ignores groups
by_cyl <- mtcars %>% group_by(cyl)
by_cyl %>% arrange(desc(wt))
# Unless you specifically ask:
by_cyl %>% arrange(desc(wt), .by_group = TRUE)

# use embracing when wrapping in a function;
# see ?rlang::args_data_masking for more details
tidy_eval_arrange <- function(.data, var) {
  .data %>%
    arrange({{ var }})
}
tidy_eval_arrange(mtcars, mpg)

# Use `across()` or `pick()` to select columns with tidy-select
iris %>% arrange(pick(starts_with("Sepal")))
iris %>% arrange(across(starts_with("Sepal"), desc))
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