Factor utilities

A collection of utility functions for factors.

combine_levels(x, levels, new_level = paste(levels, collapse = "/"))

as_factor_keep_attributes(
  x,
  x_name = deparse(substitute(x)),
  na_level = "<Missing>",
  verbose = TRUE
)

fct_discard(x, discard)

fct_explicit_na_if(x, condition, na_level = "<Missing>")

fct_collapse_only(.f, ..., .na_level = "<Missing>")

Arguments

x

(factor)
factor variable or object to convert (for as_factor_keep_attributes).

levels

(character)
level names to be combined.

new_level

(string)
name of new level.

x_name

(string)
name of x.

na_level

(string)
which level to use for missing values.

verbose

(flag)
defaults to TRUE. It prints out warnings and messages.

discard

(character)
levels to discard.

condition

(logical)
positions at which to insert missing values.

.f

(factor or character)
original vector.

...

(named character)
levels in each vector provided will be collapsed into the new level given by the respective name.

.na_level

(string)
which level to use for other levels, which should be missing in the new factor. Note that this level must not be contained in the new levels specified in ....

Value

• combine_levels: A factor with the new levels.

• as_factor_keep_attributes: A factor with same attributes (except class) as x. Does not modify x if already a factor.

• fct_discard: A modified factor with observations as well as levels from discard dropped.

• fct_explicit_na_if: A modified factor with inserted and existing NA converted to na_level.

• fct_collapse_only: A modified factor with collapsed levels. Values and levels which are not included in the given character vector input will be set to the missing level .na_level.

Functions

• combine_levels(): Combine specified old factor Levels in a single new level.

• as_factor_keep_attributes(): Converts x to a factor and keeps its attributes. Warns appropriately such that the user can decide whether they prefer converting to factor manually (e.g. for full control of factor levels).

• fct_discard(): This discards the observations as well as the levels specified from a factor.

• fct_explicit_na_if(): This inserts explicit missing values in a factor based on a condition. Additionally, existing NA values will be explicitly converted to given na_level.

• fct_collapse_only(): This collapses levels and only keeps those new group levels, in the order provided. The returned factor has levels in the order given, with the possible missing level last (this will only be included if there are missing values).

Note

Any existing NAs in the input vector will not be replaced by the missing level. If needed, explicit_na() can be called separately on the result.

See also

cut_quantile_bins() for splitting numeric vectors into quantile bins.

forcats::fct_na_value_to_level() which is used internally.

forcats::fct_collapse(), forcats::fct_relevel() which are used internally.

Examples

x <- factor(letters[1:5], levels = letters[5:1])
combine_levels(x, levels = c("a", "b"))
#> [1] a/b a/b c   d   e  
#> Levels: e d c a/b

combine_levels(x, c("e", "b"))
#> [1] a   e/b c   d   e/b
#> Levels: e/b d c a

a_chr_with_labels <- c("a", "b", NA)
attr(a_chr_with_labels, "label") <- "A character vector with labels"
as_factor_keep_attributes(a_chr_with_labels)
#> Warning: automatically converting character variable a_chr_with_labels to factor, better manually convert to factor to avoid failures
#> [1] a         b         <Missing>
#> attr(,"label")
#> [1] A character vector with labels
#> Levels: a b <Missing>

fct_discard(factor(c("a", "b", "c")), "c")
#> [1] a b
#> Levels: a b

fct_explicit_na_if(factor(c("a", "b", NA)), c(TRUE, FALSE, FALSE))
#> [1] <Missing> b         <Missing>
#> Levels: a b <Missing>

fct_collapse_only(factor(c("a", "b", "c", "d")), TRT = "b", CTRL = c("c", "d"))
#> [1] <Missing> TRT       CTRL      CTRL     
#> Levels: TRT CTRL <Missing>