Separate Age Group Column into Min and Max Age of Range

Takes the age group stored in age_group and creates two variables, age_min and age_max with the age boundaries of the group. By default, separate_age_groups() assumes that the age group definitions are separated by a dash ("-"), possibly with whitespace on either side. The separator can be specified using the sep argument.

separate_age_groups(data, age_group = age_group, ...,
  sep = "\\s*-\\s*", into = c("age_min", "age_max"))

Arguments

data	A data frame.
age_group	Unquoted column name containing the age grouping.
...	Not used other than to require explicit naming of arguments.
sep	Separator between columns. If character, is interpreted as a regular expression. The default value is a regular expression that matches any sequence of non-alphanumeric values. If numeric, interpreted as positions to split at. Positive values start at 1 at the far-left of the string; negative value start at -1 at the far-right of the string. The length of sep should be one less than into.
into	Character vector of column names for separated age_group. If NULL, then _min and _max will be appended to the name of the age_group column. Must be two names in the order min then max.

See also

format_age_groups() for the specification of the age group label format and to convert age boundaries into age group labels.

Other age processors: complete_age_groups, filter_age_groups, format_age_groups, recode_age_groups, standardize_age_groups

Examples

d_age_group <- dplyr::tibble(
  id = 1:4,
  age_group = c("0 - 4", "10 - 14", "65 - 69", "85+")
)

separate_age_groups(d_age_group)
#> # A tibble: 4 x 4
#>      id age_group age_min age_max
#>   <int> <chr>       <dbl>   <dbl>
#> 1     1 0 - 4           0       4
#> 2     2 10 - 14        10      14
#> 3     3 65 - 69        65      69
#> 4     4 85+            85     Inf