Complete Age Groups

Completes age groups by adding missing age groups, either within the age range from age_gt to age_lt or using the full age list from seer_std_ages. If the columns age_min or age_max are missing from the input data, separate_age_groups() is first called to expand the age group variable.

complete_age_groups(data, ..., age_gt = NULL, age_lt = NULL,
  age_group = age_group, fill = list(n = 0), include_unknown = FALSE,
  std_age_groups = fcds_const("age_group"))

Arguments

data	A data frame.
...	Column specification passed on to `tidyr::complete()`. Used to identify additional columns that should also be completed. Columns that aren't declared here and do not have a default `fill` value will have `NA` values in the resulting output.
age_gt	Youngest age (inclusive).
age_lt	Eldest age (inclusive).
age_group	Unquoted column name containing the age grouping.
fill	A named list that for each variable supplies a single value to use instead of `NA` for missing combinations.
include_unknown	Should the "Unknown" age group be included?
std_age_groups	Character vector containing expected (or standard) age groups.

Examples

dplyr::tibble(
  age_group = c("10 - 14", "15 - 19", "25 - 29"),
  n = 10:12
) %>%
  complete_age_groups(age_gt = 10, age_lt = 35)
#> # A tibble: 5 x 2
#>   age_group     n
#>   <ord>     <dbl>
#> 1 10 - 14      10
#> 2 15 - 19      11
#> 3 20 - 24       0
#> 4 25 - 29      12
#> 5 30 - 34       0

set.seed(42)

# Create an example data frame with age_groups at several grouping levels
tidyr::crossing(
  group = LETTERS[1:3],
  sub_group = paste(1:3),
) %>%
  # Add a column with equivalent levels to `sub_group`
  dplyr::mutate(sub_group_equal = letters[as.integer(sub_group)]) %>%
  # Add age groups for ages < 25 to each group level
  tidyr::crossing(
    age_group = fcds_const("age_group")[1:5]
  ) %>%
  # Remove 20% of the age_groups
  dplyr::sample_frac(0.80) %>%
  # Use complete_age_groups() to complete the grouping,
  # using tidyr::complete() syntax to specificy which additional columns
  # are completed.
  complete_age_groups(age_lt = 25, group, tidyr::nesting(sub_group, sub_group_equal))
#> # A tibble: 45 x 4
#>    group sub_group sub_group_equal age_group
#>    <chr> <chr>     <chr>           <ord>    
#>  1 A     1         a               0 - 4    
#>  2 A     1         a               5 - 9    
#>  3 A     1         a               10 - 14  
#>  4 A     1         a               15 - 19  
#>  5 A     1         a               20 - 24  
#>  6 A     2         b               0 - 4    
#>  7 A     2         b               5 - 9    
#>  8 A     2         b               10 - 14  
#>  9 A     2         b               15 - 19  
#> 10 A     2         b               20 - 24  
#> # … with 35 more rows

Arguments

See also

Examples