Add total table to a tab

Deprecated in 2.0.0, defunct in 2.1.0 – the total table is built directly by the totaltab argument of tab(). tab_totaltab() still works on an existing tab.

Usage

tab_totaltab(
  tabs,
  totaltab = c("table", "line", "no"),
  name = "Ensemble",
  data = NULL
)

Arguments

tabs

A tibble of class tab, made with tab_plain or tab.

totaltab

With subtables (the levels of tab_vars) : "table" adds a complete total table, "line" a total table of a single general-total row, "no" removes any existing total table.

name

The name of the total table, as a single string.

data

The original database : only useful for mean columns (numeric variables), whose variances — needed by tab_ci — can only be computed from the microdata.

Value

A tibble of class tab. Total-table rows are then detected with is_tottab.

Examples

 data <- dplyr::starwars |> dplyr::filter(!is.na(sex))

data |>
  tab_plain(sex, hair_color, gender) |>
  tab_totaltab("line")
#> Warning: `tab_totaltab()` was deprecated in tabxplor 2.0.0.
#> ℹ Please use the `totaltab` argument of `tab()` instead.
#> The step-by-step chain is superseded: tab() / tab_num() compute this in one
#> pass.
#> ℹ The arithmetic is shared, so the numbers are identical -- only the chaining
#>   API goes.
#> # A tabxplor tab: 6 × 14
#> # Groups:         gender [3]
#>   gender sex            auburn `auburn, grey` `auburn, white` black blond blonde
#>                            <n>            <n>             <n>   <n>   <n>    <n>
#> 1 femin… female              1              0               0     3     0      1
#> 2 femin… none                0              0               0     0     0      0
#> 
#> 3 mascu… none                0              0               0     0     0      0
#> 4 mascu… hermaphroditic      0              0               0     0     0      0
#> 5 mascu… male                0              1               1     9     3      0
#> 
#> 6 Ensem… TOTAL ENSEMBLE      1              1               1    12     3      1
#> # ℹ 6 more variables: brown <n>, `brown, grey` <n>, grey <n>, none <n>,
#> #   white <n>, `NA` <n>