Add totals to a tab

Deprecated in 2.0.0, defunct in 2.1.0 – totals are built directly by tab() (a total row is always computed, one total column shown). tab_tot() still works on an existing tab.

Usage

tab_tot(
  tabs,
  tot = c("row", "col"),
  name = "Total",
  totcol = "last",
  data = NULL
)

Arguments

tabs

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

tot

c("col", "row") or "both" print total rows and total columns ; "row" or "col" print only one type ; "no" removes all totals.

name

The names of the totals, as a character vector of length one or two (c("Total_row", "Total_column") to name rows and cols differently).

totcol

"last" prints a total column for the last factor column variable only ; "each" prints one for each column variable.

data

The original database : only useful for mean columns, whose total-row variances — needed by tab_ci — can only be computed from the microdata.

Value

A tibble of class tab. Total rows are then detected with is_totrow, and total columns with is_totcol.

Examples

data <- dplyr::starwars

data |>
  tab_plain(sex, hair_color) |>
  tab_tot("col", totcol = "each")
#> Warning: `tab_tot()` was deprecated in tabxplor 2.0.0.
#> ℹ Please use the `tot` 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 The step-by-step chain is superseded: tab() / tab_num() compute this in one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: 5 × 14
#>   sex            auburn `auburn, grey` `auburn, white` black blond blonde brown
#>                     <n>            <n>             <n>   <n>   <n>    <n>   <n>
#> 1 female              1              0               0     3     0      1     5
#> 2 hermaphroditic      0              0               0     0     0      0     0
#> 3 male                0              1               1     9     3      0    11
#> 4 none                0              0               0     0     0      0     0
#> 5 NA                  0              0               0     1     0      0     2
#> # ℹ 6 more variables: `brown, grey` <n>, grey <n>, none <n>, white <n>,
#> #   `NA` <n>, Total_hair_color <n>