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Plain single cross-table

Source: R/tab-leaf.R
tab_plain.Rd

[Superseded]

One bare cross-table of counts or percentages, from ONE row variable and ONE column variable. Superseded by tab(), which does the same and everything around it (several variables, colours, totals, tests) – but it stays the smallest entry point into the aggregate core, and takes the same ci / ci_method / conf_level / stars / display arguments, resolved by the same rules, so its numbers agree with tab()'s cell for cell.

Usage

tab_plain(
  data,
  row_var,
  col_var,
  tab_vars,
  wt,
  ...,
  num = FALSE,
  df = FALSE,
  .fine = NULL,
  .by_table = FALSE
)

Arguments

data

A data frame.

row_var, col_var

[Deprecated] Singular aliases of row_vars/col_vars (which now accept several variables). Kept working.

tab_vars

<tidy-select> Tab variables: one subtable per combination of their levels. Leave empty for a simple cross-table.

wt

A weight variable, of class numeric. Leave empty for unweighted results.

...

Every other argument of tab() – pct, color, ci, tot, ... – passed by name. See tab(); a typo gets a suggestion.

num

Set to TRUE to obtain a table with normal numeric vectors (not fmt).

df

Set to TRUE to obtain a plain data.frame (not a tibble), with normal numeric vectors (not fmt). Useful, for example, to pass the table to correspondence analysis with FactoMineR.

.fine, .by_table

Internal. .fine is a pre-computed count-aggregate to roll up from instead of scanning the raw data (used by tab_counts and the scan-fusion path); .by_table forces the table-by-table path.

Value

A tibble of class tabxplor_tab. If ... (tab_vars) are provided, a tab of class tabxplor_grouped_tab. All non-text columns are fmt vectors of class tabxplor_fmt, storing all the data necessary to print formats and colors. Columns with row_var and tab_vars are of class factor : every added factor will be considered as a tab_vars and used for grouping. To add text columns without using them in calculations, be sure they are of class character.

Examples

# \donttest{
# the leaf builds the cells AND their intervals: `ci` is resolved here exactly as in tab(),
# so tab_plain(ci = "ref") and tab(ci = "ref") agree cell for cell.
dplyr::starwars |>
  tab_plain(sex, hair_color, tot = c("row", "col"), pct = "row",
            ci = "ref", color = "difference", color_signif = "grey_non_signif")
#> # A tabxplor tab: 6 × 14
#>   sex            auburn `auburn, grey` `auburn, white`  black blond blonde brown
#>                  <row%>         <row%>          <row%> <row%> <row> <row%> <row>
#> 1 female             6%             0%              0%    19%    0%     6%   31%
#> 2 hermaphroditic     0%             0%              0%     0%    0%     0%    0%
#> 3 male               0%             2%              2%    15%    5%     0%   18%
#> 4 none               0%             0%              0%     0%    0%     0%    0%
#> 5 NA                 0%             0%              0%    25%    0%     0%   50%
#> 6 Total              1%             1%              1%    15%    3%     1%   21%
#> # ℹ 6 more variables: `brown, grey` <row%>, grey <row%>, none <row%>,
#> #   white <row%>, `NA` <row%>, Total <row% (n)>
#> # difference (Total): -30 -15 -5 +5 +15 +30 [grey: non-significant or under ±5 points]
# }