Output frequencies cross tabulated with a grouping column

Usage

tab_counts_one_grouped(
  data,
  col,
  cross,
  prop = "total",
  percent = TRUE,
  values = c("n", "p"),
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data: A tibble.
col: The column holding factor values.
cross: The column holding groups to split.
prop: The basis of percent calculation: "total" (the default), "cols", or "rows".
percent: Proportions are formatted as percent by default. Set to FALSE to get bare proportions.
values: The values to output: n (frequency) or p (percentage) or both (the default).
labels: If TRUE (default) extracts labels from the attributes, see codebook.
clean: Prepare data by data_clean.
...: Placeholder to allow calling the method with unused parameters from tab_counts.

Value

A volker tibble.

Examples

library(volker)
data <- volker::chatgpt

tab_counts_one_grouped(data, adopter, sd_gender)
#> 
#> 
#> |Innovator type                                    |      total|   female|     male| diverse|
#> |:-------------------------------------------------|----------:|--------:|--------:|-------:|
#> |I try new offers immediately                      |   15% (15)|   2% (2)| 12% (12)|  1% (1)|
#> |I try new offers rather quickly                   |   62% (63)| 25% (25)| 38% (38)|  0% (0)|
#> |I wait until offers establish themselves          |   22% (22)| 13% (13)|   9% (9)|  0% (0)|
#> |I only use new offers when I have no other choice |     1% (1)|   0% (0)|   1% (1)|  0% (0)|
#> |total                                             | 100% (101)| 40% (40)| 59% (60)|  1% (1)|