Data cube creation

dcc6(
  .data,
  .variables,
  .funs_list = list(n = ~dplyr::n()),
  .total = "Totale",
  order_type = extract_unique4,
  .all = TRUE
)

dcc6_fixed(
  .data,
  .variables,
  .funs_list = list(n = ~dplyr::n()),
  .total = "Totale",
  order_type = extract_unique5,
  .all = TRUE,
  fixed_variable = NULL
)

Arguments

.data

data frame to be processed.

.variables

variables to split data frame by, as a character vector (c("var1", "var2")).

.funs_list

a list of function calls in the form of right-hand formula.

.total

character string with the name to give to the subset of data that includes all the observations of a variable (default: "Totale").

order_type

a function like extract_unique or extract_unique2.

.all

logical, indicating if functions have to be evaluated on the complete dataset.

fixed_variable

name of the variable for which you do not want to estimate the total

Examples

dcc6(invented_wages, .variables = c("gender", "sector"), .funs_list = list(n = ~dplyr::n()), .all = TRUE)
#> # A tibble: 9 x 3 #> gender sector n #> * <fct> <fct> <int> #> 1 Totale Totale 1000 #> 2 Totale secondary 455 #> 3 Totale tertiary 545 #> 4 men Totale 547 #> 5 men secondary 289 #> 6 men tertiary 258 #> 7 women Totale 453 #> 8 women secondary 166 #> 9 women tertiary 287
dcc6(invented_wages, .variables = c("gender", "sector"), .funs_list = list(n = ~dplyr::n()), .all = FALSE)
#> # A tibble: 8 x 3 #> gender sector n #> <fct> <fct> <int> #> 1 Totale secondary 455 #> 2 Totale tertiary 545 #> 3 men Totale 547 #> 4 men secondary 289 #> 5 men tertiary 258 #> 6 women Totale 453 #> 7 women secondary 166 #> 8 women tertiary 287