HCPC_tab: Describe Clusters with One Table: the Former Form

In ggfacto: Graphs for Correspondence Analysis

Describe Clusters with One Table: the Former Form

Description

Deprecated. 'HCPC_tab(data, row_vars, clust, wt)', and 'clust_tab()' given a data frame first, are the former form of clust_tab, which now takes the analysis first and reads the active variables, the weights and the rows from it: 'clust_tab(res.mca, data, clust)'.

Usage

HCPC_tab(
  data,
  row_vars = character(),
  clust,
  wt,
  excl = NA,
  color = "difference",
  pct = "col",
  row_tot = "% of population",
  cleannames = TRUE,
  ...
)

Arguments

data	A data frame.
row_vars	<tidy-select> The variables to describe the clusters with. Numeric ones become mean rows.
clust	The variable with the clusters, as a bare name or a string, or the clusters themselves. Rows without a cluster are left out.
wt	The weight variable. Leave empty for unweighted results.
excl	The levels not to show, matched exactly by name; their individuals still count in the percentages. 'NA', the default, hides the missing values (and the levels named '<VAR>.NA'); 'excl = NULL' shows every level.
color	The colour measure, see tab. With '"difference"' (the default), percentages are coloured by their difference with the whole population, and means by their difference in standard deviations — but not both in one table, which a single ladder cannot grade: there, means stay uncoloured, and '"ratio"' colours every row.
pct	'"col"' (default) reads each cluster as a distribution: of the people in this cluster, what percentage are in this level. '"row"' reads each level as a distribution across clusters.
row_tot	The name of the row giving each cluster's share of the population.
cleannames	Set to FALSE to keep the level and cluster names as they are, prefix numbers like "1-" and text in parentheses included.
...	Additional arguments to pass to tab.

Value

A tabxplor table — see [ggfacto_summary] for how it prints.

ggfacto documentation built on Sept. 23, 2026, 1:08 a.m.