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Create a direct categorical mock-data specification

Source: R/mock_spec.R
mock_categorical.Rd

mock_categorical() is the simple direct API for categorical variables. It returns a validated mock_spec; it does not generate data.

Usage

mock_categorical(
  name,
  levels,
  proportions = NULL,
  rtype = "factor",
  missing_codes = character(0),
  missing_proportions = numeric(0),
  garbage_rules = list(),
  provenance = NULL,
  model_hint = "auto",
  spec_version = .mock_spec_version
)

Arguments

name

Variable name.

levels

Character vector of valid levels or codes.

proportions

Optional probabilities aligned to levels.

rtype

R output type. Defaults to "factor".

missing_codes

Explicit missing-code values.

missing_proportions

Missing-code probabilities aligned to missing_codes.

garbage_rules

List of intentional invalid-value rules.

provenance

Optional provenance metadata. Defaults to the direct API.

model_hint

Backend hint.

spec_version

Character version of the specification shape.

Value

A validated mock_spec object containing one categorical variable.

Details

Use mock_categorical() when specifying one variable directly in R code. Use mock_spec_categorical() with mock_spec() when composing several variables or when writing an adapter from another metadata source.

See also

mock_spec(), mock_spec_categorical()

Other direct specification APIs: mock_continuous(), mock_date()

Examples

smoking_spec <- mock_categorical(
  "smoking",
  levels = c("never", "former", "current"),
  proportions = c(0.5, 0.3, 0.2),
  rtype = "character"
)
validate_mock_spec(smoking_spec)
#> MockData mock_spec validation result: valid