audit_sequence_data: Audit Long-Format Sequence Data

In gp3sequences: Transparent Analysis of Ordered Categorical Sequences

Audit Long-Format Sequence Data

Description

Examines a long-format data frame against the neutral gp3sequences sequence-data contract without modifying the input.

Usage

audit_sequence_data(
  data,
  sequence_id_col,
  order_col,
  state_col,
  duration_col = NULL,
  metadata_cols = NULL,
  expected_states = NULL
)

Arguments

data	A data frame containing ordered state observations.
sequence_id_col	Name of the sequence identifier column.
order_col	Name of the numeric sequence-order column.
state_col	Name of the categorical state column.
duration_col	Optional name of a numeric duration column.
metadata_cols	Optional character vector naming columns that should remain constant within each sequence.
expected_states	Optional vector of known or permitted state values.

Details

The audit checks column mappings, empty inputs, missing identifiers, missing or non-numeric order values, duplicated positions, integer order gaps, unordered rows, missing states, consecutive repeated states, single-row sequences, invalid durations, inconsistent metadata, unexpected states, and unused factor levels.

The function reports structural properties only. It does not infer psychological, cognitive, emotional, or diagnostic states.

Value

A data frame with one row per detected issue and the stable columns sequence_id, row, column, issue_code, severity, value, message, and action. Severity values are error, review, and info.

Examples

sequences <- data.frame(
  id = rep(c("s1", "s2"), each = 3L),
  position = rep(1:3, times = 2L),
  state = c("home", "search", "product", "home", "category", "product")
)

audit_sequence_data(
  sequences,
  sequence_id_col = "id",
  order_col = "position",
  state_col = "state"
)

gp3sequences documentation built on Aug. 23, 2026, 5:10 p.m.