Get value frequencies for a column

Returns the top-N most frequent distinct values for a column in an OMOP CDM table, along with their counts. This is useful for profiling categorical or low-cardinality columns such as type_concept_id or unit_concept_id. Counts below the disclosure threshold are suppressed, and concept names are resolved where available.

Usage

ds.omop.value.counts(
  table,
  column,
  top_n = 20,
  concept_id = NULL,
  cohort = NULL,
  scope = c("per_site", "pooled"),
  pooling_policy = "strict",
  symbol = "omop",
  conns = NULL,
  execute = TRUE
)

Arguments

table

Character; the CDM table name (e.g., "condition_occurrence").

column

Character; the column to count distinct values for (e.g., "condition_type_concept_id").

top_n

Integer; the number of most frequent values to return (default: 20).

concept_id

Integer or NULL; optional concept ID to restrict rows to a single concept of the table before counting values (e.g., the value_as_concept_id categories for one measurement concept). Default: NULL for all rows. The server applies the same disclosure controls to the concept-filtered population.

cohort

Cohort reference (a dsomop_cohort_handle, a cohort_definition_id, or a server-side cohort table name), or NULL.

scope

Character; "per_site" (default) or "pooled".

pooling_policy

Character; "strict" (default) or "pooled_only_ok".

symbol

Character; the session symbol (default: "omop").

conns

DSI connection object(s) or NULL to use the session default.

execute

Logical; if FALSE, return a dry-run result containing only the generated call code (default: TRUE).

Value

A dsomop_result object with $per_site (named list of data frames with columns value, count_value), $pooled (combined value counts when pooled), and $meta.

Examples

if (FALSE) { # \dontrun{
vc <- ds.omop.value.counts("condition_occurrence",
                            "condition_type_concept_id",
                            top_n = 10, scope = "pooled")
vc$pooled
} # }