op-agg-set-frequency - Pulse Documentation

name: op-agg-set-frequency
description: Per-bit row count — how many rows had each set label selected.
kind: operator
category: AGG
operator: AGG_SET_FREQUENCY
type: reference
applies_to: process, compose, predict
examples_tags: [cardinality-analysis, cross-tabulation]

Use when

For a multi-select field, how many rows chose each option, over all rows or per group.

Questions it answers:

How many respondents selected each brand they have heard of?
How many customers use each payment method?

Use something else:

GROUP_CATEGORY when the field holds one value per row: group by it, then count.
AGG_SET_DISTINCT_VALUES when you want how many different combinations were chosen.

Params

None. Weight-aware ("weight": null opts out): Σw per member — map values become floats.

Inputs

Param	Accepted field types
`Field`	any set rung — `set_u8`, `set_u16`, `set_u32`, `set_u64`, `set_u128`, `set_u256`

Output

Rich map[string]int — label→row count (weighted: map[string]float64, Σw). Scalar fallback = max single-label frequency.

Components

Weighted adds floor sum_weights, n_eff (probability), n_weight_invalid.

Universal floor {n, n_null} plus operator-specific:

Key	Type	Notes
`total_label_observations`	int	Sum of popcounts (label selections)
`distinct_labels`	int	Distinct labels seen ≥ once
`per_label_count`	`map[string]int`	Label → row count

Mergeability: Partial — bin-by-bin sum, but map allocation expensive; staged at terminal flush
Margin: summable for crosstab

Gotchas

Survey-friendly default (“respondents per issuer”).
Used as Crosstab Cell aggregator the result is a map-valued cell payload.
Per-row a respondent may contribute to multiple bins — total_label_observations can exceed n.

See

pulse_examples_search tags=[cardinality-analysis]
Skills: aggregation-design, crosstab-guide, response-components

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