Purpose

Creates one row per combination of key fields and calculates a sum, count, minimum, maximum or average. Without keys, it calculates a total for the entire dataset; keys alone, without measures, produce unique combinations.

Inputs and outputs

One input, in. The out output contains the keys and specified aggregate fields.

Parameters

ParameterSettings and valuesOptions and limits
excludedFields excluded from grouping roles; they do not appear in the result.Count: 0–16384
keysFields whose combined values define a group.Count: 0–100
aggregatesMeasures: column — the field, op — the operation, name — the result name.Count: 0–100
decimalThe decimal separator for numeric values in the input data.Options: ., ,
Default: .

Aggregate operations

ParameterWhat it configures
sumThe sum of all normalised values.
countThe number of rows in the group, including empty values.
min / maxThe smallest or largest normalised number.
avgThe sum of normalised values divided by the number of rows in the group.

Step-by-step configuration

  1. Define the result’s granularity and select keys, such as Product and Month.
  2. Add measures and choose sum/count/min/max/avg. count does not require a value field.
  3. Set unique result names and the decimal separator.
  4. Check the group count and total against a small, known dataset.

Rules and diagnostics

  • Empty values and ordinary text count as zero in numeric aggregates. Therefore, avg includes those rows in its denominator.
  • Invalid numeric representations, cell errors and unsupported types retain their diagnostics and may stop the block.
  • A measure field does not automatically remain a key/excluded field at the same time; grouping normalises its role.
  • Key types matter: do not convert a text code such as “001” to a number unnecessarily.

Configuration example

Group sales by Product and Month, using Value → sum named Total, and add count named Rows. For A/Jan/10 and A/Jan/15, the result is A/Jan/25/2.