surface↓pipeline↓group
Pipelinepipeline · returns table

GROUP

Group by column and aggregate another

Table-in, table-out — composes downstream of SELECTs.

pipelinellmpipeline-composabletext

Syntax

THEN GROUP({{ group_by }}, {{ agg_column }})
THEN GROUP({{ group_by }}, {{ agg_column }}, {{ agg_func }})

Arguments

nametypedescription
group_byVARCHAR—
agg_columnVARCHAR—
agg_func(optional)VARCHAR—
_tableTABLE—

About

PIPELINE cascade for grouping and aggregating data. Uses pure Python/pandas - no LLM calls. Usage: SELECT * FROM sales THEN GROUP('category', 'revenue') -- sum by default SELECT * FROM sales THEN GROUP('category', 'revenue', 'mean') -- average SELECT * FROM sales THEN GROUP('region', 'orders', 'count') -- count

Examples

Aggregates rows by key and returns the summed measure

SELECT
  *
FROM
  (
    VALUES
      ('A', 10),
      ('A', 15),
      ('B', 3)
  ) AS t (category, amount) THEN GROUP ('category', 'amount') THEN PYTHON (
    'result = pd.DataFrame({"a_total":[int(df.loc[df["category"] == "A", "amount_sum"].iloc[0])]})'
  )

Nearby rabbit holes

same domain
pipeline

ADD_STYLES

Apply theme styling to a chart specification

pipelinellmpipeline-composabletext
pipeline

ANALYZE

Analyze query results with LLM based on a prompt

pipelinellmpipeline-composabletext
pipeline

DEDUPE

Remove duplicate rows

pipelinellmpipeline-composabletext
pipeline

ENRICH

Add LLM-computed columns to query results

pipelinellmpipeline-composabletext
pipeline

FILTER

Filter query results using LLM-based semantic matching

pipelinellmpipeline-composabletext
pipeline

INVESTIGATE

Investigative analysis - explores related data to answer questions

pipelinellmpipeline-composabletext
Climb back to The Looking Glass