Remove duplicate rows
Table-in, table-out — composes downstream of SELECTs.
THEN DEDUPETHEN DEDUPE {{ columns }}THEN DEDUPE({{ columns }})| name | type | description |
|---|---|---|
| columns(optional) | VARCHAR | — |
| _table | TABLE | — |
Removes exact duplicate rows while preserving unique records
SELECT
*
FROM
(
VALUES
('john@example.com', 'John'),
('john@example.com', 'John'),
('jane@example.com', 'Jane')
) AS t (email, name) THEN DEDUPE THEN PYTHON ('result = pd.DataFrame({"row_count":[len(df)]})')Apply theme styling to a chart specification
Analyze query results with LLM based on a prompt
Add LLM-computed columns to query results
Filter query results using LLM-based semantic matching
Group by column and aggregate another
Investigative analysis - explores related data to answer questions
Remove duplicate rows
Table-in, table-out — composes downstream of SELECTs.
THEN DEDUPETHEN DEDUPE {{ columns }}THEN DEDUPE({{ columns }})| name | type | description |
|---|---|---|
| columns(optional) | VARCHAR | — |
| _table | TABLE | — |
Removes exact duplicate rows while preserving unique records
SELECT
*
FROM
(
VALUES
('john@example.com', 'John'),
('john@example.com', 'John'),
('jane@example.com', 'Jane')
) AS t (email, name) THEN DEDUPE THEN PYTHON ('result = pd.DataFrame({"row_count":[len(df)]})')Apply theme styling to a chart specification
Analyze query results with LLM based on a prompt
Add LLM-computed columns to query results
Filter query results using LLM-based semantic matching
Group by column and aggregate another
Investigative analysis - explores related data to answer questions