```json { "action": "tool_call", "reasoning": "The question asks for distribution statistics (min, max, mean, median, spread) across all numeric columns. From the card, the numeric columns in raw.titanic are: Age, Fare, SibSp, Parch, Pclass, Survived, and PassengerId. I'll write ONE SQL query that computes all these statistics for all numeric columns at once, rather than querying each column separately. I'll use DuckDB's aggregate functions: MIN, MAX, AVG, MEDIAN, and STDDEV for spread.", "tool": "query_sql", "args": { "sql": "SELECT COUNT(*) as total_rows, COUNT(Age) as age_non_null, MIN(Age) as age_min, MAX(Age) as age_max, AVG(Age) as age_mean, MEDIAN(Age) as age_median, STDDEV(Age) as age_stddev, COUNT(Fare) as fare_non_null, MIN(Fare) as fare_min, MAX(Fare) as fare_max, AVG(Fare) as fare_mean, MEDIAN(Fare) as fare_median, STDDEV(Fare) as fare_stddev, COUNT(SibSp) as sibsp_non_null, MIN(SibSp) as sibsp_min, MAX(SibSp) as sibsp_max, AVG(SibSp) as sibsp_mean, MEDIAN(SibSp) as sibsp_median, STDDEV(SibSp) as sibsp_stddev, COUNT(Parch) as parch_non_null, MIN(Parch) as parch_min, MAX(Parch) as parch_max, AVG(Parch) as parch_mean, MEDIAN(Parch) as parch_median, STDDEV(Parch) as parch_stddev, COUNT(Pclass) as pclass_non_null, MIN(Pclass) as pclass_min, MAX(Pclass) as pclass_max, AVG(Pclass) as pclass_mean, MEDIAN(Pclass) as pclass_median, STDDEV(Pclass) as pclass_stddev, COUNT(Survived) as survived_non_null, MIN(Survived) as survived_min, MAX(Survived) as survived_max, AVG(Survived) as survived_mean, MEDIAN(Survived) as survived_median, STDDEV(Survived) as survived_stddev, COUNT(PassengerId) as passengerid_non_null, MIN(PassengerId) as passengerid_min, MAX(PassengerId) as passengerid_max, AVG(PassengerId) as passengerid_mean, MEDIAN(PassengerId) as passengerid_median, STDDEV(PassengerId) as passengerid_stddev FROM raw.titanic", "purpose": "Compute distribution statistics (min, max, mean, median, standard deviation) for all numeric columns in the titanic dataset", "source": "raw" } } ```