GoKawiil← All posts
the-stats-duck — our open-source DuckDB extension — just shipped v0.6.0, and in keeping with the whole operation, the release is named i-m-not-dead. It very much isn't!
In case you haven't met it before: the-stats-duck is the statistics engine that Bedevere and KoliLang lean on. It allows DuckDB to do real statistics — distributions, tests, regression, even plots — without ever leaving SQL. MIT-licensed, and it runs anywhere DuckDB runs — including a browser!
Which is quite handy, because every demo below is a live Bedevere instance running the-stats-duck right here in your browser. The dataset is the famous Palmer Penguins — change the SQL and re-run it.
SELECT * FROM 'penguins' ; Copy
The first thing anyone would usually do with a new dataset is squint at it. meta() squints for you the full profile — one row per column:
SELECT column_name, kind, n_missing , n_distinct, mean, median, stddev, top FROM meta( 'penguins' ) ; Copy
It overlaps with DuckDB's built-in SUMMARIZE , but meta() is a table function — so you can join it, filter it, and compose it in CTEs. Do you need to know "how many numeric columns, and how many missing values total?" That's just aggregation over meta() .
Yes, ordinary least squares, in a SQL query, with the formula syntax you already know:
SELECT * FROM lm_summary( 'penguins' , formula : = 'body_mass_g ~ flipper_length_mm + bill_length_mm' ); Copy
... continue reading