<invoke name="tool_call"> <parameter name="reasoning">Most columns are categorical, so compute normalized mutual information between all pairs of the analytically relevant columns (plus amount magnitude bucket and year) in one query.</parameter> <parameter name="tool">query_sql</parameter> <parameter name="args">{"sql":"WITH b AS (SELECT \"Sr No\" id, coalesce(trim(\"Industry Vertical\"),'NA') iv, coalesce(trim(SubVertical),'NA') sv, coalesce(trim(\"City Location\"),'NA') city, coalesce(trim(InvestmentnType),'NA') itype, coalesce(trim(Remarks),'NA') rem, right(trim(\"Date dd/mm/yyyy\"),4) yr, coalesce(CAST(floor(log10(CASE WHEN try_cast(replace(\"Amount in USD\",',','') AS DOUBLE) > 0 THEN try_cast(replace(\"Amount in USD\",',','') AS DOUBLE) END)) AS VARCHAR),'NA') amt FROM raw.startup_funding), u AS (SELECT id,'industry_vertical' c, iv v FROM b UNION ALL SELECT id,'subvertical',sv FROM b UNION ALL SELECT id,'city',city FROM b UNION ALL SELECT id,'investment_type',itype FROM b UNION ALL SELECT id,'remarks',rem FROM b UNION ALL SELECT id,'year',yr FROM b UNION ALL SELECT id,'amount_log10_bucket',amt FROM b), p AS (SELECT x.c c1, y.c c2, x.v v1, y.v v2, count(*) n FROM u x JOIN u y ON x.id=y.id AND x.c<y.c GROUP BY ALL), q AS (SELECT c1,c2,n, sum(n) OVER (PARTITION BY c1,c2) N, sum(n) OVER (PARTITION BY c1,c2,v1) n1, sum(n) OVER (PARTITION BY c1,c2,v2) n2 FROM p), mi AS (SELECT c1,c2, sum(n*1.0/N*ln(n*N*1.0/(n1*n2))) mi FROM q GROUP BY c1,c2), h AS (SELECT c, -sum(k*1.0/T*ln(k*1.0/T)) h, count(*) distinct_vals FROM (SELECT c,v,count(*) k, sum(count(*)) OVER (PARTITION BY c) T FROM u GROUP BY c,v) GROUP BY c) SELECT mi.c1, mi.c2, round(mi.mi,3) mutual_info, round(mi.mi/least(h1.h,h2.h),3) nmi_min_entropy, h1.distinct_vals d1, h2.distinct_vals d2 FROM mi JOIN h h1 ON h1.c=mi.c1 JOIN h h2 ON h2.c=mi.c2 ORDER BY nmi_min_entropy DESC","purpose":"Pairwise normalized mutual information between categorical/binned columns"}</parameter> </invoke>