Instant Actuarial Analysis with Codestral and DuckDB 1.0

import duckdb

# Using Mistral's new Codestral model to generate optimized DuckDB 1.0 logic
# This pattern enables 'Human-in-the-loop' data exploration without RAM overhead

sql_query = """
SELECT 
    policy_region, 
    count(*) AS total_policies,
    avg(exposure) AS avg_exposure
FROM read_csv_auto('large_policy_data_*.csv')
GROUP BY ALL
HAVING avg_exposure > 5000
"""

# Execution via DuckDB's new out-of-core engine
performance_df = duckdb.query(sql_query).to_df()
print(performance_df)