# List all CSV files in the folder csv_files = [f for f in os.listdir(csv_folder) if f.endswith('.csv')]
Now you have a single file, world_cup.db , containing the entire history of the tournament.
To evaluate coach impact across separate tournament eras, you join the match data with team managers:
This file contains the true, fully normalized relational schema. Redundant variables are stripped out, and users must rely on primary and foreign keys to reconstruct explicit relationships across the 27 tables.
That is why the is a hidden gem for sports analysts and SQL practitioners.
SELECT w.year, ROUND(CAST(SUM(m.home_goals + m.away_goals) AS FLOAT) / COUNT(*), 2) AS avg_goals FROM Matches m JOIN WorldCups w ON m.tournament_id = w.tournament_id GROUP BY w.year ORDER BY w.year;
if __name__ == '__main__': conn = sqlite3.connect('worldcup.db') create_tables(conn) insert_data(conn) fetch_data(conn) conn.close()