: Run Monte Carlo models to forecast group-stage advancement or identify potential bracket winners. GitHubhttps://github.com The Fjelstul World Cup Database - GitHub
Once the data is imported, we can begin to explore and analyze it. jfjelstul worldcup data-sqlite
# Load the data into a pandas dataframe worldcup_df = pd.read_sql_query("SELECT * FROM worldcup", conn) : Run Monte Carlo models to forecast group-stage
The raw data can be compiled directly from the jfjelstul/worldcup GitHub Repository . Use Python to extract the .csv assets from the package's codebook and pipeline them into SQLite: Use Python to extract the
The database distinguishes itself from raw CSV dumps by being . Instead of a single wide table, the data is split into subject-specific tables linked by foreign keys. This reduces redundancy and allows for precise SQL joins.
SELECT winner, COUNT(*) as num_titles FROM worldcup WHERE winner IS NOT NULL GROUP BY winner ORDER BY num_titles DESC;