10 Years of Eurojackpot Data with Polars

mkdir eurojackpot-analysis
cd eurojackpot-analysis
python -m venv .venv
source .venv/bin/activate
pip install polars matplotlib

wget https://www.howtolosemoneyfast.com/downloads/eurojackpot-history.json

import polars as pl
import matplotlib.pyplot as plt
from pathlib import Path
from typing import Union

def load_lottery_data(file_path: Union[str, Path]) -> pl.DataFrame:
    """Loads historical lottery data from a JSON file."""
    path = Path(file_path)
    if not path.exists():
        raise FileNotFoundError(f"Dataset not found at: {path}")
    return pl.read_json(path)

def calculate_number_frequencies(df: pl.DataFrame, column_name: str, top_n: int = 10) -> pl.DataFrame:
    """Calculates the frequency of drawn numbers."""
    return (
        df.select(pl.col(column_name).explode())
        .group_by(column_name)
        .agg(pl.len().alias("frequency"))
        .sort("frequency", descending=True)
        .head(top_n)
    )

def analyze_payout_distribution(df: pl.DataFrame) -> pl.DataFrame:
    """Calculates summary statistics for minor prize tiers."""
    payouts_df = df.select(
        pl.col("date"), 
        pl.col("prizeDistribution")
    ).unnest("prizeDistribution")

    summary_stats = payouts_df.select([
        pl.col("2 + 1").drop_nulls().mean().round(2).alias("2 Main + 1 Euro"),
        pl.col("3 + 0").drop_nulls().mean().round(2).alias("3 Main + 0 Euro"),
        pl.col("3 + 1").drop_nulls().mean().round(2).alias("3 Main + 1 Euro")
    ])
    return summary_stats

def plot_reality_check(top_main: pl.DataFrame, payout_stats: pl.DataFrame):
    """Generates a professional dual-plot visualization."""

    # Set up a professional plotting style
    plt.style.use('ggplot')
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 6))
    fig.suptitle("Eurojackpot Historical Analysis: The Illusion of Strategy", fontsize=16, fontweight='bold')

    # --- Plot 1: "Hot" Numbers ---
    # Convert Polars columns to lists for Matplotlib
    numbers = [str(n) for n in top_main["mainNumbers"].to_list()]
    frequencies = top_main["frequency"].to_list()

    ax1.bar(numbers, frequencies, color='#2c3e50', edgecolor='black')
    ax1.set_title("Top 10 Most Frequent Main Numbers", fontsize=12)
    ax1.set_xlabel("Lottery Number")
    ax1.set_ylabel("Times Drawn")

    # Add a cynical watermark/text box
    ax1.text(0.05, 0.95, "Past performance does not\nindicate future results.", 
             transform=ax1.transAxes, fontsize=10, verticalalignment='top', 
             bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))

    # --- Plot 2: Payout Reality ---
    # Extract column names and their single row values
    tiers = payout_stats.columns
    avg_payouts = payout_stats.row(0)

    ax2.bar(tiers, avg_payouts, color='#e74c3c', edgecolor='black')
    ax2.set_title("Average Payouts for Common 'Wins'", fontsize=12)
    ax2.set_xlabel("Matching Tiers")
    ax2.set_ylabel("Average Payout (€)")

    # Add exact values on top of the bars
    for i, v in enumerate(avg_payouts):
        ax2.text(i, v + 0.5, f"€{v:.2f}", ha='center', fontweight='bold')

    plt.tight_layout()

    # Save the plot so you can upload it straight to your blog
    output_filename = "eurojackpot_reality_check.png"
    plt.savefig(output_filename, dpi=300)
    print(f"\n[+] Chart successfully generated and saved as '{output_filename}'")

    # Show the plot window
    plt.show()

def main():
    pl.Config.set_tbl_formatting("ASCII_MARKDOWN")
    pl.Config.set_tbl_hide_column_data_types(True)

    file_path = "eurojackpot-history.json"

    try:
        print("Initializing Eurojackpot Historical Analysis...\n")
        df = load_lottery_data(file_path)

        # Get top 10 for a better looking chart
        top_main = calculate_number_frequencies(df, "mainNumbers", top_n=10)
        payout_stats = analyze_payout_distribution(df)

        # Generate the visualization
        plot_reality_check(top_main, payout_stats)

    except Exception as e:
        print(f"Analysis failed: {e}")

if __name__ == "__main__":
    main()