54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
 
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#!/usr/bin/env python3
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"""
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Einfache Eurojackpot Bereichsanalyse
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"""
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import pandas as pd
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from collections import Counter
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def analyze_ranges():
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"""Analysiert Zahlenbereiche in Eurojackpot-Daten."""
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# Daten laden
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df = pd.read_csv("/Users/sebastianfrohlich/Library/Mobile Documents/com~apple~CloudDocs/Jupyter Notebooks/Eurojackpot/data/AlleEurojackpotzahlen.csv", sep=';')
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print(f"Anzahl Ziehungen: {len(df)}")
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# Alle Zahlen sammeln
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all_numbers = []
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for col in ['Z1', 'Z2', 'Z3', 'Z4', 'Z5']:
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all_numbers.extend(df[col].tolist())
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# Bereiche definieren
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ranges = {
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'1-10': list(range(1, 11)),
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'11-20': list(range(11, 21)),
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'21-30': list(range(21, 31)),
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'31-40': list(range(31, 41)),
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'41-50': list(range(41, 51))
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}
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print(f"\nGesamt gezogene Zahlen: {len(all_numbers)}")
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print("="*50)
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# Analyse pro Bereich
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for range_name, range_numbers in ranges.items():
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count = sum(1 for num in all_numbers if num in range_numbers)
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percentage = (count / len(all_numbers)) * 100
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print(f"{range_name:6}: {count:4} Zahlen ({percentage:5.1f}%)")
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print("="*50)
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# Häufigste Zahlen
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number_counts = Counter(all_numbers)
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print("\nHäufigste 10 Zahlen:")
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for num, count in number_counts.most_common(10):
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print(f"Zahl {num:2}: {count:3} mal")
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print("\nSeltenste 10 Zahlen:")
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for num, count in number_counts.most_common()[-10:]:
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print(f"Zahl {num:2}: {count:3} mal")
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if __name__ == "__main__":
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analyze_ranges()
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