import pandas as pd
from sklearn.preprocessing import MinMaxScaler

def prepare_data(file_path):
    data = pd.read_csv(file_path, sep=';')

    data = pd.get_dummies(data, columns=['Sex', 'Medal'])
    data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event'])

    data = data.fillna(0)
    scaler = MinMaxScaler()
    data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns)

    return data

if __name__ == "__main__":
    file_path = 'olympics-124-years-datasettill-2020/Data.csv'
    data = prepare_data(file_path)

    data.to_csv('processed_data.csv', index=False)