17 lines
475 B
Python
17 lines
475 B
Python
import pandas as pd
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from sklearn.preprocessing import MinMaxScaler
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data_path = 'data.csv'
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processed_data_path = 'processed_data.csv'
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data = pd.read_csv(data_path, sep=';')
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data = pd.get_dummies(data, columns=['Sex', 'Medal'])
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data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event'])
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scaler = MinMaxScaler()
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data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns)
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data.to_csv(processed_data_path, index=False)
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